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.

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.

This article focuses on enhancing mathematics education in academic lyceums through the application of interactive methods. It discusses the role of modern educational technologies, active learning strategies, and project-based learning in mathematics education. Additionally, the effectiveness of interactive methods in increasing student engagement, fostering critical thinking, and developing problem-solving skills is analyzed. The article serves as a valuable resource for teachers, education specialists, and academic lyceum administrators.

Mazkur maqolada offshor kompaniyalarining xalqaro xususiy huquq doirasidagi huquqiy maqomi tahlil qilinadi. Asosiy e’tibor kompaniyaga nisbatan qo‘llaniladigan shaxsiy qonunni (lex societatis) aniqlovchi ikkita asosiy yondashuv — inkorporatsiya nazariyasi va asosiy faoliyat ko‘rsatiladigan joy nazariyasining (real seat theory) nazariy hamda amaliy tafovutlariga qaratiladi. Tadqiqotda qiyosiy-huquqiy, keys-tahlil va doktrinal yondashuvlar orqali offshor yurisdiktsiyalarning huquqiy xususiyatlari, xalqaro sud amaliyoti va O‘zbekiston qonunchiligidagi mavjud tartiblar tahlil qilinadi.

Ushbu maqolada fizika yo‘nalishidagi universitet talabalari uchun yarimo‘tkazgichli lazerlarni o‘qitishda axborot texnologiyalari va virtual laboratoriyalardan foydalanish masalasi nazariy jihatdan tahlil qilingan. Amaldagi ta’lim jarayonida mazkur texnologiyalarning yetarli darajada qo‘llanilmayotgani muammo sifatida ko‘rsatib o‘tilgan. Lazer hodisasining murakkab fizik tabiati va uni an’anaviy metodlar bilan tushuntirishdagi qiyinchiliklar yoritilgan. Shuningdek, zamonaviy axborot-kommunikatsiya texnologiyalari, xususan interaktiv dasturlar, 3D modellashtirish, virtual laboratoriyalar va multimedia vositalarining talabalarda mavzuni tushunishga bo’lgan ta’siri o’rganilgan.