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

Discovery of novel 4-hydroxyquinolines as indoleamine 2, 3-dioxygenase 1 inhibitors by virtual screening

Objective To discover novel indoleamine 2, 3-dioxygenase 1 (IDO1) inhibitors with new scaffold structures by screening ZINC and Chembridge databases using pharmacophore modeling and molecular docking. Methods We performed virtual screening of the ZINC database by molecular docking targeting the enzymatic active site of IDO1. The compounds with high scores were selected for enzyme activity test to find the new leads; A pharmacophore model was constructed based on 3 established IDO1 inhibitors that had been tested in clinical trials for virtual screening of the analogues of the lead compounds. The compounds matching the pharmacophore model were selected for inhibitory activity test, and the molecular dynamics was simulated to explore the binding mode of the compounds to IDO1. Results With molecular docking, we identified 11 lead compounds from more than 2 million virtual compounds and measured their enzyme activity. Among them, ZINC91657208 with a skeleton of 4-hydroxyquinoline was found to effectively inhibit the enzyme activity of IDO1 with an IC50 value of 77.15 μmol/L. Thirty-one analogues were obtained by substructure retrieval with 4-hydroxyquinoline skeleton. Ten compounds were selected by pharmacophore virtual screening and their inhibitory effect on the enzyme activity of IDO1 was tested. Three of the 10 compounds showed obvious inhibitory activities, and among them Chembridge29374490 had the lowest IC50 of 37.78 μmol/L, whose root mean square deviations (RMSD) of the skeleton were 1Å and 2.4Å after equilibrium by molecular dynamics simulation. Conclusion We identified new 4-hydroxyquinoline IDO1 inhibitors from ZINC and Chembridge databases

Simple and Robust Log-Likelihood Ratio Calculation of Coded MPSK Signals in Wireless Sensor Networks for Healthcare

The simple and robust log-likelihood ratio (LLR) computation of coded Multiple Phase Shift Keying (MPSK) signals in Wireless Sensor Networks (WSNs) is considered under both phase noncoherent and Rayleigh fading channels for healthcare applications. We first simplify the optimal LLR for phase noncoherent channel, the estimation of the instantaneous channel state information (CSI) for both the fading amplitude and the additive white Gaussian noise (AWGN) is successfully avoided, and the complexity-intensive process for zero-order Bessel function of the first kind is also perfectly eliminated. Furthermore, we also develop the simplified LLR under Rayleigh fading channel. Correspondingly, the variance estimation for both AWGN and the statistical characteristic of the fading amplitude is no longer required, and the complicated process for implementation of the exponential function is also successfully avoided. Compared to the calculation of optimal LLR with full complexity, the proposed method is implementation-friendly, which is practically desired for energy-limited WSNs. The simulations are developed in the context of low-density parity-check (LDPC) codes, and the corresponding results show that the detection performance is extremely close to that of the full-complexity LLR metrics. That is, the performance degradation is efficiently prevented, whereas complexity reduction is also successfully achieved

Multiple-Symbol Detection Scheme for IEEE 802.15.4c MPSK Receivers over Slow Rayleigh Fading Channels

Although the full multiple-symbol detection (MSD) for IEEE 802.15.4c multiple phase shift keying (MPSK) receivers gives much better performance than the symbol-by-symbol detection (SBSD), its implementation complexity is extremely heavy. We propose a simple MSD scheme based on two implementation-friendly but powerful strategies. First, we find the best and second-best decisions in each symbol position with the standard SBSD procedure, and the global best decision is frozen. Second, for the remaining symbol positions, only the best and second-best symbol decisions, not all the candidates, are jointly searched by the standard MSD procedure. The simulation results indicate that the packet error rate (PER) performance of the simplified MSD scheme is almost the same as that of the full scheme. In particular, at PER of 1×10−3, no more than 0.2 dB performance gap is observed if we just increase the observation window length N to 2. However, the number of decision metrics needed to be calculated is reduced from 256 to 2. Thus, much balance gain between implementation complexity and detection performance is achieved

