The study examines the acceptance and sustainability of vegetarian, vegan, and flexitarian diets, focusing on the health and environmental benefits of reducing animal-derived proteins. Our objective was to investigate the level of acceptance of these dietary trends across different age groups and health statuses and understand how sustainability awareness and health consciousness impact dietary decisions. We used a mixed-method approach to achieve this, conducting eight in-depth interviews and a survey with 329 participants from various demographic backgrounds. Our qualitative analysis revealed that individual and family health consciousness, along with sustainability considerations, play a significant role in dietary choices, particularly among younger generations who are more open to sustainable eating. Quantitative results show that access to information and educational resources strongly influences dietary decisions, further supporting the spread of environmentally conscious eating habits. The practical significance of our research lies in highlighting the importance of educational campaigns and public health policies that can foster broader societal acceptance of sustainable diets. Educational institutions and community organizations can help facilitate the transfer of knowledge necessary for adopting such diets. Our findings emphasize the role of targeted communication strategies in increasing awareness of the benefits of plant-based diets. Furthermore, these insights underline the potential of policy interventions to make sustainable food choices more accessible and appealing to a wider population. Future research could focus on exploring economic incentives and examining long-term health and environmental outcomes associated with these diets.

Climate change is an important factor that must be considered by designers of large infrastructure projects, with its effects anticipated throughout the infrastructure’s useful life. This paper discusses how engineers can address climate change adaptation in design holistically and sustainably. It offers a framework for adaptation in engineering design, focusing on risk evaluation over the entire life cycle. This approach avoids the extremes of inaction and designing for worst-case impacts that may not occur for several decades. The research reviews case studies and best practices from different parts of the world to demonstrate effective design solutions and adjustment measures that contribute to the sustainability and performance of infrastructure. The study highlights the need for interdisciplinary cooperation, sophisticated modeling approaches, and policy interventions for developing robust infrastructure systems.

Transit-oriented development is a concept that focuses on developing areas in and around transit nodes to create added value. The concept concentrates on integrating mass public transport networks with non-motorized modes of transport, minimizing the usage of motorized vehicles, and fostering the growth of dense, mixed-use areas with medium to high spatial intensity. This research examines the effects of altering the business model to create Transit Oriented Development (TOD) in Jakarta, contrasting it with PT Moda Raya Transports (PT MRT). We collected data by conducting in-depth interviews with experts and distributing questionnaires to seven respondents who work at this We used the Business Model Canvas (BMC) to identify business models and the internal resources needed for the implementation process. process. Therefore, six elements in BMC were used to conduct changes, and based on the results, RBV analysis was pe PT MRT needs to enhance its internal power to a competitive advantage level in order to effectively manage changes. We need to conduct further research on how the business model can influence the creation of transit-oriented development areas.

The usage of cybersecurity is growing steadily because it is beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone is connected through the internet. It’s much easier for a thief to connect important data through cyber-attacks. Everyone needs cybersecurity to protect their precious personal data and sustainable infrastructure development in data science. However, systems protecting our data using the existing cybersecurity systems is difficult. There are different types of cybersecurity threats. It can be phishing, malware, ransomware, and so on. To prevent these attacks, people need advanced cybersecurity systems. Many software helps to prevent cyber-attacks. However, these are not able to early detect suspicious internet threat exchanges. This research used machine learning models in cybersecurity to enhance threat detection. Reducing cyberattacks internet and enhancing data protection; this system makes it possible to browse anywhere through the internet securely. The Kaggle dataset was collected to build technology to detect untrustworthy online threat exchanges early. To obtain better results and accuracy, a few pre-processing approaches were applied. Feature engineering is applied to the dataset to improve the quality of data. Ultimately, the random forest, gradient boosting, XGBoost, and Light GBM were used to achieve our goal. Random forest obtained 96% accuracy, which is the best and helpful to get a good outcome for the social development in the cybersecurity system.

The area of lake surface water is shrinking rapidly in Central Asia. We explore anthropogenic and climate factors driving this trend in Shalkar Lake, located in the Aral Sea region in Kazakhstan, Central Asia. We employ the Landsat satellite archive to map interannual changes in surface water between 1986 and 2021. The high temporal resolution of our dataset allows us to analyze the water surface data to investigate the time series of surface water change, economic and agricultural activities, and climate drivers like precipitation, evaporation, and air temperature. Toward this end, we utilize dynamic linear models (DLM). Our findings suggest that the shrinking of Shalkar Lake does not exhibit a systemic trend that could be associated with climate factors. Our empirical analysis, adopted to address local conditions, reveals that water reduction in the area is related to human interventions, particularly agricultural activities during the research period. On the other hand, the retrospectively fitted values indicate a semi-regular periodicity despite anthropogenic factors. Our results demonstrate that climate factors still play an essential role and should not be disregarded. Additionally, considering long-term climate projections in environmental impact assessment is crucial. The projected increase in temperatures and the corresponding decline in lake size highlights the need for proactive measures in managing water resources under changing climatic conditions.

considering the rate of the currency channel, this study aims to analyze the effect of government foreign debt on labour demand in Indonesia. The Real Effective Exchange Rate (REER) is used to quantify the exchange rate, while estimates of the labour force participation rate characterize labour demand. this study expands upon the cobb-Douglass production function by including public debt as an integral element of the statistical model. The current study examines time series data from 1994 to 2022 and uses the Vector Error Correction Model (VECM) for estimation. in conclusion, the results suggest that an increase in government external debt would result in a decline in labour demand, especially during economic shock associated with an expansion of the government deficit. Moreover, the Real Effective Exchange Rate has a beneficial long-term impact on labour demand. enhancing the purchasing power and stimulating investment through the appreciation of the domestic currency against foreign currencies will consequently increase economic productivity.