The Radon Monitoring System in Daya Bay Reactor Neutrino Experiment

We developed a highly sensitive, reliable and portable automatic system (H$^{3}$) to monitor the radon concentration of the underground experimental halls of the Daya Bay Reactor Neutrino Experiment. H$^{3}$ is able to measure radon concentration with a statistical error less than 10\% in a 1-hour measurement of dehumidified air (R.H. 5\% at 25$^{\circ}$C) with radon concentration as low as 50 Bq/m$^{3}$. This is achieved by using a large radon progeny collection chamber, semiconductor $\alpha$-particle detector with high energy resolution, improved electronics and software. The integrated radon monitoring system is highly customizable to operate in different run modes at scheduled times and can be controlled remotely to sample radon in ambient air or in water from the water pools where the antineutrino detectors are being housed. The radon monitoring system has been running in the three experimental halls of the Daya Bay Reactor Neutrino Experiment since November 2013

Measurement of Cosmic-ray Muons and Muon-induced Neutrons in the Aberdeen Tunnel Underground Laboratory

We have measured the muon flux and production rate of muon-induced neutrons at a depth of 611 m water equivalent. Our apparatus comprises three layers of crossed plastic scintillator hodoscopes for tracking the incident cosmic-ray muons and 760 L of gadolinium-doped liquid scintillator for producing and detecting neutrons. The vertical muon intensity was measured to be $I_{\mu} = (5.7 \pm 0.6) \times 10^{-6}$ cm$^{-2}$s$^{-1}$sr$^{-1}$. The yield of muon-induced neutrons in the liquid scintillator was determined to be $Y_{n} = (1.19 \pm 0.08 (stat) \pm 0.21 (syst)) \times 10^{-4}$ neutrons/($\mu\cdot$g$\cdot$cm$^{-2}$). A fit to the recently measured neutron yields at different depths gave a mean muon energy dependence of $\left\langle E_{\mu} \right\rangle^{0.76 \pm 0.03}$ for liquid-scintillator targets.Comment: 14 pages, 17 figures, 3 table

Further investigation on chaos of real digital filters

This Letter displays, via the numerical simulation of a real digital filter, that a finite-state machine may behave in a near-chaotic way even when its corresponding infinite-state machine does not exhibit chaotic behavior

LArPix: Demonstration of low-power 3D pixelated charge readout for liquid argon time projection chambers

We report the demonstration of a low-power pixelated readout system designed for three-dimensional ionization charge detection and digital readout of liquid argon time projection chambers (LArTPCs). Unambiguous 3D charge readout was achieved using a custom-designed system-on-a-chip ASIC (LArPix) to uniquely instrument each pad in a pixelated array of charge-collection pads. The LArPix ASIC, manufactured in 180 nm bulk CMOS, provides 32 channels of charge-sensitive amplification with self-triggered digitization and multiplexed readout at temperatures from 80 K to 300 K. Using an 832-channel LArPix-based readout system with 3 mm spacing between pads, we demonstrated low-noise ($<$500 e$^-$ RMS equivalent noise charge) and very low-power ($<$100 $\mu$W/channel) ionization signal detection and readout. The readout was used to successfully measure the three-dimensional ionization distributions of cosmic rays passing through a LArTPC, free from the ambiguities of existing projective techniques. The system design relies on standard printed circuit board manufacturing techniques, enabling scalable and low-cost production of large-area readout systems using common commercial facilities. This demonstration overcomes a critical technical obstacle for operation of LArTPCs in high-occupancy environments, such as the near detector site of the Deep Underground Neutrino Experiment (DUNE).Comment: 19 pages, 10 figures, 1 ancillary animation. V3 includes minor revisions based on referee comment

EFFECTS OF REHABILITATION ON BACK MUSCLE CONTRACTION PATTERNS OF LOW BACK PAIN PATIENTS

The aims of this study were to conduct a comparative investigation of muscle function between low back pain (LBP) patients and normal subjects, as well as to explore whether intensive rehabilitation can change back muscle contraction synergy. 20 normal subjects and 20 patients with chronic LBP were asked to perform symmetrical and asymmetrical tasks. LBP patients were tested in the weeks immediately before and after 12-week LBP rehabilitation treatment. Tasks include “carrying” weights up and down with a 45° left rotation. Eight channel surface EMG electrodes were placed on the surface of paraspinal muscles. correlation between right and left corresponding muscles as well as between pre- and post-treatment were calculated. Lifting capacity for LBP patients were also measured before and after treatment. EMG profiles showed that the muscle activity strategies varied between normal subjects and LBP patients. The correlation coefficients for spinal muscles have shown very reproducible intra-subject muscle contraction synergies. Unbalanced EMG patterns found in LBP patients under symmetrical tasks were not affected by rehabilitation treatment

White Paper: Measuring the Neutrino Mass Hierarchy

This white paper is a condensation of a report by a committee appointed jointly by the Nuclear Science and Physics Divisions at Lawrence Berkeley National Laboratory (LBNL). The goal of this study was to identify the most promising technique(s) for resolving the neutrino mass hierarchy. For the most part, we have relied on calculations and simulations presented by the proponents of the various experiments. We have included evaluations of the opportunities and challenges for these experiments based on what is available already in the literature.Comment: White paper prepared for Snowmass-201

An Improved Algorithm for Fast K-Word Proximity Search Based on Multi-Component Key Indexes

A search query consists of several words. In a proximity full-text search, we want to find documents that contain these words near each other. This task requires much time when the query consists of high-frequently occurring words. If we cannot avoid this task by excluding high-frequently occurring words from consideration by declaring them as stop words, then we can optimize our solution by introducing additional indexes for faster execution. In a previous work, we discussed how to decrease the search time with multi-component key indexes. We had shown that additional indexes can be used to improve the average query execution time up to 130 times if queries consisted of high-frequently occurring words. In this paper, we present another search algorithm that overcomes some limitations of our previous algorithm and provides even more performance gain. This is a pre-print of a contribution published in Arai K., Kapoor S., Bhatia R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in Intelligent Systems and Computing, vol 1251, published by Springer, Cham. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-55187-2_3