This study aims to predict whether university students will make efficient use of Artificial Intelligence (AI) in the coming years, using a statistical analysis that predicts the outcome of a binary dependent variable (in this case, the efficient use of AI). Several independent variables, such as digital skills management or the use of Chat GPT, are considered.The results obtained allow us to know that inefficient use is linked to the lack of digital skills or age, among other factors, whereas Social Sciences students have the least probability of using Chat GPT efficiently, and the youngest students are the ones who make the worst use of AI.

Urban trees are one of the valuable storage in metropolitan areas. Nowadays, a particular attention is paid to the trees and spends million dollars per year to their maintenance. Trees are often subjected to abiotic factors, such as fungi, bacteria, and insects, which lead to decline mechanical strength and wood properties. The objective of this study was to determine the potential degradation of Elm tree wood by Phellinus pomaceus fungi, and Biscogniauxia mediteranae endophyte. Biological decay tests were done according to EN 113 standard and impact bending test in accordance with ASTM-D256-04 standard. The results indicated that with longer incubation time, weight loss increased for both sapwood and heartwood. Fungal deterioration leads to changes in the impact bending. In order to manage street trees, knowing tree characteristics is very important and should be regularly monitored and evaluated in order to identify defects in the trees.

Due to the lack of clear regulation of management accounting at the state level in Russia, the authors conducted a study based on an analysis of information sources, an expert survey on their reliability, and a case method, which resulted in a reporting form compiled for the production process of an agro-industrial enterprise (grain products) as part of inter-organizational company cooperation. The developed management reporting system (composed of eight consecutive stages: standard reports, specialized reports, itemized query reports, notification reports, statistical reports, prognostic reports, modeling results reports, and process optimization reports), on one hand, allows solving a set of tasks to increase the competitiveness of Russian agro-industrial enterprises within the framework of inter-organizational management accounting. On the other hand, the introduction of ESG principles into the management reporting system (calculation of the environmental (E) index, which assesses the company’s impact on the natural ecosystem and covers emissions and efficient use of natural resources in the agricultural production process) increases the level of control and minimizes the risks of an unfair approach of individual partners to environmental issues.

The direct expansion heat pump with solar energy is an energy conversion system used for water heating applications, air heating for air conditioning buildings, water desalination, solar drying, among others. This paper reviews the main designs and analysis of experiments in order to identify the fundamental objectives of any experiment which may be: to determine the factors that have a significant influence, to obtain a mathematical model and/or to optimize performance. To achieve this task, the basic and advanced configuration of this system is described in detail in order to characterize its thermal performance by means of energy analysis and/or exergy-based analysis. This review identifies possible lines of research in the area of design and analysis of experiments to develop this water heating technology for industrial applications.

In the process of X-ray transmission imaging, the mutual occlusion between structures will lead to the image information overlap, and the computed tomography (CT) method is often required to obtain the structure information at different depths, but with low efficiency. To address these problems, an X-ray focused on imaging algorithm based on multi-line scanning is proposed, which only requires the scene target to pass through the detection area along a straight line to extract multi-view information, and uses the optical field reconstruction theory to achieve the de-obscured reconstruction of the structure at a specified depth with high real-time. The results of multi-line scan and X-ray reconstruction of the target show that the proposed method can reconstruct the information of any specified depth layer, and it can perform fast imaging detection of the mutually occluded target structures and improve the recognition of the occluded targets, which has a good application prospect.

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.