Investigation of Metaverse in cryptocurrency

Metaverse is an immersive 3D virtual environment, a true virtual artificial community in which avatars act as the user's alter ego and interact with each other. If we do not manage the hype for the metaverse, which has recently been receiving a surge in interest, the metaverse will fail to cross the chasm. This article conducts a comprehensive survey on computational arts, in which seven critical topics are relevant to the metaverse, describing novel artworks in blended virtual-physical realities. The topics first cover the building elements for the metaverse, e.g. Virtual scenes and characters, auditory, textual elements. Next, several remarkable types of novel creations in the expanded horizons of metaverse cyberspace have been reflected, such as immersive arts, robotic arts, and other user-centric approaches fuelling contemporary creative outputs.

Impaired remapping of social relationships in older adults

Social relationships are a central aspect of our everyday life, yet our ability to change established social relationships is an under-investigated topic. Here, we use the concept of cognitive mapping to investigate the plasticity of social relationships in younger and older adults. We describe social relationships within a ‘social space’, defined as a two-dimensional grid composed of the axis ‘power’ and ‘affiliation’, and investigate it using a 3D virtual environment with interacting avatars. We show that participants remap dimensions in ‘social space’ when avatars show conflicting behavior compared to consistent behavior and that, while older adults show similar updating behavior than younger adults, they show a distinct reduction in remapping social space. Our data provide first evidence that older adults show more rigid social behavior when avatars change their behavior in the dimensions of power and affiliation, which may explain age-related social behavior differences in everyday life.

Prediction of garment fit level in 3D virtual environment based on artificial neural networks

This paper proposes a probabilistic neural network-based model for predicting and controlling garment fit levels from garment ease allowances, digital pressures, and fabric mechanical properties measured in a three-dimensional (3D) virtual environment. The predicted fit levels include both comprehensive and local fit levels. The model was set up by learning from data measured during a series of virtual (input data) and real try-on (output data) experiments and then simulated to predict different garment styles, for example, loose and tight fits. Finally, the performance of the proposed model was compared with the Linear Regression model, the Support Vector Machine model, the Radial Basis Function Artificial Neural Network model, and the Back Propagation Artificial Neural Network model. The results of the comparison revealed that the prediction accuracy of the proposed model was superior to those of the other models. Furthermore, we put forward a new interactive garment design process in a 3D virtual environment based on the proposed model. Based on interactions between real pattern adjustments and virtual garment demonstrations, this new design process will enable designers to rapidly, accurately, and automatically predict relevant garment fit levels without undertaking expensive and time-consuming real try-ons.

Unexpected changes in learned task contingencies trigger sharp wave ripples in the primate hippocampus during virtual navigation

The hippocampi and mesial temporal lobes play a central role in episodic memory and associative learning. It is unclear how unexpected experience influences learning. Hippocampal sharp wave ripples (SWR) are an electrical biomarker of memory consolidation. We tracked when and where SWR occur during 2 tasks. Local field potentials were recorded in the hippocampi, entorhinal cortices and amygdalae of non-human primates (NHP; n=3) performing reversal and associative learning tasks in a 3D virtual environment. Our results show hippocampal SWR occurred when learned task contingencies were unexpectedly altered. Surprise rewards and reward denial were associated with SWR rates 9.8x and 8.0x greater than expected rewards. The highest density of SWR occurred in zones where errors were made. SWR were preceded by event-related potentials in the amygdala but not entorhinal cortex. Our results suggest that SWR generation in primates may prioritize behaviourally relevant experience for commitment to memory to allow flexible learning.

Urban Ecosystem Services (UES) Assessment within a 3D Virtual Environment: A Methodological Approach for the Larger Urban Zones (LUZ) of Naples, Italy

The complexity of the urban spatial configuration, which affects human wellbeing and landscape functioning, necessitates data acquisition and three-dimensional (3D) visualisation to support effective decision-making processes. One of the main challenges in sustainability research is to conceive spatial models adapting to changes in scale and recalibrate the related indicators, depending on scale and data availability. From this perspective, the inclusion of the third dimension in the Urban Ecosystem Services (UES) identification and assessment can enhance the detail in which urban structure–function relationships can be studied. Moreover, improving the modelling and visualisation of 3D UES indicators can aid decision-makers in localising, analysing, assessing, and managing urban development strategies. The main goal of the proposed framework is concerned with evaluating, planning, and monitoring UES within a 3D virtual environment, in order to improve the visualisation of spatial relationships among services and to support site-specific planning choices.

AeroVR: An immersive visualisation system for aerospace design and digital twinning in virtual reality

ABSTRACTOne of today’s most propitious immersive technologies is virtual reality (VR). This term is colloquially associated with headsets that transport users to a bespoke, built-for-purpose immersive 3D virtual environment. It has given rise to the field of immersive analytics—a new field of research that aims to use immersive technologies for enhancing and empowering data analytics. However, in developing such a new set of tools, one has to ask whether the move from standard hardware setup to a fully immersive 3D environment is justified—both in terms of efficiency and development costs. To this end, in this paper, we present AeroVR—an immersive aerospace design environment with the objective of aiding the component aerodynamic design process by interactively visualizing performance and geometry. We decompose the design of such an environment into function structures, identify the primary and secondary tasks, present an implementation of the system, and verify the interface in terms of usability and expressiveness. We deploy AeroVR on a prototypical design study of a compressor blade for an engine.