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Although South Africa was the first country to register and roll out oral pre-exposure prophylaxis (PrEP) biomedical human immunodeficiency virus (HIV) prevention intervention in sub-Saharan Africa (SSA), its uptake remains low, particularly among adolescent girls and young women (AGYW). The uptake of PrEP may have worsened during the Coronavirus disease 2019 (COVID-19) pandemic. Some innovative interventions to improve PrEP uptake among AGYW have been implemented. This study aims to evaluate the effectiveness of PrEP innovative interventions implemented during COVID-19 towards reducing the risk of HIV infection among AGYW in South Africa. An exploratory, descriptive design will be conducted to carry out four study objectives. Firstly, to carry out a systematic review of innovative PrEP interventions implemented during COVID-19 in SSA countries. Secondly, to conduct a stakeholder analysis to identify PrEP stakeholders and interview them on their views on the implemented interventions. Thirdly, to assess the implementation outcomes of the innovative interventions using document reviews and Consolidated Framework for Implementation Research. Fourthly, to develop a framework for an improved PrEP service delivery among AGYW. Qualitative data will be captured in ATLAS.ti software (Technical University, Berlin, Germany) version 23 and analysed via thematic analysis. A statistical software package (STATA) version 18 (College Station, TX, USA) will be used to capture quantitative data and analyse them via descriptive analysis. The generated evidence will be used towards the development of framework, guidelines, and policies to strengthen the uptake of, scale-up, and adherence to PrEP among AGYW. [ABSTRACT FROM AUTHOR]

This paper explores the research trends in the literature about supply chain disruptions published over the last 20 years through a comprehensive review and keyword-based analysis. A sample of 4239 papers retrieved from Scopus was analyzed to identify the key themes covered and the shifts in time of those themes. The results highlight a significant rise in the number of publications on supply chain disruptions since 2021, reflecting the dynamic nature of supply chains and the need to adapt them to increasingly complex scenarios. The findings point out the importance of resilience and risk management but also the progressive shift toward technological innovations and digital tools, as a means to enhance supply chain robustness and sustainability in response to recent global disruptions (e.g., the COVID-19 pandemic, the Russia–Ukraine conflict, and the climate change). From the analyses carried out, interesting opportunities for future research directions are delineated. This study represents a unicum in the scientific literature in terms of the number of articles analyzed, the timespan, as well as the scientometric approach adopted. Finally, the paper highlights the main trends in the field of supply chain disruptions, providing valuable insights for future research activities. [ABSTRACT FROM AUTHOR]

The interest of the research community in happiness and its associated issues has been steadily growing over the years, including during the period marked by the COVID-19 pandemic. The pandemic has brought about significant changes in various aspects of people's lives. In this study, the objective is to analyze the themes and the most significant trends in papers dedicated to happiness in the context of COVID-19 during the period following the onset of the pandemic. To achieve this, the authors have compiled a dataset of papers sourced from Clarivate Analytics' Web of Science Core Collection database, which were extracted using keywords related to both happiness and COVID-19. This database comprises 1932 articles. The researchers have conducted a comprehensive bibliometric analysis of this dataset, providing insights into the most prolific authors in this field, the most frequently cited documents, and the preferred journals for publishing this research. The authors also explore details related to collaboration networks and author clusters. An n-gram analysis is performed on titles, abstracts, keywords, and keywords plus, offering a deeper understanding of the primary research themes. Furthermore, the contributors present a review of the top 10 most cited papers, which completes the analysis and underscores the research trends related to happiness in the context of COVID-19. [ABSTRACT FROM AUTHOR]

The article titled "COVID-19 Prevention and Treatment—2nd Edition" is a collection of research and review articles related to various aspects of COVID-19. The articles are divided into four themes: treatment, prevention, mechanism of action, and general and specific conditions of pathology. The treatment section focuses on drug treatment, convalescent plasma use, extracorporeal membrane oxygenation (ECMO), endotracheal intubation (ETI), and the global effectiveness of COVID-19 treatment. The prevention section discusses vaccination efficacy and the identification of antibodies associated with decreased clinical immunity. The mechanism of action section explores biomarkers associated with the loss of taste or olfactory ability. The general and specific conditions of pathology section examines ageusia and swallowing in COVID-19 patients. The collection emphasizes the need for a comprehensive approach to COVID-19 prevention and treatment. [Extracted from the article]

Patients with cancer can be immunocompromised because of their disease and/or due to anticancer therapy. In this population, severe influenza virus infections are associated with an elevated risk of morbidity and mortality. Influenza vaccination is therefore highly recommended in cancer patients, including those receiving anticancer therapy. However, vaccination coverage remains far below the recommended target for vulnerable subjects. Six specialists in oncology, hematology, immunology, and public health/vaccinology convened with the objective of developing strategies, based on evidence and clinical experience, for improving influenza vaccination coverage in cancer patients. This viewpoint provides an overview of current influenza vaccination recommendations in cancer patients, discusses barriers to vaccination coverage, and presents strategies for overcoming said barriers. New immunization issues raised by the COVID-19 pandemic are also addressed. Future directions include improving public education on influenza vaccination, providing the media with accurate information, improving knowledge among healthcare professionals, improving access to vaccines for cancer patients, co-administration of the influenza and COVID-19 vaccines, increased collaboration between oncologists and other health professionals, increased accessibility of digital vaccination registries to specialists, shared information platforms, and promoting immunization campaigns by healthcare systems with the support of scientific societies. [ABSTRACT FROM AUTHOR]

Background and Objectives: Accelerated orthodontics represents a significant shift in dental practice aimed at reducing treatment times while maintaining optimal patient outcomes. This bibliometric analysis evaluated the research landscape of accelerated orthodontics from 2012 to 2023, focusing on publication trends, citation patterns, influential journals, leading institutions, and key contributors. Materials and Methods: A comprehensive search in Scopus identified 600 relevant articles, with the top 50 most-cited papers encompassing systematic reviews, randomized controlled trials, and experimental studies. Key techniques, such as corticotomy and piezocision, have been frequently highlighted for their effectiveness in expediting tooth movement. Results: The analysis revealed fluctuating annual scientific outputs, with notable peaks driven by technological advancements and increased patient demand for quicker orthodontic solutions. However, the production of high-impact papers was hindered by delays in citation accumulation and disruptions caused by the COVID-19 pandemic. Keyword analysis identified critical themes, such as orthodontic tooth movement, malocclusion, and demographic factors, while a global collaboration map underscored extensive international research partnerships. Leading journals included the American Journal of Orthodontics and Dentofacial Orthopedics, and prominent institutions such as the University of California at Los Angeles played significant roles in advancing the field. Conclusions: This study provides a comprehensive overview of the current state of accelerated orthodontics, emphasizing the need for continued research, particularly RCTs, to further refine and validate accelerated orthodontic techniques and improve clinical outcomes. [ABSTRACT FROM AUTHOR]

