Many financial crises have occurred in recent decades, such as the International Debt Crisis of 1982, the East Asian Economic Crisis of 1997–2001, the Russian economic crisis of 1992–1997, the Latin American debt Crisis of 1994–2002, the Global Economic Recession of 2007–2009, which had a strong impact on international relations. The aim of this article is to create an econometric model of the indicator for identifying crisis situations arising in stock markets. The approach under consideration includes data for preprocessing and assessing the stability of the trend of time series using higher-order moments. The results obtained are compared with specific practical situations. To test the proposed indicator, real data of the stock indices of the USA, Germany and Hong Kong in the period World Financial Crisis are used. The scientific novelty of the results of the article consists in the analysis of the initial and given initial moments of high order, as well as the central and reduced central moments of high order. The econometric model of the indicator for identifying crisis situations arising considered in the work, based on high-order moments plays a pivotal role in crisis detection in stock markets, influencing financial innovations in managing the national economy. The findings contribute to the resilience and adaptability of the financial system, ultimately shaping the trajectory of the national economy. By facilitating timely crisis detection, the model supports efforts to maintain economic stability, thereby fostering sustainable growth and resilience in the face of financial disruptions. The model's insights can shape the national innovation ecosystem by guiding the development and adoption of monetary and financial innovations that are aligned with the economy's specific needs and challenges.

Intelligent toy design and development talents need to master certain electronic intelligent control, arts and crafts design, product modeling design and other skills. There is a shortage of intelligent toy designers in our country, and toy enterprises are in urgent need of professional and technical personnel engaged in toy product modeling and functional design. Therefore, it is urgent to cultivate intelligent toy design and development talents. This paper explores the necessity of cross-professional training of intelligent toy design and development talents, relies on teachers' scientific research and enterprise projects, etc., takes graduation projects as a breakthrough, pushes back the talent training curriculum system, and proposes an cross-professional collaborative training model. Through cross-professional combination training intelligent toy design talents, so that they have the design thinking of toy designers and a certain degree of electronic engineer design thinking, can better adapt to the rapid development of modern toy design industry, enterprises changing new requirements.

Banana (Musa spp.) productivity is limited by sodic soils, which impairs root growth and nutrient uptake. Analyzing root traits under stress conditions can aid in identifying tolerant genotypes. This study investigates the root morphological traits of banana cultivars under sodic soil stress conditions using Rhizovision software. The pot culture experiment was laid out in a Completely Randomized Design (CRD) under open field conditions, with treatments comprising the following varieties: Poovan (AAB), Udhayam (ABB), Karpooravalli (ABB), CO 3 (ABB), Kaveri Saba (ABB), Kaveri Kalki (ABB), Kaveri Haritha (ABB), Monthan (ABB), Nendran (AAB), and Rasthali (AAB), each replicated thrice. Parameters such as the number of roots, root tips, diameter, surface area, perimeter, and volume were assessed to evaluate the performance of different cultivars. The findings reveal that Karpooravali and Udhayam cultivars exhibited superior performance in terms of root morphology compared to other cultivars under sodic soil stress. These cultivars displayed increased root proliferation, elongation, and surface area, indicating their resilience to sodic soil stress. The utilization of Rhizovision software facilitated precise measurement and analysis of root traits, providing valuable insights into the adaptation mechanisms of banana cultivars to adverse soil conditions.

One of the biggest environmental problems that has affected the planet is global warming, due to high concentrations of carbon (CO₂), which has led to crops such as coffee being affected by climate change caused by greenhouse gases (GHG), especially by the increase in the incidence of pests and diseases. However, carbon sequestration contributes to the mitigation of GHG emissions. The objective of this work was to evaluate the carbon stored in above and below ground biomass in four six-year-old castle coffee production systems. In a trial established under a Randomized Complete Block Design (RCBD) with the treatments Coffee at free exposure (T1), Coffee-Lemon (T2), Coffee-Guamo (T3) and Coffee-Carbonero (T4), at three altitudes: below 1,550 masl, between 1,550 and 2,000 masl and above 2,000 masl. Data were collected corresponding to the stem diameters of coffee seedlings and shade trees with which allometric equations were applied to obtain the carbon variables in the aerial biomass and root and the carbon variables in leaf litter and soil obtained from their dry matter. Highly significant differences were obtained in the four treatments evaluated, with T4 being the one that obtained the highest carbon concentration both in soil biomass with 100.14 t ha^-1 and in aerial biomass with 190.42 t ha^-1.