Thuy Nguyen

Circular economy (CE), a sustainability concept that promotes resource efficiency and waste reduction, has garnered significant popularity in recent years due to its potential to address pressing environmental and economic challenges. This study employs the Bayesian mindsponge framework (BMF) to explore what drives young adults’ pro-environmental behavior and purchases of green products at different levels of price. The results show that young adult’s knowledge of CE and care about environmental protection and energy saving encourages the practice of waste classification, while factors that affect their willingness to pay (WTP) more for green and energy-saving products vary at different price tiers.

To achieve herd immunity against Covid-19, the willingness of residents to get vaccinated and successful vaccination policies go hand in hand. This paper aims to understand the perceptions, acceptance, hesitation, and refusal of Covid-19 vaccines in Nghe An, Vietnam. We used an online survey to collect data during March of 2021. The Bayesian regression model (BRM) was used to identify the factors affecting vaccination decisions. The empirical results show that respondents’ livelihoods were considerably affected by the Covid-19 pandemic, and there was a subtle difference in Covid-19 impacts on the lives of urban residents and their rural counterparts. In addition, respondents reported an overall positive attitude towards Covid-19 vaccination in which 84.28% were willing to get vaccinated, 14.85% were hesitant, and 0.87% refused vaccination. Their vaccination decisions were associated with vaccine side effects, information, income, job type, gender, and trust in government. Our findings offer policy implications for devising strategies for vaccine distribution in the study area and beyond.

A major challenge for research in artificial intelligence is to develop systems that can infer the goals, beliefs, and intentions of others (i.e., systems that have theory of mind, ToM). In this research, we propose a cognitive ToM framework that uses a well-known theory of decisions from experience to construct a computational representation of ToM. Instance-based learning theory (IBLT) is used to construct a cognitive model that generates ToM from the observation of other agents' behavior. The IBL model of the observer distinguishes itself from previous models of ToM that make unreasonable assumptions about human cognition, are hand-crafted for particular settings, complex, or unable to explain a cognitive development of ToM compared to human's ToM. The IBL model learns from the observation of goal-directed agents' behavior in a gridworld navigation task, and it infers and predicts the behaviors of the agents in new gridworlds across different degrees of decision complexity in similar ways to the way human observers do. We provide evidence for the alignment of the IBL observer's predictions under various levels of decision complexity. We also advance the demonstration of the IBL predictions using a classic test of false beliefs (the Sally–Anne test), which is commonly used to test ToM in humans. We discuss our results and the potential of the IBL observer model to improve human–machine interactions.

We investigate a system of two species exploiting a common resource. We consider both abiotic (i.e. with a constant resource supply rate) and biotic (i.e. with resource reproduction and self-limitation) resources. We are interested in the asymmetric competition where a given consumer is the locally superior resource exploiter (LSE) and the other is the locally inferior resource exploiter (LIE). They also interact directly via interference competition in the sense that LIE individuals can use two opposite strategies to compete with LSE individuals: we assume, in the first case, that LIE uses an avoiding strategy, i.e. LIE individuals go to a non-competition patch to avoids competition with LSE individuals, and in the second one, LIE uses an aggressive strategy, i.e. being very aggressive so that LSE individuals have to go to a non-competition patch. We further assume that there is no resource in the non-competition patch so that individuals have to come back to the competition patch for their maintenance, and the migration process acts on a fast time scale in comparison with demography and competition processes. The models show that being aggressive is efficient for LIE’s survival and even provoke global extinction of the LSE and this result does not depend on the nature of resource.

We present a mathematical model of two competing marine species that are harvested. We consider three models according to different levels of complexity, without and with species refuge and density-independent and density-dependent species movement between fishing area and refuge. We particularly study the effects of the fishing pressure on the outcome of the competition. We focus on conditions that allow an inferior competitor to invade as a result of fishing pressure. The model is discussed in relationship to the case of the thiof and the octopus along the Atlantic West African coast. At the origin, the thiof was abundant and the octopus scarce in that region. Since, the fishing pressure has strongly increased in some fishing areas leading to the depletion of the thiof and the invasion of its competitor, the octopus.