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From Engagement to Concerns: Social Media Use Among a Sample of Australian Public Health Professionals
No full textIssue Addressed
Social media plays a crucial and diverse role in health promotion and public health. However, professionals often cite various concerns and a lack of knowledge of how to use it effectively. This study aimed to explore the use of social media by Australian health promotion and public health professionals.
Methods
A cross-sectional online survey was conducted between July and August 2023 with people aged 18 years or older currently working in a public health or health promotion role in Australia.
Results
One hundred and fifty eligible responses were obtained. Participants were predominantly female (85%) and aged between 18 and 39 years (50%). Most participants (40%) rated themselves as having an intermediate social media competency level, and 60% had never undertaken social media training. The majority used social media in their professional role (77%) for dissemination (68%), education (62%) and advocacy (54%) purposes. However, several concerns were highlighted, including the validity of information on social media (43%) and inappropriate online behaviour (40%).
Conclusions
Despite high levels of social media use for education and advocacy purposes, participants had concerns about using social media in a professional context and about the reliability and quality of information acquired through social media. Training on effectively navigating social media and verifying the accuracy of available information is worthy of future attention.
So What?
These findings will inform the development of a massive open online course that aims to equip health promotion and public health professionals with the skills to use social media for public health education and advocacy
Hybrid Deep Learning Model for Accurate Short-Term Electricity Price Forecasting
No full textAccurate short-term electricity price forecasting (STEPF) is critical for efficient energy market operations, guiding investment strategies, resource allocation, and consumer behavior. This study introduces a hybrid deep learning approach specifically designed to improve STEPF accuracy by leveraging historical Hourly Ontario Energy Price (HOEP) data from 2017 to 2019. The model integrates advanced techniques, including data preprocessing and denoising through a Stacked Denoising Autoencoder (SDAE), along with enhanced temporal modeling via Bidirectional Long Short-Term Memory (BiLSTM) and Gated Recurrent Unit (GRU) networks. By capturing the complex dynamics inherent in electricity pricing data, the proposed hybrid model significantly enhances forecasting accuracy. Trained on data from 2017 and 2018, with 2019 used for testing, the model achieves a strong correlation coefficient (R = 99.86%) and substantially lowers forecasting errors. Comparative evaluations against established forecasting methods highlight the model's superior performance. This work demonstrates the practical value of deep learning techniques in the energy sector, particularly in responding to the volatility of demand and supply in real-time electricity markets
From social innovation to institutional governance: Unveiling urban rooftop farming in Dhaka city using YouTube video analysis
Full text linkUrban sustainability relies on maintaining a delicate balance between humans and nature. Urban rooftop farming
(URF) has emerged as a potentially transformative practice in this regard. However, ensuring effective imple mentation of URF requires appropriate parameters that align with citizens’ ambitions. This study delves into
residents’ experiences practicing URF in Dhaka city, advocating for a separate policy to sustain this sector and
enhance the megacity’s overall environmental health. The research explores URF implementation in Dhaka and
scrutinizes urban residents’ engagement with this practice through YouTube video analysis. The study uses bi nary logistic regression to examine the associations between residents’ socio-demographic characteristics and
their motivations for URF participation. Additionally, K-means clustering techniques identify distinct groups of
urban gardeners based on their recommendations for government organizations. The findings reveal that a
predominantly male cohort with minimal URF training engages in the practice across diverse social strata,
resulting in varied motivations. Gardeners in mixed land-use neighborhoods exhibit robust motivation, notably
seeking URF policy guidelines and information hubs from government institutions. The study underscores the
importance of inclusive stakeholder perspectives in effective policy formulation. It calls for integrating insights
from government bodies, developers, and specialists to address URF within Dhaka city’s intricate urban fabric
The effectiveness of applying project-based and work-integrated learning educational strategies in engineering courses
