Automatic Text Summaration of COVID-19 Scientific Research Topics Using Pre-trained Model from HuggingFace®

By identifying and extracting relevant information from articles, automated text summarizing helps the scientific and medical sectors. Automatic text summarization is a way of compressing text documents so that users may find important information in the original text in less time. We will first review some new works in the field of summarizing that use deep learning approaches, and then we will explain the "COVID-19" summarization research papers. The ease with which a reader can grasp written text is referred to as the readability test. The substance of text determines its readability in natural language processing. We constructed word clouds using the abstract's most commonly used text. By looking at those three measurements, we can determine the mean of "ROUGE-1", "ROUGE-2", and "ROUGE-L". As a consequence, "Distilbart-mnli-12-6" and "GPT2-large" are outperform than other. <br>

Automatic Text Summaration of COVID-19 Scientific Research Topics Using Pre-trained Model from HuggingFace®

By identifying and extracting relevant information from articles, automated text summarizing helps the scientific and medical sectors. Automatic text summarization is a way of compressing text documents so that users may find important information in the original text in less time. We will first review some new works in the field of summarizing that use deep learning approaches, and then we will explain the "COVID-19" summarization research papers. The ease with which a reader can grasp written text is referred to as the readability test. The substance of text determines its readability in natural language processing. We constructed word clouds using the abstract's most commonly used text. By looking at those three measurements, we can determine the mean of "ROUGE-1", "ROUGE-2", and "ROUGE-L". As a consequence, "Distilbart-mnli-12-6" and "GPT2-large" are outperform than other. <br>

Perceptions of Auditor Negligence: The Effects of Big Data Visualisations on Jurors’ Decisions

<p>This study analyses the effects of Big Data visualisations on jurors’ decisions in audit litigation cases. Specifically, the study investigates the effects of different types of Big Data visualisations (word clouds or bar graphs) and different sources of Big Data (emails or social media posts) on jurors’ perceptions of auditors’ work and the size of the negligence awards that jurors recommend. The study theorises that the emotions elicited and the reliability of the data used to create visualisations such as word clouds will have dramatic effects on jury verdicts in audit negligence trials. There is considerable literature to support this assertion. However, after data collection, it was discovered that jurors are not influenced by the emotions elicited by visualisations. Rather, participants were very sceptical of more novel types of visualisations, such as word clouds, but could be persuaded by the inherent emotions elicited and the reliability of the data if they found the visualisation useful.</p>

Perceptions of Auditor Negligence: The Effects of Big Data Visualisations on Jurors’ Decisions

<p>This study analyses the effects of Big Data visualisations on jurors’ decisions in audit litigation cases. Specifically, the study investigates the effects of different types of Big Data visualisations (word clouds or bar graphs) and different sources of Big Data (emails or social media posts) on jurors’ perceptions of auditors’ work and the size of the negligence awards that jurors recommend. The study theorises that the emotions elicited and the reliability of the data used to create visualisations such as word clouds will have dramatic effects on jury verdicts in audit negligence trials. There is considerable literature to support this assertion. However, after data collection, it was discovered that jurors are not influenced by the emotions elicited by visualisations. Rather, participants were very sceptical of more novel types of visualisations, such as word clouds, but could be persuaded by the inherent emotions elicited and the reliability of the data if they found the visualisation useful.</p>

Internal Tremors and Vibration Symptoms Among People with Post-Acute Sequelae of SARS-CoV-2: A narrative review of patient reports

To introduce the perspective of patients who have PASC with vibrations and tremors as a prominent component, we leveraged the efforts by Survivor Corps, a grassroots COVID-19 patient advocacy group, to gather information from people in their Facebook group suffering from vibrations and tremors. Survivor Corps collected 140 emails and 450 Facebook comments from members. From the emails, we identified 22 themes and 7 broader domains based on common coding techniques for qualitative data and the constant comparative method of qualitative data analysis. Facebook comments were analyzed using Word Clouds to visualize frequency of terms. The respondents’ emails reflected 7 domains that formed the basis of characterizing their experience with vibrations and tremors. These domains were: (1) symptom experience, description, and anatomic location; (2) initial symptom onset; (3) symptom timing; (4) symptom triggers or alleviators; (5) change from baseline health status; (6) experience with medical establishment; and (7) impact on people’s lives and livelihood. There were 22 themes total, each corresponding to one of the broader domains. The Facebook comments Word Cloud revealed that the 10 most common words used in comments were: tremors (64), covid (55), pain (51), vibrations (43), months (36), burning (29), feet (24), hands (22), legs (21), back (20). Overall, these patient narratives described intense suffering, and there is still no diagnosis or treatment available.

Capturing Twitter Negativity Pre- vs. Mid-COVID-19 Pandemic: An LDA Application on London Public Transport System

The coronavirus pandemic has affected everyday life to a significant degree. The transport sector is no exception, with mobility restrictions and social distancing affecting the operation of transport systems. This research attempts to examine the effect of the pandemic on the users of the public transport system of London through analyzing tweets before (2019) and during (2020) the outbreak. For the needs of the research, we initially assess the sentiment expressed by users using the SentiStrength tool. In total, almost 250,000 tweets were collected and analyzed, equally distributed between the two years. Afterward, by examining the word clouds of the tweets expressing negative sentiment and by applying the latent Dirichlet allocation method, we investigate the most prevalent topics in both analysis periods. Results indicate an increase in negative sentiment on dates when stricter restrictions against the pandemic were imposed. Furthermore, topic analysis results highlight that although users focused on the operational conditions of the public transport network during the pre-pandemic period, they tend to refer more to the effect of the pandemic on public transport during the outbreak. Additionally, according to correlations between ridership data and the frequency of pandemic-related terms, we found that during 2020, public transport demand was decreased while tweets with negative sentiment were being increased at the same time.

