Deflection in higher dimensional spacetime and asymptotically non-flat spacetimes

Using a perturbative technique, in this work we study the deflection of null and timelike signals in the extended Einstein-Maxwell spacetime, the Born-Infeld gravity and the charged Ellis-Bronnikov (CEB) spacetime in the weak field limit. The deflection angles are found to take a (quasi-)series form of the impact parameter, and automatically takes into account the finite distance effect of the source and observer. The method is also applied to find the deflections in CEB spacetime with arbitrary dimension. It's shown that to the leading non-trivial order, the deflection in some $n$-dimensional spacetimes is of the order $\mathcal{O}(M/b)^{n-3}$. We then extended the method to spacetimes that are asymptotically non-flat and studied the deflection in a nonlinear electrodynamical scalar theory. The deflection angle in such asymptotically non-flat spacetimes at the trivial order is found to be not $\pi$ anymore. In all these cases, the perturbative deflection angles are shown to agree with numerical results extremely well. The effects of some nontrivial spacetime parameters as well as the signal velocity on the deflection angles are analyzed.Comment: 30 pages, 7 figures; title modified; to match published version in Class.Quant.Gra

Viewport Prediction for Volumetric Video Streaming by Exploring Video Saliency and Trajectory Information

Volumetric video, also known as hologram video, is a novel medium that portrays natural content in Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). It is expected to be the next-gen video technology and a prevalent use case for 5G and beyond wireless communication. Considering that each user typically only watches a section of the volumetric video, known as the viewport, it is essential to have precise viewport prediction for optimal performance. However, research on this topic is still in its infancy. In the end, this paper presents and proposes a novel approach, named Saliency and Trajectory Viewport Prediction (STVP), which aims to improve the precision of viewport prediction in volumetric video streaming. The STVP extensively utilizes video saliency information and viewport trajectory. To our knowledge, this is the first comprehensive study of viewport prediction in volumetric video streaming. In particular, we introduce a novel sampling method, Uniform Random Sampling (URS), to reduce computational complexity while still preserving video features in an efficient manner. Then we present a saliency detection technique that incorporates both spatial and temporal information for detecting static, dynamic geometric, and color salient regions. Finally, we intelligently fuse saliency and trajectory information to achieve more accurate viewport prediction. We conduct extensive simulations to evaluate the effectiveness of our proposed viewport prediction methods using state-of-the-art volumetric video sequences. The experimental results show the superiority of the proposed method over existing schemes. The dataset and source code will be publicly accessible after acceptance

Establishment of the Luoping Biota National Geopark in Yunnan, China

Geoparks in China have been a great success story, with 284 national geoparks and 41 of them accorded UNESCO international status, the highest number for any country in the world. We track the progress of one of the geoparks, Luoping Biota National Geopark in Yunnan Province, from initial plans after its discovery as a key site for the exceptional preservation of Middle Triassic marine fossils in 2007, to acceptance as a National Geopark in 2011. Geoparks combine great scientific importance with accessibility and attraction for tourists. The scientific importance of Luoping is in the fossils, thousands of specimens of marine invertebrates, fishes and reptiles, together with rare elements from land (e.g. insects, plants), representing an important phase in the Mesozoic Marine Revolution, when life was recovering from devastation at the end of the Permian, and 8 million years later, had developed stable ecosystems with a new structure, dominated by predatory fishes and reptiles. The touristic importance of the Luoping Biota Geopark has already been demonstrated by rapid development of facilities and high visitor numbers

A new millipede (Diplopoda, Helminthomorpha) from the Middle Triassic Luoping biota of Yunnan, Southwest China

AbstractA new helminthomorph millipede,Sinosoma luopingensenew genus new species, from the Triassic Luoping biota of China, has 39 body segments, metazonites with lateral swellings that bear a pair of posterolateral pits (?insertion pits for spine bases), and sternites that are unfused to the pleurotergites. This millipede shares a number of characters with nematophoran diplopods, but lacks the prominent dorsal suture characteristic of that order. Other “millipede” material from the biota is more problematic. Millipedes are a rare part of the Luoping biota, which is composed mainly of marine and near-shore organisms. Occurrences of fossil millipedes are exceedingly rare in Triassic rocks worldwide, comprising specimens from Europe, Asia, and Africa, and consisting of juliform millipedes and millipedes that are either nematophorans or forms very similar to nematophorans.</jats:p

Exceptional appendage and soft-tissue preservation in a Middle Triassic horseshoe crab from SW China

Abstract Horseshoe crabs are classic “living fossils”, supposedly slowly evolving, conservative taxa, with a long fossil record back to the Ordovician. The evolution of their exoskeleton is well documented by fossils, but appendage and soft-tissue preservation is extremely rare. Here we analyse details of appendage and soft-tissue preservation in Yunnanolimulus luopingensis, a Middle Triassic (ca. 244 million years old) horseshoe crab from Yunnan Province, SW China. The remarkable preservation of anatomical details including the chelicerae, five pairs of walking appendages, opisthosomal appendages with book gills, muscles, and fine setae permits comparison with extant horseshoe crabs. The close anatomical similarity between the Middle Triassic horseshoe crabs and their recent analogues documents anatomical conservatism for over 240 million years, suggesting persistence of lifestyle. The occurrence of Carcinoscorpius-type claspers on the first and second walking legs in male individuals of Y. luopingensis indicates that simple chelate claspers in males are plesiomorphic for horseshoe crabs, and the bulbous claspers in Tachypleus and Limulus are derived

Study on the Performance of High-Speed Rail Damage of Four Different Materials

For four types of railway rails, corresponding rolling tests have been executed by using the JD-1 wheel/rail simulation device based on the Hertz simulation method, which can ensure the reciprocal contact condition between simulation rail and wheel under experimental conditions approximate to practical contact conditions. The results indicate that, for the rail material which has a higher hardness, the wear volume was less and the plastic deformation layer was thinner after the rolling test, but the crack propagation was more significant and the fatigue damage was severer, showing that its wear resistance was better. The analysis shows that the fatigue resistance of U71Mn rail was better, and considering fatigue is the main failure type for high-speed rail, so it is more suited to the high-speed railway

Dynamic evolution of sentiments in Never Let Me Go: Insights from multifractal theory and its implications for literary analysis

The moods, feelings and attitudes represented in a novel will resonate in the reader by activating similar sentiments. It is generally accepted that sentiment analysis can capture aspects of such moods, feelings and attitudes and can be used to summarize a novel's plot in a story arc. With the availability of a number of algorithms to automatically extract sentiment-based story arcs, new approaches for their utilization becomes pertinent. We propose to use nonlinear adaptive filtering and fractal analysis in order to analyze the narrative coherence and dynamic evolution of a novel. Using Never Let Me Go by Kazuo Ishiguro, the winner of the 2017 Nobel Prize for Literature as an example, we show that: 1) nonlinear adaptive filtering extracts a story arc that reflects the tragic trend of the novel; 2) the story arc displays persistent dynamics as measured by the Hurst exponent at short and medium time scales; 3) the plots dynamic evolution is reflected in in the time-varying Hurst exponent. We argue that these findings are indicative of the potential multifractal theory has for computational narratology and large-scale literary analysis. Specifically, that the global Hurst exponent of a story arc is an index of narrative coherence that can identify bland, incoherent and coherent narratives on a continuous scale. And, further, that the local time-varying Hurst exponent captures variation of a novel's plot such that the extrema have specific narratological interpretations