Особенности инвестирования в человеческий капитал

Article about the features of investment in human capital. Explore different areas of investment in human capital, and also addresses the problems associated with investing in human capital and ways to solve them. The author proves the thesis futile investment in human capital and labor without the efforts of the media. This article attempts to prove a similar investment in human and physical capital

Experience at Russian State Agrarian University – Moscow Timiryazev Agricultural Academy on introduction and integration of precision agriculture technology

Traditional and precision agriculture technologies are compared on the basis of the field experiment. Problems of soil and crop survey and mapping are discussed

Theoretical and practical aspects of basic soil treatment in the conditions of modern soil management systems in Russia

The questions of inserting and implementing the different methods of basic soil treatment in the different crop plantings in the conditions of steppe zone in Nizhnee Povolzhye and Central Part of Non-chernozem Belt of the Russian Federation are analyzed. Systemize and complex research of the above questions are caused by multivalued opinions of agrarian scientists that are involved in the practical aspects of agrarian production towards them. On the results of long term researches is defined that the most effective and practice in cereal crop rotations are the basic soil management systems combining the different methods of tillage, mini-till and no-till soil treatment along with usage of modern machines and aggregates. In the conditions of field experiment at Centre of Precision Farming of Russian State Agrarian University - Moscow Timiryazev Agricultural Academy, along with the others, the tasks on economic efficiency and ecological safety that are the basis of precision farming concept are being solved

Change of Ecological and Biological Properties of Cespitose and Podsolic Soil at Binomial Deposits Exposed to Local Wild Fire

The article deals with the ground wild fire impact on physical and chemical and ecological and biological condition of cespitose and podsolic soils on binomial deposits of the Meshcherska province of Gus-Khrustalny district, the Vladimir region under different forest cultures type. In the course of the study, a clear differentiation of changes in the microbiological pool of sod-podzolic soil on bicompartmental deposits under different types of forests was established. The quantitative composition of ammonia factors after exposure to pyrogenic exposure decreased on the sod-podzolic soil of coniferous forests, while the number of photographers, mushrooms, and oligotrophs sharply decreases in the area of pyrogenic exposure in the mixed forest. Within the territory exposed to fire, there is a decrease in the content of organic matter, as well as the content of other biophilic elements. The physical properties of sod-podzolic soil on bicompartmental deposits are also subject to change, in the direction of significant deterioration

Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults

Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p< 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling