YouTube as a Source of Educational Content in Teenagers' Learning Practices

YouTube is one of the most popular online social spaces nowadays combining features of both a huge repository of information and a social networking service. Millions of people use this video-sharing platform daily. Entertainment (sports, comedy, music, movie trailers), information seeking (missed news, product reviews, research on a specific topic), and educational purposes (how-to videos, learning math, or tactics for video games) were discussed as main motivational aspects for watching YouTube videos (Lagger et al. 2017). Usage of YouTube for educational purposes became particularly relevant for teenagers as a support for their home-schooling. Our goal is to find out what strategies teenagers use to find relevant educational content on the service and how important this content was for their everyday learning practices before and during the COVID pandemic. We analyzed online behavior of 34, 14 to 15-year old teenagers (47% male) who took part in a long-term adventure trip with digital media left aside. We gathered quantitative data seven months before the trip (March 2019), just before the trip (October 2019), on the last day of the trip (April 2020), and five months after the trip (September 2020). We also conducted in-depth interviews with nine teenagers, who named YouTube as their favourite online service. Our intention is now to conduct nine additional interviews with the same teenagers to see whether their everyday learning practices changed within the last year. Implications drawn from this study, further research perspectives, and limitations will be presented and discussed. © The Authors, (2022). All Rights Reserved. No reproduction, copy or transmission may be made without written permission from the individual authors.

Changes in mobility patterns and the switching roles of second homes as a result of the first wave of COVID-19

The COVID-19 pandemic has already had significant impact on tourist flows worldwide. The requirements of safe models of tourism in the time of COVID-19, avoiding crowded localities and providing individual types of accommodation, can largely be met in second homes. This study aims to examine whether and how the COVID-19 pandemic and related restrictions impacted the usage patterns of second homes in terms of: (1) the number of visits and length of stay, (2) the purpose of the second-home utilisation. An integral part of the study was to recognise how these new and existing im/mobilities were determined by a range of personal, social, contextual, and relational factors. The data collected from direct interviews and online surveys was tested using sign and Wilcoxon tests, while the interactive classification tree (C&RT) model was used to explain the reasons for changing or maintaining an existing second-home usage pattern. The research results showed that for most second-home owners their home-usage pattern remained the same as in 2019. If it changed, it was more common to extend the stay by moving in, working at a distance, or commuting to work, rather than to shorten the stay at the second home. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

Correlation Analysis of Usage Pattern in Home Appliance with Boosting Algorithm

Energy consumption in the home increases recently due to the extremely hot or cold weather. Because of COVID 19, many people stay in the home and energy consumption in the home is increasing very much. Moreover, many homes are using new electric home appliances such as dishwasher or washer dryer which consumes much electric energy for a long duration. To reduce electric energy consumption and use energy more efficiently, the usage pattern of the home appliance should be analyzed. In the paper, we propose a pattern analysis method of the home appliance using Boosting technique. Boosting method is a sort of ensemble machine learning algorithm and is based on the decision tree. The correlation between home appliance usage can be analyzed with the result of feature importance in boosting algorithm. To verify the method, we analyzed the electric usage record in the UK with boosting algorithm. © 2022 IEEE.

Contrasting the Expectations and Experiences Related to Mobile Health Use for Chronic Pain: Questionnaire Study.

BACKGROUND: Chronic pain is a prolonged condition that deteriorates one's quality of life. Treating chronic pain requires a multicomponent approach, and in many cases, there are no "silver bullet" solutions. Mobile health (mHealth) is a rapidly expanding category of solutions in digital health with proven potential in chronic pain management. OBJECTIVE: This study aims to contrast the viewpoints of 2 groups of people with chronic pain concerning mHealth: people who have adopted the use of mHealth and those who have not. We highlight the benefits of mHealth solutions for people with chronic pain and the perceived obstacles to their increased adoption. We also provide recommendations to encourage people to try mHealth solutions as part of their self-care. METHODS: The Prolific crowdsourcing platform was used to collect crowdsourced data. A prescreening questionnaire was released to determine what type of pain potential participants have and whether they are currently using mHealth solutions for chronic pain. The participants were invited based on their experience using mHealth to manage their pain. Similar questions were presented to mHealth users and nonusers. Qualitative and quantitative analyses were performed to determine the outcomes of this study. RESULTS: In total, 31 responses were collected from people (aged 19-63 years, mean 31.4, SD 12.1) with chronic pain who use mHealth solutions. Two-thirds (n=20, 65%) of the users identified as female and 11 (35%) as male. We matched these mHealth users with an equal number of nonusers: 31 responses from the pool of 361 participants in the prescreening questionnaire. The nonusers' ages ranged from 18 to 58 years (mean 30.8, SD 11.09), with 15 (50%) identifying as female and 15 (50%) as male. Likert-scale questions were analyzed using the Mann-Whitney-Wilcoxon (MWW) test. Results showed that the 2 groups differed significantly on 10 (43%) of 23 questions and shared similar views in the remaining 13 (57%). The most significant differences were related to privacy and interactions with health professionals. Of the 31 mHealth users, 12 (39%) declared that using mHealth solutions has made interacting with health or social care professionals easier (vs n=22, 71%, of nonusers). The majority of the nonusers (n=26, 84%) compared with about half of the users (n=15, 48%) expressed concern about sharing their data with, for example, third parties. CONCLUSIONS: This study investigated how mHealth is currently used in the context of chronic pain and what expectations mHealth nonusers have for mHealth as a future chronic pain management tool. Analysis revealed contrasts between mHealth use expectations and actual usage experiences, highlighting privacy concerns toward mHealth solutions. Generally, the results showed that nonusers are more concerned about data privacy and expect mHealth to facilitate interacting with health professionals. The users, in contrast, feel that such connections do not exist.

