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

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

The Full m Index Sets of P2×Pn

Shiu and Kwong (2008) studied the full friendly index set of P2×Pn, which only addressed the cases where m=0 or 1. In this paper, we significantly extend their work by determining the full m index set MP2×Pn for all values of m. Our key approach is to utilize graph embedding and recursion methods to deduce MP2×Pn for general m. In particular, we embed small graphs like C4 and K2 into P2×Pn and apply recursive techniques to prove the main results. This work expands the scope of previous graph labeling studies and provides new insights into determining the full m index set of product graphs. Given the broad range of applications for labeled graphs, this research can potentially impact fields like coding theory, communication network design, and more

Phytoplankton Community Structure and Its Relationship with Environmental Factors in Nanhai Lake

In order to determine the characteristics of phytoplankton community structure in Nanhai Lake in Baotou City and its relationship with environmental factors, water and phytoplankton samples were collected and composition and biomass were investigated at six sites in the spring, summer, and autumn of 2021. This article used correlation analysis and redundancy analysis (RDA) combined with the community turnover index (BC) to analyze the phytoplankton functional groups. The results showed that 7 phyla and 68 genera of phytoplankton were identified in the water body, of which Chlorophyta, Bacillariophyta, Cyanobacteria, Chrysophyta, Euglenophyta, Cryptophyta, and Pyrrophyta accounted for 34%, 32%, 16%, 6%, 4%, 4%, and 3%, respectively. The phytoplankton in the water body was classified into 23 functional groups, of which MP and D functional groups were the long−term dominant functional groups, indicating that the habitat is a turbid water body. The ecological state index (Q) value ranged from 1.94 to 3.13, with an average value of 2.74. The comprehensive nutritional index (TSIM(∑)) was between 49.32 and 52.11, with an average value of 51.72, indicating that Nanhai Lake was in a mesotrophic state. Correlation analysis and redundancy analysis (RDA) showed that multiple nutrients, transparency (SD), chemical oxygen demand (COD), water temperature (WT), and Chlorophyll a (Chl−a) were the main environmental factors affecting the biomass of dominant functional groups in the water body. The study showed the characteristics of the functional groups of algae in a precious urban lake in arid and semi−arid areas of China and their relationship with environmental factors (physical and chemical indicators, anions and cation ions, and heavy metal ions), and provided a scientific basis for its water quality evaluation

Effect of interface evolution on thermal conductivity of vacuum hot pressed SiC/Al composites

International audienc

Effect of Interface Evolution on Thermal Conductivity of Vacuum Hot Pressed SiC/Al Composites

International audienc

Nanoparticle-Based Drug Delivery Systems: An Inspiring Therapeutic Strategy for Neurodegenerative Diseases

Neurodegenerative diseases are common, incurable neurological disorders with high prevalence, and lead to memory, movement, language, and intelligence impairments, threatening the lives and health of patients worldwide. The blood–brain barrier (BBB), a physiological barrier between the central nervous system and peripheral blood circulation, plays an important role in maintaining the homeostasis of the intracerebral environment by strictly regulating the transport of substances between the blood and brain. Therefore, it is difficult for therapeutic drugs to penetrate the BBB and reach the brain, and this affects their efficacy. Nanoparticles (NPs) can be used as drug transport carriers and are also known as nanoparticle-based drug delivery systems (NDDSs). These systems not only increase the stability of drugs but also facilitate the crossing of drugs through the BBB and improve their efficacy. In this article, we provided an overview of the types and administration routes of NPs, highlighted the preclinical and clinical studies of NDDSs in neurodegenerative diseases, and summarized the combined therapeutic strategies in the management of neurodegenerative diseases. Finally, the prospects and challenges of NDDSs in recent basic and clinical research were also discussed. Above all, NDDSs provide an inspiring therapeutic strategy for the treatment of neurodegenerative diseases