Infrastructure decision-making has traditionally been focused on the use of cost-benefit analysis (CBA) and multicriteria decision analysis (MCDA). Nevertheless, there remains no consensus in the infrastructure sector regarding a favored approach that comprehensively integrates resilience principles with those tools. This review focuses on how resilience has been evaluated in infrastructure projects. Initially, 400 papers were sourced from Web of Science and Scopus. After a preliminary review, 103 papers were selected, and ultimately, the focus was narrowed down to 56 papers. The primary aim was to uncover limitations in both CBA and MCDA, exploring various strategies for amalgamating them and enhancing their potential to foster resilience, sustainability, and other infrastructure performance aspects. Results were classified based on different rationalities: i) objectivist, ii) conformist, iii) adjustive, and iv) reflexive. The analysis revealed that while both CBA and MCDA contribute to decision-making, their perceived strengths and weaknesses differ depending on the chosen rationality. Nonetheless, embracing a broader perspective, fostering participatory methods, and potentially integrating both approaches seem to offer more promising avenues for assessing the resilience of infrastructures. The goal of this research proposal is to devise an integrated approach for evaluating the long-term sustainability and resilience of infrastructure projects and constructed assets.

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.

This study explores the factors that affect consumer adoption of reusable packaging in South Korea’s food delivery market. Adopting a mixed-method that includes interviews and an online survey of 137 consumers aged 18 to 30, the analysis, using an ordered probit model, reveals key drivers of the likelihood of switching to food delivery services using reusable packaging. Positive influences include environmental concerns, intention to take action on disposable packaging, willingness to pay extra, and awareness that reusable packaging does not require washing. However, challenges such as hygiene concerns and higher delivery fees deter consumers from switching to reusable package option. Demographic factors like living arrangements and gender show minimal impact. In response to the findings, the study suggests strategic solutions, including a pilot program, to overcome barriers and effectively demonstrate the benefits of reusable containers.

Problem statement: An environmentally conscious consumer’s perspective can shift as they look for things that are gentler on the planet. Conversely, businesses engage in greenwashing when they try to cover up their lacklustre environmental initiatives. The current research was used the theory of rational choice behaviour to examine a model that connects corporate green washing and consumers’ green purchase intentions via the mediating roles of perceived risk, green trust and green confusion about food and beverage brands in Saudi Arabia. Research motivation: Sustainable business practices have been developed and adopted by corporations in response to the growing interest in environmentally friendly lifestyles and green products. However, green washing has become increasingly common as a means for businesses to give off the impression that they care about the environment when they really don’t. Research methodology: The online survey was used to obtain data directly from consumers about their views on green washing by corporations. Primary data was analysed using appropriate statistical tools and techniques in SPSS, AMOS and SmartPLS software, such as Correlation, Regression, Structural Equation Modelling (SEM), etc. Results: In terms of perceived greenness and confusion, the results showed that green wash mediates the relationship between green purchasing intention and greenness. There is a two-way correlation between consumers’ intentions to buy environmentally friendly products and their levels of green perception, and green confusion. The findings of this study were broadening our understanding of the consequences of green washing. Conclusions: All things considered, the study was encouraging more research on the subject and be a useful tool for academics, corporate managers, and students interested in environmental sustainability, product innovation, and green branding. According to the results, businesses can improve their green purchasing intentions by cutting down on green washing and focusing instead on building a positive reputation for their brand and encouraging customer loyalty. Corporate performance and social environment sustainability can both benefit greatly from this paper’s expansion of knowledge regarding the processes of individual customer psychological effects after perceptions of corporate greenwashing behaviour.

This study aims at exploring the direct impact of positive mental health through 6 factors on quality of life among students with disabilities and diabetes at Saudi universities, as well as the moderating impact of physical fitness on all direct relationships among all variables of the study. Employing a quantitative research methodology, using self-administered surveys distributed to a sample of students with disabilities and diabetes at numerous Saudi Arabian universities. 468 completed surveys were received and subjected to statistical analysis, using PLS-SEM, and the study uncovered significant positive direct relationships between all positive mental health sub factors and quality of life among students. Additionally, the study revealed that physical fitness acts as a moderator in all direct relationships These findings offer valuable insights for universities, in order to develop and implement psychological support and academic adjustments policies ensuring students have access to health and wellness programs, and engage local communities in the creation of policies that can help students with disabilities.

This study investigates the impact of extreme rainfall events on soil erosion in the downstream Parnaíba River Basin, located in the Brazilian Cerrado. The analysis focused on rainfall erosivity (R factor) and soil erodibility (K factor) as key indicators. The average erosivity in the region was 9051 MJ mm h⁻¹ha⁻¹year⁻¹, with a variation between 7943 and 10,081 MJ mm h⁻¹ha⁻¹year⁻¹, suggesting a high erosive potential, mainly in the rainiest months, from December to April. The soils of the studied area, mainly Ultisols and Chernosols, present high to very high erodibility, with K factor values ranging from 0.025 to 0.050 t h MJ⁻¹ mm⁻¹. Furthermore, fieldwork revealed areas, near highways, with apparently fragile soils, as well as rills and gullies, identified through photographs taken during fieldwork. These locations, due to the combination of high erosivity and susceptible soils, were considered prone to the occurrence of erosion processes, representing an additional risk to local infrastructure. The spatialization of R and K factors, along with field observations, showed that much of the area is at high risk of erosion and landslides, particularly in regions with greater topographic variability and proximity to water bodies. These results provide a basis for the development of mitigation strategies, being important for the effective prevention of landslides.