Oriental University

Water evaporation prediction for environmental monitoring, irrigation management, and meteorological modeling is growing nowadays. This study develops a new optimized deep learning model with a modified regression model for water evaporation prediction. Initially, in this study, a dataset was collected from publicly available sources on the internet. The collected dataset faced class imbalance issues; to address these issues Random Over-Sampling method (ROS) is utilized. Then, during preprocessing, Z-score normalization is employed to scale features to a specified range. Preprocessing is done to process the feature selection model, extended recursive feature elimination (EX-RFE) is used, which finds the important features and helps the effective prediction. Finally, they developed a novel optimized stacked long short-term modified support vector regression (OS-LSTM-MSVR) for effective water evaporation prediction, which enhanced performance and offered an optimal solution. Furthermore, a new enhanced Gauss map Frilled lizard optimization (GM-FLO) is utilized to fine-tune the hyperparameters of the developed model. Additionally, implementation outcomes demonstrate that the OS-LSTM-MSVR model obtained an MAE reduction of 0.3551 and an RMSE reduction of 0.5343 compared to the baseline approaches. The optimization significantly enhanced generalization, with an R2 value of 0.9901 across all test folds.

Language acquisition and reading comprehension are complex cognitive processes shaped by both genetic and epigenetic factors. Epigenetic mechanisms-including DNA methylation, histone modification, and chromatin remodeling-regulate gene expression patterns that guide neurodevelopment, synaptic plasticity, and cortical patterning, thereby influencing the neural circuits underlying language and literacy. Environmental inputs, such as early language exposure, educational interventions, and socioeconomic context, interact with these epigenetic programs to modulate linguistic and reading skills across development. Core reading networks, comprising the left temporoparietal, ventral occipitotemporal, and inferior frontal circuits, support phonological, orthographic, and semantic processing and exhibit experience-dependent plasticity mediated by epigenetic regulation. Evidence from longitudinal and cross-species studies indicates that targeted educational practices can induce beneficial epigenetic changes, enhancing language acquisition and reading proficiency. Understanding the interplay between epigenetic regulation, neural mechanisms, and environmental factors provides a foundation for optimizing literacy interventions and informs strategies for mitigating reading-related difficulties in both typical and at-risk populations.

Precision medicine relies on the development of therapeutic systems capable of molecular-level manipulation. Traditional drug delivery remains restricted by poor bioavailability, rapid systemic clearance, and non-specific distribution, leading to adverse effects in healthy tissues. Surface-engineered nanocarriers address these hurdles through sophisticated functionalization strategies. Organic, inorganic, and carbon-based nanoplatforms provide versatile templates for encapsulation and controlled release. Functional layers, such as polyethylene glycol, establish a hydrated shield that prevents opsonization and extends circulation half-life. Integration of specific ligands including antibodies, peptides, and small molecules enables active targeting through receptor-mediated endocytosis, facilitating site-specific accumulation at diseased sites like solid tumors. Stimuli-responsive designs allow for triggered release in response to pathological environments, such as acidic pH or enzymatic overexpression. Specialized techniques like red blood cell hitchhiking and the recruitment of endogenous proteins allow for the traversal of the blood-brain barrier and pulmonary endothelium. Despite therapeutic potential, clinical translation is delayed by manufacturing complexities, batch-to-batch variability, and immunological responses such as accelerated blood clearance. Refining the nano-bio interface through biomimetic design remains essential for achieving consistent human clinical efficacy. Successful implementation of these smart platforms marks a significant shift toward personalized, patient-centric therapeutics, offering a clear path to minimize systemic toxicity while maximizing curative outcomes across various diseases

This article examines the mechanisms of local regulation of labor relations within the general secondary education system of the Republic of Uzbekistan. It analyzes the legal framework, including the Labor Code and the Law "On Education," and explores the role of local normative documents such as collective agreements and internal labor regulations. The study provides a detailed dynamic analysis of social protection funds allocated through collective agreements between 2020 and 2025. Furthermore, it proposes a transition from authoritarian to democratic management models through enhanced social partnership, digital integration, and KPI-based evaluation systems to improve the efficiency of labor relations in schools.