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Older adults are more vulnerable to the negative impacts of infectious diseases than younger individuals. However, regardless of the importance and effectiveness of vaccines to reduce morbidity and mortality, issues remain with vaccine hesitancy among this population. Older adults' sources of immunization information and their level of trust in those sources may play a role in their vaccination behaviors. This research aimed to better understand the role of information sources and related issues of trust as related to vaccine uptake among older adults. A community-based, cross-sectional survey was conducted with 901 older adults in North Dakota in May-July 2022. Measures included extent of reliance on specific sources of immunization information, levels of trust, and uptake for influenza, pneumonia, shingles, and COVID-19 vaccinations. Immunization information sources were grouped into medical experts, informal, and public outlets. Results indicated older adults were more likely to rely on medical experts than informal sources or public outlets for immunization information. Greater reliance on medical experts was associated with a greater likelihood of vaccine uptake for all vaccines, while reliance on public outlets was associated with a greater likelihood of vaccine uptake only for COVID primary series and boosters. Reliance on informal sources for immunization information was associated with a reduced likelihood of vaccine uptake for all vaccines except shingles. Nearly half of respondents were uncertain who to trust for vaccine information. Uncertainty who to trust for immunization information significantly mediated the associations between reliance on medical experts and uptake for most vaccines indicating that trust in medical experts fosters vaccine uptake. Increasing reliance on medical experts as sources of immunization information is vital to increasing vaccine uptake among older adults. Additionally, this population must be assisted in increasing their ability to successfully assess the trustworthiness of immunization information sources. [ABSTRACT FROM AUTHOR]

Numerous studies have demonstrated that connected autonomous vehicles and human-driven vehicles are now coexisting throughout a transitional phase. Traffic flow can be improved, the system can be stabilized, and less energy will be used with dedicated lanes for connected autonomous vehicles. Additionally, with few communication resources, no communication delivery is ever perfect, leading to issues with poly-information uncertainty. First, this paper provides a macroscopic model of heterogeneous traffic flow from the perspective of vehicle dynamics employing electronic throttle dynamics and poly-information uncertainty with/without dedicated lanes. Second, the mixed traffic flow linear stability criterion is derived using the linear stability theory. The third portion, which was based on the theoretical analysis, focused on the consequences of dedicated lane configurations on traffic flow as well as a discussion of the effects of various parameters on the stability of mixed traffic flow and energy consumption emissions. Finally, we modeled the Huanshan Road in Jinan, China using the experimental VISSIM platform. The analysis and demonstration of a two-way, four-lane road with or without dedicated lanes. The findings demonstrate that increasing connected autonomous vehicles penetration and dedicated lanes construction can increase traffic capacity, enhance the stability of traffic flow, and lower energy use and additional emissions. It is important to keep in mind that dedicated lanes must be built at an appropriate connected autonomous vehicle penetration rate to boost traffic flow without squandering resources. • A macro model is developed to describe the CAV dedicated lane setups and poly-information uncertainties • The performance of the system is optimized from the smoothness and stability of the traffic flow density wave • The impacts of poly-information uncertainties on the stability and energy consumption of traffic flow system • Trialability of dedicated lanes in a comparative comparison of real-world settings under specific circumstances [ABSTRACT FROM AUTHOR]

In group decision making (GDM), due to complexity of various factors, decision makers (DMs) often provide incomplete preference relations (PRs) in preference matrix. Interval-valued probabilistic uncertain linguistic term set (IVPULTS) is a flexible and accurate tool to depict evaluation information of experts. In this paper, we mainly propose a new concept pertaining to interval-valued probabilistic uncertain linguistic preference relation (IVPULPR) that applies the IVPULTS to preference relations. Firstly, some new basic theoretical concepts of IVPULTS are developed including ordered IVPULTS, normalization method and new expectation function. Secondly, we establish several goal programming models to estimate the unknown elements in incomplete IVPULPR and propose the expected additive consistency of IVPULPR. To improve the consistency level, two optimization models are constructed based on the idea of minimum adjustment. Thirdly, we derive the experts' weights in terms of information uncertainty, where a new method to measure information uncertainty of IVPULTS is proposed. For the sake of improving group consensus, we construct a group consensus index (GCI) and two optimization models depending on the adjustment mechanism of expert weight. Finally, a complete GDM framework with incomplete IVPULPR is devised based on the analysis of IVPULPR consistency and group consensus. Through an experiment analysis by using an UCI dataset, we find that the proposed GDM model can not only precisely express fuzzy preference information of DMs, but also ensure achievement of acceptable consistency and group consensus under the condition of not changing the initial preference as much as possible. [ABSTRACT FROM AUTHOR]