Full text linkEngineering educational institutions consistently emphasise incorporating practical learning skills in their curriculum to enhance students' professional knowledge as well as cognitive knowledge. One of the teaching strategies to accomplish this goal is project-based learning (PBL) which promotes opportunities for students to develop solutions for real-world problems. Compared to direct instruction in traditional education, PBL provides opportunities for better student engagement as they are developing a product. Another educational approach that is receiving high attention from curriculum developers in engineering education is Work-integrated learning (WIL). The intended outcome of WIL is to teach students current work environment skills in the field and increase graduates' employability. PURPOSE OR GOAL: In this study, a teaching approach that includes both PBL and WIL was developed to investigate student experience. The model was reviewed to assess the inclusion of professional and cognitive skills in the learning outcomes, as well as the effectiveness of the educational model in improving the graduates' employability. We also evaluated the effectiveness of integrating real- world scenarios into educational programs through WIL and PBL methods and their impact on student learning success. APPROACH OR METHODOLOGY/METHODS: To incorporate real-world projects and learning environments, a collaboration with industry is essential. Therefore, the projects were designed in partnership with external industry stakeholders through Innovation Central Perth (ICP) and academic staff from Curtin University. ICP invites student expressions of interest to participate in finding solutions for industry problems in the form of internships, work experience, and campus-based projects. Successful candidates work directly with external stakeholders and academic mentors to ensure both professional and theoretical learning are incorporated into the project work. ACTUAL OR ANTICIPATED OUTCOMES: The study was conducted from 2021 to 2023. Throughout this two-year period, student learning success, measured through employability metrics, demonstrated a remarkable success rate of 90% employed. The program also shows a high level of satisfaction from companies involved, at 98%. Moreover, there was an increase in industry engagement with the university. CONCLUSIONS/RECOMMENDATIONS/SUMMARY: In conclusion, the ICP project case studies supported the effectiveness of the engineering educational strategies that integrate PBL and WIL. It promotes professional skills, student engagement and autonomy in knowledge construction. The study shows that this educational model improved students' critical thinking, collaboration, teamwork, and problem-solving skills in an authentic learning environment. According to the findings, it also directly contributes to the employability of the graduate
The Three Nonnormative Traits (TNT) and (dis-)liking in work and nonwork settings
No full textPast research on the Three Nonnormative Traits (TNT) has shown that high versus low levels of HEXACO honesty-humility, agreeableness, and conscientiousness – but not emotionality, openness to experience, and extraversion – distinguish who we like from who we dislike in free-text descriptions. This study of 297 participants extends this work by comparing descriptions of liked and disliked targets from work settings to those from nonwork settings. We found conscientiousness descriptors strongly distinguished liked from disliked work targets, whereas honesty-humility and agreeableness were relevant to both target types. We also replicated one trait-similarity effect for openness to experience, but only in the nonwork context. Exploratory analyses generally showed only small differences in liking and disliking between different subtypes of targets within the work or nonwork context
Flexural performance of composite prefabricated concrete sandwich panels with pultruded square GFRP tubular shear connectors
No full textThe flexural performance of composite prefabricated concrete sandwich panels (PCSP) with pultruded square glass fibre-reinforced polymer (GFRP) tubular shear connectors was examined in this study. Five PCSPs were tested under a static four-point bending load to reveal the influence of the direction and spacing of shear connectors, and thickness of the insulation layer on their flexural performance. All the tested panels exhibited flexural failure mode caused by vertical cracks on the bottom and top concrete wythes along the length of the panels. In addition to flexural failure, panels with combined tension-compression connectors showed punching failure of the compression connectors through the bottom concrete wythe. A panel with tension connectors showed 43 % and 26 % higher peak load-bearing capacity than the panel with straight and combined tension-compression connectors, respectively. The reduction in the spacing of shear connectors had a negligible influence on the strength of the panel. The cracking and ultimate strengths of the tested panels were theoretically estimated, showing a reasonable match with the experimental results. Moreover, the evaluation of the degree of composite action (DCA) in the panels revealed that the panel with tension connectors can achieve almost full composite action in yield and peak loading stages
Flexible grant schemes: a systematic scoping review
