This study aimed to examine the compliance of post-disaster emergency assembly areas with their planning criteria in the Battalgazi district of Malatya province. This district is one of the settlements that was most affected by the two big earthquakes that occurred in Türkiye on 6 February 2023. The emergency assembly areas were evaluated qualitatively based on the criterion of “appropriateness”, with the sub-variables of “usability”, “accessibility”, and “safety”. They were also evaluated quantitatively based on the criterion of “adequacy” with the sub-variable “per capita m²”. There are a total of 103 neighborhoods in the district. However, there are only eight emergency assembly areas in total within its boundaries. According to the results of this study, only 7.5% of the current population of the district resides within 500 m of the emergency assembly areas. The fact that four emergency assembly areas (Hürriyet Park, Şehit Kemal Özalper High School, the Community Garden, Battalgazi Municipality) are situated next to each other and there are emergency assembly areas in only six of the 103 neighborhoods within the municipal boundaries shows that were significant problems in the decisions made regarding their locations. In addition, it was determined that there were disadvantages in terms of accessibility and usability within the criterion of appropriateness, while there were some positive aspects in terms of safety. When examined with regard to the criterion of adequacy, it was determined that the emergency assembly areas at Mişmiş Park, the Community Garden, Battalgazi Municipality, and Şehit Kemal Özalper High School were most adequate, while the emergency assembly areas at Hürriyet Park, Fırat Neighborhood Mukhtar, Nevzat Er Park, and 100 Yıl İmam Hatip Secondary School were least adequate.

Noise pollution in construction sites is a significant concern, impacting worker health, safety, communication, and productivity. The current study aims to assess the paramount consequences of ambient noise pollution on construction activities and workers’ productivity in Peshawar, Pakistan. Noise measurements have been recorded at four different construction sites in Peshawar at different times of the day. Statistical analysis and Relative Importance Index (RII) are employed to evaluate the data Risk variables, such as equipment maintenance, noise control, increased workload, material handling challenges, quality control issues, and client satisfaction. The results indicated that noise levels often exceeded permissible limits, particularly in the afternoon, posing significant worker risks. In addition, RII analysis identified communication difficulties, safety hazards, and decreased productivity as significant issues. The results show that noise pollution is directly linked with safety risks, decreased performance, and client dissatisfaction and needs immediate attention by authorities. This paper proposes a strategic policy framework, recommending uniform hand signals and visual communication methods without noise for workers, worker training about safety, and using wearable devices in noisy settings. Communication training for teams and crane operators, proactive quality control, and customer-oriented project schedules are also proposed. These recommendations aim to mitigate the adverse effects of noise pollution, enhance construction industry resilience, and improve overall operational efficiency, worker safety, and client satisfaction in the construction sector of Peshawar, aligning with policy and sustainable development objectives.

Food safety in supply chains remains a critical concern due to the complexity of global distribution networks. This study develops a conceptual framework to evaluate how food safety risks influence supply chain performance through predictive analytics. The framework identifies and minimizes food safety risks before they cause serious problems. The study examines the impact of food safety practices, supply chain transparency, and technological integration on adopting predictive analytics. To illustrate the complex dynamics of food safety and supply chain performance, the study presents supply chain transparency, technological integration, and food safety practices and procedures as independent variables and predictive analytics as a mediator. The results show that supply chain managers' capacity to anticipate and control risks related to food safety can be improved by predictive analytics, leading to safer food production and distribution methods. The research recommends that businesses create scalable cloud-based predictive model solutions, combine data sources, and employ cutting-edge AI and machine learning tools. Companies should also note that strong, data-driven approaches to food safety require cooperative data sharing, regulatory compliance, training initiatives and ongoing improvement.

Public-Private Partnerships (PPPs) are mostly presented as a means to introduce efficient procurement methods and better value for money to taxpayers. However, the complexity of the PPP mechanism, their lack of transparency, accounting rules and implicit liabilities make it often impossible to perceive the amount of public expenditure involved and the long-run impact on taxpayers, providing room for fiscal illusion, i.e., the illusion that PPPs are much less expensive than traditional public investments. This psaper, thanks to a systematic review of the literature on the EU countries experience, tries to unveil the sources of this illusion by looking at the reasons behind the PPPs’ choice, their real costs, and the sources of fiscal risks. The literature suggests that PPPs are more costly than public funding, especially when contingent liabilities are not taken into account, and are employed as mechanisms to circumvent budgetary restrictions and to spend off-balance. The paper concludes that the public sector should share more risks with private sectors by reducing the amount of guarantees, and should prevent governments from operating through a sleight of hand that deflects attention away from off-balance financing, by applying a neutral fiscal recording system.

During the COVID-19 pandemic, individuals and their families faced various risk factors, which in some cases resulted in divorce. Adolescents in such families had to grapple with COVID-19 across the world, the risk factors faced by adolescents have largely been under-risk factors associated with COVID-19 and divorce. Despite the rise of divorce during studied, especially among adolescents in South Africa. This study aimed to explore the risk factors experienced by adolescents from divorced households during the COVID-19 pandemic and make recommendations for policy and development. This study employed a phenomenological research design in alignment with qualitative research. Purposive sampling was used to recruit five female adolescents in Johannesburg. Data was collected using semi-structured interviews and focus groups. Data was analyzed thematically using Braun and Clarke’s six steps of data analysis. The findings revealed that conflict at home, mental illness, physical and social isolation, a lack of paternal support, and diminished educational performance emerged as risk factors faced by the participants. These findings underscore the need for psychological interventions to help address the risk factors faced by adolescents whose parents divorced during the pandemic and those who face similar circumstances during future crises.

Project risk management in the mining industry is necessary to identify, analyze and reduce uncertainty. The engineering features of mining enterprises, by their nature, require improved risk management tools. This article proves the relevance of creating a simulation model of the production process to reduce uncertainty when making investment decisions. The purpose of the study is to develop an algorithm for deciding on the economic feasibility of creating a simulation experiment. At the same time, the features and patterns of the cases for which the simulation experiment was carried out were studied. Criteria for feasibility assessment of the model introduction based on a qualitative parameters became the central idea for algorithm. The relevance of the formulated algorithm was verified by creating a simulation model of a potassium salt deposit with subsequent optimization of the production process parameters. According to the results of the experiment, the damage from the occurrence of a risk situations was estimated as a decrease in conveyor productivity by 32.6%. The proposed methods made it possible to minimize this risk of stops in the conveyor network and assess the lack of income due to the risk occurrences.