AVstack: An Open-Source, Reconfigurable Platform for Autonomous Vehicle Development

Pioneers of autonomous vehicles (AVs) promised to revolutionize the driving experience and driving safety. However, milestones in AVs have materialized slower than forecast. Two culprits are (1) the lack of verifiability of proposed state-of-the-art AV components, and (2) stagnation of pursuing next-level evaluations, e.g., vehicle-to-infrastructure (V2I) and multi-agent collaboration. In part, progress has been hampered by: the large volume of software in AVs, the multiple disparate conventions, the difficulty of testing across datasets and simulators, and the inflexibility of state-of-the-art AV components. To address these challenges, we present AVstack, an open-source, reconfigurable software platform for AV design, implementation, test, and analysis. AVstack solves the validation problem by enabling first-of-a-kind trade studies on datasets and physics-based simulators. AVstack solves the stagnation problem as a reconfigurable AV platform built on dozens of open-source AV components in a high-level programming language. We demonstrate the power of AVstack through longitudinal testing across multiple benchmark datasets and V2I-collaboration case studies that explore trade-offs of designing multi-sensor, multi-agent algorithms

Faster Min-Plus Product for Monotone Instances

In this paper, we show that the time complexity of monotone min-plus product of two $n\times n$ matrices is $\tilde{O}(n^{(3+\omega)/2})=\tilde{O}(n^{2.687})$, where $\omega < 2.373$ is the fast matrix multiplication exponent [Alman and Vassilevska Williams 2021]. That is, when $A$ is an arbitrary integer matrix and $B$ is either row-monotone or column-monotone with integer elements bounded by $O(n)$, computing the min-plus product $C$ where $C_{i,j}=\min_k\{A_{i,k}+B_{k,j}\}$ takes $\tilde{O}(n^{(3+\omega)/2})$ time, which greatly improves the previous time bound of $\tilde{O}(n^{(12+\omega)/5})=\tilde{O}(n^{2.875})$ [Gu, Polak, Vassilevska Williams and Xu 2021]. Then by simple reductions, this means the following problems also have $\tilde{O}(n^{(3+\omega)/2})$ time algorithms: (1) $A$ and $B$ are both bounded-difference, that is, the difference between any two adjacent entries is a constant. The previous results give time complexities of $\tilde{O}(n^{2.824})$ [Bringmann, Grandoni, Saha and Vassilevska Williams 2016] and $\tilde{O}(n^{2.779})$ [Chi, Duan and Xie 2022]. (2) $A$ is arbitrary and the columns or rows of $B$ are bounded-difference. Previous result gives time complexity of $\tilde{O}(n^{2.922})$ [Bringmann, Grandoni, Saha and Vassilevska Williams 2016]. (3) The problems reducible to these problems, such as language edit distance, RNA-folding, scored parsing problem on BD grammars. [Bringmann, Grandoni, Saha and Vassilevska Williams 2016]. Finally, we also consider the problem of min-plus convolution between two integral sequences which are monotone and bounded by $O(n)$, and achieve a running time upper bound of $\tilde{O}(n^{1.5})$. Previously, this task requires running time $\tilde{O}(n^{(9+\sqrt{177})/12}) = O(n^{1.859})$ [Chan and Lewenstein 2015].Comment: 26 page

A fossil oceanic lithosphere preserved inside a continent

The recycling of oceanic lithosphere into the deep mantle at subduction zones is one of the most fundamental geodynamic processes on Earth. During the closure of an ocean, ancient oceanic slabs are thought to be consumed entirely in subduction zones due to their negative buoyancy. Yet, it is recently suggested that small pieces of oceanic slabs could be trapped along paleo-subduction zones. What remains far more enigmatic is whether significant portions of paleo-oceanic lithosphere could eventually avoid the fate of subduction and be accreted to continental lithosphere, thus contributing to continental growth through time. We present seismic evidence for a preserved paleo-oceanic lithosphere beneath the Junggar region in northwestern China. We show that unsubducted oceanic lithosphere in the West Junggar has been preserved beneath the Junggar Basin, becoming a piece of the Eurasian continent.</p

Pea albumin extracted from pea (Pisum sativum L.) seed protects mice from high fat diet-induced obesity by modulating lipid metabolism and gut microbiota

Plant protein has been reported to play a key role in the prevention of obesity and associated complications. It is unknown whether pea albumin may exert anit-obesity and obesity-associated metabolic disorders alleviation. Pea albumin was isolated from pea seed (Pisum sativum L.) and determined its functional role for anti-obesity and metabolic disorders alleviation in high fat diet (HFD)-fed mice. Pea albumin administration reduced body weight gain, improved glucose tolerance and insulin sensitivity, reduced inflammatory cytokines secretion, and alleviated hepatic steatosis in HFD-fed mice. Interestingly, pea albumin inhibited lipid accumulation in 3T3-L1 cells in vitro and modulated lipid metabolism by upregulating critical proteins implicated in lipolysis and fatty acid oxidation, and downregulating lipogenesis in vivo. Moreover, pea albumin restored gut microbial composition to normal fat diet condition and selectively promoted the growth of beneficial gut bacteria (Akkermansia, Parabacteroides etc.). Collectively, the data demonstrated that pea albumin protects mice from HFD-induced obesity and associated metabolic disorders

Topology and evolution of international trade network for fish and fish products

In this study, a complex network method was employed to quantify the changing role of countries in fish trade and the dynamic characteristics of fish globalization. Based on the United Nations Comtrade Database, the International Trade Network for Fish and Fish Products (ITN-Fish) was constructed as a series of weighted-directed networks for each year from 1990 to 2018. Almost all countries and territories worldwide have participated in the fish trade. In 2018, the network identified 229 fish traders. The share of developing countries in imports and exports has increased. Traders actively establish new trade relations, which improve network connectivity. However, these relations only account for a small part of the fish trade. The high connectivity allows risks to spread rapidly in the world through hubs such as the United States and China, which raises concerns about the robustness of these weak links in the Sino-US trade conflict and the outbreak of COVID-19. However, we have optimistic expectations on this issue. The dynamic of network topology property shows that the globalization of fish trade flourished between 1990 and 2018. Although, due to the financial crisis and its subsequent impact, the total amount of fish trade declined in 2009 and 2015, the network structure was not seriously affected, and the trend of topology property remained unchanged. Based on the construction of the international trade network, its node attribute, and its structural attribute, fish trade maintains the trend of globalization. Countries should actively adhere to trade globalization to promote the development of the fish trade