The article provides information on the importance of dietary fiber and some trace elements in red beets in the treatment of constipation.

The emergence of the first electronic dictionaries and their capabilities. Principles of dictionary creation. The need for electronic dictionaries.

Reinforcement learning (RL) methods are increasingly used in the field of legal practice to improve decision making, automate routine tasks, and optimize legal processes. Using RL techniques, legal professionals can create systems that are able to learn from their environment, adjust strategies, and improve performance over time. In legal contexts, RL can be applied to a variety of tasks, including contract analysis, case prediction, and legal document classification, among others. RL's ability to manage sequential decision-making processes makes it particularly useful in managing the complexities and uncertainties inherent in legal decision-making where actions (such as drafting documents or providing legal advice) may have far-reaching consequences. In legal practice, RL models can help predict case outcomes, determine the best legal strategies, and even optimize contract negotiations based on past results. Through continuous feedback, these models will improve over time and become more effective in suggesting optimal actions for lawyers and other legal professionals. Implementation of RL-based systems is expected to streamline legal workflows, reduce human error, and provide innovative solutions to longstanding challenges in legal research, litigation, and compliance.

Balanıń rawajlanıwı qorshaǵan ortalıqqa, ómirdiń qalay kelip shıǵıwına, tárbiyasına tuwrıdan-tuwrı baylanıslı. Boyına ósiw baqsha jasındaǵı hám kishi jastaǵı mektep balaları ushın tán. Balalardı dene tárbiyasınıń tiykarı bolıp, densawlıqtı bekkemlew hám durıs fizikalıq rawajlandırıw bolıp esaplanadı. Dene tárbiyasınıń tiykarǵı wazıypaları – oqıwshılardı salamatlastırıw, olardı fizikalıq rawajlanıwı, háreket tájiriybelerimizge iye bolıwı hám fizikalıq sıpatlardıń rawajlanıwın jaqsılawdan ibarat.

In today’s globally interconnected academic and professional landscape, English competence is invaluable asset across divorse fields, including engineering, medicine, and technology. However, students in non-linguistic specialties often prioritize their primary studies over language skills, which can lead to an undervaluation of English proficiency. This article explores methods to raise English learning awareness among these students, focusing on motivational approaches, contextual learning, and istitutional support. By offering tailored strategies, the study aims to boost engagement and proficiency in English among non-linguistic students.