In the continuously evolving field of E-government, understanding the breadth and depth of academic research is crucial for advancing governmental digital transformation and policy development. This study employs visual bibliometric analysis, using the Web of Science database to map the evolution trajectory of E-government research from 2000 to 2023. By utilizing CiteSpace for a comprehensive examination of 4536 academic articles, this paper outlines the growth patterns and thematic evolution within the field. The development of the E-government field is delineated into four distinct phases: the budding period (2000–2003), the bottleneck period (2004–2014), the development period (2015–2018), and the growth period (2019–2023), which are each marked by unique thematic shifts and technological advancements. The research results reveal the transformation of research focus in different periods, from the initial focus on the technological means and the electronic transformation of government services, moving on to more complex issues such as E-government acceptance and government transparency and corruption, and ultimately to the current focus on innovation and smart cities. In addition, the paper also clarifies that the research boom that began in 2019 is driven by technological innovation opportunities, the improvement in infrastructure, and multidisciplinary research. By depicting these developmental stages and emerging trends, this study not only unveils past academic efforts but also forecasts future research directions, thereby providing valuable insights for researchers and policymakers aiming to understand and implement effective E-government strategies. [ABSTRACT FROM AUTHOR]

This article investigates the impact of the COVID-19 pandemic on logistics and supply chain processes through a two-phase analysis. First, a literature review maps the existing studies, published from 2021 to 2023 (101 papers), offering a view of the multiple challenges faced by supply chains during the pandemic emergency. The literature analysis makes use of descriptive statistics, thematic classifications and cross-analyses to provide a detailed overview of the issues raised by the COVID-19 pandemic and of the related implications. Second, a case study targeting a logistics operator was conducted, to derive practical insights into the real-world implications of pandemic disruptions. The study highlights the importance of proactive risk management strategies and the role of Industry 4.0 technologies to improve supply chain resilience and sustainability. Hence, this research contributes to a deeper understanding of the impact of the COVID-19 pandemic on logistics and supply chain processes and offers valuable guidance for companies, especially those working in the transport and logistics field. [ABSTRACT FROM AUTHOR]

COVID-19 is an enveloped virus with a single-stranded R N A genome. The surface of the virus contains spike proteins, which enable the virus to attach to host cells and enter the interior of the cells. After entering the cell, the virus exploits the host cell's mechanisms for replication and dissemination. Since the end of 2019, COVID-19 has spread rapidly around the world, leading to a large-scale epidemic. In response to the COVID-19 pandemic, the global scientific community quickly launched vaccine research and development. Vaccination is regarded as a crucial strategy for controlling viral transmission and mitigating severe cases. In this paper, we propose a novel mathematical model for COVID-19 infection incorporating vaccine-induced immunization failure. As a cornerstone of infectious disease prevention measures, vaccination stands as the most effective and efficient strategy for curtailing disease transmission. Nevertheless, even with vaccination, the occurrence of vaccine immunization failure is not uncommon. This necessitates a comprehensive understanding and consideration of vaccine effectiveness in epidemiological models and public health strategies. In this paper, the basic regeneration number is calculated by the next generation matrix method, and the local and global asymptotic stability of disease-free equilibrium point and endemic equilibrium point are proven by methods such as the Routh–Hurwitz criterion and Lyapunov functions. Additionally, we conduct fractional-order numerical simulations to verify that order 0.86 provides the best fit with COVID-19 data. This study sheds light on the roles of immunization failure and fractional-order control. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic was a health, economic, and financial crisis. The aviation sector was one of the most severely hit. Despite the extensive literature on this, COVID-Finance has been focused on stock returns, neglecting what could be learnt from the spreads of airlines' credit default swaps (CDSs). This would seem of the utmost importance, given the epicenter of the crisis within the credit market. In this paper, an in-depth analysis of airlines' CDS spreads is conducted. It is found that they were severely hit, for all airlines studied. However, the results of the PSY test showed that speculative trading led the surge, as explosive roots were found in the spreads of all these aviation firms. The dramatic increase in CDS spreads has contributed to already high borrowing costs for airlines. Our results suggest that aviation bail outs have helped to mitigate spreads' explosiveness. Monetary policy measures have also limited, albeit indirectly, the funding risk posed by the government bail outs. By the end of March 2021, spreads were no longer explosive, and were approaching, at highly heterogeneous paces, their pre-pandemic values. Notwithstanding, airlines' stock prices have been notably resistant to recovery. [ABSTRACT FROM AUTHOR]

The paper is set within the methodological framework of the Territorial Impact Assessment (TIA) process, which is an instrument designed to facilitate sustainable and cohesive policy-making choices at the European level. The article is developed within the context of a European H2020-RICE cooperative project, which utilises the STeMA (Sustainable Territorial Economic/Environmental Management Approach) TIA methodology to investigate the potential relationship between statistical economic indicators, specifically Gross Domestic Product, and related parameters (metadata), and Earth Observation (EO) data. The objective is to provide evidence of socioeconomic trends during the Coronavirus 2019 pandemic in the Lazio Region (Italy), with a particular focus on the metropolitan area of the Rome capital city Rome. In line with the pertinent European context and the scientific literature on the subject, the paper examines the potential for combining classical and Earth observation indicators to assess macroeconomic dimensions of development, specifically in terms of gross domestic product (GDP). The results of the analysis indicate the presence of certain correlations between grey data and EO information. The STeMA-TIA approach allows for the measurement and correlation of both qualitative and quantitative statistical indicators with typological functional areas (in accordance with European Commission-EC and Committee of Ministers responsible for Spatial/Regional Planning—CEMAT guidance) at the NUTS (Nomenclature des unités territoriales statistiques) 2 and 3 levels. This facilitates the territorialisation of information, enabling the indirect comparison of data with satellite data and economic trends. A time series of data was gathered and organised for the purpose of facilitating comparison between different periods, beginning with 2019 and extending to the present day. In order to measure and monitor the evolution of the selected territorial economies (the Lazio Region), a synthetic index (or composite indicator) was developed in the economic and epidemic dimensions. This index combines single values of indicators according to a specific STeMA methodology. It is important to note that there are some critical observations to be made about the impact on GDP, due to the discrepancy between the indicators in the two fields of observation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to apply Bronfenbrenner's ecological systems theory to explore the literature on how Conditional Cash Transfer (CCT) and Unconditional Cash Transfer (UCT) programs might support positive mental health outcomes. The paper begins with transnational considerations of stress, such as poverty and COVID-19, and their impact on mental health. Bronfenbrenner's theory is applied to better understand the mechanisms by which CCT and UCT programs can potentially lead to positive outcomes for children and families who face such stressors. The implications of cash transfer programs are subsequently discussed in terms of how they might promote positive mental health outcomes among families globally. This theoretical application paper concludes with a call for transnational research to explore connections between cash transfer programs and mental health outcomes for children/adolescents and their parents/caregivers. [ABSTRACT FROM AUTHOR]

