СТАТИСТИЧЕСКАЯ ОЦЕНКА ВЛИЯНИЯ РЫНОЧНЫХ ФАКТОРОВ НА ЦЕНЫ ЗЕРНОВЫХ И ЗЕРНОБОБОВЫХ КУЛЬТУР В СИБИРСКОМ ФЕДЕРАЛЬНОМ ОКРУГЕ

The article is devoted to the research of the storage infrastructure and transport and logistics support of the grain market and its processed products in the Siberian Federal District. The study made it possible to determine the state and importance of the storage infrastructure and transport and logistics support in the development of the grain market of the regions of the district. The article provides information about the grain storage infrastructure in the regions of the Siberian Federal District, the gross harvest of grain and leguminous crops in 2021 and the availability of elevators. The main problems in the field of grain storage have been identified. The characteristics of the main hopper cars transporting Siberian grain from the district by rail are presented. The volumes of export and domestic rail transportation from the Siberian Federal District are determined in dynamics. The discrepancy between the state of the storage infrastructure and transport and logistics support in the Siberian Federal District with the growing needs of the grain market and its processed products has been determined. The main directions in which the storage infrastructure and transport and logistics support of the grain market in the district should be developed are presented. The conclusion is made about the need for state support of the storage infrastructure and transport and logistics support of the grain market in the Siberian Federal District.

During the first few months of 1890, thousands of destitute, starving Bija-speaking semi-pastoralists from Eastern Sudan made their way to Sawākin in search of food. Though the region was plagued by both drought and locust swarms during the 1889-1890 cultivaaon year, ecological hazards are insufficient to explain the famine that precipitated this refugee migration. In the second half of the nineteenth century, Eastern Sudanese semi-pastoraluts produced less than half of the grain that they consumed. These communities depended on trading pastoral products for grain imported from India via Red Sea ports. The 1889-1890 famine was not caused by a reduction in grain imports; during this time Eastern Sudanese grain markets were kept well stocked and the price of durra (Sorghum bicolor) remained stable. Rather, at the end of 1889, semi-pastoral communities suddenly lacked the capital to purchase and the goods to trade for diet sustenance, suggesting that a rinderpest epizootic depleted their cattle stocks. Famine continued to plague Eastern Sudan during the 1890-1891 cultivation year. Unlike the famine during the previous year, this famine was, in fact, caused by a grain shortage. By July 1890, the Mahdht garrison at Kassala was unable to provide adequate provisions for both its soldiers and camp followers. Consequently, thousands of malnourished camp followers migrated from the Gash Delta, north of Kassala, to the Tawkar Delta, on the Red Sea coast, thereby increasing the demand for grain in the Red Sea hills. At the same time, the British military leadership stationed at Sawākin decided to starve the population of the Red Sea hills into submission. British officers prohibited all commerce between Sawākin and the interior and ceased all forms of food aid—which resulted in a rapid rise in the price of grain in Eastern Sudan and to widespread starvation, banditry, and death in the Red Sea hills and the Tawkar Delta.

Power quality characteristics and long term trends can be acquired by wide-area permanent measurements of the power quality in electric power supply networks. For economic reasons, redundant measuring results should be avoided. This paper introduces a procedure based on correlation and regression analysis of fictitious simulated measurement time series. Similar behavior of nodes will be detected, which allows to reduce the number of necessary measuring devices respectively determine their optimal installation site. At the present stage, this procedure is elaborated for the wide-area measurement of harmonic voltages. The application of this procedure on three different distribution networks is also presented in this paper.

