Compared with insulin glargine, insulin degludec narrows the day-to-day variability in the glucose-lowering effect rather than lowering blood glucose levels

Background: Changes in the day-to-day variability in the glucose-lowering effect of insulin [fluctuations of blood glucose levels (BG) seen during the same time period] that occur when insulin glargine (glargine) is replaced with insulin degludec (degludec) have not been sufficiently evaluated. Subjects: Five diabetics with unstable BG undergoing basal-bolus treatment using insulin glargine as basal insulin. Methods: Basal insulin was changed from glargine to same-dose degludec. The subjects’ HbA1c, glycoalbumin, and 1.5-anhydro-D-glucitol were measured before and after the switchover. Fasting blood glucose concentration (FBG) and predinner blood glucose concentration (PDBG) were measured continuously for 28 days immediately before the switchover, and 28 days immediately thereafter, to compare and evaluate 1) the changes in their mean values and standard deviations (SDs) before and after the switchover, and 2) the frequency of appearance of BG of over 180 mg/dL (BG ≥ 180) and under 70 mg/dL (BG Results: The levels of HbA1c, glycoalbumin, FBG’s mean value, SDs, BG ≥ 180 and BG Conclusion: The possibility was shown that degludec, to a greater extent than glargine, suppressed daily fluctuations of FBG and PDBG, suppressed the occurrence frequency of hyperglycemia and hypoglycemia, and exerted more steady hypoglycemic actions.

Assessing the Performance of a Dynamical Downscaling Simulation Driven by a Bias-Corrected CMIP6 Dataset for Asian Climate

In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three simulations were conducted with a 25-km grid spacing for the period 1980–2014.The first simulation(WRF_ERA5)was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)dataset and served as the validation dataset.The original GCM dataset(MPI-ESM1-2-HR model)was used to drive the second simulation(WRF_GCM),while the third simulation(WRF_GCMbc)was driven by the bias-corrected GCM dataset.The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models.Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors(RMSEs)of the climatological mean of downscaled variables,including temperature,precipitation,snow,wind,relative humidity,and planetary boundary layer height by 50%–90%compared to the WRF_GCM.Similarly,the RMSEs of interannual-tointerdecadal variances of downscaled variables were reduced by 30%–60%.Furthermore,the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities.The leading empirical orthogonal function(EOF)shows a monopole precipitation mode in the WRF_GCM.In contrast,the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China.This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.

A topology-based bounded rationality day-to-day traffic assignment model

This paper analyzes the day-to-day adjustment process of users’behaviors in a transport network which is affected by relevant alterations such as disruptions due to critical events which cause the impossibility to use one or more links.For representing the progressive adjustment of the flows on the network to reach a new equilibrium,a dayto-day discrete-time model is proposed,based on the idea that people are bounded rational in their choices,i.e.they often do not behave according to the optimal solution but they accept solutions they consider satisfying.Users,in their choice process,are influenced by the topological similarity between the route they are currently using and others.This means that they tend to prefer the solutions that are more similar to the one they are already using.In parallel,users exhibit a myopic behavior,i.e.,they tend to overestimate the goodness of a route if,when using it,they suddenly experience a significant reduction in travel time compared to what they are used to.In the paper it is shown that such route choice behaviour implies that the steady state of the system corresponds to a Bounded Rational User Equilibrium,i.e.,a state that does not diverge from the user equilibrium more than a certain value which increases when the relative importance given to the topological similarity grows.The model also assumes that these biases vanish,at least with respect to those routes that are most frequently used by users,after a sufficient amount of time.Under certain conditions,it is then shown that the steady state can eventually collapse into a User Equilibrium.The effectiveness of the proposed model is assessed via simulation results in which two test networks are analyzed in detail to show the evolution of the users’behaviour in a transport network after a disruption.

A Trend towards a Stable Warm and Windless State of the Surface Weather Conditions in Northern and Northeastern China during 1961–2014

This study investigates the trends in the mean state and the day-to-day variability （DDV） of the surface weather conditions over northern and northeastern China （NNEC） during 1961-2014 using CN05.1 observational data. In this study, we show that the surface temperature （wind speed） has increased （decreased） over NNEC and that the DDV of the surface temperatures and wind speeds has decreased, indicating a trend towards a stable warm and windless state of the surface weather conditions over NNEC. This finding implies a trend towards more persistent hot and windless episodes, which threaten human health and aggravate environmental problems. The trends are also examined in reanalysis data. Both the ERA-40 and the NCEP data show an increasing （decreasing） trend in the mean state of the surface temperatures （wind speeds）. However, the reanalysis data show a consistent decreasing trend in the DDV of the surface weather conditions only in the spring. The underlying reason for the decreased DDV of the surface weather conditions is further analyzed, focusing on the spring season. Essentially, the decreased DDV of the surface weather conditions can be attributed to a decrease in synoptic-scale wave activity, which is caused by a decrease in the baroclinic instability. There is a contrasting change in the baroclinic instability over East Asia, showing a decreasing （increasing） trend north （south） of 40°N. This contrasting change in the baroclinic instability is primarily caused by a tropospheric cooling zone over East Asia at approximately 40°N, which influences the meridional temperature gradient over East Asia.