Systematic inflammatory response syndrome (SIRS) and the accompanying sepsis pose a huge threat to human health worldwide. Heparin is a part of the standard supportive care for the disease. However, the molecular mechanism is not fully understood yet, and the potential signaling pathways that play key roles have not yet been elucidated. In this paper, the main findings regarding the molecular mechanisms associated with the beneficial effects of heparin, including inhibiting HMGB-1-driven inflammation reactions, histone-induced toxicity, thrombo-inflammatory response control and the new emerging mechanisms are concluded. To set up the link between the preclinical research and the clinical effects, the outcomes of the clinical trials are summarized. Then, the structure and function relationship of heparin is discussed. By providing an updated analysis of the above results, the paper highlights the feasibility of heparin as a possible alternative for sepsis prophylaxis and therapy. [ABSTRACT FROM AUTHOR]

Comparing hospitals using multicriteria methods facilitates a thorough assessment of performance across multiple dimensions, supports informed decision-making, promotes accountability, and drives continuous improvement in healthcare delivery. This paper aims to apply multicriteria methods to assess hospitals in Slovakia in the pre-crisis (2019), crisis (2021), and post-crisis (2023) periods of the COVID-19 pandemic. The assessment is conducted using four multicriteria methods, i.e., a ranking method, scoring method, normed variable method, and TOPSIS method, and nonmetric multidimensional scaling (NMDS). The research sample comprises a group of hospitals classified under the sector (SK) NACE 86.1—Hospital activities. Seven indicators (financial and non-financial) were entered into the analysis. The results show that the agreement among the employed multicriteria evaluation methods was statistically significant. Moreover, the findings demonstrate that Slovak hospital rankings based on the selected criteria vary over time. The perfect quality of the NMDS models, as indicated by stress values below 0.025, shows that NMDS analysis provides a highly accurate and reliable representation of hospital comparisons. By combining multicriteria methods with NMDS, we harness the strengths of each approach to improve decision-making and achieve greater insights into intricate datasets. A comprehensive assessment of hospitals allows for the identification of the system's strengths and weaknesses, which can be utilized to formulate new improvement strategies. As an additional benefit, this paper includes a bibliometric analysis, offering a systematic evaluation and synthesis of existing research on multicriteria evaluation methods. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic brought into prominence several emergent medical and surgical entities, but, also, it served as trigger and contributor for numerous apparently unrelated ailments such as arterial and venous thromboembolic complications. Additional risk factors for these thrombotic traits may be concurrent (known or unknown) malignancies, including at hepatic level. Among these, cholangiocarcinoma (CCA), a rare cancer of intra- and extra-hepatic biliary ducts, represents a very aggressive condition that typically associates local and distant advanced stages on first presentation requiring a prompt diagnosis and a stratified management. This neoplasia has been reported to present a large spectrum of paraneoplastic syndromes in terms of dermatologic, renal, systemic, neurologic, endocrine, and cardiovascular settings, that, overall, are exceptional in their epidemiologic impact when compared to other cancers. Our aim was to introduce a most unusual case of CCA-associated distant thrombosis in a male adult who initially was considered to experience COVID-19-related thrombotic features while having a history of obesity and bariatric surgery. This is a hybrid type of paper: this clinical vignette is accompanied by two distinct sample-focused analyses as a basis for discussion; they each had different methods depending on their current level of statistical evidence. We only included English-published articles in PubMed, as follows: Firstly, we conducted a search of reports similar to the present case, regarding distant vein thrombosis in CCA, from inception until the present time. We performed a literature search using the keywords "cholangiocarcinoma", "thrombosis", and "Trousseau's syndrome" and identified 20 cases across 19 original papers; hence, the current level of evidence remains very low Secondly, we searched for the highest level of statistical evidence concerning the diagnosis of venous thrombosis/thromboembolism in patients who underwent COVID-19 infection (key search terms were "COVID-19", alternatively, "coronavirus", and "SARS-CoV-2", and "thrombosis", alternatively, "thromboembolism") and included the most recent systematic reviews and meta-analyses that were published in 2024 (from 1 January 2024 until 8 July 2024). After excluding data on vaccination against coronavirus or long COVID-19 syndrome, we identified six such articles. To conclude, we presented a probably unique case of malignancy with an initial manifestation consisting of recurrent superficial vein thrombosis under anticoagulation therapy, with no gastrointestinal manifestations, in a patient with a notable history for multiple episodes of SARS-CoV-2 infection and a prior endocrine (gastric) surgery. To our knowledge, this is the first identification of a CCA under these specific circumstances. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has affected all Sustainable Development Goals (SDGs), leading to setbacks in various Latin American countries. In Brazil, progress in technological development and the adoption of sustainable practices by organizations has been significantly hindered. Yet, there remains a limited understanding of the long-term impacts on the country's development, and a structured national plan for recovery and resuming progress toward the SDGs is lacking. This paper aims to investigate the repercussions of COVID-19 on SDGs 9 (industry, innovation, and infrastructure) and 12 (sustainable consumption and production) in the context of a latecomer country such as Brazil. This study adopted the Delphi-based scenario and Fuzzy Delphi approach and involved the participation of 15 sustainability experts with extensive experience in the Brazilian industrial sector. The findings elucidate the long-term impacts of the pandemic on these SDGs, focusing on Brazil's socioeconomic landscape and developmental challenges. The pandemic worsened pre-existing issues, hindering infrastructure modernization, technological investment, and sustainable practices. Insufficient research funding, industry modernization, and small business integration further impede progress. Additionally, the paper identifies implications for research, companies, and public policies, aiming to provide actionable insights for fostering sustainable development in the post-pandemic era. [ABSTRACT FROM AUTHOR]

The global impact of the COVID-19 pandemic has been profound, placing significant challenges upon healthcare systems and the world economy. The pervasive presence of illness, uncertainty, and fear has markedly diminished overall life satisfaction. Consequently, sentiment analysis has gained substantial traction among scholars seeking to unravel the emotional and attitudinal dimensions of this crisis. This research endeavors to provide a bibliometric perspective, shedding light on the principal contributors to this emerging field. It seeks to spotlight the academic institutions associated with this research domain, along with identifying the most influential publications in terms of both paper volume and h-index metrics. To this end, we have meticulously curated a dataset comprising 646 papers sourced from the ISI Web of Science database, all centering on the theme of sentiment analysis during the COVID-19 pandemic. Our findings underscore a burgeoning interest exhibited by the academic community in this particular domain, evident in an astonishing annual growth rate of 153.49%. Furthermore, our analysis elucidates key keywords and collaborative networks within the authorship, offering valuable insights into the global proliferation of this thematic pursuit. In addition to this, our analysis encompasses an n-gram investigation across keywords, abstracts, titles, and keyword plus, complemented by an examination of the most frequently cited works. The results gleaned from these endeavors offer crucial perspectives, contribute to the identification of pertinent issues, and provide guidance for informed decision-making. [ABSTRACT FROM AUTHOR]