• The general membership functions of four types thresholds for the grades on attribute eigenvalue are proposed. • The trust information uncertainty degree in social network is researched. • A new method to generate the incomplete social network based on the trust information uncertainty degree and variable weight function is proposed. • A novel multi-objective decision optimization model for network security situation grade assessment under multi-source information is proposed. Grade assessment of network security situation is summarized as a typical multi-index grade assessment problem. However, the existed methods for grade assessment of network security situation do not consider multi-source information such as the trust information among experts, the preference information among companies and heterogeneous information of companies. The above problems are unable to be solved through traditional assessment methods. The aim of this paper is to establish a novel multi-objective decision model for the grade assessment of network security situation under multi-source information. On the basis of describing the grade assessment problem of network security situation, the membership functions of four-type thresholds for the grades on attribute eigenvalue are put forward. Two trust information uncertainty degrees in social network are defined, and the trust transfer operator based on trust information uncertainty degree and multi-path trust integration method based on the variable weight function is proposed. Afterwards, a new method to generate the incomplete social network is used to identify the weights of experts. Then, a multi-objective decision grade assessment optimization model is further established to obtain the network security situation grades and grade discrimination based on the two-tuple linguistic operator. The proposed method provides a theoretical basis for constructing and testing the grade assessment of network security situation. Meanwhile, it develops the grade assessment system of advanced network security situation and improves the ability to protect network security. [ABSTRACT FROM AUTHOR]

Long-term development in computer manufacturing is crucial to satisfying the demands for the software and hardware needed for artificial intelligence (AI) computation. However, the computer manufacturing sector is highly energy-intensive and resource-consuming, making company sustainability an issue. The framework developed in this study incorporates 15 sustainability criteria focusing predominantly on the economy, society, environment, and risk perspectives. A novel hybrid approach that integrates the ISVTNN (interval single-valued trapezoidal neutrosophic number), DEMATEL (decision-making trial and evaluation laboratory), and PGRA (probability-based grey relational analysis) techniques is proposed. This approach is applied to evaluate the interdependent weights of the criteria for a comprehensive calculation of the performance of the evaluated companies based on probabilities. The inclusion of ISVTNNs allows not only for the broader consideration of information uncertainty but also for more effective integration of experts' judgments. To verify the robustness of the proposed model, three sensitivity analyses were conducted. The results show no significant changes in the rankings of the evaluated companies, demonstrating the stability and reliability of the model. The proposed framework and methodology can serve as the foundation for assessing the sustainable performance of companies in the electronics manufacturing industry. This study indirectly strengthens the backbone of the AI system, by improving sustainability assessment in the computer manufacturing sector (which is integral to the foundation for AI computation). In the AI-driven era, it can be expected that hardware demands will skyrocket, making sustainable manufacturing the linchpin for long-term operational success, resilience, and industry growth. • Developed a novel group decision-making approach for assessing corporate sustainability performance. • Integrated ISVTNN to measure uncertainty and effectively amalgamate expert opinions. • The proposed ISVTNN PGRA retains fuzziness, calculating through probabilistic means. • Demonstrated approach efficacy across six electronics manufacturing enterprises. • Sensitivity analysis underscores the approach's robustness. [ABSTRACT FROM AUTHOR]

Both education for sustainable development (ESD) and service quality in higher education are two dominant areas of recent academic research. Due to the multifaceted and complex nature of higher education, it is crucial to adequately understand the perceptions of various stakeholders regarding the sustainability and service quality of higher education institutes (HEIs). Inspired by multi-criteria group decision-making (MCGDM), this study focuses on developing a systematic and integrated framework for evaluating sustainable service quality in higher education from a multi-stakeholder perspective. To this end, 20 criteria related to sustainability and service quality in higher education are identified and incorporated into five dimensions to create a comprehensive evaluation criteria system. In addition, epistemic uncertainty, conflict management, and individual bounded rationality are the main challenges in reaching group consensus among stakeholders. Considering the unique theoretical advantages of the intuitionistic fuzzy set (IFS) theory, Dempster-Shafer evidence theory (DSET), and TODIM method, they can be integrated to propose a fuzzy group decision-making method. Specifically, a linguistic preference scale is applied to express stakeholders' subjective judgments and construct an initial evaluation matrix. The DSET is extended based on belief divergence and belief entropy to fuse the uncertain and conflicting group evaluation information. A combination of IFS and TODIM, called IF-TODIM, is utilized to prioritize alternative HEIs by considering uncertainty representation and loss aversion behavior. Finally, the feasibility and effectiveness of the proposed methodology are demonstrated through a case study of maritime transportation education in China. The results enable policy-makers to make informed decisions and develop educational strategies that satisfy stakeholders, with the potential for great value in developing sustainable and high-quality higher education. • A synthetic evaluation criteria system embeds sustainability and service quality in higher education. • A holistic consideration of multiple stakeholders in higher education is suggested. • An integrated MCGDM method is proposed to evaluate the sustainable service quality of HEIs. • The modified DSET based on belief divergence and belief entropy is used for conflict management. • The IF-TODIM method addresses information uncertainty and individual bounded rationality. [ABSTRACT FROM AUTHOR]