360BEV: Panoramic Semantic Mapping for Indoor Bird's-Eye View

Seeing only a tiny part of the whole is not knowing the full circumstance. Bird's-eye-view (BEV) perception, a process of obtaining allocentric maps from egocentric views, is restricted when using a narrow Field of View (FoV) alone. In this work, mapping from 360{\deg} panoramas to BEV semantics, the 360BEV task, is established for the first time to achieve holistic representations of indoor scenes in a top-down view. Instead of relying on narrow-FoV image sequences, a panoramic image with depth information is sufficient to generate a holistic BEV semantic map. To benchmark 360BEV, we present two indoor datasets, 360BEV-Matterport and 360BEV-Stanford, both of which include egocentric panoramic images and semantic segmentation labels, as well as allocentric semantic maps. Besides delving deep into different mapping paradigms, we propose a dedicated solution for panoramic semantic mapping, namely 360Mapper. Through extensive experiments, our methods achieve 44.32% and 45.78% in mIoU on both datasets respectively, surpassing previous counterparts with gains of +7.60% and +9.70% in mIoU. Code and datasets are available at the project page: https://jamycheung.github.io/360BEV.html.Comment: Code and datasets are available at the project page: https://jamycheung.github.io/360BEV.html. Accepted to WACV 202

Behind every domain there is a shift: adapting distortion-aware vision transformers for panoramic semantic segmentation

In this paper, we address panoramic semantic segmentation which is under-explored due to two critical challenges: (1) image distortions and object deformations on panoramas; (2) lack of semantic annotations in the 360∘ imagery. To tackle these problems, first, we propose the upgraded Transformer for Panoramic Semantic Segmentation, ie, Trans4PASS+, equipped with Deformable Patch Embedding (DPE) and Deformable MLP (DMLPv2) modules for handling object deformations and image distortions whenever (before or after adaptation) and wherever (shallow or deep levels). Second, we enhance the Mutual Prototypical Adaptation (MPA) strategy via pseudo-label rectification for unsupervised domain adaptive panoramic segmentation. Third, aside from Pinhole-to-Panoramic ( Pin2Pan ) adaptation, we create a new dataset (SynPASS) with 9,080 panoramic images, facilitating Synthetic-to-Real ( Syn2Real ) adaptation scheme in 360∘ imagery. Extensive experiments are conducted, which cover indoor and outdoor scenarios, and each of them is investigated with Pin2Pan and Syn2Real regimens. Trans4PASS+ achieves state-of-the-art performances on four domain adaptive panoramic semantic segmentation benchmarks. Code is available at https://github.com/jamycheung/Trans4PASS

Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation

In this paper, we address panoramic semantic segmentation which is under-explored due to two critical challenges: (1) image distortions and object deformations on panoramas; (2) lack of semantic annotations in the 360-degree imagery. To tackle these problems, first, we propose the upgraded Transformer for Panoramic Semantic Segmentation, i.e., Trans4PASS+, equipped with Deformable Patch Embedding (DPE) and Deformable MLP (DMLPv2) modules for handling object deformations and image distortions whenever (before or after adaptation) and wherever (shallow or deep levels). Second, we enhance the Mutual Prototypical Adaptation (MPA) strategy via pseudo-label rectification for unsupervised domain adaptive panoramic segmentation. Third, aside from Pinhole-to-Panoramic (Pin2Pan) adaptation, we create a new dataset (SynPASS) with 9,080 panoramic images, facilitating Synthetic-to-Real (Syn2Real) adaptation scheme in 360-degree imagery. Extensive experiments are conducted, which cover indoor and outdoor scenarios, and each of them is investigated with Pin2Pan and Syn2Real regimens. Trans4PASS+ achieves state-of-the-art performances on four domain adaptive panoramic semantic segmentation benchmarks. Code is available at https://github.com/jamycheung/Trans4PASS.Comment: Extended version of CVPR 2022 paper arXiv:2203.01452. Code is available at https://github.com/jamycheung/Trans4PAS

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Yeast Two-Hybrid Screen Identifies PKA-Riα Interacting Proteins during Mouse Spermiogenesis

cAMP-dependent protein kinase (PKA) signaling plays various roles during mammalian spermatogenesis, ranging from the regulation of gene expression to the modulation of sperm motility. However, the molecular mechanisms that govern the multifaceted functions of PKA during spermatogenesis remain largely unclear. We previously found that PKA regulatory subunit I α (RIα) and catalytic subunit α (Cα) co-sediment with polyribosomal fractions of mouse testis lysate on sucrose gradient and the stimulation of PKA activity facilitates protein synthesis in post-meiotic elongating spermatids, indicating that type I PKA is intricately associated with protein translation machinery and regulates protein synthesis during mouse spermiogenesis. Since PKA activity is often regulated by interacting proteins that form complexes with its regulatory subunits, the identification of PKA-RIα interacting proteins in post-meiotic spermatogenic cells will facilitate our understanding of its regulatory roles in protein synthesis and spermiogenesis. In the present study, we applied a yeast two-hybrid screen to identify PKA-Riα-binding proteins using a cDNA library generated from mouse round and elongating spermatids. Numerous proteins were found to potentially interact with PKA-RIα, including proteostasis modulators, metabolic enzymes, cytoskeletal regulators, and mitochondrial proteins, many of which are specifically expressed in testes. Consistently, the examination of MENA (mouse ENA/VASP homolog) in developing mouse testes suggested that post-meiotic spermatogenic cells express a short isoform of MENA that interacts with PKA-RIα in yeast two-hybrid assay. The identification of PKA-RIα interacting proteins provides us solid basis to further explore how PKA signaling regulates protein synthesis and cellular morphogenesis during mouse spermatogenesis

