Comparison of the Effect of Glycemic Control in Type 2 Diabetes Outpatients Treated With Premixed and Basal Insulin Monotherapy in China

Background: Basal and premixed insulin have been widely used for insulin therapy of type 2 diabetes mellitus (T2DM) in China. The aim of this study is to compare the sustained efficacy of basal and premixed insulin therapies in T2DM outpatients with insulin monotherapy.Materials and Methods: The survey was conducted in 602 hospitals across China from April to June in 2013. The participants included outpatients who were receiving basal or premixed insulin monotherapy for more than 3 months, and the outcome was attaining a glycated hemoglobin A1C (HbA1c) of <7.0% as a measure of sustained glycemic control.Results: A total of 49,119 T2DM outpatients on basal (n = 11,967) or premixed insulin (n = 37,152) monotherapy were included in the final analyses. Using multivariable model analysis, patients using premixed insulin exhibited a better glycemic control, with more outpatients achieving the target HbA1c level than those using basal insulin (model 1, OR 0.695, 95%CI 0.664–0.728; model 2, OR 0.708, 95%CI 0.676–0.742; model 3, OR 0.717, 95%CI 0.684–0.752; model 4, OR 0.750, 95%CI 0.715–0.787). Using subgroup analysis stratified by age, sex, duration of diabetes, duration of insulin treatment, and complications, still more outpatients in every subgroup treated with premixed insulin achieved the target HbA1c (HbA1c < 7%) than those receiving basal insulin.Conclusions: Premixed insulin monotherapy had a better glycemic control (HbA1c < 7.0%) than basal insulin monotherapy for Chinese T2DM outpatients in daily

Research on modified silicone compound photocatalyst by doping N

In order to improve the visible light response and reaction efficiency of nitrogen-doped TiO2 set urea as nitrogen source, and silica gel as the load reagent adopt sol-gel method to prepare powder of nitrogen-doped TiO2 supported on SiO2 , use equal volume impregnation method to load MnO2 on catalyst, and then obtain the composite photocatalyst after drying, and roasting .The prepared composite catalysts were characterized by XPS, TEM, SEM, XRD and other methods. Moreover, the photo-catalytic activity of the composite catalysts under visible-light region was tested, and the influences of nitrogen content and calcinations temperature on the photo-catalytic activity were investigated. The results show that:(1) the range of light response of modified composite catalyst was expanded from ultraviolet region to visible-light region, which results in high visible-light catalytic activity in the degradation of methyl orange.(2) Through the mechanism of photo-catalytic reaction and the treatment effect analysis, MnO2 as catalytic resulting O2 can be served as a good electronic capture agent and improve the reaction efficiency.(3)With the reduction of nitrogen content,and the increase of calcination temperature, the visible-light catalytic activity was weakened.(4) The activity of catalyst was reused six times, without significant reduction and had excellent efficiency and stability

Research on position inverse solution of electric-driven Stewart platform based on Simulink

The structural characteristics and modes of the Stewart platform driven by electric cylinders are briefly introduced. Based on Simulink, the modelling method of the platform is analysed. To obtain the coordinate transformation of Stewart platform, the rotation matrix and homogeneous transformation are resolved, and the mathematical model of the electric-driven Stewart platform is established related to the structural characteristics. The simulation model of input and output signals is constructed by using graphical user interface (GUI) module provided by Simulink. The motion simulation curves of six electric actuators under different position and posture are obtained, which gives benefit to understand and control the different motion states of the electric-driven Stewart platform

The Key Application Technology of Desulfurized Gypsum in Dry-Mixed Mortar

In this paper, in view of the problem of low early and late strength of dry-mixed mortar prepared by cement-fly ash-slag powder composite cementing system, the ratio of mixing fly ash and slag powder to replace cement is 70%. To study the effect of desulfurization gypsum (FGD) on improving the activity of the system. The results show that adding desulfurized gypsum, which accounts for 6% to 8% of the total mass of the cementitious material, has no adverse effect on the workability and can significantly improve the compressive resistance of the slurry. Strength and tensile bonding strength, shrinkage rate is reduced by more than 10%, and the ability to resist carbonization is improved to make the mortar volume more stable

SGDAN—A Spatio-Temporal Graph Dual-Attention Neural Network for Quantified Flight Delay Prediction

There has been a lot of research on flight delays. But it is more useful and difficult to estimate the departure delay time especially three hours before the scheduled time of departure, from which passengers can reasonably plan their travel time and the airline and airport staff can schedule flights more reasonably. In this paper, we develop a Spatio-temporal Graph Dual-Attention Neural Network (SGDAN) to learn the departure delay time for each flight with real-time conditions at three hours before the scheduled time of departure. Specifically, it first models the air traffic network as graph sequences, what is, using a heterogeneous graph to model a flight and its adjacent flights with the same departure or arrival airport in a special time interval, and using a sequence to model the flight and its previous flights that share the same aircraft. The main contributions of this paper are using heterogeneous graph-level attention to learn the influence between the flight and its adjacent flight together with sequence-level attention to learn the influence between the flight and its previous flight in the flight sequence. With aggregating features from the learned influence from both graph-level and sequence-level attention, SGDAN can generate node embedding to estimate the departure delay time. Experiments on a real-world large-scale data set show that SGDAN produces better results than state-of-the-art models in the accurate flight delay time estimation task