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The successes of reinforcement learning in recent years are underpinned by the characterization of suitable reward functions. However, in settings where such rewards are non-intuitive, difficult to define, or otherwise error-prone in their definition, it is useful to instead learn the reward signal from expert demonstrations. This is the crux of inverse reinforcement learning (IRL). While eliciting learning requirements in the form of scalar reward signals has been shown to be effective, such representations lack explainability and lead to opaque learning. We aim to mitigate this situation by presenting a novel IRL method for eliciting declarative learning requirements in the form of a popular formal logic---Linear Temporal Logic (LTL)---from a set of traces given by the expert policy.

In this paper, the effect of tactile affordance during the design of Extended Reality (XR) based environments is presented. Tactile affordance is one of the Human eXtended Reality Interaction (HXRI) criteria which help lay the foundation for human-centricXR-based training environments. XR-based training environments developed for two surgical procedures have been used to study the role of tactile affordance. The first XR environment is developed for the Condylar plating surgical procedure which is performed to treat the fractures of the femur bone and the second XR environment is developed to train users in endotracheal intubation. Three studies have been conducted to understand the influence of different interactionmethods to elevate tactile affordance in XR-based environments. The studies and the results of the studies have been exhaustively discussed in this paper.

Boron carbide (B4C) has been well studied both theoretically and experimentally in its bulk form due to its exceptional hardness and use as a high-temperature thermoelectric. However, the properties of its two-dimensional nanosheets are not well established. In this paper, using van der Waals-corrected density-functional theory simulations, we show that bulk B4C can be cleaved along different directions to form B4C nanosheets with low formation energies. We find that there is minimal dependence of formation energies on cleavage planes and surface terminations, even though the bulk is not van der Waals layered. This anomalous stability of B4C nanosheets is found to be a result of surface reconstructions that are unique to B-rich systems. While the density of states of the bulk B4C indicate that it is a semiconductor, the B4C nanosheets are found to be predominantly metallic. We attribute this metallic behavior to a redistribution of charges on the surface bonds of the films. The Seebeck coefficients of the B4C films remain comparable to those of the bulk and are nearly constant as a function of temperature. Our results provide guidance for experimental synthesis efforts and future application of B4C nanosheets in nanoelectronic and thermoelectric applications.