This paper addresses the significant problem of identifying the relevant background and contextual literature related to deep learning (DL) as an evolving technology in order to provide a comprehensive analysis of the application of DL to the specific problem of pneumonia detection via chest X-ray (CXR) imaging, which is the most common and cost-effective imaging technique available worldwide for pneumonia diagnosis. This paper in particular addresses the key period associated with COVID-19, 2020–2023, to explain, analyze, and systematically evaluate the limitations of approaches and determine their relative levels of effectiveness. The context in which DL is applied as both an aid to and an automated substitute for existing expert radiography professionals, who often have limited availability, is elaborated in detail. The rationale for the undertaken research is provided, along with a justification of the resources adopted and their relevance. This explanatory text and the subsequent analyses are intended to provide sufficient detail of the problem being addressed, existing solutions, and the limitations of these, ranging in detail from the specific to the more general. Indeed, our analysis and evaluation agree with the generally held view that the use of transformers, specifically, vision transformers (ViTs), is the most promising technique for obtaining further effective results in the area of pneumonia detection using CXR images. However, ViTs require extensive further research to address several limitations, specifically the following: biased CXR datasets, data and code availability, the ease with which a model can be explained, systematic methods of accurate model comparison, the notion of class imbalance in CXR datasets, and the possibility of adversarial attacks, the latter of which remains an area of fundamental research. [ABSTRACT FROM AUTHOR]

This document is a comment on a review paper titled "Could Selenium Supplementation Prevent COVID-19? A Comprehensive Review of Available Studies." The authors of the comment are experienced selenium researchers who take issue with the assessments made in the review. They argue that the review is not comprehensive and fails to include important studies that support the association between selenium and COVID-19 outcomes. The authors also address specific criticisms made by the reviewers regarding their own work and highlight the importance of further research into the role of selenium in COVID-19. [Extracted from the article]

This document is an editorial from the journal Biomedicines, discussing a special issue on the latest research in post-COVID conditions. The COVID-19 pandemic has led to a significant increase in research, with a focus on managing acute cases and preventing the spread of the virus. However, there is now a growing concern about the development of long-lasting symptoms after the acute infection, known as long-COVID or post-COVID-19 condition. This special issue includes fourteen papers covering topics such as the treatment of post-COVID-19 condition, the impact of SARS-CoV-2 infection on neonates, risk factors for severe COVID-19, and the phenotyping of post-COVID pain. The papers discuss various treatment strategies, the potential transmission of the virus during pregnancy, risk factors for severe disease, and different types of post-COVID pain. Overall, this special issue provides valuable insights into the understanding and management of post-COVID conditions. [Extracted from the article]

The present paper investigates the relationship between stock prices, credit ratings, and ESG scores for banks internationally. First, it describes stock prices and ESG scores at an annual frequency, as well as stock price and credit risk at a daily frequency. The relationships between (a) stock price and credit rating returns with ESG score returns and (b) among ESG scores are examined by pairwise annual correlation, and daily correlations are examined between price and credit rating returns. Furthermore, Granger causality is used to examine the relationships between the following: (a) price and ESG score annual returns; (b) price and credit rating daily returns; and (c) total and pillar annual ESG scores. This study makes a significant contribution to the literature by providing a detailed temporal analysis using both annual and daily data frequencies, which is relatively rare in the field. There is evidence of statistically and empirically important relations in the form of pairwise correlations. The regressions reveal a low significance of few ESG score changes in explaining credit rating changes. A unique aspect of this paper is the comprehensive analysis of 16 granular ESG scores, including overall scores, pillar scores, and sub-scores, allowing for a multi-faceted understanding of how specific ESG factors impact financial metrics. We found evidence of the significance of COVID-19 in all research questions. Additionally, this paper highlights the impact of the COVID-19 pandemic on the relationships between ESG scores, credit ratings, and stock prices, offering timely insights into the heightened importance and volatility of ESG factors during crisis periods. Future research needs to shed more light on this relationship, however. [ABSTRACT FROM AUTHOR]

During the 2022 summer, Europe experienced heatwaves with record temperatures, and a study has argued that they caused about 62,000 deaths between 30 May and 4 September. The total number of excess deaths during the same period was about 137,000, indicating that the heatwaves were a substantial contributor. Not ruling out that explanation entirely, this paper argues that it was unlikely a strong cause. First, if the heatwaves were a strong cause of numerous deaths, one would assume that the older and deprived were relatively likely to die. However, during the 2022 summer heatwaves in England, which were claimed to have caused about 2900 deaths, the oldest age cohort did not have a higher excess death rate than the middle age cohort, and the excess death rate actually decreased with deprivation status. Moreover, Iceland had among Europe's highest excess death rates during the summer, which cannot be attributed to heatwaves. During June, July, and August 2022, comparable southern hemisphere countries furthermore had high excess death rates, which cannot be attributed to heatwaves either, as it was during their winter. Also, Europe's excess death rate was higher during the 2022–2023 winter than during the 2022 summer, and intuitively not attributed to heatwaves, but neither to cold weather, as that winter was abnormally mild. Finally, the paper discusses the puzzling issue that about 56% more women than men, relative to the population, presumably died from the heatwaves. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic disrupted economic processes and various facets of daily life, including education, necessitating adjustments to help society adapt to the temporary status quo, with Romanian educational institutions being profoundly affected, and a full transition to online learning was mandated by central authorities in March 2020. The paper's scope is to assess the sustainability of e-learning in Romanian higher education in the aftermath of the COVID-19 outbreak. The study was conducted on bachelor students from three Romanian universities through an online questionnaire with a sample size of 505 valid responses. This study aims to investigate the relationships between information quality (IQ), system quality (SQ), service quality (SEQ), and quality of life (QL) within an integrated model, based on the variables of the technology acceptance model (TAM) and performance models of information systems (IS). Specifically, the research explores how these factors, along with the mediating roles of perceived usefulness (PU) and perceived ease of use (PEOU), influence students' behavioral intention to adopt e-learning systems (BISE) and actual use of them (EUOES) as a sustainable solution for post-pandemic COVID-19 education. Partial least squares structural equation modeling (PLS–SEM) was the selected method for data analysis performed with SmartPLS 4.0 software. The research results demonstrated that PU and PEOU showed a positive correlation relationship and were significantly influenced by IQ, SQ, and QL in the educational setting. The study also revealed that PEOU and PU exerted a positive influence on students' behavioral intention to adopt e-learning systems (BISE) sustainably and on their actual use (EUOES). This study benefits universities and higher education institutions by providing insights into enhancing e-learning platforms and integrating technology effectively, as well as by supporting the formulation of sustainable online learning strategies beyond the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

New epidemics encourage the development of new mathematical models of the spread and forecasting of infectious diseases. Statistical epidemiology data are characterized by incomplete and inexact time series, which leads to an unstable and non-unique forecasting of infectious diseases. In this paper, a model of a conditional generative adversarial neural network (CGAN) for modeling and forecasting COVID-19 in St. Petersburg is constructed. It takes 20 processed historical statistics as a condition and is based on the solution of the minimax problem. The CGAN builds a short-term forecast of the number of newly diagnosed COVID-19 cases in the region for 5 days ahead. The CGAN approach allows modeling the distribution of statistical data, which allows obtaining the required amount of training data from the resulting distribution. When comparing the forecasting results with the classical differential SEIR-HCD model and a recurrent neural network with the same input parameters, it was shown that the forecast errors of all three models are in the same range. It is shown that the prediction error of the bagging model based on three models is lower than the results of each model separately. [ABSTRACT FROM AUTHOR]

