715 research outputs found
Muslim Acculturation in a Catholic Country: Its Associations With Religious Identity, Beliefs, and Practices
Flexibility in existential beliefs and worldview: Testing measurement invariance and factorial structure of the existential quest scale in an Italian sample of adults
Does Existential Flexibility Associate With Individuals’ Acceptance of Inequality? A Study Relating Existential Questing to Values and to Prejudice
This study investigated whether existential quest, a relatively new construct defining individual willingness to reflect on existential issues such as the meaning of life and death, was negatively associated with generalized prejudice through the mediation with personal values of universalism and conservation (conformity, security, and tradition). A structural equation model was performed on a convenience sample of 1136 Italian adults. Results confirmed a negative indirect relationship with generalized prejudice mediated by universalism. Findings support the argument that engagement with existential issues is associated with the value of universalism, which in turn is associated with lower levels of generalized prejudice. The present study contributes to the scholarly literature to explain the concept of existential quest
I feel Moroccan, I feel Italian, and I feel Muslim: Second generation Moroccans and identity negotiation between religion and community belonging
Potentially combined effect of the invasive seaweed Caulerpa cylindracea (Sonder) and sediment deposition rates on organic matter and meiofaunal assemblages
The seaweed Caulerpa cylindracea (Sonder) is one of the most successful marine bioinvaders worldwide. Caulerpa cylindracea can influence the quantity and biochemical composition of sedimentary organic matter (OM). However, it is still unknown if the effects of C. cylindracea on both OM and small metazoans (i.e. meiofauna) can change according to different sediment deposition rates. To provide insights on this, we investigated the biochemical composition of sediments along with the abundance and composition of meiofaunal assemblages in sediments colonized and not-colonized by the seaweed C. cylindracea under different regimes of sediment deposition. Our results show that the presence of the invasive alga C. cylindracea could alter quantity, biochemical composition, and nutritional quality of organic detritus and influence the overall functioning of the benthic system, but also that the observed effects could be context-dependent. In particular, we show that the presence of C. cylindracea could have a positive effect on meiofaunal abundance wherever the sediment deposition rates are low, whereas the contextual presence of high to medium sedimentation rates can provoke an accumulation of sedimentary organic matter, less favourable bioavailability of food for the benthos, and consequent negative effects on meiofauna
PlanCollabNL: Leveraging Large Language Models for Adaptive Plan Generation in Human-Robot Collaboration
"Hey, robot. Let's tidy up the kitchen. By the way, I have back pain today". How can a robotic system devise a shared plan with an appropriate task allocation from this abstract goal and agent condition? Classical AI task planning has been explored for this purpose, but it involves a tedious definition of an inflexible planning problem. Large Language Models (LLMs) have shown promising generalisation capabilities in robotics decision-making through knowledge extraction from Natural Language (NL). However, the translation of NL information into constrained robotics domains remains a challenge. In this paper, we use LLMs as translators between NL information and a structured AI task planning problem, targeting human-robot collaborative plans. The LLM generates information that is encoded in the planning problem, including specific subgoals derived from an NL abstract goal, as well as recommendations for subgoal allocation based on NL agent conditions. The framework, PlanCollabNL, is evaluated for a number of goals and agent conditions, and the results show that correct and executable plans are found in most cases. With this framework, we intend to add flexibility and generalisation to HRC plan generation, eliminating the need for a manual and laborious definition of restricted planning problems and agent models
Improved task planning through failure anticipation in human-robot collaboration
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe human state is defined in terms of capacity, knowledge and motivation. The system has been implemented in a standardised environment using the Planning Domain Definition Language (PDDL) and the modular ROSPlan framework, and we have validated the approach in multiple simulation settings. Our results show that using the human model fosters an appropriate task allocation while allowing failure anticipation, replanning in time to prevent it.Peer ReviewedPostprint (author's final draft
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