EgoVM: Achieving Precise Ego-Localization using Lightweight Vectorized Maps

Accurate and reliable ego-localization is critical for autonomous driving. In this paper, we present EgoVM, an end-to-end localization network that achieves comparable localization accuracy to prior state-of-the-art methods, but uses lightweight vectorized maps instead of heavy point-based maps. To begin with, we extract BEV features from online multi-view images and LiDAR point cloud. Then, we employ a set of learnable semantic embeddings to encode the semantic types of map elements and supervise them with semantic segmentation, to make their feature representation consistent with BEV features. After that, we feed map queries, composed of learnable semantic embeddings and coordinates of map elements, into a transformer decoder to perform cross-modality matching with BEV features. Finally, we adopt a robust histogram-based pose solver to estimate the optimal pose by searching exhaustively over candidate poses. We comprehensively validate the effectiveness of our method using both the nuScenes dataset and a newly collected dataset. The experimental results show that our method achieves centimeter-level localization accuracy, and outperforms existing methods using vectorized maps by a large margin. Furthermore, our model has been extensively tested in a large fleet of autonomous vehicles under various challenging urban scenes.Comment: 8 page

Development of a Ground Based Remote Sensing Approach for Direct Evaluation of Aerosol-Cloud Interaction

The possible interaction and modification of cloud properties due to aerosols is one of the most poorly understood mechanisms within climate studies, resulting in the most significant uncertainty as regards radiation budgeting. In this study, we explore direct ground based remote sensing methods to assess the Aerosol-Cloud Indirect Effect directly, as space-borne retrievals are not directly suitable for simultaneous aerosol/cloud retrievals. To illustrate some of these difficulties, a statistical assessment of existing multispectral imagers on geostationary (e.g., GOES)/Moderate Resolution Imaging Spectroradiometer (MODIS) satellite retrievals of the Cloud Droplet Effective Radius (Reff) showed significant biases especially at larger solar zenith angles, further motivating the use of ground based remote sensing approaches. In particular, we discuss the potential of using a combined Microwave Radiometer (MWR)—Multi-Filter Rotating Shadowband Radiometer (MFRSR) system for real-time monitoring of Cloud Optical Depth (COD) and Cloud Droplet Effective Radius (Reff), which are combined with aerosol vertical properties from an aerosol lidar. An iterative approach combining the simultaneous observations from MFRSR and MWR are used to retrieve the COD and Reff for thick cloud cases and are extensively validated using the DoE Southern Great Plains (SGP) retrievals as well as regression based parameterized model retrievals. In addition, we account for uncertainties in background aerosol, surface albedo and the combined measurement uncertainties from the MWR and MFRSR in order to provide realistic uncertainty estimates, which is found to be ~10% for the parameter range of interest in Aerosol-Cloud Interactions. Finally, we analyze a particular case of possible aerosol-cloud interaction described in the literature at the SGP site and demonstrate that aerosol properties obtained at the surface can lead to inconclusive results in comparison to lidar-derived aerosol properties near the cloud base

A high performance flexible recyclable supercapacitor with polyaniline by casting in unconventional proportion

Abstract(#br)A new type of recyclable flexible solid-state supercapacitor with good electrochemical performance and folder ability is produced through a facile method. Polyvinylidene fluoride - acetylene black - polyethylene glycol - polyaniline (PVDF-AB-PEG-PANI) film electrode with excellent processability and tailorability is prepared by casting strategy, which uses large amount of PVDF as film former. The new electrode has good performance with excellent flexibility (d r < 1 mm and capacity retention 97.4 % after folding 1000 times) and electrochemical performance (It can utilize the active substance efficiently that it closes to the theoretical value, with high areal capacitance of 890.44 mF cm −2 and volumetric capacitance of 89.04 F cm −3 ). A capacitance retention of 72.5 % is obtained for the supercapacitor based on this electrode after 5000 charging/discharging cycles, even polyaniline is synthesized by conventional method. The most interesting thing is that, the supercapacitor based on this electrode can easily be recycled and reused (capacity retention 97.1 % after 4 recycle times)

ULK1/2 Constitute a Bifurcate Node Controlling Glucose Metabolic Fluxes in Addition to Autophagy