Influence of the sociodemographic profile of hunters on the knowledge and use of faunistic resources

Background Hunting wild animals is essential for nutrition, clothing, predator control and disease treatment. As part of a system based on food choices and uses, it is influenced by ecological, economic and sociocultural patterns. In this context, the aim is to identify the game fauna of interest in the Brazilian semiarid region;indicate the methods, uses, patterns of choices and cultural importance of the fauna and identify which sociodemographic variables influence the knowledge and use of faunal resources. Methods Information on hunting and fauna use was obtained through semi-structured interviews, complemented with free interviews and informal conversations. The cultural importance of the species was calculated through the current use value. The generalized linear model was created to verify whether the sociodemographic profile of hunters influences the knowledge and use of game species. Results The results showed a representativeness of 56 species. The group of birds was the most representative in terms of taxonomic richness (48.2%), followed by the group of mammals (26.8%), reptiles (21.4%) and amphibians (3.6%). The animals mentioned are used for food, trade, control hunting (slaughter of animals considered invaders of property or harmful to humans), pets, zootherapy and ornamentation. Sociodemographic variables shaped the knowledge of faunal resources, in which the age of hunters showed a negative correlation with the number of known species. Conclusions The meaning and forms of use attributed to each species depend on ecological, economic and sociocultural factors, which dictate the relationship between human communities and natural resources. Socioeconomic variables shape hunting patterns in all its aspects, whether in perception that hunters have of the resources, forms of use and utilization of hunting strategies.

Relative synonymous codon usage of ORF1ab in SARS-CoV-2 and SARS-CoV.

BACKGROUND: COVID-19, as a novel coronavirus disease caused by new coronavirus SARS-CoV-2, spreads all over the world, and brings harm to human in many countries. Humans suffered a lot from both SARS-CoV-2 now and by SARS-CoV in the year 2003. It is important to understand the differences and the relationships between these two types of viruses. OBJECTIVE: To compare relative synonymous codon usage of ORF1ab gene in SARS-CoV-2 and SARS-CoV, relative synonymous codon usage of their genomes are studied in this paper from the bioinformatics perspective. METHODS: The ORF1ab gene, which is an important non-structural polyprotein coding gene and now used for nucleic acid detection markers in many measurement method, in both SARS-CoV-2 (30 strains) and SARS-CoV (20 strains) are considered to be the research object in the present paper. The relative synonymous codon usage values of the ORF1ab gene are calculated to characterize the differences and the evolutionary characteristics among 50 strains. RESULTS: There is a significant difference between SARS-CoV and SARS-CoV-2 when the relative synonymous codon usage value of ORF1ab genes is concerned. The results suggest that codon usage pattern of SARS-CoV is more similar to human than that of the SARS-CoV-2, and that the inner difference in SARS-CoV-2 strains is larger than that of SARS-CoV, which denote the larger diversity exits in the SARS-CoV-2 virus. CONCLUSION: These results show that the relative synonymous codon usage values in the coronavirus could be used for further research on their evolutionary phenomenon.

Characterization of codon usage pattern in SARS-CoV-2.

The outbreak of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed significant threats to international health. The genetic traits as well as evolutionary processes in this novel coronavirus are not fully characterized, and their roles in viral pathogenesis are yet largely unknown. To get a better picture of the codon architecture of this newly emerging coronavirus, in this study we perform bioinformatic analysis, based on publicly available nucleotide sequences of SARS-CoV-2 along with those of other members of human coronaviruses as well as non-human coronaviruses in different hosts, to take a snapshot of the genome-wide codon usage pattern of SARS-CoV-2 and uncover that all over-represented codons end with A/U and this newly emerging coronavirus has a relatively low codon usage bias, which is shaped by both mutation pressure and natural selection. Additionally, there is slight variation in the codon usage pattern among the SARS-CoV-2 isolates from different geo-locations. Furthermore, the overall codon usage pattern of SARS-CoV-2 is generally similar to that of its phylogenetic relatives among non-human betacoronaviruses such as RaTG13. Taken together, we comprehensively analyze the characteristics of codon usage pattern in SARS-CoV-2 via bioinformatic approaches. The information from this research may not only be helpful to get new insights into the evolution of SARS-CoV-2, but also have potential value for developing coronavirus vaccines.