No abstract

JUNO is a massive liquid scintillator detector with a primary scientific goal of determining the neutrino mass ordering by studying the oscillated anti-neutrino flux coming from two nuclear power plants at 53 km distance. The expected signal anti-neutrino interaction rate is only 60 counts per day (cpd), therefore a careful control of the background sources due to radioactivity is critical. In particular, natural radioactivity present in all materials and in the environment represents a serious issue that could impair the sensitivity of the experiment if appropriate countermeasures were not foreseen. In this paper we discuss the background reduction strategies undertaken by the JUNO collaboration to reduce at minimum the impact of natural radioactivity. We describe our efforts for an optimized experimental design, a careful material screening and accurate detector production handling, and a constant control of the expected results through a meticulous Monte Carlo simulation program. We show that all these actions should allow us to keep the background count rate safely below the target value of 10 Hz (i.e. ∼1 cpd accidental background) in the default fiducial volume, above an energy threshold of 0.7 MeV.

In today's digital information age, the conflict between the public's growing awareness of their own data protection and the data owners' inability to obtain data ownership has become increasingly prominent. The emergence of blockchain provides a new direction for data protection and data tokenization. Nonetheless, existing cryptocurrencies such as Bitcoin using Proof-of-Work are particularly energy intensive. On the other hand, classical protocols such as Byzantine agreement do not work efficiently in an open environment. Therefore, in this paper, we propose a permission-less blockchain with a novel double-DAG (directed acyclic graph) architecture called DLattice, where each account has its own Account-DAG and all accounts make up a greater Node-DAG structure. DLattice parallelizes the growth of each account's Account-DAG, each of which is not influenced by other accounts' irrelevant transactions. DLattice uses a new DPoS-BA-DAG(PANDA) protocol to reach consensus among users only when the forks are observed. Based on proposed DLattice, we introduce a process of data tokenization, including data assembling, data anchoring, and data authorization. We implement DLattice and evaluate its performance on 25 ECS virtual machines, simulating up to 500 nodes. The experimental results show that DLattice reaches a consensus in 10 seconds, achieves desired throughput, and incurs almost no penalty for scaling to more users. INDEX TERMS Blockchain, data tokenization, consensus algorithm, byzantine agreement protocols, directed acyclic graph.