Thermocapillary Flow in an Annular Two-Layer Liquid System

 By means of a hybrid lattice Boltzmann method, thermocapillary flow, driven by the surface tension owing to a horizontal temperature gradient along the interface in immiscible two-layer liquid system, is simulated numerically. The dynamic behavior of the interface is captured by using phase-field theory. The dependence of flow and interface deformation on the density ratio, Capillary number and aspect ratio, is investigated

Reduced-Complexity Multiple-Symbol Detection of O-QPSK Signals in Smart Metering Utility Networks

In this work, an implementation-friendly multiple-symbol detection (MSD) scheme is proposed for the IEEE 802.15.4g offset quadrature phase shift keying (O-QPSK) receivers over the slow fading channel. The full MSD scheme presents better detection performance than the symbol-by-symbol detection (SBSD) scheme, yet its complexity increases exponentially as the observation window length increases. We introduce a simplified MSD scheme based on two powerful strategies. We first seek the optimal and suboptimal decisions in each symbol position with the standard SBSD procedure. Then, the aforementioned optimal and suboptimal decisions instead of all candidates are jointly searched with the standard MSD procedure. That is, only the most and second most reliable candidates in each symbol position are selected to participate in the final detection. The simulation results demonstrate that the new MSD scheme can achieve more encouraging energy gain than the SBSD scheme, while the high complexity of full MSD is also effectively reduced. A more legitimate compromise between detection performance and complexity is thus accomplished, which enables smart metering utility networks (SUN) nodes to achieve energy saving and maximum service life

Multi-Omics Integration to Reveal the Mechanism of Sericin Inhibiting LPS-Induced Inflammation

Sericin is a natural protein with high application potential, but the research on its efficacy is very limited. In this study, the anti-inflammatory mechanism of sericin protein was investigated. Firstly, the protein composition of sericin extracts was determined by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). This was then combined with Enzyme-linked Immunosorbent Assay (ELISA) and Quantitative Real-time PCR (qRT-PCR), and it was confirmed that the anti-inflammation ability of sericin was positively correlated with the purity of sericin 1 protein. Finally, RNA-seq was performed to quantify the inhibitory capacity of sericin sample SS2 in LPS-stimulated macrophages. The gene functional annotation showed that SS2 suppressed almost all PRRs signaling pathways activated by lipopolysaccharides (LPS), such as the Toll-like receptors (TLRs) and NOD-like receptors (NLRs) signaling pathways. The expression level of adaptor gene MyD88 and receptor gene NOD1 was significantly down-regulated after SS2 treatment. SS2 also reduced the phosphorylation levels of NF-κB P65, P38, and JNK, thereby reducing the expressions of IL-1β, IL-6, INOS, and other inflammatory cytokines. It was confirmed that sericin inhibited LPS-induced inflammation through MyD88/NF-κB pathway. This finding provides necessary theoretical support for sericin development and application

Preliminary Calibration of Spherical Proportional Counter for Low Energy Nuclear Recoils

International audienceNeutrino physics and dark matter detection are frontier topics of current particle physics. Good rock shielding, ultra low background and ultra low energy threshold are key factors to detect signals successfully from neutrino and WIMPs scattering in underground experiments. Thus, a novel large volume spherical proportional counter has been set up in IHEP, which adopted an ultra small front-end capacitor with ultra low energy threshold (few keV) and a single center dynode that creates a strong radial electric field. This simple and robust structure enable the signal to be read out through a single electronic channel. Charges deposited in the gaseous vessel, drifting to the central electrode followed by amplification and collection. In the preliminary calibration of the prototype, it can not only detect but also identify the alpha and neutron particles precisely. The pretest results and performance of the detector reveal its possible application for future neutron background, neutrino and dark matter measurement