Bukhara State University

Fig fruits (Ficus carica L.), also known as the fig tree, is fruit subtropical A deciduous plant that is widely consumed as food in many countries, figs have a wide range of culinary uses, being consumed fresh, dried, candied, and candied. Their inclusion in the diet is characteristic of the Mediterranean diet, which is recognized as one of the healthiest diets and is associated with an increased lifespan. Due to the short shelf life of ripe figs, their production or processing into a new end product, such as pastilles, could contribute to the use and popularization of this tropical fruit and provide a wide range of products. Therefore, the aim of this study was to develop fig pastilles and determine the physicochemical properties and sensory characteristics of fig pastilles. A total of six pastille formulations were developed, based on different amounts of added fig puree (10%, 12%, 14%, 16%, 18%, and 20% fig puree). Texture profile, water activity, total soluble solids, color, pH, moisture, ash, fiber, and antioxidant activity were analyzed. The results showed that Formulation F (20% fig puree) demonstrated the highest moisture (18.59%), ash (2.43%), fiber (2.65%), and antioxidant activity (36.58%) values. The production of this product will be in high demand in the international functional food market, since no synthetic preservatives or artificial colors were used. The fig pastilles were successfully developed and are brownish-orange in color, round in shape, 1.0-1.2 cm in diameter, and weigh approximately 1.2-1.5 g. Formulation B (12% fig fruit puree) has a Brix value of 62.70 at a pH of 4.3, a sweet taste, and a water activity of 0.54. Color analysis revealed L* (59.76), a* (23.71), and b* (34.33) values, which gave the fig fruit pastilles a brownish-orange color. Composition B (12% fig fruit puree) was highly rated by tasters and retained its good texture and color after refrigeration for two months at temperatures below 18°C. Thus, the analysis showed that the physicochemical properties of the resulting fig fruit pastilles were improved, they were rich in antioxidants, and received the approval of the tasters. Therefore, figs may be a potential natural ingredient for the production of pastilles, promoting their use in the food industry.

The aim of the study was to estimate the efficiency of a peer-based teaching and cooperative learning intervention in forensic users with a complex neurodivergent profile (Autism Spectrum Disorder, Attention-Deficit/Hyperactivity Disorder, and intellectual disabilities). The research question was that peer-facilitated learning would increase social communication, emotional regulation, engagement, and self-efficacy and decrease behavioral incidents as compared to usual clinician-facilitated interventions. The quasi-experimental mixed-methods study design was used, including 84 adult forensic service users who were divided into a collaborative learning group (led by peers, n=42) and a control group (led by a clinician, n=42). Psychosocial measurements and institutional behavioral records were used to measure outcomes at a 12-week post-intervention point and six months of follow-up to evaluate the effect of the intervention. There were repeated measures ANOVA, regression, and mediation analyses. Social communication (F (2,162) = 8.94, p < 0.001) and emotional regulation (F (2,162) = 7.63, p <0.01) had significant time x group interaction effects. Big effect sizes in the post-test (Cohen’s d = 1.21 and d = 1.08, respectively) and the gains at follow-up were found. Incidents of behavioral engagement were a significant predictor of behavioral incident reductions (β = −0.42, p < 0.01). The peer-led group showed a 56% decrease in behavioral episodes as compared to 15% in the control group, and continued to improve after six months. Collaborative learning led by peers had a considerable positive impact on socio-emotional functionality and minimized the behavioral risk of neurodivergent forensic service users. Their results suggest the incorporation of neurodiversity-informed, peer-mediated methodology into the context of forensic rehabilitation to promote responsivity, engagement, and desistance in the long run.

This article highlights the pedagogical foundations for developing children's creative thinking potential in preschool educational institutions. It analyzes the content of the concept of creative thinking, the characteristics of its formation in preschool age, and the possibilities of its development through visual-art activities. The study also substantiates the methodological potential of the open-ended tasks method aimed at developing key components of creative thinking in children, such as originality, flexibility, fluency of ideas, elaboration, and reflection. The article emphasizes the pedagogical importance of organizing visual-art activities based on a creative approach, the facilitator role of the educator, and the creation of an environment that supports free choice and creative expression. The research findings confirm that the use of open-ended creative tasks in preschool education serves as an effective methodological tool for developing independent thinking, creative initiative, and the ability to find unconventional solutions to problem situations among children.

