PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation

Reliable LiDAR panoptic segmentation (LPS), including both semantic and instance segmentation, is vital for many robotic applications, such as autonomous driving. This work proposes a new LPS framework named PANet to eliminate the dependency on the offset branch and improve the performance on large objects, which are always over-segmented by clustering algorithms. Firstly, we propose a non-learning Sparse Instance Proposal (SIP) module with the ``sampling-shifting-grouping" scheme to directly group thing points into instances from the raw point cloud efficiently. More specifically, balanced point sampling is introduced to generate sparse seed points with more uniform point distribution over the distance range. And a shift module, termed bubble shifting, is proposed to shrink the seed points to the clustered centers. Then we utilize the connected component label algorithm to generate instance proposals. Furthermore, an instance aggregation module is devised to integrate potentially fragmented instances, improving the performance of the SIP module on large objects. Extensive experiments show that PANet achieves state-of-the-art performance among published works on the SemanticKITII validation and nuScenes validation for the panoptic segmentation task.Comment: 8 pages, 3 figures, IROS202

A new unconventional HLA-A2-restricted epitope from HBV core protein elicits antiviral cytotoxic T lymphocytes

Cytotoxic T cells (CTLs) play a key role in the control of Hepatitis B virus (HBV) infection and viral clearance. However, most of identified CTL epitopes are derived from HBV of genotypes A and D, and few have been defined in virus of genotypes B and C which are more prevalent in Asia. As HBV core protein (HBc) is the most conservative and immunogenic component, in this study we used an overlapping 9-mer peptide pool covering HBc to screen and identify specific CTL epitopes. An unconventional HLA-A2-restricted epitope HBc141–149 was discovered and structurally characterized by crystallization analysis. The immunogenicity and anti-HBV activity were further determined in HBV and HLA-A2 transgenic mice. Finally, we show that mutations in HBc141–149 epitope are associated with viral parameters and disease progression in HBV infected patients. Our data therefore provide insights into the structure characteristics of this unconventional epitope binding to MHC-I molecules, as well as epitope specific CTL activity that orchestrate T cell response and immune evasion in HBV infected patients

Deacetylation of HSD17B10 by SIRT3 regulates cell growth and cell resistance under oxidative and starvation stresses.

17-beta-hydroxysteroid dehydrogenase 10 (HSD17B10) plays an important role in mitochondrial fatty acid metabolism and is also involved in mitochondrial tRNA maturation. HSD17B10 missense mutations cause HSD10 mitochondrial disease (HSD10MD). HSD17B10 with mutations identified from cases of HSD10MD show loss of function in dehydrogenase activity and mitochondrial tRNA maturation, resulting in mitochondrial dysfunction. It has also been implicated to play roles in the development of Alzheimer disease (AD) and tumorigenesis. Here, we found that HSD17B10 is a new substrate of NAD-dependent deacetylase Sirtuin 3 (SIRT3). HSD17B10 is acetylated at lysine residues K79, K99 and K105 by the acetyltransferase CBP, and the acetylation is reversed by SIRT3. HSD17B10 acetylation regulates its enzymatic activity and the formation of mitochondrial RNase P. Furthermore, HSD17B10 acetylation regulates the intracellular functions, affecting cell growth and cell resistance in response to stresses. Our results demonstrated that acetylation is an important regulation mechanism for HSD17B10 and may provide insight into interrupting the development of AD

The genomic and bulked segregant analysis of \u3ci\u3eCurcuma alismatifolia\u3c/i\u3e revealed its diverse bract pigmentation

Compared with most flowers where the showy part comprises specialized leaves (petals) directly subtending the reproductive structures, most Zingiberaceae species produce showy ‘‘flowers’’ through modifications of leaves (bracts) subtending the true flowers throughout an inflorescence. Curcuma alismatifolia, belonging to the Zingiberaceae family, a plant species originating from Southeast Asia, has become increasingly popular in the flower market worldwide because of its varied and esthetically pleasing bracts produced in different cultivars. Here, we present the chromosome-scale genome assembly of C. alismatifolia ‘‘Chiang Mai Pink’’ and explore the underlying mechanisms of bract pigmentation. Comparative genomic analysis revealed C. alismatifolia contains a residual signal of wholegenome duplication. Duplicated genes, including pigment-related genes, exhibit functional and structural differentiation resulting in diverse bract colors among C. alismatifolia cultivars. In addition, we identified the key genes that produce different colored bracts in C. alismatifolia, such as F3\u275’H, DFR, ANS and several transcription factors for anthocyanin synthesis, as well as chlH and CAO in the chlorophyll synthesis pathway by conducting transcriptomic analysis, bulked segregant analysis using both DNA and RNA data, and population genomic analysis. This work provides data for understanding the mechanism of bract pigmentation and will accelerate breeding in developing novel cultivars with richly colored bracts in C. alismatifolia and related species. It is also important to understand the variation in the evolution of the Zingiberaceae family

Search for light dark matter from atmosphere in PandaX-4T

We report a search for light dark matter produced through the cascading decay of $\eta$ mesons, which are created as a result of inelastic collisions between cosmic rays and Earth's atmosphere. We introduce a new and general framework, publicly accessible, designed to address boosted dark matter specifically, with which a full and dedicated simulation including both elastic and quasi-elastic processes of Earth attenuation effect on the dark matter particles arriving at the detector is performed. In the PandaX-4T commissioning data of 0.63 tonne$\cdot$year exposure, no significant excess over background is observed. The first constraints on the interaction between light dark matter generated in the atmosphere and nucleus through a light scalar mediator are obtained. The lowest excluded cross-section is set at $5.9 \times 10^{-37}{\rm cm^2}$ for dark matter mass of $0.1$ MeV$/c^2$ and mediator mass of 300 MeV$/c^2$. The lowest upper limit of $\eta$ to dark matter decay branching ratio is $1.6 \times 10^{-7}$

A Search for Light Fermionic Dark Matter Absorption on Electrons in PandaX-4T

We report a search on a sub-MeV fermionic dark matter absorbed by electrons with an outgoing active neutrino using the 0.63 tonne-year exposure collected by PandaX-4T liquid xenon experiment. No significant signals are observed over the expected background. The data are interpreted into limits to the effective couplings between such dark matter and electrons. For axial-vector or vector interactions, our sensitivity is competitive in comparison to existing astrophysical bounds on the decay of such dark matter into photon final states. In particular, we present the first direct detection limits for an axial-vector (vector) interaction which are the strongest in the mass range from 25 to 45 (35 to 50) keV/c$^2$

Relationship between Oxidation of Metal Surface Layer and Air Quality in Wuhan

In order to find out the relationship of steel futures price with different manganese content, a local fractional algorithm is proposed in this paper. We use three analytical tools - price discovery analysis, arbitrage analysis and a case study approach to assess the magnitude of price divergence risk and determine the hedging effectiveness of steel billet futures. The results show that the proposed method can thus improve overall system performance substantially

Relationship between Oxidation of Metal Surface Layer and Air Quality in Wuhan

In order to find out the relationship of steel futures price with different manganese content, a local fractional algorithm is proposed in this paper. We use three analytical tools - price discovery analysis, arbitrage analysis and a case study approach to assess the magnitude of price divergence risk and determine the hedging effectiveness of steel billet futures. The results show that the proposed method can thus improve overall system performance substantially