Green Computing practice in ICT Based Method

Green computing is the system of implementing virtual computing technology that ensure minimum energy consumption and reduces environmental waste while using computer. ICT Based Teaching and Learning (ICT-BTL) tools can be implemented for effective and quality education especially during the pandemic like Covid 19. The researchers collect the data from original sources with their personal experiences and eagerness to understand the concept in depth and the applicability for prospective mankind. The results include positive impacts of developing and implementing the green computing for ICT-BTL tools in smart class rooms. ICT experts and entrepreneurs believe in initiating the virtual classroom operations for the betterment of future and protecting from the faster growing technology era in education and research industry. The present study can be initiated for developing modern classrooms and ICT based education system with 3D presentation, demonstration of practical examples in the realistic manner.

The Making of Homo Socialist: The Discursive Analysis of the Ideological Production of Class in China, 1949–1976

Based on a critique of the history project titled “Oral History of Peasants’ Ordinary Life in the Revolutionary Era of China,” this article provides an analysis of class ideology production from Land Reform Movement to the Cultural Revolution in China. Thirty years of socialist construction in China was based on the craft of making the Homo Socialist. The focus here is on how personal experiences were transformed into state-endorsed conduct via the discourse of class and class struggle. Over the course of the sociopolitical transformations leading to the Cultural Revolution, “class” changed from a socioeconomic designation to a political behavioral metaphor, and in the end a purely symbolic gesture; personal experiences were transformed from hallmarks of class privilege to virtual identification with imagined class struggle. And the peasants went from being “owners of bitterness” to “debtors of bitterness” on the way to becoming “sinners of the revolution”—who gradually submitted themselves to the regime in the name of revolution, liberation, and redemption. These transformations were realized through discursive practices connecting personally embodied experiences with the abstract Marxist theory of class and class struggle. Examining the shifting nature of class ideology production helps to explain how the Chinese Communist Party understood the effects of its governance and how people found class ideology meaningful to them, even when it reached the point of absurdity.

Pedagogical and Personal Experiences Motivating Indigenous Students to Pursue Medical Studies

When it comes to accessibility to healthcare and medical education, inequalities prevail within ethnically diverse populations, especially among Indigenous Peoples. The main objective of this qualitative study was to explore how Indigenous female medical students’ motivations played a role in their pursuit of a medical career. We use the Self-Determination theory to frame this study and conduct individual open-ended interviews with four female Indigenous students’ regarding their motivational sources for applying to medical school. We provide an illustrative scenario for each identified motivational source through a thematic analysis. Results revealed two main sources of motivations: (Jones et al., Acad Med, 2019, 94 (4), 512–519) pedagogical experiences (i.e., contextual factors at school, academic interests, and opportunities) and (Sloof et al., Med Educ, 2021, 55 (5), 653) personal experiences (i.e., family support and influence, and future career prospects). Indigenous students’ personal experiences were more prevalent and described autonomous forms of motivations, whereas sources of motivation that were pedagogically oriented reflected more controlled forms of motivations. Different types of motivations can be useful, but not sufficient for the tipping point when the time comes for medical school applications. Learning about specialized Indigenous streams for admissions played the most influential role in students’ decision-making to pursue medical studies. Promoting the visibility of the Indigenous stream coupled with the identification of different forms of motivation could be informative when outlining evidence-based recommendations with the aim of improving inequalities within the health professions.

“The Internal Police Officer Has Not Retired but Has Slowed Down”: Israeli Women Reframe Their Aging Experiences in the Second Half of Life

Compared with gains, losses have received a substantial amount of research and public attention. The present study aims to shed light on the positive gains associated with older age from the perspective of older women. Five focus groups with 19 Israeli women over the age of 54 were conducted. Trailers of three different films were used to stimulate discussion about old age and aging and allow for reflections on societal norms in light of personal experiences. Focus group interviews were analyzed thematically. Respondents identified four contexts, characterized by reframing their experiences against societal norms. These included gender stereotypes, physical appearance, interpersonal relations, and employment. This study represents an opening to a different discourse around old age, which is characterized by gains and possibilities brought about by changes in reframing one’s experiences, while distancing oneself and exerting free will vis à vis social norms.

