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Examination of social worlds of risky drinking. Insights from Twitter data analysis
Get PDFRich nature of social media data offers a great opportunity to examine social worlds of its users. Further to wide range of topics being discussed on social media, alcohol-related content is prevalent on social media and studies have found an association between this content and increased consumption of alcohol, cravings for alcohol and addiction. This study analyses social media data to examine social worlds of risky drinking in Victoria, Australia. This study conducted a scoping literature review and two online surveys, one with the general community and the other with health professionals, to determine key words to search for on social media sites. These keywords were used in a social media analytics tool called Talkwalker to generate quantitative and qualitative data on the social media users and their conversations. NVIVO was used for developing categories and themes in a sample of 172 posts. A total of 1,021 results were obtained from Twitter. The main demographic group found to be involved in conversations about drinking alcohol on Twitter was young fathers aged 25–34 years. The culture of alcohol consumption in Victoria for Twitter users is reflective of Australia’s drinking culture within which risky drinking, and in particular binge drinking, is normalised. © 2024 Ahmed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Working speed optimization of the fully automated vegetable seedling transplanter
Get PDFThe purpose of this study was to determine the optimal operating speeds for a low-speed automated vegetable transplanter that utilized a modified linkage cum hopper-type planting unit. A biodegradable seedling plug-tray feeding mechanism is employed by the transplanter. Using kinematic simulation software, the planter unit’s movement was simulated under various operating conditions. The resulting trajectories were compared based on variables like plant spacing, soil intrusion area, soil intrusion perimeter, and horizontal hopper displacement in the soil. It was discovered that the best results occurred at 200, 250, and 300 mm/s and 40, 50, and 60 rpm combinations. Following testing in a soil bin facility, it was discovered that the ideal operating speeds performed well when transplanting pepper seedlings, with measured plant spacing that was nearly identical to the theoretical spacing. While the planting angle in various speed combinations was found to be significantly different, but still within acceptable bounds, the planting depth in each case did not differ statistically. The optimal speed combinations that were chosen resulted in minimal damage to the mulch film. The best speeds for the transplanter were found through this investigation, and these speeds can be used as a foundation for refining the other mechanisms in the transplanter. © the Author(s), 2024
Utility-based reinforcement learning : unifying single-objective and multi-objective reinforcement learning
Get PDFResearch in multi-objective reinforcement learning (MORL) has introduced the utility-based paradigm, which makes use of both environmental rewards and a function that defines the utility derived by the user from those rewards. In this paper we extend this paradigm to the context of single-objective reinforcement learning (RL), and outline multiple potential benefits including the ability to perform multi-policy learning across tasks relating to uncertain objectives, risk-aware RL, discounting, and safe RL. We also examine the algorithmic implications of adopting a utility-based approach. © 2024 International Foundation for Autonomous Agents and Multiagent Systems
Examining the importance of athletic mindset profiles for level of sport performance and coping
Get PDFThis study examined how growth and fixed mindset beliefs coexist within athletes to form distinct Athletic Mindsets; and whether these composite mindsets differentially predict level of sport performance and athletic coping skills. Athletes in Australia (N = 281, 52% male, M age = 32.21, SD = 14.40) completed self-report questionnaires measuring mindset, athletic coping, and level of sport performance. Cluster analysis of growth and fixed belief variables identified four distinct athletic mindset profiles: High-Growth/Low-Fixed, Low Growth /Low Fixed, Low Growth /High Fixed, and High-Growth/High Fixed. Analysis revealed that athletes with a HighG/LowF mindset were more likely to participate at higher levels of sport performance than athletes with the other three mindsets, and that this predictive effect was mediated by greater athletic coping skills. These findings indicate that growth and fixed mindset beliefs coexist and interact, and that possessing a HighG/LowF mindset benefits sports performance and coping. These findings illustrate support for the use of athletic mindset profiles to predict level of sport performance and inform coaching strategies. © 2023 International Society of Sport Psychology
Entrepreneurship and subjective wellbeing in China : exploring linkages and potential channels
Get PDFWe analyse the effect of entrepreneurship on subjective wellbeing in China. To do so, we use four waves of the nationally representative China Family Panel Studies (CFPS) longitudinal survey data. Employing a suite of quasi-experimental analytical procedures, we find that being an entrepreneur increases subjective wellbeing in China. Our estimates suggest that being an entrepreneur results in a 0.46 standard deviation higher subjective wellbeing than not being an entrepreneur. This finding is robust to different quasi-experimental methods. We also find that entrepreneurship enhances subjective wellbeing more among males and rural residents. Results on mediation analysis suggests that social and economic status are important channels through which entrepreneurship influences subjective wellbeing. © 2024 The Author
Perspectives of mental health clinicians on physical health of young people with early psychosis
