Healthy together Victoria and childhood obesity study: effects of a large scale, community-based cluster randomised trial of a systems thinking approach for the prevention of childhood obesity among secondary school students 2014–2016

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Abstract

Background

Healthy Together Victoria (HTV) was a Victorian Government initiative that sought to reduce the prevalence of overweight and obesity through targeting chronic disease risk factors including physical activity, poor diet quality, smoking, and harmful alcohol use. The intervention involved a boosted workforce of > 170 local-level staff in 12 communities; employed to deliver system activation around health and wellbeing for individuals, families and communities. A cluster randomised trial (CRT) of a systems thinking approach to obesity prevention was embedded within HTV. We present the two-year changes in overweight and obesity and associated behaviours among secondary school students across Victoria, Australia.

Methods

Twenty-three geographically bounded areas were randomised to intervention (12 communities) or comparison (11 communities). Randomly selected secondary schools within each community were invited to participate in the trial in 2014 and 2016. Students in Grade 8 (aged approximately 13–15 years) and Grade 10 (aged approximately 15–16 years) at participating schools were recruited using an opt-out approach across July–September 2014 and 2016. Primary outcomes were body mass index (BMI) and waist circumference. Secondary outcomes were physical activity, sedentary behaviour, diet quality, health-related quality of life, and depressive symptoms. Linear mixed models were fit to estimate the intervention effect adjusting for child/school characteristics.

Results

There were 4242 intervention children and 2999 control children in the final analysis. For boys, the two-year change showed improvement in intervention versus control for waist circumference (difference in change: − 2.5 cm; 95% confidence interval [CI]: − 4.6, − 0.5) and consumption of sugar-sweetened beverages per day (< 1 serve: 8.5 percentage points; 95% CI: 0.6, 16.5). For girls, there were no statistically significant differences between conditions.

Conclusions

HTV seemed to produce favourable changes in waist circumference and sugar-sweetened beverage consumption for boys, however, no effect on BMI was observed. Although the HTV intervention was cut short, and the period between data collection points was relatively short, the changes observed in HTV contribute to the growing evidence of whole-of-community interventions targeting childhood obesity.

Trial registration

This trial is unregistered. The intervention itself was a policy setting delivered by government and our role was the collection of data to evaluate the effect of this natural experiment. That is, this study was not a trial from the classical point of view and we were not responsible for the intervention.

Modeling future (2021–2050) meteorological drought characteristics using CMIP6 climate scenarios in the Western Cape Province, South Africa

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Abstract

Consistent drought modelling under plausible shared socioeconomic–representative concentration pathways (SSP–RCPs) are crucial for effectively managing future drought risk in agricultural environments. The Western Cape (WC) is one of South Africa’s main agro-based provinces and faces a mounting threat of water insecurity due to recurrent drought. The objective of this study was to predict meteorological drought hazard for 2021–2050 based on three CMIP6 scenarios: SSP5–8.5, SSP2–4.5 and SSP1–2.6. Precipitation simulations generated by the sixth version of Model for Interdisciplinary Research on Climate (MIROC6) under the SSP5–8.5, SSP2–4.5 and SSP1–2.6 scenarios were used from fifteen stations across the six AEZs of the WC province. The Standardised Precipitation Index (SPI) was computed at 12-month timescales. Trend analysis of precipitation datasets and the SPI-values were done at p < 0.05 using the Mann–Kendall (M–K) test. The findings revealed negative precipitation trends of − 7.6 mm/year in Ceres, while positive trends of 0.3 mm/year were observed in Malmesbury. These findings indicate an improvement from − 7.8 and − 6.4 mm/year in the same regions, respectively, compared to historical trends observed between 1980 and 2020. The results suggest that in 2042 and 2044, Bredasdorp will experience − 2 < SPI < − 1.5 under the SSP2–4.5 scenarios, while Matroosberg in 2038 under the SSP5–8.5 will experience SPI > − 2. The findings of this study will assist in the development of proactive planning and implementation of drought mitigation strategies and policies aimed at reducing water insecurity in AEZs.

E-Commerce Logistics and Supply Chain Network Optimization for Cross-Border

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Abstract

E-commerce is a growing industry that primarily relies on websites to provide services and products to businesses and customers. As a brand-new international trade, cross-border e-commerce offers numerous benefits, including increased accessibility. Even though cross-border e-commerce has a bright future, managing the global supply chain is crucial to surviving the competitive pressure and growing steadily. Traditional purchase volume forecasting uses time-series data and a straightforward prediction methodology. Numerous customer consumption habits, including the number of products or services, product collections, and taxpayer subsidies, influence the platform's sale quantity. The use of the EC supply chain has expanded significantly in the past few years because of the economy's recent rapid growth. The proposed method develops a Short-Term Demand-based Deep Neural Network and Cold Supply Chain Optimization method for predicting commodity purchase volume. The deep neural network technique suggests a cold supply chain demand forecasting framework centred on multilayer Bayesian networks (BNN) to forecast the short-term demand for e-commerce goods. The cold supply chain (CS) optimisation method determines the optimised management inventory. The research findings demonstrate that this study considers various influencing factors and chooses an appropriate forecasting technique. The proposed method outperforms 96.35% of Accuracy, 97% of Precision and 94.89% of Recall.