Electrochemical Properties of Niobium Coating for Biomedical Application

The preparation of the Nb coating was performed on the bare Ti–6Al–4V alloy using the double glow discharge plasma technique. It was characterized that the Nb coating exhibited a face centered cubic (fcc) crystal structure and a pronounced (200) preferred orientation. The SEM micrograph of the cross section for the coating displayed dense microstructure with a thickness of approximately 18 µm. The critical load (Lc) of the coating was determined to be about 83.5 N by the scratch tests. The electrochemical corrosion resistance of the coating was examined in Ringer’s solution at 37 °C by a series of electrochemical techniques, including open-circuit potential (OCP), potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), and a Mott–Schottky analysis. As the result of the potentiodynamic polarization, the Nb coating possessed a more positive corrosion potential and lower corrosion current density than the Ti–6Al–4V substrate. EIS fitting date showed that the Nb coating always possessed a higher value of impedance and lower effective capacitance than those of the substrate during the five days of immersion testing. The main component of the passive film developed on the Nb coating was Nb2O5, confirmed by an X-ray photoelectron spectroscopy (XPS) analysis. A Mott–Schottky analysis demonstrated typical n-type semiconductor characteristics of the Nb coating, and both the donor density and flat band potential of the coating were lower than those of the substrate at all the given formation potential. These investigations demonstrate that the Nb coating can significantly improve the corrosion protection of uncoated Ti–6Al–4V and is thus a promising coating for the surface protection of bioimplants

Yeast Two-Hybrid Screen Identifies PKA-Riα Interacting Proteins during Mouse Spermiogenesis

cAMP-dependent protein kinase (PKA) signaling plays various roles during mammalian spermatogenesis, ranging from the regulation of gene expression to the modulation of sperm motility. However, the molecular mechanisms that govern the multifaceted functions of PKA during spermatogenesis remain largely unclear. We previously found that PKA regulatory subunit I α (RIα) and catalytic subunit α (Cα) co-sediment with polyribosomal fractions of mouse testis lysate on sucrose gradient and the stimulation of PKA activity facilitates protein synthesis in post-meiotic elongating spermatids, indicating that type I PKA is intricately associated with protein translation machinery and regulates protein synthesis during mouse spermiogenesis. Since PKA activity is often regulated by interacting proteins that form complexes with its regulatory subunits, the identification of PKA-RIα interacting proteins in post-meiotic spermatogenic cells will facilitate our understanding of its regulatory roles in protein synthesis and spermiogenesis. In the present study, we applied a yeast two-hybrid screen to identify PKA-Riα-binding proteins using a cDNA library generated from mouse round and elongating spermatids. Numerous proteins were found to potentially interact with PKA-RIα, including proteostasis modulators, metabolic enzymes, cytoskeletal regulators, and mitochondrial proteins, many of which are specifically expressed in testes. Consistently, the examination of MENA (mouse ENA/VASP homolog) in developing mouse testes suggested that post-meiotic spermatogenic cells express a short isoform of MENA that interacts with PKA-RIα in yeast two-hybrid assay. The identification of PKA-RIα interacting proteins provides us solid basis to further explore how PKA signaling regulates protein synthesis and cellular morphogenesis during mouse spermatogenesis

Determination of Supercooling Degree, Nucleation and Growth Rates, and Particle Size for Ice Slurry Crystallization in Vacuum

Understanding the crystallization behavior of ice slurry under vacuum condition is important to the wide application of the vacuum method. In this study, we first measured the supercooling degree of the initiation of ice slurry formation under different stirring rates, cooling rates and ethylene glycol concentrations. Results indicate that the supercooling crystallization pressure difference increases with increasing cooling rate, while it decreases with increasing ethylene glycol concentration. The stirring rate has little influence on supercooling crystallization pressure difference. Second, the crystallization kinetics of ice crystals was conducted through batch cooling crystallization experiments based on the population balance equation. The equations of nucleation rate and growth rate were established in terms of power law kinetic expressions. Meanwhile, the influences of suspension density, stirring rate and supercooling degree on the process of nucleation and growth were studied. Third, the morphology of ice crystals in ice slurry was obtained using a microscopic observation system. It is found that the effect of stirring rate on ice crystal size is very small and the addition of ethylene glycoleffectively inhibits the growth of ice crystals. The results in this paper can provide theoretical guidance and technical support for the development of vacuum icemakers