This qualitative research aimed to study the effectiveness of the local health constitution in controlling the spread of COVID-19. It reports the role of local communities, government agencies, and healthcare providers in implementing and enforcing local health constitutions and how their engagement can be improved to enhance surveillance. We also reported factors that influence compliance and strategies for improving compliance. We also evaluated the long-term sustainability of local health institutions beyond the pandemic. The population and sample group consisted of key members of the local health constitution teams at the provincial, sub-district, and village levels in the rural area of Ubon Ratchathani. Participants were purposively selected and volunteered to provide information. It included health science professionals, public health volunteers, community leaders, and local government officials, totaling 157 individuals. The study was conducted from December 2022 to September 2023. Our research shows that local health constitutions can better engage and educate communities to actively participate in pandemic surveillance and prevention. This approach is a learning experience for responding to emergencies, such as new infectious diseases that may arise in the future. This simplifies the work of officials, as everyone understands the guidelines for action. Relevant organizations contribute to disease prevention efforts, and there is sustainable improvement in work operations.

The paper examines the underlying science determining the performance of hybrid engines. It scrutinizes a full range of orthodox gasoline engine performance data, drawn from two sources, and how it would be modified by hybrid gasoline vehicle engine operation. The most significant change would be the elimination of the negative consequences of urban congestion, stop-start, and engine driving, in favour of a hybrid electric motor drive. At intermediate speeds there can be other instances where electric motors might give a more efficient drive than an engine. Hybrid operation is scrutinised and the electrical losses estimated. There also remains scope for improvements in engine combustion. 

This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. The proposed methodologies and optimization focus on balancing the mean efficiency and variability by adjusting the concentration parameter of the Von Mises distribution, which models directional variability in thermal conductivity. The study highlights the superiority of the Von Mises distribution in achieving more consistent and efficient thermal performance compared to the uniform distribution. We also conducted a sensitivity analysis of the parameters for further insights. The results show that optimal tuning of the concentration parameter can significantly reduce efficiency variability while maintaining a mean efficiency above the desired threshold. This demonstrates the importance of considering both stochastic effects and directional consistency in thermal systems, providing robust and reliable design strategies.

In many cases, the expected efficiency advantages of public-private partnership (PPP) projects as a specific form of infrastructure provision did not materialize ex post. From a Public Choice perspective, one simple explanation for many of the problems surrounded by the governance of PPPs is that the public decision-makers being involved in the process of initiating and implementing PPP projects (namely, politicians and public bureaucrats) in many situations make low- cost decisions in the sense of Kirchgässner (1948–2017). That is, their decisions may have a high impact on the wealth of the jurisdiction in which the PPP is located (most notably, on the welfare of citizen-taxpayers in this jurisdiction) but, at the same time, these decisions often only have a low impact on the private welfare of the individual decision-makers in politics and bureaucracy. The latter, for example, in many settings often have a low economic incentive to monitor/control what the private-sector partners are doing (or not doing) within a PPP arrangement. The purpose of this paper is to draw greater attention to the problems created by low-cost decisions for the governance of PPPs. Moreover, the paper discusses potential remedies arising from the viewpoint of Public Choice and Constitutional Political Economy.

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.