Rover: A virtual reality puzzle game about creating an experience that helps the player rediscover something about themselves, like dream and family.

With the development of virtual reality technology, VR is currently replacing old systems and modifying practices and processes in many fields, such as automotive, healthcare, training and psychological therapies (Salanitri et al., 2018). Amongst these fields, the industry of games particularly enjoys an increasingly mature technique in virtual reality technology. It is in no small part because such technology provides an immersive experience during the games, and it in turn enhances players’ comprehension upon the affections incurred in the games. Encountered with such an emerging visual carrier, many products and programs await creation. Throughout this project, motion patterns and visual presentations in the world of games are critically discussed, as well as the distinctive values that are communicated via a combination between virtual reality technology and the view of first person. To present this, players will be provided with inspirations to re-discover themselves from aspects or a dream or a memory

Multidimensional Graph Neural Networks for Wireless Communications

Graph neural networks (GNNs) have been shown promising in improving the efficiency of learning communication policies by leveraging their permutation properties. Nonetheless, existing works design GNNs only for specific wireless policies, lacking a systematical approach for modeling graph and selecting structure. Based on the observation that the mismatched permutation property from the policies and the information loss during the update of hidden representations have large impact on the learning performance and efficiency, in this paper we propose a unified framework to learn permutable wireless policies with multidimensional GNNs. To avoid the information loss, the GNNs update the hidden representations of hyper-edges. To exploit all possible permutations of a policy, we provide a method to identify vertices in a graph. We also investigate the permutability of wireless channels that affects the sample efficiency, and show how to trade off the training, inference, and designing complexities of GNNs. We take precoding in different systems as examples to demonstrate how to apply the framework. Simulation results show that the proposed GNNs can achieve close performance to numerical algorithms, and require much fewer training samples and trainable parameters to achieve the same learning performance as the commonly used convolutional neural networks

Emerald Ash Borer and the application of biological control in Virginia

The emerald ash borer (Agrilus planipennis; EAB) is an invasive wood-boring beetle whose larvae feed on ash phloem. After only 1-5 years of infestation, the larvae create extensive tunnels under the bark that disrupt the tree’s ability to transport water and nutrients, which eventually girdles and kills the tree. Since 2008, EAB has spread to all but the eastern-most counties in Virginia. Bological control is one strategy to limit EAB populations. In this project we study control by native agents (woodpeckers) and imported agents (parasitoid wasps). Mathematical models of host-parasitoid interactions and simulations based on both models and field studies will be presented. Our novel contribution extends the basic Nicholson-Bailey model to a partial refuge system, realized in Virginia where EAB infests both ash and white fringetrees with fringetrees less attractive to the parasitoids. We determine ranges for model parameters that result in stable equilibrium populations

Role of crystal-field-splitting and longe-range-hoppings on superconducting pairing symmetry of La3_3Ni2_2O7_7

We study the bilayer two-orbital model for superconducting pairing symmetry of La$_3$Ni$_2$O$_7$ under pressure. By combining density-functional-theory (DFT), maximally-localized-Wannier-function, and linearized Eliashberg equation with random-phase-approximation, we find that the superconducting pairing symmetry of La$_3$Ni$_2$O$_7$ is robustly $d_{xy}$ if its DFT band structure is accurately reproduced in the downfolded model. We further show that fine-tuning of crystal-field-splitting between two Ni-$e_g$ orbitals qualitatively affects superconducting pairing symmetry of the bilayer two-orbital model, which changes from $d_{xy}$ to $s_{\pm}$ as the crystal-field-splitting exceeds a critical value. When the model only includes nearest-neighbor and second-nearest-neighbor hoppings, the crystal-field-splitting obtained by fitting to the DFT band structure is larger than the critical value and thus leads to $s_{\pm}$ superconducting pairing symmetry. When all nonzero long-range-hoppings are also included in the model, the fitted crystal-field-splitting is reduced and smaller than the critical value, which makes $d_{xy}$ superconducting pairing symmetry more favorable than $s_{\pm}$ symmetry. Our work demonstrates that in downfolded effective models, the details of band structure can play a crucial role in determining pairing symmetry in multi-orbital unconventional superconductors (such as La$_3$Ni$_2$O$_7$).Comment: 11 pages and 4 figure

Nutrient Resorption and Stoichiometric Characteristics of Wuyi Rock Tea Cultivars

Nutrient resorption is an important strategy for plants to retain critical nutrients from senesced leaves and plays important roles in nutrient cycling and ecosystem productivity. As a main economic crop and soil and water conservation species, Wuyi Rock tea has been widely planted in Fujian Province, China. However, foliar nutrient resorptions of Wuyi Rock tea cultivars have not been well quantified. In this study, three Wuyi Rock tea cultivars (Wuyi Jingui, Wuyi Rougui, and Wuyi Shuixian) were selected in the Wuyishan National Soil and Water Conservation, Science and Technology Demonstration Park. Resorption efficiencies of nitrogen (NRE), phosphorus (PRE), and potassium (KRE) along with their stoichiometric characteristics were determined. PRE of the three tea cultivars was significantly higher than KRE and NRE, indicating that tea cultivars were P limited due to low P availability for the tea growth. With the exception of Wuyi Rougui, leaf N and P contents of the other two cultivars (Wuyi Jingui and Wuyi Shuixian) had strong homeostasis under the changing soil environments. Leaf thickness and specific leaf area were positively and significantly correlated with KRE, and total chlorophyll concentration was positively correlated with NRE, indicating that leaf functional traits can be used as indicators for nutrient resorption status. Wuyi Rock tea cultivars had strong adaptabilities to the environments and had high carbon sequestration capabilities; thus, they and could be introduced into nutrient-poor mountainous areas for both economic benefits and soil and water conservation