More than malware: unmasking the hidden risk of cybersecurity regulations

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Abstract

Cybersecurity investments are made within a complex and ever-evolving environment, where regulatory changes represent a significant risk factor. While cybersecurity regulations aim to minimize cyber risks and enhance protection, the uncertainty arising from frequent changes or new regulations can significantly impact organizational response strategies. This paper explores the determinants and implications of regulatory risks associated with cybersecurity, aiming to provide a deeper understanding of how these risks influence strategic decision-making. The study delves into the suggestion of preventive and mitigative controls that enable businesses to adapt to and mitigate potential disruptions caused by regulatory changes, thereby preserving their established cybersecurity practices. Another key contribution of this study is the introduction of a stochastic econometric model that illustrates how regulatory risks and uncertainties can affect investment behaviors, often prompting a “wait-and-see” stance. This model synthesizes the complex relationship among investment choices, regulatory changes, and cybersecurity risks, providing insights into the dynamic nature of cybersecurity investment strategies. The research findings offer valuable guidance for risk management and strategic planning in cybersecurity investments. By comprehensively understanding the drivers and impacts of regulatory risks, businesses and policymakers can develop more effective risk evaluation and management approaches. This is essential for sustaining a strong cybersecurity posture while navigating the changing regulatory environment.

Intensity of economic relationships: a spatial econometric analysis of regional economic growth in China

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Abstract

Since inter-regional commodity trade within a country can flow freely, the intensity of economic relationships (IER) between regions may affect the level of the regional convergence. This relationship is explored using an extended spatial Durbin model with 1992–2010 prefecture data in China. Two sample cases are conducted for spatial heterogeneity. We find that while the intensity of economic relationships plays little role in regional growth, the spatial lag of the intensity of economic relationships does matter. Further, the positive contribution of IER to regional growth gradually increases over time. In addition, IER has a positive effect on convergence velocity at the prefectural level but a negative effect at the provincial level. The modifiable areal unit problem is addressed with both scale effects (provincial level data are adopted) and zoning effect (two kinds of delineation of the study area); for the latter effect, a case study of Central China with two samples from the central region and the central core region was analyzed using zoning effect tests. Bayesian comparison analysis results support the finding that the data-driven model results are consistent with the theory-driven model. Our conclusions are robust with respect to alternative fixed effects, measurement of intensity of economic relationships, and the choice of the spatial weight matrix, but vary across types of spatial units due to market segmentation.

Exploring the nexus between fiscal decentralization and ecological sustainability: a fresh perspective from the moderating role of geopolitical risk and updated international evidence

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Abstract

Fiscal decentralization has been long employed to enhance the utilization of financial resources for sustainable development. Nevertheless, its effectiveness in limiting ecological degradation is ambiguous, especially when a country faces geopolitical risks. Different from previous works which separately examine the impacts of either fiscal decentralization or geopolitical risks on ecological sustainability, this research examines the moderating role of geopolitical risks on the non-linear relationship between fiscal decentralization and ecological footprints across different levels of environmental condition. An advanced panel quantile regression is applied to a sample of 23 advanced and emerging market economies from 1990 to 2018. The empirical results indicate that the nexus between revenue decentralization and ecological footprint follows an inverted U-shaped pattern at the 20th to 60th quantiles of ecological footprint. Meanwhile, the linkage between expenditure and ecological footprint reflects a U-shaped pattern across all quantiles. Notably, geopolitical risk strongly moderates the connection between fiscal decentralization and ecological footprint with the role being stronger in the case of revenue decentralization. This research provides valuable implementations to tailor policies for transferring revenue and expenditure responsibilities to sub-governmental bodies towards sustainability targets based on their current ecological conditions and contexts of geopolitical instability.

An investigation of the effect of drawdown pressure on sand production in an Iranian oilfield using a hybrid numerical modeling approach

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Abstract

Reservoir pressure reduction due to continuous production from oil and gas wells affects the sand production rate. An increase in drawdown pressure and/or a decrease in reservoir pressure increases the sand production rate. Since the problem of sand production is one of the main issues in the Asmari sandstone formation located in one of the oilfields in the southwest of Iran, therefore, in this research, the variations in the sand production rate due to the changes in the reservoir and drawdown pressures were investigated. So, for the first time, a hybrid numerical model of finite difference method (FDM)—discrete element method (DEM)—finite element method (FEM)—computational fluid dynamics (CFD) was developed. This numerical model investigated the increase in the sand production rate due to variations in reservoir pressure with a constant bottom-hole flowing pressure. Then, by performing an extensive sensitivity analysis on different values of reservoir pressure and drawdown pressure, the changes in the sanding rate, the critical drawdown pressure, and the safe drawdown line were determined. The results showed that, if the production flow rate of the well is constant, increasing the drawdown pressure can change the sand production rate only to a certain extent, and more than that, will be produced at a constant rate. Also, adjusting the drawdown pressure within a safe range does not necessarily keep the sand production rate constant at a permissible value for a long time, while by keeping the bottom hole flowing pressure constant within an acceptable range, the sand production rate can be controlled for a longer period.

Cross-platform social dynamics: an analysis of ChatGPT and COVID-19 vaccine conversations

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Abstract

The role of social media in information dissemination and agenda-setting has significantly expanded in recent years. By offering real-time interactions, online platforms have become invaluable tools for studying societal responses to significant events as they unfold. However, online reactions to external developments are influenced by various factors, including the nature of the event and the online environment. This study examines the dynamics of public discourse on digital platforms to shed light on this issue. We analyzed over 12 million posts and news articles related to two significant events: the release of ChatGPT in 2022 and the global discussions about COVID-19 vaccines in 2021. Data was collected from multiple platforms, including Twitter, Facebook, Instagram, Reddit, YouTube, and GDELT. We employed topic modeling techniques to uncover the distinct thematic emphases on each platform, which reflect their specific features and target audiences. Additionally, sentiment analysis revealed various public perceptions regarding the topics studied. Lastly, we compared the evolution of engagement across platforms, unveiling unique patterns for the same topic. Notably, discussions about COVID-19 vaccines spread more rapidly due to the immediacy of the subject, while discussions about ChatGPT, despite its technological importance, propagated more gradually.