Experience of Physical Therapy Students Mentoring Older Adults with Health Literacy Tools

Health literacy is a top priority for Healthy People 2030. Healthy People 2030 defines personal health literacy as “the degree to which individuals have the ability to find, understand, and use information and services to inform health-related decisions and actions for themselves and others.” The purpose is to understand the experience of physical therapy students using health literacy tools with older adults to promote the adoption of health literacy tools in healthcare encounters. This project analyzes the reflection responses from students using qualitative methods. The qualitative methods included student reflection papers, word clouds, and focus groups. Twelve students participated in focus groups/ reflections. Thirty-seven students participated in word clouds. Health literacy tools included plain language, teaching teach back and “Ask me 3”®. Students were taught by student leaders and faculty about the meaning of health literacy and oral communication tools. Pairs of students provided health education with health literacy tools to older adults. Students then participated in a small group reflection to create word clouds. Students answered questions and provided five words that best answer each question. Students believed the benefits of health literacy tools for older adults includes better learning, participation and engagement. Reasons to use health literacy in the future were improved older adult independence, education and adherence. Students completed reflections and interviews at the end of the year to detail their experience with the health literacy tools. The pedagogical approach highlighted the value of experiential learning for the students while mentoring older adults.

What Matters Most in Life? A German Cohort Study on the Sources of Meaning and Their Neurobiological Foundations in Four Age Groups

Existing work in the field of positive psychology suggests that people can draw meaning from a variety of sources. The present study aimed to identify the most important sources of meaning and to explore the role of age and neural adaptation processes in this context. As part of a large German cohort study, 1,587 individuals between 12 and 94 years were asked to provide a maximum of five responses to the question “What matters most to you in life?” We divided the study population into four age groups and analyzed the obtained answers qualitatively and quantitatively using (1) word clouds and (2) frequency comparisons based on a summarizing content analysis. A chi-squared test was used to test the observed differences between age groups. Identified sources of meaning could be clustered into 16 main and 76 subcategories, with relationships (by 90% of respondents) and health and well-being (by 65% of respondents) being the most frequently named main categories, followed by a good living environment (by 28%), (leisure) time (by 26%), and work (by 24%). The study revealed some remarkable age-related patterns. While the importance of partnership increased with age, social networks were less important to older individuals. We also found that, for example, the importance of self-realization, success and career decreased with age, while the opposite was true for life satisfaction and peace and harmony. Security was most important to individuals in the two middle age groups between 30 and 69 years. The study advances our understanding of meaning across various ages by showing that individuals of different ages perceive different things as meaningful to them. Interpreting our results in the light of a neurobiological model of motivation systems, we argue that neural adaptation processes may play an important role in the (changing) perceptions of meaning throughout life.

Factors and consumer attitudes that affect the sustainable management of used mobile phones: A repertory grid analysis

<p>Used mobile phones with their small size but vast numbers, create a unique problem when it comes to managing the part they play in the creation of electronic waste (E-waste). Whilst previous studies have identified what consumers appear to be doing with their used mobile phones, there is also a need to better understand why they are doing it. This study investigated what factors appear to influence consumer attitudes towards adopting a more sustainable approach when dealing with their used mobile phones. A reuse, refurbish and recycle strategy was used as a lens to examine the current literature from which an initial model was developed. Using the repertory grid interview technique a group of participants was interviewed to try to determine their core beliefs when it came to managing their used mobile phones. Analysis of the interviews was completed using several analysis techniques including word clouds, percentage similarity analysis, and Honey’s content analysis. The results of the study indicate that consumers care about the effect of used mobile phones on the environment although the degree of concern appears to vary across individuals. In addition, it was identified that in general, consumers perceive reuse, refurbishing, and recycling all as positive ways to sustainably manage used mobile phones, whilst environmental awareness appears to play a significant role in engaging people with recycling and being a rational for storing used mobile phones. Finally, the study suggests that telecommunication providers when trying to improve engagement with takeback schemes should focus more on consumers’ environmental concerns and social norms, rather than financial incentives or promoting easy engagement.</p>

Factors and consumer attitudes that affect the sustainable management of used mobile phones: A repertory grid analysis

<p>Used mobile phones with their small size but vast numbers, create a unique problem when it comes to managing the part they play in the creation of electronic waste (E-waste). Whilst previous studies have identified what consumers appear to be doing with their used mobile phones, there is also a need to better understand why they are doing it. This study investigated what factors appear to influence consumer attitudes towards adopting a more sustainable approach when dealing with their used mobile phones. A reuse, refurbish and recycle strategy was used as a lens to examine the current literature from which an initial model was developed. Using the repertory grid interview technique a group of participants was interviewed to try to determine their core beliefs when it came to managing their used mobile phones. Analysis of the interviews was completed using several analysis techniques including word clouds, percentage similarity analysis, and Honey’s content analysis. The results of the study indicate that consumers care about the effect of used mobile phones on the environment although the degree of concern appears to vary across individuals. In addition, it was identified that in general, consumers perceive reuse, refurbishing, and recycling all as positive ways to sustainably manage used mobile phones, whilst environmental awareness appears to play a significant role in engaging people with recycling and being a rational for storing used mobile phones. Finally, the study suggests that telecommunication providers when trying to improve engagement with takeback schemes should focus more on consumers’ environmental concerns and social norms, rather than financial incentives or promoting easy engagement.</p>