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Featured ApplicationThe present cross-sectional analysis aimed to evaluate the level of interest in oral and dental needs and teledentistry applications among the elderly, as well as whether COVID-19 pandemic outbreaks were influenced by real-time surveillance, using Google Trends. As the number of elderly dental patients continues to increase, there is a growing need for specific interventions that address the biological and psychological issues of this population. Teledentistry represents a healthcare delivery system that can overcome these problems, although the oral and dental care provision methods involved are still unknown to most people. Indeed, there is a need to raise awareness of the indications for teledentistry, the available interventions, and the potential benefits for the oral and dental care of elderly patients.Considering the increasing need for oral and dental care in the elderly, teledentistry has been proposed to improve the education of elderly patients in oral health maintenance and risk factor control, identify patients' concerns in advance, facilitate monitoring, and save time and money. The present cross-sectional analysis of Google search data through real-time surveillance with Google Trends aimed to determine Google users' interest in oral and dental needs and teledentistry applications in the elderly, and to compare search volumes before and after the COVID-19 outbreak. Extracted CVS data were qualitatively analyzed. Pearson and Spearman correlation analyses were performed between searches for "elderly” and "teledentistry”, and all the oral and dental needs and teledentistry applications. The Mann–Whitney U test compared search volumes in the 36 months before and after the beginning of the COVID-19 pandemic. Google users' interest in the elderly and related oral and dental needs was diffusely medium–high, while teledentistry and its applications were of lower interest. Interest in teledentistry and its applications was strongly related to interest in the older population, which is consistent with the assumption that older adults represent the population segment that could benefit most from these tools. A positive correlation was also found between searches for "Elderly” and searches for almost all oral and dental needs typical of the geriatric population. Search volumes increased significantly after the outbreak of the COVID-19 pandemic. More information about teledentistry should be disseminated to increase knowledge and awareness, especially among older patients, about its indications, applications, and advantages.
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Passenger flow prediction is of great significance in the operation and management of subways, especially in reducing energy consumption and improving service quality. Due to the impact of COVID-19, subway passenger flow fluctuates a lot, which makes passenger flow estimation or forecasting a very challenging task. This article mainly carries out two aspects of work to solve the task of subway passenger flow prediction under pandemic. First, this article introduces search engine data as a new data source and provides a systematic method to extract valid quires and search volumes that are closely associated with subway passenger flow under pandemic. Second, this article combines the fuzzy theory and neural network to propose a deep learning architecture called "deep spatiotemporal fuzzy neural network” to deal with the complex spatiotemporal features and uncertain external data of subway passenger flow prediction. Experiments on the actual dataset of the Beijing subway prove the superiority of the model and the effectiveness of search engine data in subway passenger flow forecasting.
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La "reinvención" de las ciudades, mediante el turismo masivo y la reconfiguración de sus barrios céntricos, ha transformado estas en espacios de consumo y entretenimiento. El objetivo del texto es reflexionar sobre cómo este proceso ha acarreado importantes externalidades negativas a sus ciudadanos, para a continuación, poner énfasis en los cambios que las restricciones de movilidad provocadas por la pandemia de la COVID-19 supusieron para los habitantes de dos ciudades españolas turistificadas, Barcelona y Madrid. También indaga sobre las posibles alternativas hacia un turismo post-COVID más sostenible e inclusivo. La metodología contempla una amplia revisión bibliográfica sobre los procesos de gentrificación y de turistificación y sus contradicciones, la búsqueda de datos oficiales sobre la evolución del turismo internacional -y español- durante los períodos prepandémico y pandémico, y la elaboración de cuadros y gráficos. Entre los resultados, destaca un análisis sobre lo que significó para los ciudadanos de estas ciudades, la restricción de la actividad turística: el aumento de su protagonismo en los espacios públicos, en los comercios locales y también en el mercado inmobiliario, usurpado en las últimas décadas, por los procesos de turistificación y gentrificación.Alternate :The "reinvention" of cities, through mass tourism and the reconfiguration of their downtown neighborhoods, has transformed them into spaces for consumption and entertainment. The objective of the text is to reflect on how this process has brought significant negative externalities to its citizens, and then, emphasize the changes that the mobility restrictions caused by the pandemia of the COVID-19 meant for the inhabitants of two Spanish tourist cities, Barcelona and Madrid. It also investigates possible alternatives towards more sustainable and inclusive postcovid tourism. The methodology contemplates a wide bibliographic review of the processes of gentrification and tourist and their contradictions, the search for official data on the evolution of international -and spanish- tourism during pre-pandemic and pandemic periods, and the elaboration of tables and graphics. Among the results, stands out an analysis of what the restriction of tourist activity meant for the citizens of these cities: the increase in their protagonism in public spaces, in local shops and also in the real estate market, usurped in recent decades, due to the processes of touristification and gentrification.