The article examines which fine tuning strategy is most rational for Uzbek and Russian neural machine translation under low resource conditions and domain variation. The analysis compares six model lines, MarianMT, mBART 50, M2M100, NLLB 200, uzT5, and SeamlessM4T, through a structured set of linguistic diagnostics that includes agglutination, analytic verb forms, terminology, named entities, script variation, and discourse dependent ambiguity. The study is not presented as a large scale benchmark with new numerical scores. Instead, it offers an evidence based analytical comparison grounded in Russian language scholarship, open academic reports, and an author designed stress test for Uzbek and Russian. The main result is that no single architecture is optimal for every scenario. NLLB 200 and mBART 50 appear most promising as core backbones for supervised adaptation, MarianMT remains useful in narrow institutional domains, uzT5 is valuable as an Uzbek aware auxiliary model, and SeamlessM4T is strategically relevant for future speech to speech pipelines rather than as the default pure text solution.

This article examines the pedagogical views reflected in the literary and publicistic works of Sadriddin Ayni. As a prominent writer, educator, and public intellectual of Central Asia, Ayni articulated a coherent vision of enlightenment, moral upbringing, social justice, and national awakening through education. The study analyzes his key works and highlights their contribution to the development of modern pedagogical thought in the region.

This study investigates the translation patterns and equivalence strategies of collocations in a parallel corpus consisting of English-Uzbek translations. Collocations, as recurrent word combinations, pose significant challenges in translation due to their language-specific nature and varying degrees of semantic transparency. Using a corpus-based approach, this research analyzes 500 collocation instances extracted from literary and technical texts to identify translation strategies, frequency patterns, and equivalence types. The findings reveal that translators employ diverse strategies including literal translation, substitution, paraphrase, and cultural adaptation depending on collocation type and context. Statistical analysis demonstrates that verb-noun collocations exhibit the highest variation in translation equivalents, while adjective-noun combinations show more consistent patterns. The study contributes to translation studies by providing empirical evidence on collocation translation behavior and offers practical implications for translator training and machine translation development.

This article, employing a comprehensive approach, analyzes the influence of the state land cadastre system on investment processes in the context of contemporary economic reforms. In an era of intensifying global competition, growing importance of regional development, and digital governance, the role of the land cadastre in shaping the investment environment is significantly increasing. In this regard, the scientific and methodological formation of indicators, the integration of spatial-statistical indices, and the effective use of digital cadastral data are critical conditions for ensuring economic sustainability and investment security. Empirical data indicate that in 2020–2024, regions with a fully digitalized cadastral system experienced an average increase in investment inflow of 27–35%. This confirms the importance of the accuracy and transparency of cadastral information as a key factor in investment activity. The research findings contribute to the development of a modern concept for land resource management, substantiate investment decisions based on spatial data, and further scientifically reinforce the functional significance of the digital cadastral system in economic processes.

This article presents the results of a study on the physiological characteristics of water exchange in corn varieties under varying soil moisture conditions. The findings indicate that the physiological activity and water exchange traits of the studied corn varieties differ depending on soil moisture levels and their inherent biological characteristics. Variations were observed in transpiration intensity and overall physiological responses under different moisture regimes. Under water deficit conditions, the Andijon-36 and Yangiobod varieties demonstrated higher productivity compared to other varieties. These results provide a scientific basis for identifying relatively drought-tolerant corn varieties suitable for cultivation under arid and semi-arid conditions.

Evaluating writing skills in secondary education requires accurate, automated approaches that capture both semantic meaning and linguistic quality. Traditional methods often rely on surface-level features such as grammar, vocabulary, or word count, which fail to assess deeper coherence and contextual relevance in student essays. Existing approaches struggle with subjectivity, limited generalization, and insufficient semantic understanding. To address these challenges, this study proposes a Semantic Embedding Model using a Siamese Neural Network (SNN) framework, which measures semantic similarity between student responses and reference texts. The model leverages contextual embeddings to effectively capture meaning, coherence, and writing quality beyond syntactic measures. The proposed method can be applied for essay grading, skill assessment, and providing feedback to students and educators. Experimental results demonstrate improved accuracy, fairness, and consistency in evaluating writing skills compared to traditional evaluation systems.