В этой статье речь пойдёт о выразительном чтении, которое направлено на формирование духовно богатой, всесторонне развитой творческой личности студентов. На практических занятиях выразительное чтение поможет глубже понять текст, ощутить его эмоциональную окраску. Выразительное чтение поможет лучше выразить свои мысли и эмоции, что полезно для общения. А чтение вслух требует внимания и концентрации, что помогает улучшить память и способность к длительным занятиям.

The etiological structure and peculiarities of clinical and epidemiological manifestations of acute intestinal infections in hospitalised children are studied. A retrospective study of the case histories of 2479 children hospitalised with the clinic of acute intestinal infection was carried out. All patients underwent standard laboratory examination, including clinical, biochemical, instrumental diagnostic methods, bacteriological and molecular-biological studies to verify the causative agent. The epidemiological anamnesis of all children was clarified, and the frequency of background and concomitant diseases was studied. The diagnosis of intestinal infection was verified in 925 children (38%). Bacterial intestinal infections were detected in 610 (65 % of the transcripts).

Mazkur maqolada “O‘zbekistonning eng yangi tarixi” fanini o‘qitish jarayonida o‘quvchilarda ijtimoiy kompetensiyani shakllantirishning asosiy yo‘nalishlari yoritilgan. Maqolada ijtimoiy kompetensiya tushunchasining mazmun-mohiyatini sharhlab, uni tarixiy ong, fuqarolik pozitsiyasi va madaniy merosga munosabat orqali shakllantirish usullarini ko‘rsatib beradi. Shuningdek, dars jarayonlarida interaktiv metodlardan foydalanish, tarixiy voqealarga tanqidiy yondashuvni rivojlantirish va zamonaviy o‘quv materiallaridan foydalanish bo‘yicha tavsiyalar berilgan.

Рассмотрены виды тестовых заданий по филологическим дисциплинам и методика их создания, дано определение теста, пояснено понятие предметной области. Тестовые задания разделены на виды, приведены примеры. Показано, что компетентностные знания, умения и навыки студентов можно оценить на основе тестовых образцов.

This paper focuses on the selection and justification of deep learning models for emotion classification tasks. It provides a comprehensive analysis of various neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, Long Short-Term Memory networks, and Transformer models, assessing their performance in recognizing and classifying human emotions from multimodal data sources. The study examines the strengths and limitations of each model with respect to data type, training efficiency, computational complexity, and generalization capabilities. Furthermore, criteria for optimal model selection tailored to real-world emotion recognition applications are discussed. The findings contribute to enhancing the accuracy and robustness of emotion classification systems and offer valuable guidelines for researchers and practitioners developing advanced affective computing solutions.