Eight species of the genus Diodontus Curtis (Crabronidae: Pemphredoninae: Pemphredonini) from Palearctic and Oriental Regions of China are reported and described, of which five species recorded for the first time from China: D. handlirschi Kohl, D. insidiosus Spooner, D. kuroo Tsuneki, D. spinicerus Kazenas and D. tiemudzhin Tsuneki. A key to the species of Diodontus from China is provided too.
In the article in order to find ways to increase the competitiveness of human capital, effective directions of its development, the use of tools of economic and mathematical modeling is proposed. To build economic and mathematical models, the official data of the State Statistics Service of Ukraine were processed and with the help of correlation and regression analysis the factors that have the greatest impact on the development of human capital were selected. For certain factors influencing human capital, trend lines are constructed using different types of approximating dependence. Econometric modeling of the influence of factors on the development of human capital is carried out and a number of economic and mathematical models of human capital development are developed, in particular a model of human capital development, a model of national labor market development, a model of social labor productivity growth, a model of state influence on human capital development, a model of influence of factors of human capital development on the growth of gross domestic product. The forecast values of the parameters of human capital development are calculated on the basis of the constructed models.
The objective of this study is to differentiate normal and abnormal neonatal cardiac dynamics through a diagnostic methodology based on dynamic systems, conducting a blind study. 140 Holter studies were taken within the limits of clinical normality and with different cardiac pathologies of newborns. Conventional evaluations were blinded, and maximum and minimum heart rates were taken every hour as well as the number of heartbeats for 21 hours, to generate neonatal heart attractors. The space occupied by each attractor was calculated and its fractal dimension was found using the Box-Counting method, determining its physical-mathematical diagnosis. The space occupied by each neonatal cardiac attractor differentiates normal states of acute pathologies, achieving a sensitivity and specificity of 100%, as well as a kappa coefficient of 1. The diagnostic capacity of the methodology and its clinical applicability was confirmed in the selected Holter studies for research.