This paper analyzes the effects of central bank interventions via large-scale purchases of government debt securities on the pricing of stock market indices. This study examines the effects of changes in the size of the Federal Reserve's balance sheet in three intervention scenarios: during the 2008–2013 period, the 2020–2022 period, and in the years between by using the instrumental variables three-stage least squares (3SLS) method for a time series approach, and calculates the effects of these interventions on each index in a fund of funds setup using the panel data strategy. This study confirms that large-scale purchases of government debt securities in response to the Great Recession and COVID-19 crises influenced the pricing of equity markets via their effect on the pricing of treasury bonds, with different degrees of sensitivity of each index to the effects on yields. Although the findings apply to the U.S. market, the results indicate that the pricing of small capitalization indices such as the Russell 2000 are less sensitive to changes in treasury yields caused by central bank interventions than large capitalization indices such as the DJIA. This research contributes to the understanding of financial asset pricing, particularly by identifying price distortions within equity market portfolios. [ABSTRACT FROM AUTHOR]

The global spread of Coronavirus (COVID-19) has prompted imperative research into scalable and effective detection methods to curb its outbreak. The early diagnosis of COVID-19 patients has emerged as a pivotal strategy in mitigating the spread of the disease. Automated COVID-19 detection using Chest X-ray (CXR) imaging has significant potential for facilitating large-scale screening and epidemic control efforts. This paper introduces a novel approach that employs state-of-the-art Convolutional Neural Network models (CNNs) for accurate COVID-19 detection. The employed datasets each comprised 15,000 X-ray images. We addressed both binary (Normal vs. Abnormal) and multi-class (Normal, COVID-19, Pneumonia) classification tasks. Comprehensive evaluations were performed by utilizing six distinct CNN-based models (Xception, Inception-V3, ResNet50, VGG19, DenseNet201, and InceptionResNet-V2) for both tasks. As a result, the Xception model demonstrated exceptional performance, achieving 98.13% accuracy, 98.14% precision, 97.65% recall, and a 97.89% F1-score in binary classification, while in multi-classification it yielded 87.73% accuracy, 90.20% precision, 87.73% recall, and an 87.49% F1-score. Moreover, the other utilized models, such as ResNet50, demonstrated competitive performance compared with many recent works. [ABSTRACT FROM AUTHOR]

This paper considers the articles presented in this Special Issue and argues that, in most developed education systems in Western countries, there have been four major shifts in how school education is understood and delivered over the course of human history, from a time when only the wealthy and privileged received an education to the present day. It tracks changes in school leadership since the 1980s, when a combination of efforts to improve the effectiveness of schools and efforts to decentralise schools led to self-managing schools and changed responsibilities for school leaders. It reflects on whether the recent impact of the COVID-19 pandemic on school communities may lead to a fifth major shift in school education. This article discusses four different school leadership approaches that have emerged in Western education since the 1980s, instructional leadership, transformational leadership, distributed leadership, and leadership for learning, and argues that of these four, leadership for learning would be the most appropriate leadership approach in a post-COVID-19 future. [ABSTRACT FROM AUTHOR]

Background: Tryptophan is widely present in foods such as peanuts, milk, and bananas, playing a crucial role in maintaining metabolic homeostasis in health and disease. Tryptophan metabolism is involved in the development and progression of immune, nervous, and digestive system diseases. Although some excellent reviews on tryptophan metabolism exist, there has been no systematic scientometric study as of yet. Methods: This review provides and summarizes research hotspots and potential future directions by analyzing annual publications, topics, keywords, and highly cited papers sourced from Web of Science spanning 1964 to 2022. Results: This review provides a scientometric overview of tryptophan metabolism disorder-triggered diseases, mechanisms, and therapeutic strategies. Conclusions: The gut microbiota regulates gut permeability, inflammation, and host immunity by directly converting tryptophan to indole and its derivatives. Gut microbial metabolites regulate tryptophan metabolism by activating specific receptors or enzymes. Additionally, the kynurenine (KYN) pathway, activated by indoleamine-2, 3-dioxygenase (IDO) and tryptophan 2, 3-dioxygenase, affects the migration and invasion of glioma cells and the development of COVID-19 and depression. The research and development of IDO inhibitors help to improve the effectiveness of immunotherapy. Tryptophan metabolites as potential markers are used for disease therapy, guiding clinical decision-making. Tryptophan metabolites serve as targets to provide a new promising strategy for neuroprotective/neurotoxic imbalance affecting brain structure and function. In summary, this review provides valuable guidance for the basic research and clinical application of tryptophan metabolism. [ABSTRACT FROM AUTHOR]

Two epidemics, a new coronavirus disease (hereafter COVID-19) and pine wilt disease (hereafter PWD) whose causal agent is the pine wood nematode Bursaphelenchus xylophilus, are similar in terms of disease spread, particularly in an important role of the latent carrier in the spread of the disease. In Japan, damage caused by PWD has gradually decreased over the past 40 years, not because of successful control of PWD, but because pine forests susceptible to pine wilt have been drastically reduced by the disease. Meanwhile, COVID-19, which was first identified in China in 2019, became a pandemic in 2020 and caused long-term disruptions to people's lives worldwide. Even after the declaration of the end of the emergency by the WHO in May 2023, the coronavirus continues to produce new variants and maintains the potential for new waves of infection. In this paper, I would like to discuss the issues of control measures for the forest disease PWD, especially for the measures against asymptomatic carrier trees, with reference to the efforts implemented for COVID-19, which is more closely related to human society. This is because an asymptomatic carrier has been a blind spot in conventional PWD control measures, and I believe that a fundamental review of control measures considering this aspect is essential, and understanding the similarities between COVID-19 management and PWD control can provide guidance on how to effectively deal with both human and plant epidemics. [ABSTRACT FROM AUTHOR]