Get PDFThe aim of this study is to explore the views and understanding of youth mental health clinicians with regard to the physical health of young people with early psychosis and their perspectives on lifestyle interventions improving the health and well-being of young people with early psychosis. Physical health disparities leading to premature mortality among people with mental illness are well evident in the literature. Mental health and physical health are directly correlated. The risk of poor physical health often begins before the onset of mental ill health. Young people with early psychosis are highly susceptible to poor physical health. A co-designed integrated approach focusing on early prevention and intervention in overall well-being and health is imminent for this targeted population to prevent poor physical health trajectory across the lifespan. Ten clinicians were recruited and participated in this study through semi-structured interviews. Five themes were identified: (i) Impact of early psychosis, (ii) Focus of care, (iii) Conversations around physical health, (iv) Co-location of specialist roles and (v) Health literacy. The findings of this study confirm the dimensional impact of early psychosis on the well-being and health of young people through the vicious cycle of early psychosis. Promotion of health literacy along with social connectedness and elements of self-determination, as well as having a prime focus on the individuals' experience in the journey of health promotion through participation in lifestyle interventions, has been identified as critically prominent. © 2023 The Authors. International Journal of Mental Health Nursing published by John Wiley & Sons Australia, Ltd
Psychometrics’ properties of sports commitment questionnaire-2 among racquet sports athletes in Malaysia
Get PDFBackground. Sports psychologists believe sports commitment is important to indicate the desire to continue or cease participation in sports from a psychosocial perspective. The Sports Commitment Questionnaire-2 (SCQ-2) has been developed and validated to investigate athletes’ commitment in sports settings in Western countries but not in Malaysia. Hence, it is essential to establish instrument validity before being widely used in Malaysia, especially among athletes. Objectives. This study aimed to evaluate the psychometric properties of the Sports Commitment Questionnaire-2 (SCQ-2) among Malaysian racquet sports athletes. Methods. This is a cross-sectional study, a total of 416 players (245 males/ 171 females, µ age=29.94±11.47) completed the SCQ-2 (Scanlan et al., 2016) consisting of 58 items measuring ten factors and two dimensions of sports commitment. We examined the psychometric properties of SCQ-2, by conducting Confirmatory Factor Analysis and examined discriminant validity and composite reliability (CR). Results. Initial fit indices of the hypothesized measurement model did not achieve satisfactory fit. But, after further model modification i.e., deleting 3 items resulted in good data fit (CFI=0.90, RMSEA=0.05, TLI=0.90, X²/df=2.14). Discriminant validity also met the suggested cutoff value (< 0.90). whereas CR values were acceptable for the subscales ranging from 0.77 to 0.89. Convergent validity (AVE, ranging from 0.50 to 0.58) and discriminant validity (<0.90) were also established. Conclusion. The SCQ-2 showed adequate validity and reliability which enable sports practitioners to access athletes' commitment in a sports context
“What parts of the plants do we eat, is this STEM?” – a study of Chinese kindergarten teachers' STEM professional development
No full textThe emerging value of STEM in society puts demands on Chinese kindergarten teachers to involve STEM teaching in play-based settings. As reported in the literature, societal expectations regarding kindergarten STEM education pose challenges for teachers, who often do not feel adequately prepared in STEM knowledge. This lack of preparation may indicate a lack of confidence and competence in STEM teaching among teachers. To study Chinese kindergarten teachers' confidence and competence in STEM teaching, we conducted an educational experiment where researchers and teachers collaborated on this problem. Our study identified that teachers experienced two micro-crises in STEM teaching. The first was “what to teach” and the second was “how to teach”. The findings highlighted that the primary challenges faced by the focused teachers were because a lack of STEM teaching experience, rather than lack of STEM knowledge as argued in the literature. The educational experiment created a social situation that supports teachers' STEM teaching experience in play. Through the educational experiment, STEM teaching becomes personally meaningful for teachers, which contributes to promoting their confidence and competence in STEM education
Enhancing telemarketing success using ensemble-based online machine learning
Get PDFTelemarketing is a well-established marketing approach to offering products and services to prospective customers. The effectiveness of such an approach, however, is highly dependent on the selection of the appropriate consumer base, as reaching uninterested customers will induce annoyance and consume costly enterprise resources in vain while missing interested ones. The introduction of business intelligence and machine learning models can positively influence the decision-making process by predicting the potential customer base, and the existing literature in this direction shows promising results. However, the selection of influential features and the construction of effective learning models for improved performance remain a challenge. Furthermore, from the modelling perspective, the class imbalance nature of the training data, where samples with unsuccessful outcomes highly outnumber successful ones, further compounds the problem by creating biased and inaccurate models. Additionally, customer preferences are likely to change over time due to various reasons, and/or a fresh group of customers may be targeted for a new product or service, necessitating model retraining which is not addressed at all in existing works. A major challenge in model retraining is maintaining a balance between stability (retaining older knowledge) and plasticity (being receptive to new information). To address the above issues, this paper proposes an ensemble machine learning model with feature selection and oversampling techniques to identify potential customers more accurately. A novel online learning method is proposed for model retraining when new samples are available over time. This newly introduced method equips the proposed approach to deal with dynamic data, leading to improved readiness of the proposed model for practical adoption, and is a highly useful addition to the literature. Extensive experiments with real-world data show that the proposed approach achieves excellent results in all cases (e.g., 98.6% accuracy in classifying customers) and outperforms recent competing models in the literature by a considerable margin of 3% on a widely used dataset. © 2018 Tsinghua University Press