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Introduction: Sotrovimab is a monoclonal therapy authorized for emergency use (EUA) on May 26, 2021, by the US (FDA) for treatment of mild-to-moderate coronavirus disease (COVID-19) in adults and children > 12 years old). The drug showed positive viral testing in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and, reduced risk for progressing to severe COVID-19, including hospitalization or death1. Objective: This paper reviewed published data on safety of Sotrovimab 500mg in COVID-19 patients. Methods: The study based on reviewing published literature. Pubmed and FDA web was searched for data on Safety of Sotrovimab use in COVID-19 patients (May2021-May2022). Results: Gupta A et al2 reported among (n = 291 Sotrovimab group, n = 292 placebo group) mild diarrhea occurred in 5 cases (1%) in Sotrovimab group, compared to 1 case of moderate diarrhea, while diarrhea occurred in 3 patients in placebo group. One patient who received Sotrovimab had moderate dyspnea, an infusion-related reaction that was related to Sotrovimab. Hospitalization adverse events occurred in 2% of Sotrovimab group and in 6% in placebo group. No death or serious adverse events e.g., hematological disorders or liver damage were related to Sotrovimab. Further study by Gupta A et al3 for Sotrovimab (n = 528) or placebo (n = 529) reported that adverse events were infrequent and are similar between two groups (22% for Sotrovimab vs 23% for placebo);the most common events were diarrhea with Sotrovimab (n = 8;2%) and COVID-19 pneumonia with placebo (n = 22;4%). Kreuzberger N et al4 reported treatment with Sotrovimab may reduce the number of participants with oxygen requirement weaned in 3 days and risk of all-cause hospitalization or death without exhibiting significant adverse reaction. Fernandes G et al5 observed that following administration of Sotrovimab to kidney transplant recipients infected with Omicron variant, two patients required hospitalization for oxygen therapy. None were admitted to the intensive care unit or died. Conclusion: This review found limited number of safety studies of Sotrovimab in COVID-19, which reflects low numbers of publications. This is probably because of the Emergency utilization of drug and limitation of use in many countries. Lately, FDA US announced Sotrovimab is no longer authorized to treat COVID-19 in US due to increases in the proportion of COVID-19 cases caused by the Omicron variants6. Further data is needed to evaluate Sotrovimab safety in COVID-19 patients and examine risk-benefit, adverse events, and risk correlation to disease severity in patients with various risk factors.
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[...]this special issue highlights the most up-to-date research in this field. The paper “Dimensionality Reduction for the Internet of Things Using the Cuckoo Search Algorithm: Reduced Implications of Mesh Sensor Technologies” highlights a problem in the Internet of Things network and presents a unique cuckoo search-based outdoor data management system. [...]of the low-dimensional data, classification accuracy is improved, while complexity and expense are lowered. The results of the suggested method’s simulation demonstrated that using intrusion detection systems based on cloud-fog in the Internet of Things can be extremely effective in recognizing attacks with the least number of errors in this network.
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The past decade has witnessed a growth in the use of knowledge graph technologies for advanced data search, data integration, and query-answering applications. The leading example of a public, general-purpose open knowledge network (aka knowledge graph) is Wikidata, which has demonstrated remarkable advances in quality and coverage over this time. Proprietary knowledge graphs drive some of the leading applications of the day including, for example, Google Search, Alexa, Siri, and Cortana. Open Knowledge Networks are exciting: they promise the power of structured database-like queries with the potential for the wide coverage that is today only provided by the Web. With the current state of the art, building, using, and scaling large knowledge networks can still be frustratingly slow. This article describes a National Science Foundation Convergence Accelerator project to build a set of Knowledge Network Programming Infrastructure systems to address this issue.
