The boundary contour method for magneto-electro-elastic media with quadratic boundary elements

AbstractThis paper presents a development of the boundary contour method (BCM) for magneto-electro-elastic media. First, the divergence-free of the integrand of the magneto-electro-elastic boundary element is proved. Second, the boundary contour method formulations are obtained by introducing quadratic shape functions and Green’s functions [Ding, H.J., Jiang, A.M., 2004. A boundary integral formulation and solution for 2D problems in magneto-electro-elastic media. Computers and Structures, 82 (20–21), 1599–1607] for magneto-electro-elastic media and using the rigid body motion solution to regularize the BCM and avoid computation of the corner tensor. The BCM is applied to the problem of magneto-electro-elastic media. Finally, numerical solutions for illustrative examples are compared with exact ones. The numerical results of the BCM coincide very well with the exact solution, and the feasibility and efficiency of the method are verified

Multi-sensor Image Data Fusion based on Pixel-Level Weights of Wavelet and the PCA Transform

Abstract -The goal of image fusion is to create new images that are more suitable for the purposes of human visual perception, object detection and target recognition. For Automatic Target Recognition (ATR), we can use multi-sensor data including visible and infrared images to increase the recognition rate. In this paper, we propose a new multiresolution data fusion scheme based on the principal component analysis (PCA) transform and the pixel-level weights wavelet transform including thermal weights and visual weights. In order to get a more ideal fusion result, a linear local mapping which based on the PCA is used to create a new "origin" image of the image fusion. We use multiresolution decompositions to represent the input images at different scales, present a multiresolution/ multimodal segmentation to partition the image domain at these scales. The crucial idea is to use this segmentation to guide the fusion process. Physical thermal weights and perceptive visual weights are used as segmentation multimodals. Daubechies Wavelet is choosen as the Wavelet Basis. Experimental results confirm that the proposed algorithm is the best image sharpening method and can best maintain the spectral information of the original infrared image. Also, the proposed technique performs better than the other ones in the literature, more robust and effective, from both subjective visual effects and objective statistical analysis results

The management correlation between metabolic index, cardiovascular health, and diabetes combined with cardiovascular disease

BackgroundCardiovascular disease (CVD) has become a major cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). Although there is also evidence that multifactorial interventions to control blood glucose, blood pressure, and lipid profiles can reduce macrovascular complications and mortality in patients with T2DM, the link between these risk factors has not been established.MethodsOn 10 December 2018, 1,920 people in four cities in Anhui Province were included. Latent category analysis (LCA) was used to explore the clustering mode of HRBs (health risk behaviors). The primary exposure was HRBs and exercise and diet interventions, and the primary outcome was CVD and other variables, including zMS, triglyceride-glucose index (TyG), TyG-WC (waist circumference), TyG-BMI, TG/HDL, and cardiovascular health (CVH). A multivariable logistic regression model was used to establish the relationship between HRBs, exercise, diet interventions, and CVD. Moderate analysis and mediation moderation analysis were employed by the PROCESS method to explore the relationship between these variables. Sensitivity analysis explored the robustness of the model.ResultsThe mean age was 57.10 ± 10.0 years old. Overall, CVD affects approximately 19.9% of all persons with T2DM. Macrovascular complications of T2DM include coronary heart disease, myocardial infarction (MI), cardiac insufficiency, and cerebrovascular disease. Elderly age (χ2 = 22.70), no occupation (χ2 = 20.97), medium and high socioeconomic status (SES) (χ2 = 19.92), higher level of TyG-WC (χ2 = 6.60), and higher zMS (χ2 = 7.59) were correlated with high CVD. Many metabolic indices have shown a connection with T2DM combined with CVD, and there was a dose−response relationship between HRB co-occurrence and clustering of HRBs and zMS; there was a dose−response relationship between multifactorial intervention and CVH. In the mediation moderation analysis, there was an association between HRB, gender, TyG, TyG-BMI, and CVD. From an intervention management perspective, exercise and no diet intervention were more significant with CVD; moreover, there was an association between intervention management, gender, zMS, TyG-WC, TyG-BMI, TG/HDL, and CVD. Finally, there was an association between sex, CVH, and CVD. Sensitivity analysis demonstrated that our results were robust.ConclusionsCVD is one of the common complications in patients with type 2 diabetes, and its long-term outcome will have more or less impact on patients. Our findings suggest the potential benefits of scaling up multifactorial and multifaceted interventions to prevent CVD in patients with T2DM

Association of sleep behaviors, insulin resistance surrogates, and the risk of hypertension in Chinese adults with type 2 diabetes mellitus

ObjectiveOur aim was to evaluate the association between midday napping, combined sleep quality, and insulin resistance surrogates and the risk of hypertension in patients with type 2 diabetes mellitus (T2DM).MethodsData were collected using a standardized questionnaire. Binary logistic regression was performed to estimate the odds ratio (OR) and 95% confidence interval (CI) for the risk of hypertension. Systolic and diastolic blood pressure were grouped as categorical variables and unpaired two-sided Student’s t-test and Spearman correlation analysis were performed to estimate the association between different blood pressure levels and insulin resistance surrogates.ResultsThe overall prevalence rate of hypertension was 50%. Age (OR = 1.056, 95% CI:1.044–1.068), poor sleep quality (OR = 1.959, 95% CI:1.393–2.755), hyperlipidemia (OR = 1.821, 95% CI:1.462–2.369), family history of hypertension (OR = 2.811, 95% CI:2.261–3.495), and obesity (OR = 5.515, 95% CI:1.384–21.971) were significantly associated with an increased risk of hypertension. Midday napping for 1–30 min was negatively correlated with the risk of hypertension (OR = 0.534, 95% CI:0.305–0.936, P <0.05).ConclusionPoor sleep quality and obesity are independent risk factors for hypertension. Midday napping (1–30 min) is associated with a decreased risk of hypertension in patients with T2DM

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

Real-Time Simulation of Fluid Scenes by Smoothed Particle Hydrodynamics and Marching Cubes

Simulating fluid scenes in 3DGIS is of great value in both theoretical research and practical applications. To achieve this goal, we present an algorithm for simulation of fluid scenes based on smoothed particle hydrodynamics. A 3D spatial grid partition algorithm is proposed to increase the speed for searching neighboring particles. We also propose a real-time interactive algorithm about particle and surface topography. We use Marching Cubes algorithm to extract the surface of free moving fluids from particles data. Experiments show that the algorithms improve the rate of rendering frame in realtime, reduce the computing time, and extract good real effects of fluid surface

Remote Sensing Image Fusion Based on Average Gradient of Wavelet Transform

Abstract-Image fusion is one of the important techniques to enhance image information of remote sensing. In order to adequately make use of all kinds of remote sensing images information such as SPOT Panchromatic and three-band Landsat multi-spectral images, a novel remote sensing image fusion scheme based on average gradient of wavelet transform is proposed. In the fusion processing, the fused approximate coefficients are obtained with weighted average method. For the bigger average gradient of the each decomposed approximate coefficient, we choose a big power gene. The other approximate coefficient chooses a small one. The fused detailed coefficients are obtained by setting each coefficient equal to the corresponding input image wavelet coefficient that has the greatest average gradient. The information entropy and the image clarity are proposed as the quantitative evaluation criteria to assess this proposed method and some other methods. The visual and statistical analyses of experimental results show that the proposed fusion method is more effective than the other methods mentioned in this paper