Mobile Metaverse: A Road Map from Metaverse to Metavehicles

With the rapid development of communication technologies and extended reality (XR), the services and applications of the Metaverse are gradually entering our lives. However, the current development of the Metaverse provides users with services that are homogeneous with the user experience that the Internet has brought in the past, making them more like an extension of the Internet. In addition, as a mobile application carrier for the Metaverse, it is also worth considering how vehicles with diverse onboard components can develop in synergy with the Metaverse. In this article, we focus on the core of the Metaverse, namely user experience, and provide a road map from Metaverse to Metaverse vehicles (Metavehicles). Specifically, we first elaborate on six features of the Metaverse from the perspective of user experience and propose a hierarchical framework for the Metaverse based on the evolutionary logic of the features. Under the guidance of this framework, we discuss the empowerment of onboard components of Metavehicles on the development of the Metaverse, and analyze the service experience that Metavehicles can bring to two types of users, namely drivers and passengers. Finally, considering the differentiated development levels of Metaverse and autonomous driving, we further establish a hierarchical framework for Metavehicles from three aspects (i.e., enhance Metaverse, enhance driving experience, and enhance entertainment experience), providing an evolutionary path for the development of Metavehicles.Comment: 7 pages, 5 figure

Numerical analysis of flow noises in the square cavity vortex based on computational fluid dynamics

In order to study turbulence conditions in an underwater square cavity, the large eddy simulation method was adopted to analyze flow field distributions in the cavity as well as its development and pressure pulsation characteristics at some key positions. MATLAB was also adopted to realize Fast Fourier Transform of signals in time domain and obtain pressure pulsation levels in frequency domain. Based on the analyzed results, pressure pulsation characteristics of key points in the cavity were further discussed. The results showed that pressure pulsation frequencies and characteristics were different with different positions in the square cavity and were closely related with relevant vortex motion states. It was found through comparisons with the experimental results, that pressure pulsation simulation had a good consistency with the experiment when the analyzed frequency was more than 31.5 Hz. As a result, feasibility and accuracy of numerical simulation and Fourier analysis methods were verified. Finally, a numerical model of square cavity in near sound field was built, and sound source intensity distributions at two frequency points were extracted. It could be found that the sound source intensity was large at the rear-edge step, which was consistent with the intensity distribution of vortices. Therefore, reliability of the numerical model in this paper was indirectly verified in the results

Automatic thickness estimation for skeletal muscle in ultrasonography: evaluation of two enhancement methods

BACKGROUND: Ultrasonography is a convenient technique to investigate muscle properties and has been widely used to look into muscle functions since it is non-invasive and real-time. Muscle thickness, a quantification which can effectively reflect the muscle activities during muscle contraction, is an important measure for musculoskeletal studies using ultrasonography. The traditional manual operation to read muscle thickness is subjective and time-consuming, therefore a number of studies have focused on the automatic estimation of muscle fascicle orientation and muscle thickness, to which the speckle noises in ultrasound images could be the major obstacle. There have been two popular methods proposed to enhance the hyperechoic regions over the speckles in ultrasonography, namely Gabor Filtering and Multiscale Vessel Enhancement Filtering (MVEF). METHODS: A study on gastrocnemius muscle is conducted to quantitatively evaluate whether and how these two methods could help the automatic estimation of the muscle thickness based on Revoting Hough Transform (RVHT). The muscle thickness results obtained from each of the two methods are compared with the results from manual measurement, respectively. Data from an aged subject with cerebral infarction is also studied. RESULTS: It’s shown in the experiments that, Gabor Filtering and MVEF can both enable RVHT to generate comparable results of muscle thickness to those by manual drawing (mean ± SD, 1.45 ± 0.48 and 1.38 ± 0.56 mm respectively). However, the MVEF method requires much less computation than Gabor Filtering. CONCLUSIONS: Both methods, as preprocessing procedure can enable RVHT the automatic estimation of muscle thickness and MVEF is believed to be a better choice for real-time applications

Coupling Artificial Neurons in BERT and Biological Neurons in the Human Brain

Linking computational natural language processing (NLP) models and neural responses to language in the human brain on the one hand facilitates the effort towards disentangling the neural representations underpinning language perception, on the other hand provides neurolinguistics evidence to evaluate and improve NLP models. Mappings of an NLP model's representations of and the brain activities evoked by linguistic input are typically deployed to reveal this symbiosis. However, two critical problems limit its advancement: 1) The model's representations (artificial neurons, ANs) rely on layer-level embeddings and thus lack fine-granularity; 2) The brain activities (biological neurons, BNs) are limited to neural recordings of isolated cortical unit (i.e., voxel/region) and thus lack integrations and interactions among brain functions. To address those problems, in this study, we 1) define ANs with fine-granularity in transformer-based NLP models (BERT in this study) and measure their temporal activations to input text sequences; 2) define BNs as functional brain networks (FBNs) extracted from functional magnetic resonance imaging (fMRI) data to capture functional interactions in the brain; 3) couple ANs and BNs by maximizing the synchronization of their temporal activations. Our experimental results demonstrate 1) The activations of ANs and BNs are significantly synchronized; 2) the ANs carry meaningful linguistic/semantic information and anchor to their BN signatures; 3) the anchored BNs are interpretable in a neurolinguistic context. Overall, our study introduces a novel, general, and effective framework to link transformer-based NLP models and neural activities in response to language and may provide novel insights for future studies such as brain-inspired evaluation and development of NLP models

Study on coupled heat-water-vapor transfer in buffer material based on SPH method

To study the hydrothermal evolution law in buffer materials, based on the heat balance equation of unsaturated soil and the quality control equation of water migration, a coupled heat-water-vapor model of unsaturated soil is proposed. This model comprehensively considers the transition process of water vapor, the heat transfer caused by water flow and vapor migration, as well as the influence of temperature potential on water flow and vapor migration. The smoothed particle hydrodynamics (SPH) method can be used to calculate their evolution process conveniently. In the solution, the vapor content of heat balance equation is solved first, and then the water content and temperature field are solved, so as the coupling of temperature field between water and vapor field is implemented. The rationality of the model is verified by the tested results of soil column test. According to the established theoretical model, the heat-water-vapor three-field coupling problem of the buffer material in the repository was simulated and studied, and the hydrothermal evolution law inside the buffer material was revealed. On this basis, the influence of the change of groundwater pressure and heat source temperature on the hydrothermal evolution law of buffer material was further analyzed

Biogas desulfurization under anoxic conditions using synthetic wastewater and biogas slurry

A feasibility study was conducted to determine whether aerated biogas slurry is a suitable nutrient solution for biogas desulfurization systems with a biotrickling filter. At a loading rate of 36.20 g-H2S m(-3)h(-1), the H2S and NOx--N removal efficiencies were 84.7% (average elimination capacity of 30.67 g-H2S m(-3)h(-1)) and 60.9%, respectively, when utilizing synthetic wastewater in a simultaneous biogas desulfurization and wastewater de nitrification system. However, these efficiencies were just 61.9% (average elimination capacity of 22.42 g-H2S m(-3)h(-1)) and 49.2%, respectively, when biogas slurry was used. High-throughput sequencing revealed that the Thiobacillus and Sulfurimonas genera were the main functional bacteria. Alpha- and beta-diversity analyses showed that the H2S loading rate significantly affected the microbial community structure, especially in the system utilizing aerated biogas slurry. Finally, based on the results, we describe a feasible approach to using biogas slurry for biogas desulfurization