Obesity, the current pandemic, is associated with alarming rises among children and adolescents, and the forecasts for the near future are worrying. The present paper aims to draw attention to the short-term effects of the excess adipose tissue in the presence of a viral infection, which can be life-threatening for pediatric patients, given that the course of viral infections is often severe, if not critical. The COVID-19 pandemic has been the basis of these statements, which opened the door to the study of the repercussions of obesity in the presence of a viral infection. Since 2003, with the discovery of SARS-CoV-1, interest in the study of coronaviruses has steadily increased, with a peak during the pandemic. Thus, obesity has been identified as an independent risk factor for COVID-19 infection and is correlated with a heightened risk of severe outcomes in pediatric patients. We sought to determine the main mechanisms through which obesity is responsible for the unfavorable evolution in the presence of a viral infection, with emphasis on the disease caused by SARS-CoV-2, in the hope that future studies will further elucidate this aspect, enabling prompt and effective intervention in obese patients with viral infections, whose clinical progression is likely to be favorable. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of air quality and climate variability during the first wave of COVID-19 associated with accelerated transmission and lethality in Wuhan in China and four European metropolises (Milan, Madrid, London, and Bucharest). For the period 1 January–15 June 2020, including the COVID-19 pre-lockdown, lockdown, and beyond periods, this study used a synergy of in situ and derived satellite time-series data analyses, investigating the daily average inhalable gaseous pollutants ozone (O3), nitrogen dioxide (NO2), and particulate matter in two size fractions (PM2.5 and PM10) together with the Air Quality Index (AQI), total Aerosol Optical Depth (AOD) at 550 nm, and climate variables (air temperature at 2 m height, relative humidity, wind speed, and Planetary Boundary Layer height). Applied statistical methods and cross-correlation tests involving multiple datasets of the main air pollutants (inhalable PM2.5 and PM10 and NO2), AQI, and aerosol loading AOD revealed a direct positive correlation with the spread and severity of COVID-19. Like in other cities worldwide, during the first-wave COVID-19 lockdown, due to the implemented restrictions on human-related emissions, there was a significant decrease in most air pollutant concentrations (PM2.5, PM10, and NO2), AQI, and AOD but a high increase in ground-level O3 in all selected metropolises. Also, this study found negative correlations of daily new COVID-19 cases (DNCs) with surface ozone level, air temperature at 2 m height, Planetary Boundary PBL heights, and wind speed intensity and positive correlations with relative humidity. The findings highlight the differential impacts of pandemic lockdowns on air quality in the investigated metropolises. [ABSTRACT FROM AUTHOR]

In recent years, COVID-19 and skin cancer have become two prevalent illnesses with severe consequences if untreated. This research represents a significant step toward leveraging machine learning (ML) and ensemble techniques to improve the accuracy and efficiency of medical image diagnosis for critical diseases such as COVID-19 (grayscale images) and skin cancer (RGB images). In this paper, a stacked ensemble learning approach is proposed to enhance the precision and effectiveness of diagnosis of both COVID-19 and skin cancer. The proposed method combines pretrained models of convolutional neural networks (CNNs) including ResNet101, DenseNet121, and VGG16 for feature extraction of grayscale (COVID-19) and RGB (skin cancer) images. The performance of the model is evaluated using both individual CNNs and a combination of feature vectors generated from ResNet101, DenseNet121, and VGG16 architectures. The feature vectors obtained through transfer learning are then fed into base-learner models consisting of five different ML algorithms. In the final step, the predictions from the base-learner models, the ensemble validation dataset, and the feature vectors extracted from neural networks are assembled and applied as input for the meta-learner model to obtain final predictions. The performance metrics of the stacked ensemble model show high accuracy for COVID-19 diagnosis and intermediate accuracy for skin cancer. [ABSTRACT FROM AUTHOR]

This paper focuses on the application of the Verhulst logistic equation to model in retrospect the total COVID-19 cases in Senegal during the period from April 2022 to April 2023. Our predictions for April 2023 are compared with the real COVID-19 data for April 2023 to assess the accuracy of the model. The data analysis is conducted using Python programming language, which allows for efficient data processing and prediction generation. [ABSTRACT FROM AUTHOR]

The social distancing measures in response to the COVID-19 pandemic have transformed people from social to isolated individuals. During that time, social media became a useful tool for satisfying people's need for social interaction. Previous systematic reviews, however, have focused largely on the negative impact of social media use and ignored the positive side. Hence, this systematic review examined the role of social media use in providing support—be it social, emotional or informational—during the pandemic. Four databases were systematically searched, and the selection procedure followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Protocol registration: PROSPERO (CRD42022367903). A total of 20 papers were deemed eligible for data extraction. The findings showed that active engagement on social media contributed significantly to maintaining social capital and collective resilience amidst social restrictions. The emotional support obtained from social media was proven effective in alleviating feelings of loneliness and isolation. Also, social media facilitated the rapid dissemination of information and the grassroots mobilization of support by overcoming bureaucratic hurdles and addressing urgent community needs. This review concluded by highlighting the transformative potential of social media in crisis contexts and suggesting implications for mental health interventions and community resilience strategies. [ABSTRACT FROM AUTHOR]

This paper aims to investigate how social media use and gender affect beliefs in conspiracy theories on COVID-19 and how these beliefs correlate with the frequency and patterns of their use, as well as the distribution of population density in rural, town, and urban areas. I collected data from Valcon Project surveys, analyzing the usage of social media by citizens from six European countries (Italy, Germany, France, Spain, Poland, and Ireland) on issues like the origin of the COVID-19 pandemic spread. The findings, which take into consideration gender and population density, suggest that different social media platforms affected such beliefs in different ways (platform association), and this effect is also mitigated by the specific content of such conspiracy theories (content association). [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine the relationship between corporate social responsibility (CSR) and earnings management in Gulf Cooperation Council (GCC)-listed companies. It specifically addresses the question of whether companies that practice greater corporate social responsibility are less likely to engage in earnings management practices. The study sample consisted of 300 firms listed between 2015 and 2021 on GCC bourses (Saudi Arabia, United Arab Emirates, Bahrain, Qatar, Oman, and Kuwait). In this study, we developed multiple linear regression models and collected data from the Bloomberg database, Refinitiv, annual reports, official firms' websites, and the GCC's bourse websites for the period from 2015 to 2021. In the pre-pandemic period, firms that engaged in corporate social responsibility activities were more likely to have fewer classification-shifting practices. During the pandemic era, however, this relationship became significantly positive, suggesting that firms' corporate social responsibility practices may be used to hide their opportunistic classification-shifting practices during difficult times, such as a pandemic. This paper presents a thorough investigation of how businesses may alter their behavior toward increasingly applied but understudied earnings management strategies and CSR practices during a difficult period such as a pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a significant impact on every individual in the United States. The launch of the COVID-19 vaccines is estimated to have averted millions of deaths and reduced over 18 million COVID-19-related hospitalizations. In September 2023, the updated 2023–2024 COVID-19 vaccine, which includes a monovalent component that corresponds to the omicron variant XBB.1.5, reflecting the predominant circulating variant at the time of strain selection, was approved and was recommended for use in all people ≥ 6 months of age. Despite this recommendation, the US uptake of the updated COVID-19 vaccines over the 2023–2024 season has been far from optimal, placing many people at unnecessary risk of severe COVID-19 outcomes. This paper provides an overview of the current state of COVID-19 in 2023–2024 and barriers to vaccine uptake. With the continued evolution of the virus, the potential for more virulent variants, reduced public acceptance of vaccination, and the potential barriers that contributed to low vaccine uptake are explored to provide solutions for improving COVID-19 protection for future seasons. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of how Spanish digital media reported income inequality during the first year of the COVID-19 pandemic. In this way, the goal was to study the framing of definition, contextual aspects, and depth. For this article, a tool was designed to analyse the content of the items. An analysis of news published by six digital media in Spain from March 2020 to February 2021 was conducted using content analysis. Within a sample of 2727 media stories in which there was a connection between the coronavirus and inequality, a stratified sample was used (n = 958) according to the content production by quarter and by media. The results of this study show that income inequality was the most common type of inequality reported in the media, and they cantered more on the micro level. Also, it appeared to be linked to the social gap and showed poverty as the main consequence. The frame was focused on social issues, international and national contexts, and expert sources. Finally, different levels of depth can be observed in the news items analysed, depending on the frame. [ABSTRACT FROM AUTHOR]