Wildfires have been increasing in length and frequency since the mid-1980s, which emit pollutant matter that can adversely impact human health, specifically exacerbating negative respiratory impacts (Lipner et al., 2019). Although many studies examine the respiratory impacts of worsened wildfire conditions, a limited number take place outside of the western United States, occur over prolonged periods, and look at how air quality is changing due to warming climates. The objective of this study is to investigate how air quality health index (AQHI) values have changed over a period of two decades (January 1, 2001 to December 31, 2021) in the Great Plains Air Zone (GPAZ) in southern Saskatchewan and the potential respiratory implications of AQHI changes. The study uses a mixed methods approach: time series analysis, correlation analysis, and regression analysis to analyze AQHI and a literature review to study respiratory implications of AQHI increases. We found a significant increase in AQHI over time of 19.3% (p < 0.0001, n = 7308) and three main outcomes for respiratory data: (1) individuals with respiratory conditions have increased susceptibility to worsened air conditions, (2) elevated AQHI values cause increases in healthcare admittances for respiratory conditions such as asthma and COPD, and (3) women and individuals in the age ranges of 15-65 are particularly susceptible to respiratory outcomes from wildfire smoke. The study provides areas for future research, including the implementation of apps to track respiratory outcomes, the impact of other risk factors on respiratory health, and the effects of AQHI on Indigenous populations.

The article considers the main issues regarding the essence of investments and the investment market, taking into account geopolitical and economic instability, the importance of attracting investments for the reconstruction of the country, changes in legislation and international support, the search for new investment formats and the formation of the state's investment policy. The need to study the investment market is determined by geopolitical and economic instability, the importance of attracting investments for the reconstruction of the country, changes in legislation and international support, the search for new investment formats and the formation of the state's investment policy. The purpose of the article is to study the state and prospects for the development of the investment market of Ukraine, taking into account the current state of the economy and internal and external risks. Investment market research requires a comprehensive approach using both general scientific (analysis and synthesis, induction and deduction, comparison, abstraction and modeling) and specialized methods (time series analysis, correlation and regression analysis, SWOT analysis and PEST analysis). Also, special methodological techniques are used in the research process, such as expert survey, scenario forecasting, SWOT matrices and comparative analysis of investment attractiveness of regions/industries. These methods allow for a deeper understanding of the structure, trends and prospects for the development of the investment market. The study of the investment market allowed us to identify growth points for directing resources to the most promising sectors. It was found that despite the challenges associated with the war and economic difficulties, Ukraine has significant potential for attracting investment. Support from international partners, post-war reconstruction, and the development of strategic sectors can make the country attractive to foreign and domestic capital. Thus, research into the Ukrainian investment market has not only scientific but also applied value for government agencies, businesses, international partners, and development institutions.

Multifractal spectrum analysis of nonlinear dynamical mechanisms in China’s agricultural futures markets

Accurate grid frequency prediction is essential for maintaining the stability and reliability of power systems. However, the complex dynamic characteristics of grid frequency and the nonlinear correlations among massive time series data make it challenging for traditional time series prediction methods to balance efficiency and accuracy. In this paper, we propose a Dynamic Significance–Correlation Weighting (D-SCW) method, which generates dynamic weight coefficients that evolve over time. This is achieved by constructing a joint screening mechanism of feature time series correlation analysis and statistical significance test, combined with the LightGBM gradient-boosting decision tree (GBDT) framework; accordingly, high-precision prediction of grid frequency time series data is realized. To verify the effectiveness of the D-SCW method, this study conducts comparative experiments on two actual grid operation datasets (including typical scenarios with wind/photovoltaic (PV) installations, accounting for 5–35% of the grid); additionally, the Spearman’s rank correlation coefficient method, mutual information (MI), Lasso regression, and the feature screening method of recursive feature elimination (RFE) are selected as the baseline control; root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) are adopted as assessment indicators. The results show that the D-SCW-LightGBM framework reduces the root mean squared error (RMSE) by 5.2% to 10.4% and shortens the dynamic response delay by 52% compared with the benchmark method in high renewable penetration scenarios, confirming its effectiveness in both prediction accuracy and computational efficiency.

Modelli di coordinamento verticale compatibili con lo sviluppo di filiere bio-energetiche#