Using a Machine Learning Approach to Monitor COVID-19 Vaccine Adverse Events (VAE) from Twitter Data

Social media can be used to monitor the adverse effects of vaccines. The goal of this project is to develop a machine learning and natural language processing approach to identify COVID-19 vaccine adverse events (VAE) from Twitter data. Based on COVID-19 vaccine-related tweets (1 December 2020–1 August 2021), we built a machine learning-based pipeline to identify tweets containing personal experiences with COVID-19 vaccinations and to extract and normalize VAE-related entities, including dose(s); vaccine types (Pfizer, Moderna, and Johnson & Johnson); and symptom(s) from tweets. We further analyzed the extracted VAE data based on the location, time, and frequency. We found that the four most populous states (California, Texas, Florida, and New York) in the US witnessed the most VAE discussions on Twitter. The frequency of Twitter discussions of VAE coincided with the progress of the COVID-19 vaccinations. Sore to touch, fatigue, and headache are the three most common adverse effects of all three COVID-19 vaccines in the US. Our findings demonstrate the feasibility of using social media data to monitor VAEs. To the best of our knowledge, this is the first study to identify COVID-19 vaccine adverse event signals from social media. It can be an excellent supplement to the existing vaccine pharmacovigilance systems.

Examining Cannabis, Tobacco, and Vaping Discourse on Reddit: An Exploratory Approach Using Natural Language Processing

Background: Perceptions of tobacco, cannabis, and electronic nicotine delivery systems (ENDS) are continually evolving in the United States. Exploring these characteristics through user generated text sources may provide novel insights into product use behavior that are challenging to identify using survey-based methods. The objective of this study was to compare the topics frequently discussed among Reddit members in cannabis, tobacco, and ENDS-specific subreddits.Methods: We collected 643,070 posts on the social media site Reddit between January 2013 and December 2018. We developed and validated an annotation scheme, achieving a high level of agreement among annotators. We then manually coded a subset of 2,630 posts for their content with relation to experiences and use of the three products of interest, and further developed word cloud representations of the words contained in these posts. Finally, we applied Latent Dirichlet Allocation (LDA) topic modeling to the 643,070 posts to identify emerging themes related to cannabis, tobacco, and ENDS products being discussed on Reddit.Results: Our manual annotation process yielded 2,148 (81.6%) posts that contained a mention(s) of either cannabis, tobacco, or ENDS with 1,537 (71.5%) of these posts mentioning cannabis, 421 (19.5%) mentioning ENDS, and 264 (12.2%) mentioning tobacco. In cannabis-specific subreddits, personal experiences with cannabis, cannabis legislation, health effects of cannabis use, methods and forms of cannabis, and the cultivation of cannabis were commonly discussed topics. The discussion in tobacco-specific subreddits often focused on the discussion of brands and types of combustible tobacco, as well as smoking cessation experiences and advice. In ENDS-specific subreddits, topics often included ENDS accessories and parts, flavors and nicotine solutions, procurement of ENDS, and the use of ENDS for smoking cessation.Conclusion: Our findings highlight the posting and participation patterns of Reddit members in cannabis, tobacco, and ENDS-specific subreddits and provide novel insights into aspects of personal use regarding these products. These findings complement epidemiologic study designs and highlight the potential of using specific subreddits to explore personal experiences with cannabis, ENDS, and tobacco products.

Applied Behavior Analysis as Treatment for Autism Spectrum Disorders: Topic Modeling and Linguistic Analysis of Reddit Posts

Background: It is critical for professionals to understand the discourse landscape within various online and social media outlets in order to support families of children with autism in treatment decision-making. This need is heightened when considering treatments that have garnered excitement and controversy, such as applied behavioral analysis (ABA) therapy.Method: The specific aims of this study were to identify the main themes in Reddit posts about ABA-based interventions for autism using topic modeling, to examine the linguistic aspects of Reddit conversations using the Linguistic Inquiry and Word Count (LIWC) analysis, and to examine the relationship between linguistic aspects and user category (i.e., pro- vs. anti-ABA vs. undecided, parent vs. professional vs. an individual with autism).Results: The topic modeling resulted in 11 themes that ranged across various elements, such as autism as a condition and its management, stakeholders, and consequences of autism and the support needed. The posts of individuals were focused on personal experiences and opinions as opposed to clinical and research information sharing. Linguistic analysis indicated that the posts reveal an intimate stance rather than an empirical stance.Conclusions: Results provide insight into perspectives of ABA. This type of research may help in developing and distributing appropriate and evidence-based information.

Dear John

Are 'Dear John' letters lethal weapons in the hands of men at war? Many US officers, servicemen, veterans, and civilians would say yes. Drawing on personal letters, oral histories, and psychiatric reports, as well as popular music and movies, Susan L. Carruthers shows how the armed forces and civilian society have attempted to weaponize romantic love in pursuit of martial ends, from World War II to today. Yet efforts to discipline feeling have frequently failed. And women have often borne the blame. This sweeping history of emotional life in wartime explores the interplay between letter-writing and storytelling, breakups and breakdowns, and between imploded intimacy and boosted camaraderie. Incorporating vivid personal experiences in lively and engaging prose – variously tragic, comic, and everything in between – this compelling study will change the way we think about wartime relationships.