This study conducted a systematic review of the existing literature on rhythmic gymnastics. Through searching databases such as PubMed, Web of Science, and Scopus, 37 out of 2319 articles were selected, covering training and physical fitness, nutrition and metabolism, as well as sports injuries and rehabilitation. The findings revealed that: (1) Core physical training significantly enhanced athletes’ performance; (2) Inadequate nutritional intake was prevalent; (3) The incidence of sports injuries was high, particularly those resulting from overtraining. The conclusion emphasizes the need to enhance strength training, optimize nutritional management, and further investigate injury prevention and rehabilitation measures to enhance athletes’ performance and health status.

A decent income is an important part of overcoming economic disparities in agricultural development, especially in developing countries where most of the population are small farmers. As a developing country, Indonesia has also established a decent standard of living by setting a minimum wage as a reference for a decent income at the national and regional levels. However, this benchmark is not relevant to be applied uniformly at all levels of workers. This research determines the national coffee development area as the study center. We developed the Anker living wage methodology as a simple concept for determining living income for certain worker communities, especially for small farmers in rural areas who dominate the type of work in Indonesia. a socio-spatial approach is used to visualize the distribution of the dynamics of a decent life in various conditions of farming households. We found that 96.6% of coffee farming households in the national coffee development area had an inadequate living income, and only 3.4% were at an adequate level. We conclude that the current state of agricultural land management does not guarantee a decent income, even though efforts have been made to maximize agricultural crop productivity. The spatial description also shows that this condition is evenly distributed throughout residential areas. It is hoped that this approach can become an essential reference in implementing agricultural development programs that focus on welfare and equitable development as benchmarks for sustainable development goals in the future.

To address the escalating online romance scams within telecom fraud, we developed an Adaptive Random Forest Light Gradient Boosting (ARFLGB)-XGBoost early warning system. Our method involves compiling detailed Online Romance Scams (ORS) incident data into a 24-variable dataset, categorized to analyze feature importance with Random Forest and LightGBM models. An innovative adaptive algorithm, the Adaptive Random Forest Light Gradient Boosting, optimizes these features for integration with XGBoost, enhancing early Online romance scams threat detection. Our model showed significant performance improvements over traditional models, with accuracy gains of 3.9%, a 12.5% increase in precision, recall improvement by 5%, an F1 score increase by 5.6%, and a 5.2% increase in Area Under the Curve (AUC). This research highlights the essential role of advanced fraud detection in preserving communication network integrity, contributing to a stable economy and public safety, with implications for policymakers and industry in advancing secure communication infrastructure.

Within the last four years, Lithuania has faced different foreign policy challenges due to geopolitical situations such as the Ukraine-Russia war, the migration crisis on the border with Belarus, and the conflict with China. After opening a Taiwanese representative office in Vilnius, China downgraded diplomatic relations with Lithuania. The purpose of the article is to assess the impact of the changes on international economic relations between Lithuania and China. The paper employs descriptive statistics, correlation-regression, sensitivity analysis, and agglomerative hierarchical cluster analysis. The research is based on the impact of international economic relations on international trade by analyzing separately imports and exports. Our research fills a gap in international relations and globalization theory by focusing on international collaboration between small and large countries, while the large country implements economic sanctions. In the context of Lithuania, exports to China and imports from China comprise a small percentage in the structure of international trade. Lithuania’s GDP level reacts sensitively to changes in export and import data only if they change drastically (over 50%).

New technologies always have an impact on traditional theories. Finance theories are no exception to that. In this paper, we have concentrated on the traditional investment theories in finance. The study examined five investment theories, their assumptions, and their limitation from different works of literature. The study considered Artificial Intelligence (AI) and Machine Learning (ML) as representative of financial technology (fintech) and tried to find out from the literature how these new technologies help to reduce the limitations of traditional theories. We have found that fintech does not have an equal impact on every conventional finance theory. Fintech outperforms all five traditional theories but on a different scale.

This research seeks to identify the value of a few common factors determining the speed of economic growth in Baltic states and analyzes their impact in detail on Latvia’s lagging. Latvia’s economic starting point after regaining independence because of the collapse of the Soviet Union was at least comparable to its neighbors. Still, after the implementation of liberal reforms towards a free market’ economy and 20 years of operation as an EU full member, Latvia is lagging in growth, prosperity, and innovation. Within the analysis, this scientific paper pays special attention to the three less discussed factors, namely, the impact of post-Soviet mind-set effects as a part of local innovation culture, lasting since regaining independence in 1991; the importance of the availability of talent pull, its density, diversity, and accessibility; and readiness and capability to capture external knowledge and technology adoption. The overall approach is the systemic assessment of the national innovation system and/or innovation ecosystem, trying to understand the differences between these two models. Research is performed by analysis of the performance of the local innovation ecosystem in connection with export- and Foreign Direct Investment (FDI) policies. The authors present a novel method for visually representing economic growth and its application in analyzing process development within transitional economic nations. The study uses an analytical and synthetical literature review. It offers a new GDP data visualization method useful for monitoring economic development and forecasting potential economic crises—the outcomes from aggregative literature analysis in a consolidated concept are provided for required talent policy proposals. The post-Soviet mindset is seen as a heritage and devious underdog that has left incredibly diverse consequences on today’s society, power structures, economic growth potential, and the emergence of healthy, well-managed, and sustainable innovation ecosystems. The post-Soviet mindset is a seemingly hidden and, at the same time, an intriguing factor that has a significant impact on the desire to make and implement the right decisions related to innovation, education, and other policies promoting business development. The key outcome of the article is that sociocultural aspects and differences in innovation culture led to a slow-down of Latvia’s economic growth compared to Estonia’s and Lithuania’s slightly more successful economic reforms.

This study investigated the use of digital story strategy in teaching Islamic education on achievement and how it affects the development of moral thinking. The quasi-experimental design was implemented as a methodology and the sample included of (60) students from the fourth grade from Abdul Rahman bin Awf School in Abha. The results showed that there are statistically significant differences at the significance level (α ≤ 0.05) between the average responses of students in the two groups in the test. The experimental group performed better than the control group. The findings also showed that there are statistically significant differences at the significance level (α ≤ 0.05) between the average responses of students in the two groups (experimental and control) in the moral thinking scale and favour of the experimental group.