No full textBackground Governments can take a range of approaches to funding public health initiatives. One way is through grant-making to other organisations to support the delivery of programs, projects, services, or activities. There is a growing interest in non-traditional approaches to grant-making, including flexible grant schemes. While there is no universally accepted definition of flexible grant schemes, they are commonly understood as granting models that are, unlike traditional granting models, designed to be adaptable to the needs of grantees by allowing them more f lexibility in the use of funds, project timelines or objectives. Interest in flexible grant schemes is, in part, a response to criticisms of traditional granting models that are often deemed inadequate to support multi-sectoral and placebased responses to complex public health problems. To the best of our knowledge, there have been no attempts to map the available evidence on flexible grant schemes. Therefore, this systematic scoping review aimed to explore the literature on flexible grant schemes, interpretations of flexibility across the grant schemes, the extent to which and how grant schemes have been evaluated, and key factors associated with the perceived success of grant schemes. Methods A systematic search of academic and grey literature was conducted through eight databases. We followed a widely used five-phase methodological framework for scoping reviews and utilised PRISMA-ScR Checklist to enhance the methodological rigour of the review. Results Out of 10,368 screened documents, 38 publications met the inclusion criteria. Fourteen of the 38 publications were related to public health, and 28 were published after 2010. We found a lack of clarity and consistency in the interpretation of flexibility in the included studies. Three dominant, interrelated themes were identified: adaptation, autonomy, and coordination. Five publications were self-described as evaluations, a range of service-level or infrastructure outcomes were examined, and findings were generally positive. Seven factors were identified as being associated with the perceived success of flexible grant schemes: collaboration and partnership building, staff capacity, clear and effective communication, alignment among diverse stakeholders, uncertainty, accountability, and administrative burdens. Conclusion We found that the number of publications on flexible grant schemes has substantially increased since 2010. Although interest in flexible grant schemes has increased, there is a lack of clarity and inconsistent interpretations of ‘flexibility’. We suggest greater clarity in grant guidelines to improve communication and alignment across grantees and funders. The capacity of grantees and funders to implement and administer flexible grant schemes was identified as critical to their success, suggesting that investment in capacity development is needed
Open science 2.0: revolutionizing spatiotemporal data sharing and collaboration
No full textThe Spatial Data Lab (SDL) project is a collaborative initiative by the Center for Geographic Analysis at Harvard University, KNIME, Future Data Lab, China Data Institute, and George Mason University. Co-sponsored by the NSF IUCRC Spatiotemporal Innovation Center, SDL aims to advance applied research in spatiotemporal studies across various domains such as business, environment, health, mobility, and more. The project focuses on developing an open-source infrastructure for data linkage, analysis, and collaboration. Key objectives include building spatiotemporal data services, a reproducible, replicable, and expandable (RRE) platform, and workflow-driven data analysis tools to support research case studies. Additionally, SDL promotes spatiotemporal data science training, cross-party collaboration, and the creation of geospatial tools that foster inclusivity, transparency, and ethical practices. Guided by an academic advisory committee of world-renowned scholars, the project is laying the foundation for a more open, effective, and robust scientific enterpris
Predicting overbreak and underbreak in underground longhole stoping using meta-soft computing models
No full textEffective management of overbreak (OB) and underbreak (UB) in underground stope production is critical in minimising dilution and ore loss, directly impacting the productivity and efficiency of mining operations. This study aims to predict these phenomena prior to blasting by analysing individual drillholes and eight key variables including ring sequence, drillhole dip, breakthrough status, powder factor, number of primers, rock quality designation, actual drillhole deviation, and drillhole length. Although the initial linear regression models provided moderate predictive accuracy, advanced Machine Learning (ML) techniques significantly improved results. Boosted tree models and Artificial Neural Networks (ANN) showed significant improvements in predictive performance after hyperparameter tuning, with the ANN model reaching an R2 of 0.94067 and an RMSE of 0.65527. Additionally, eight different hybrid models were developed, producing R2 values ranging from 0.59 to 0.94, achieved using various hybrid modelling techniques, including weighted average, stacking, and combinations of ANN and boosted trees. Meta-models such as Random Forest (RF) and Gradient Boosting Machines (GBM) were utilised to improve accuracy even further. The best-performing hybrid ensemble stacking model, combining RF and GBM meta-models using a weighted average approach (HESM-RF-GBM), achieved the highest performance with an R2 of 0.94502 and an RMSE of 0.45203. This study highlights the potential of ML and advanced hybrid models in optimising OB and UB predictions, leading to reduced costs and improved operational efficiency in underground mining
On Various Applications of Blockchain Technology in Real Estate
Full text linkThis thesis investigates how blockchain can improve real estate by addressing inefficiencies in transactions and investment. It develops three systems: a timestamped registration platform, a tokenized investment model using Ethereum smart contracts, and a portfolio optimization model. The findings show that blockchain enhances transparency, reduces costs, and enables fractional ownership. This research contributes to PropTech 3.0 and provides practical frameworks for applying decentralized technologies in real estate finance and asset management