Global turbulence and uncertainty force civil servants and executors to optimise public finance distribution. The COVID-19 pandemic aligned with the necessity of assessing the efficiency of healthcare financing due to its capability in overcoming the negative consequences. The paper analyses the peculiarities of healthcare financing in 34 European countries and points out trends and changes in its structure and dynamics. It also realises cluster analysis to reveal models of healthcare financing and their specific features. Panel data regression analysis was used to assess the efficiency of healthcare financing within each cluster by clarifying the relationship between healthcare expenditures and public health outcome—life expectancy. The distributed lag model was also used to test for time lags between financial inflows in healthcare and its outcome. Empirical results highlight key tips for optimising healthcare financing and creating the benchmark model. [ABSTRACT FROM AUTHOR]

As a colossal developing economy, irrational, and inefficient trades broadly exist in China's stock market and are intensified by the once-in-a-century COVID-19 pandemic. This atypical but prominent event enhances systemic risk and requires a more effective analysis tool that adapts to the investors' sentiment and behavior. Based on the behavioral asset pricing model, this paper verifies the existence of noise traders in China's stock market, measures the intensity of the noise with the NTR indicator, and examines the market noise with IANM. Furthermore, the mechanism of how COVID-19 influences the market noise through investors' behaviors is analyzed with the event study method. The findings show that, based on 92 Chinese companies, the market noise significantly exists, and the noise is associated with psychological biases including over-confidence, herding effects and regret aversion. These biases are affected to varying degrees by COVID-19-related events, leading to notable implications for market stability and investor behavior during crises. Our study provides critical insights for policymakers and investors on managing market risks and understanding behavioral impacts during unprecedented events. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has exposed individuals to various risks, including job loss, income reduction, deteriorating well-being, and severe health complications and death. In Brazil and the U.S., as well as in other countries, the initial response to the pandemic was marked by governmental underestimation, leading to inadequate public health measures to curb the spread of the virus. Although progressively mitigated, this approach played a crucial role in the impacts on local populations. Therefore, the principal aim of this paper is to evaluate the impact of COVID-19 and, indirectly, of the policies adopted by the U.S. and the Brazilian governments to prevent pandemic diffusion on income distribution. Utilizing available microdata and employing novel econometric methods (RIF-regression for inequality measures) this study shows that growth in COVID-19 prevalence significantly exacerbates economic disparities. Furthermore, the impact of COVID-19 on inequality has increased over time, suggesting that this negative impact has been intensifying. In the U.S., results indicate that working from home, the inability to work, and barriers to job-seeking significantly increase inequalities. Although further data are necessary to validate the hypothesis, this preliminary evidence suggests that the pandemic has significantly contributed to increased inequality in these two countries already characterized by increasing polarization and significant social disparities. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak directly and severely threatens global public health. Non-drug interventions in response to the COVID-19 pandemic have significantly altered urban socioeconomic activity. Understanding the different levels of city resilience to the impact of COVID-19 on urban human activities is essential. In this paper, 35 large cities in China were selected as research areas, and based on NPP-VIIRS night light images, the spatial pattern changes in human activities during the epidemic period from the end of December 2019 to December 2022 were explored. The results are as follows: (1) In the first two months of the epidemic, the luminous value of large cities showed an extensive range of decline, and the decline in different urban functional places was different. (2) There is a significant positive correlation between the urban population and the luminous change value. The closer the relationship between urban places and human activities, the stronger the correlation between the population and the luminous change value of urban places. (3) In the middle and later stages of the epidemic, the night light value of all cities showed an upward trend, but there was a difference. (4) The increase in the number of confirmed cases in the middle and later stages of the epidemic could hardly lead to a significant decrease in the value of night light on a monthly scale unless the city had a relatively large area and a relatively strict lockdown policy in that month. This study will help inform future strategies and decisions to effectively combat epidemics and the construction of resilient cities. [ABSTRACT FROM AUTHOR]

Internships can foster educational alliances between industry (business environment) and academic institutions, which can facilitate both flexibility and accelerated innovation. The purpose of this research is to search for the factors that determine HRT through the implementation of the internship program among the students at the Democritus University of Thrace and reveal the correlation between the factors. Also, this paper investigated the impact of the COVID-19 Eras on human resource training (HRT) factors and, finally, investigated the correlation between the two variables "Recruitment in the specialization" and "COVID Eras". The sample of the research consisted of 1398 students at the DUTh who implemented internships during the academic years from 2015–2016 to 2021–2022. A questionnaire with 60 variables was created for data collection. A random sampling method was applied to collect the sample. From the results of the survey, ten factors were extracted for human resource training that explained 75.512% of the total variance, and for each one, Cronbach's Alpha reliability was tested, which was high. In detail, the factors revealed were Learning Outcomes, Efficacy, Emotional Commitment, Satisfaction, Participation, Empowerment, Role Ambiguity, Role Conflict, Supervisor, and Collaboration. From the results of the study, it was evident that HR training is a multidimensional concept and is a necessary condition for the competitiveness of the firms. Training can help to improve the flexibility of the firm, but also to motivate the staff by implementing multidisciplinary training programs. Overall, internship programs are beneficial for students to develop a wide range of skills, as the hands-on experience obtained enhances and supplements the theoretical learning from educational institutions. [ABSTRACT FROM AUTHOR]

At present, COVID-19 remains a public health concern due to the ongoing evolution of SARS-CoV-2 and its prevalence in particular countries. This paper provides an updated overview of the epidemiology and pathogenesis of COVID-19, with a focus on the emergence of SARS-CoV-2 variants and the phenomenon known as 'long COVID'. Meanwhile, diagnostic and detection advances will be mentioned. Though many inventions have been made to combat the COVID-19 pandemic, some outstanding ones include multiplex RT-PCR, which can be used for accurate diagnosis of SARS-CoV-2 infection. ELISA-based antigen tests also appear to be potential diagnostic tools to be available in the future. This paper also discusses current treatments, vaccination strategies, as well as emerging cell-based therapies for SARS-CoV-2 infection. The ongoing evolution of SARS-CoV-2 underscores the necessity for us to continuously update scientific understanding and treatments for it. [ABSTRACT FROM AUTHOR]

