Analysis of the Association between Intestinal Microflora and Long-lived Elderly People

The intestinal microbiota is the cornerstone of the human intestinal microecosystem and plays an unnegligible role in the growth and health maintenance of the human body. In recent years, many studies have been committed to exploring the potential connection of gut flora and the elderly population. The changes of gut flora are affected by various factors such as age increase, disease, medication, living habits, nutritional structure, and the intestinal flora is expected to be applied to the comprehensive evaluation of elderly health and longevity in the future. Based on this, the research progress of the general elderly and its related influencing factors

Bismuth-induced phase control of GaAs nanowires grown by molecular beam epitaxy

In this work, the crystal structure of GaAs nanowires grown by molecular beam epitaxy has been tailored only by bismuth without changing the growth temperature and V/III flux ratio. The introduction of bismuth can lead to the formation of zinc-blende GaAs nanowires, while the removal of bismuth changes the structure into a 4H polytypism before it turns back to the wurtzite phase eventually. The theoretical calculation shows that it is the steadiest for bismuth to adsorb on the GaAs(111) B surface compared to the liquid gold catalyst surface and the interface between the gold catalyst droplet and the nanowire, and these adsorbed bismuth could decrease the diffusion length of adsorbed Ga and hence the supersaturation of Ga in the gold catalyst droplet. (C) 2014 AIP Publishing LLC

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

Using Affine Correspondence To Estimate 3-D Facial Pose

We describe a method for tracking a person's face through an image sequence and estimating the 3-D facial pose within each frame. It is based on an affine approximation to the motion of projected facial features such as eyes, mouth and nose. Tracking stability is maintained by enforcing the affine relationship amongst the motion of the features using linear regression and a Kalman filter. Facial pose is estimated using an ellipse-circle correspondence technique based on the affine transformation between the features in the current view and those in a fronto-parallel view. The method has the advantage of being simple to implement and not relying on assumed facial characteristics

Dense depth estimation from image sequences

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Face Tracking And Pose Estimation Using Affine Motion Parameters

We describe a method for tracking a person's face through an image sequence and estimating the 3-D facial pose within each frame. The technique is based on an affine approximation to the motion of projected facial features such as eyes, mouth and nose. Tracking stability is maintained by enforcing the affine relationship amongst the motion of the features using linear regression and application of a Kalman filter to the estimated affine parameters. Facial pose is estimated using an ellipse-circle correspondence technique based on the affine transformation between the features in the current view and those in a fronto-parallel view. The method has the advantage of being simple to implement and not relying on assumed facial characteristics. Experiments on both synthetic and real sequences illustrate the effectiveness of the approach