揭示了在外界能量供应缺乏时，细胞通过激活ULK1来介导葡萄糖分解代谢重编程以维持胞内的能量与氧化还原稳态的详细机制，并创新地发现了ULK1独立于自噬的关键功能。基于自噬和糖代谢与人类健康的重要相关性，该研究将很可能为我们预防和治疗各类代谢疾病提供新的思路和药物靶点。Metabolic reprogramming is fundamental to biological homeostasis, enabling cells to adjust metabolic routes after sensing altered availability of fuels and growth factors. ULK1 and ULK2 represent key integrators that relay metabolic stress signals to the autophagy machinery. Here, we demonstrate that, during deprivation of amino acid and growth factors, ULK1/2 directly phosphorylate key glycolytic enzymes including hexokinase (HK), phosphofructokinase 1 (PFK1), enolase 1 (ENO1), and the gluconeogenic enzyme fructose-1,6-bisphosphatase (FBP1). Phosphorylation of these enzymes leads to enhanced HK activity to sustain glucose uptake but reduced activity of FBP1 to block the gluconeogenic route and reduced activity of PFK1 and ENO1 to moderate drop of glucose-6-phosphate and to repartition more carbon flux to pentose phosphate pathway (PPP), maintaining cellular energy and redox homeostasis at cellular and organismal levels. These results identify ULK1/2 as a bifurcate-signaling node that sustains glucose metabolic fluxes besides initiation of autophagy in response to nutritional deprivation.State Key Program of National Natural Science of China， the 973 Program；National Natural Science Foundation of China for Fostering Talents in Basic Research ；the Foundation for Innovative Research Groups of the National Natural Science Foundation of China； and the 111 Project of Education of China

Deep-Sequencing Analysis of the Mouse Transcriptome Response to Infection with Brucella melitensis Strains of Differing Virulence

Brucella melitensis is an important zoonotic pathogen that causes brucellosis, a disease that affects sheep, cattle and occasionally humans. B. melitensis strain M5-90, a live attenuated vaccine cultured from B. melitensis strain M28, has been used as an effective tool in the control of brucellosis in goats and sheep in China. However, the molecular changes leading to attenuated virulence and pathogenicity in B. melitensis remain poorly understood. In this study we employed the Illumina Genome Analyzer platform to perform genome-wide digital gene expression (DGE) analysis of mouse peritoneal macrophage responses to B. melitensis infection. Many parallel changes in gene expression profiles were observed in M28- and M5-90-infected macrophages, suggesting that they employ similar survival strategies, notably the induction of anti-inflammatory and antiapoptotic factors. Moreover, 1019 differentially expressed macrophage transcripts were identified 4 h after infection with the different B. melitensis strains, and these differential transcripts notably identified genes involved in the lysosome and mitogen-activated protein kinase (MAPK) pathways. Further analysis employed gene ontology (GO) analysis: high-enrichment GOs identified endocytosis, inflammatory, apoptosis, and transport pathways. Path-Net and Signal-Net analysis highlighted the MAPK pathway as the key regulatory pathway. Moreover, the key differentially expressed genes of the significant pathways were apoptosis-related. These findings demonstrate previously unrecognized changes in gene transcription that are associated with B. melitensis infection of macrophages, and the central signaling pathways identified here merit further investigation. Our data provide new insights into the molecular attenuation mechanism of strain M5-90 and will facilitate the generation of new attenuated vaccine strains with enhanced efficacy

Investigation of the Feasibility of the Dynamic Equivalent Model of Large Photovoltaic Power Plants in a Harmonic Resonance Study

In recent years, there have been several harmonic resonance accidents around the world that involve renewable energy power plants. The frequency scanning method is the most widely used technique in engineering practice to evaluate the severity of resonance due to its simple operation and clear physical meaning. However, when establishing electromagnetic transient simulation models and conducting frequency scans, a single generation unit or a few renewable generation units are usually used to represent the original power plant for the purpose of reducing model complexity and improving the simulation efficiency. Such a practice has been found to be effective in dynamic studies around the fundamental frequency. However, its feasibility in harmonic resonance studies has not yet been fully investigated. Because of this research gap, a feasibility study is conducted in this paper by using a real-life photovoltaic power plant. The detailed harmonic model of the plant is first established using the harmonic linearization method, and the equivalent harmonic model is then developed using the power loss conservation method. The feasibility of the equivalent model was investigated in detail, and the impact of the different impedance models on the resonance analysis was analyzed. The results indicate that the conventional dynamic equivalent model can effectively reflect the harmonic resonance characteristics of photovoltaic power plants. Furthermore, a more simplified model that ignores the inductance of the collector line is recommended in this paper to further reduce the modeling complexity