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Most commonly, such measures have captured social capital: the resources that are rooted in social networks such as social connectedness, civic engagement, norms of reciprocity, and trust in others that facilitate cooperation for mutual benefit.1 Recently, health scholars have aggregated individual responses to national survey data to capture area-level attitudes of anti-Black racism, xenophobia, and homophobia to examine their associations with mortality.2-4 Other studies have used aggregate individual data from Google searches and tweets as indicators of prejudicial social environments.5,6 Questions remain about what a population-level measure of hope captures and how it should be applied in the future. [...]hope significantly increased in 2020. According to Riley et al., even before the pandemic levels of hope varied across the country, with some parts of the country experiencing declines in hope. In the past few years, the phrase "deaths of despair" has been used to describe the declines in US life expectancy and increases in deaths from suicide, drug overdose, and alcohol use.7 Despair-the absence of hope-has been linked to numerous poor health outcomes and increased mortality. [...]tracking despair has emerged as a barometer of risk of poor mental health, unhealthy behaviors, and preventable mortality.
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One of the largest citizen science projects in Africa is the Second Southern African Bird Atlas Project (SABAP2). SABAP2 is a follow-up project of the Southern African Bird Atlas Project (now labelled SABAP). The primary data collection period for the first bird atlas project was 1987 to 1991;it incorporated data from as far back as 1980, and in some regions included data until 1993, assembling a total of 7.2 million records of bird distribution. SABAP generated the Atlas of Southern African Birds in two volumes. Harrison et al. demonstrated that the SABAP database had become a valuable resource to four main user constituencies: environmental consultants, conservationists, research scientists, and birders. Academic research output (theses and papers) was summarised by Underhill;most of the 102 papers and 19 postgraduate theses listed had been based on SABAP data. Search results were manually scanned for relevance. The 'SABAP' search term alone returned 1190 results;however, as 'sabap' has alternative meanings in other languages, many results were not relevant.
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This paper examines the suitability of Google Trends data for the modeling and forecasting of interregional migration in Russia. Monthly migration data, search volume data, and macro variables are used with a set of univariate and multivariate models to study the migration data of the two Russian cities with the largest migration inflows: Moscow and Saint Petersburg. The empirical analysis does not provide evidence that the more people search online, the more likely they are to relocate to other regions. However, the inclusion of Google Trends data in a model improves the forecasting of the migration flows, because the forecasting errors are lower for models with internet search data than for models without them. These results also hold after a set of robustness checks that consider multivariate models able to deal with potential parameter instability and with a large number of regressors.
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Covid-19 had a major impact on people’s lives, including the fishing community. Mitigation strategies are needed in order to reduce the impact of Covid-19. This research was conducted in March 2021 at Sungai Kayu Village. This village is one of the coastal villages located in Sungai Apit District, Siak Regency, Riau Province. The purpose of this study is to identify structural and non-structural mitigation and analyze the mitigation strategies carried out by fishing households in Sungai Kayu Ara Village. The method used in this study using the Survey Method. The population was fishing households totaling 48 households. The technique of determining the respondents is by census, which takes all the population as respondents. Data was collected by means of observation, in-depth interviews, documentation, literature studies, and online searching of data and information. The data that used: qualitative descriptive analysis and Analytical Hierarchy Process (AHP). Structural and non-structural Covid-19 mitigation in Sungai Kayu Ara Village, Sungai Apit District, Siak Regency is more focused on implementing government policies stipulated by the Regent’s regulation on handling infectious diseases and the Regent’s regulation on the application of administrative sanctions for the enforcement of health protocols in handling infectious diseases. Mitigation strategies for fishermen households in Sungai Kayu Ara Village, Sungai Apit District, Siak Regency due to the main social engineering of the covid-19 pandemic are: Selling fish caught by fishermen online, receiving protection fund and empowering fishermen, owning a plantation business (alternative business), receiving social assistance and have saving and emergency fund.