This scientific work explores the clinical features, causes, and contemporary treatment strategies for tension-type headache in children, one of the most prevalent and often underdiagnosed neurological conditions in the pediatric population. The study highlights the multifactorial origin of tension-type headache, emphasizing psychological stress, musculoskeletal strain, and lifestyle imbalances as central contributing factors. Special attention is given to the importance of early diagnosis based on clinical evaluation, patient history, and the use of structured assessment tools designed for children. The research reviews both pharmacological and non-pharmacological treatment approaches, with a focus on behavioral therapy, cognitive-behavioral interventions, physical therapy, and biofeedback techniques. Preventive strategies such as stress management, sleep hygiene, physical activity, and nutritional regulation are also discussed as key elements in reducing the frequency and severity of headache episodes. Furthermore, the work highlights the psychosocial impact of chronic headache on children’s academic performance, emotional health, and social development.

Mazkur maqolada ta’lim muassasalarini boshqarish tizimini takomillashtirishning dolzarb jihatlari yoritilgan. Bugungi kunda ta’lim sifati va samaradorligini oshirishda menejment tizimining samarali faoliyati muhim o‘rin egallaydi. Shuning uchun ta’lim jarayonida strategik rejalashtirish, innovatsion yondashuv, raqamli boshqaruv, monitoring va baholash tizimlarini rivojlantirish orqali menejmentni zamonaviylashtirish zarurati ortib bormoqda. Maqolada samarali boshqaruv modelini shakllantirish, kadrlar salohiyatini oshirish, resurslardan oqilona foydalanish va ta’lim muassasasining ichki muhitini yaxshilash bo‘yicha amaliy takliflar berilgan. Shuningdek, xorijiy tajribalar tahlil qilinib, ularni milliy tizimga moslashtirish imkoniyatlari ham ko‘rib chiqilgan.

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.

Markaziy Osiyoda suv xavfsizligi tobora dolzarb masalaga aylanib bormoqda. Bunga iqlim o‘zgaruvchanligining kuchayishi, suvga bo‘lgan talabning ortishi hamda transchegaraviy daryolarni boshqarish bilan bog‘liq muammolar sabab bo‘lmoqda. Ushbu maqolada mintaqadagi transchegaraviy suv resurslarini boshqarish murakkabligi, milliy manfaatlar bilan mintaqaviy hamkorlik o‘rtasidagi o‘zaro bog‘liqlik asosida o‘rganiladi.

Данная работа посвящена анализу произведения «Пётр и Феврония», в котором освещаются темы любви, верности и нравственных ценностей. Через образы главных героев раскрываются истинная любовь и мудрость. Также рассматривается место произведения в религиозной и народной литературе.