Communication-Efficient Framework for Distributed Image Semantic Wireless Transmission

Multi-node communication, which refers to the interaction among multiple devices, has attracted lots of attention in many Internet-of-Things (IoT) scenarios. However, its huge amounts of data flows and inflexibility for task extension have triggered the urgent requirement of communication-efficient distributed data transmission frameworks. In this paper, inspired by the great superiorities on bandwidth reduction and task adaptation of semantic communications, we propose a federated learning-based semantic communication (FLSC) framework for multi-task distributed image transmission with IoT devices. Federated learning enables the design of independent semantic communication link of each user while further improves the semantic extraction and task performance through global aggregation. Each link in FLSC is composed of a hierarchical vision transformer (HVT)-based extractor and a task-adaptive translator for coarse-to-fine semantic extraction and meaning translation according to specific tasks. In order to extend the FLSC into more realistic conditions, we design a channel state information-based multiple-input multiple-output transmission module to combat channel fading and noise. Simulation results show that the coarse semantic information can deal with a range of image-level tasks. Moreover, especially in low signal-to-noise ratio and channel bandwidth ratio regimes, FLSC evidently outperforms the traditional scheme, e.g. about 10 peak signal-to-noise ratio gain in the 3 dB channel condition.Comment: This paper has been accepted by IEEE Internet of Things Journa

Aspheric optical surface profiling based on laser scanning and auto-collimation

Nowadays the utilization of aspheric lens has become more and more popular, enabling highly increased degree of freedom for optical design and simultaneously improving the performance of optical system. Hence this also entails a stringent requirement for fast and accurate measuring the shape of these aspheric components. In this paper, the instrument is greatly developed to satisfy the growing need to test axially symmetric aspheric surface, which is implemented by converting the pose of reflective mirror in optical path to the coordinate of reflection point on the surface when laser rapidly scans . At each movement position managed by grating-rule sensor, the rotating angle of reflective mirror is defined using position sensitive detector based on the laser auto-collimating and beam center-fitting principle. Testing a convex and a concave surfaces with highly reproducible results, including coefficient of determination better than 0.999 and RMSE less than =10, validates the feasibility of this method. In comparison to the conventional computer-generated hologram tester or interferometer, the present instrument—essentially builds on the pure geometrical optics technology—is a powerful tool to measure the aspheric surface quickly and accurately with simple structure and algorithm

The Association Between Diabetic Retinopathy and the Prevalence of Age-Related Macular Degeneration—The Kailuan Eye Study

This study aimed to investigate the prevalence of age-related macular degeneration (AMD) in patients with diabetes mellitus (DM) and diabetic retinopathy (DR) and analyze whether DR is a risk factor for AMD. This population-based epidemiological study included 14,440 people from the Kailuan Eye Study in 2016, of whom 1,618 were patients with type 2 DM aged over 50 years, and 409 had DM with DR. We analyzed whether there were differences in the prevalence of AMD between DM with DR and DM without DR, and conducted a hierarchical statistical analysis according to different stages of DR. Using variable regression analysis, we explored whether DR constituted a risk factor for AMD. In the DM population, the prevalence of wet AMD in patients with DM with and without DR was 0. 3 and 0.2%, respectively, with no significant difference (P = 0.607). Meanwhile, the prevalence of dry AMD in patients with DM with and without DR was 20.8 and 16.0%, respectively, with a significant difference. In the subgroup analysis of dry AMD, the prevalence of early, middle, and late dry AMD in DM with DR was 14.4, 5.9, and 0.5%, respectively. In DM without DR, the prevalence of early, middle, and late dry AMD was 10.5, 4.8, and 0.7%, respectively (P = 0.031). In the subgroup analysis of DR staging, statistical analysis could not be performed because of the limited number of patients with PDR. In the variable regression analysis of risk factors for dry AMD, after adjusting for age, sex, body mass index, hypertension, and dyslipidemia, DR constituted the risk factor for dry AMD. In conclusion, DM did not constitute a risk factor for AMD, and the prevalence of wet AMD and dry AMD in patients with DM and DR was higher than that in patients with DM without DR (among which dry AMD was statistically significant). Multivariate regression analysis confirmed that DR is an independent risk factor for dry AMD. Reasonable control of DM and slowing down the occurrence and development of DR may effectively reduce the prevalence of AMD in patients with DM

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

Role of liver fibrosis assessment in decision-making and efficacy surveillance for antiviral therapy in patients with chronic hepatitis B

Liver fibrosis/cirrhosis is the outcome of the progression of chronic hepatitis B and is associated with liver events and long-term prognosis. Effective antiviral therapy can delay or even reverse disease progression. Therefore, assessment of liver fibrosis degree before and during treatment is of great importance in initiating antiviral therapy, developing therapeutic regimens, and monitoring antiviral effects and complications. The semi-quantitative histological scoring system is widely acknowledged in the assessment of liver fibrosis degree and is an important basis for the initiation of antiviral therapy for hepatitis B, as well as a method commonly used for efficacy surveillance. Morphological and structural quantitative methods provide objective histological assessment of liver fibrosis and may cover the shortage of conventional semi-quantitative scoring system. Non-invasive methods for the assessment of liver fibrosis may reduce but not completely substitute liver histological examinations; a consensus has not been reached on their cut-off values to make decisions to initiate antiviral therapy, but such non-invasive methods can provide rich information on therapeutic effect and long-term prognosis