The aim of this paper is to provide a systematic insight into the socio-economic aspects of the last two economic crises in Slovenia: the Economic crisis between 2009 and 2013, and the COVID-19 crisis in 2020. A three-stage territorial model was developed as a theoretical tool for this study. The data for the analyses came from various statistical sources and from the available literature. The socio-economic aspects of both economic crises were analysed in 11 categories and at three territorial levels: macro (national), meso (regional) and micro (locational). Both economic crises differ fundamentally in many aspects. Compared to the Economic crisis, the COVID-19 crisis was much shorter and less severe, and had relatively little impact on the socio-economic structure of Slovenia and its regions. Both economic crises had some common features: reduction of interregional disparities and different development paths of regions during the crisis, as well as strong economic growth in the first year of recovery. The proposed model can be extended by additional territorial levels and by adding additional social and political-geographical aspects. [ABSTRACT FROM AUTHOR]

The twenty-first century has witnessed an extensive evolution in translation practice thanks to the accelerated progress in machine translation tools and software. With the increased scalability and availability of machine translation software empowered by artificial intelligence, translation students and practitioners have continued to show an unwavering reliance on automatic translation systems. Academically, there is little recognition of the need to develop machine translation skillsets amongst translation learners in English/Arabic translation programs. This study provides a systematic review of machine translation postediting with reference to English/Arabic machine translation. Using the Preferred Reporting Items for Systematic Review and Meta-Analysis, the paper reviewed 60 studies conducted since the beginning of the twenty-first century and classified them by different metrics to identify relevant trends and research gaps. The results showed that research on the topic has been primarily prescriptive, concentrating on evaluating and developing machine translation software while neglecting aspects related to translators' skillsets and competencies. The paper highlights the significance of postediting as an important digital literacy to be developed among Arabic translation students and the need to bridge the existing research and pedagogic gap in MT education. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive analysis of the social media posts of prefectural governors in Japan during the COVID-19 pandemic. It investigates the correlation between social media activity levels, governors' characteristics, and engagement metrics. To predict citizen engagement of a specific tweet, machine learning models (MLMs) are trained using three feature sets. The first set includes variables representing profile- and tweet-related features. The second set incorporates word embeddings from three popular models, while the third set combines the first set with one of the embeddings. Additionally, seven classifiers are employed. The best-performing model utilizes the first feature set with FastText embedding and the XGBoost classifier. This study aims to collect governors' COVID-19-related tweets, analyze engagement metrics, investigate correlations with governors' characteristics, examine tweet-related features, and train MLMs for prediction. This paper's main contributions are twofold. Firstly, it offers an analysis of social media engagement by prefectural governors during the COVID-19 pandemic, shedding light on their communication strategies and citizen engagement outcomes. Secondly, it explores the effectiveness of MLMs and word embeddings in predicting tweet engagement, providing practical implications for policymakers in crisis communication. The findings emphasize the importance of social media engagement for effective governance and provide insights into factors influencing citizen engagement. [ABSTRACT FROM AUTHOR]

The aim of this paper is to understand the long-COVID impact on cultural heritage organisations, and future research needed. COVID-19 was disruptive to cultural heritage socioeconomic activities across the world during 2020 and 2021. Whilst government intervention and changes from physical to digital engagement generally prevailed, the long-COVID impact on cultural heritage organisations, their people and users, buildings, and collections remains unknown. The extent, also, to which financing, curating, visiting, and volunteering patterns have changed is uncertain. Following the pandemic closures and associated support, cultural heritage organisations are facing continuing economic, social, political, environmental, technological, and organisational culture pressures. This research examines the existing academic literature, sector publications, annual reports and associated visitor information to understand whether cultural heritage organisations have long-COVID, whether they can survive another pandemic, and what further research is needed to be better prepared. Four case studies from the UK look at the visitor and financial impacts of COVID-19 on the British Library, the London Transport Museum, The Theatre Royal Drury Lane, and Kensington Palace. This paper contributes to heritage research by providing a deeper understanding of the impact that COVID-19 had on heritage, and how to proactively plan for similar future disruptions. The impact themes show that change did not result in a new normal but in the need for a new space, consisting of blended space (physical and digital), mixed space (indoors and outdoors), and community of practice space (isolated or cross-sector networking space). The literature highlights the significance of the sector coming together during the pandemic to share knowledge and provide support through its networks. It also highlights how important it is for such unity not to be lost but to be harnessed to support ongoing organisational sustainability and better preparedness for future crises. Finally, future research suggestions are proposed grouped into social, digital, financial, and operational research themes. [ABSTRACT FROM AUTHOR]

The informational domain related to COVID-19 reflects the degree of uncertainty and pace of evolution of the pandemic. This places a burden on peoples' searches for information to guide their choices, importantly including for COVID-19 vaccines. Thus, it is important for health communications that support vaccination campaigns to attenuate vaccine hesitancy to be accessible, including in terms of readability, and adapted to the evolving pandemic. This paper aims to understand internet searches on COVID-19 vaccination, specifically the mix of sources and readability of the sources over a two-year period (2021–2023) in Singapore, Hong Kong, and the Philippines, for search results in English, as English is a main language for each of these locations. The sources accessed through online searches in June 2021 and May 2023 were categorized by type of source and whether they were from one of the focal locations or elsewhere. The readability of information from web-search results was assessed using a set of readability tests (Flesch–Kincaid Reading Ease, Flesch–Kincaid Grade Level, Gunning Fog Index, Coleman–Liau Index, and Simple Measure of Gobbledygook Grade level). Over the two-year period there was an increase in government sources and reduction in mass media sources with distinct local patterns. Local government sources increased in Singapore whereas foreign government and multi-lateral organization sources increased in Hong Kong, with the Philippines being an intermediate pattern. In contrast to the changing mix of sources, the readability tests indicate a low proportion of URLs scoring within recommended readability thresholds across locations and types of sources over the two years. Information on COVID-19 vaccine development and deployment is an important part of health communications that includes internet search. The paper contributes to understanding health communications during a pandemic, including mix of local and non-local sources and contingency on local social and health context. [ABSTRACT FROM AUTHOR]

The author believes that the principles of statistical methods for vaccine safety can be divided into three categories: comparison of adverse event incidence rates between vaccinated and unvaccinated groups, analysis of incidentality in the vaccinated group, and a combination of both. The first category includes the cohort study; the second, the self-controlled risk interval design (SCRI); and the third, the self-controlled case series method. A single p-value alone should not determine a scientific conclusion, and analysis should be performed using multiple statistical methods with different principles. The author believes that using both the cohort study and the SCRI for analysis is the best method to assess vaccine safety. When the cohort study may not detect a significant difference owing to a low incidence rate of an adverse event in the vaccinated group or a high one in the unvaccinated group, the SCRI may detect it. Because vaccines must have a higher level of safety than the pharmaceuticals used for treatment, vaccine safety is advisable to be assessed using methods that can detect a significant difference even for any value of the incidence rate of an adverse event. The author believes that the analyses of COVID-19 vaccine safety have areas for improvement because the proportion of papers that used the cohort study and the SCRI was negligible. [ABSTRACT FROM AUTHOR]