This study investigates the binding affinities of compounds selected from the ZINC database to acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes using molecular docking, molecular dynamics simulations and MMGBSA calculations. The results indicate that the selected compounds exhibit strong binding to AChE, outperforming standard inhibitors such as galantamine and donepezil. Key amino acid residues contributing to the stabilization of the enzyme-inhibitor complexes were identified. The analysis highlights the critical role of van der Waals and electrostatic interactions in maintaining binding stability. The obtained results suggest that the selected compounds from the ZINC database represent promising candidates for the development of novel acetylcholinesterase inhibitors and may encourage further experimental and pharmacological investigations.
The genus Gagea exhibits high morphological diversity and complex taxonomy. In this study, we analyzed the phylogenetic relationships and morphological differentiation within Gagea using ITS sequences from 32 species across 9 sections. Bayesian analysis revealed 3 main clades, partially congruent with morphological traits. Our results highlight both the value of molecular data for species delimitation and the need for taxonomic revision due to cases of morphological convergence and incongruence. This study contributes to a deeper understanding of evolutionary patterns in Gagea.
In recent years, several empirical investigations have focused on a technological framework that would have increased monitoring accuracy by integrating sensor-based analytics with the operational capacity to detect and manage environmental disturbances. Therefore, the aim of this study is to find out what sustainability outcomes will emerge when IoT-based environmental monitoring is implemented in the eco-tourism context. The analysis of environmental parameters to change their response patterns due to the deployment and the intensity of the amount of this monitoring in the ecosystem are the main benefits of this approach. The empirical data of the analysis are data collected by a sensor-based monitoring network in the eco-tourism sector in Uzbekistan; the comparison group is represented by pre-implementation observations. The results from the empirical estimation indicate that sites with more than one monitoring zone, having a calibrated sensor network, or integration of an adaptive feedback mechanism are more likely to be environmentally responsive. The results obtained in the MIMIC-SEM analysis indicate that there are significant differences with the results of the simple ordinary least squares estimation, not only for ecological sustainability in eco-tourism sites but also for the other latent constructs for several of the environmental indicators used in the model. It is evident that maintaining a higher level of calibration is an effective strategy to increase ecological sustainability across eco-tourism sites. However, adaptive monitoring and digital calibration reduce ecological pressure and improve the overall environmental performance.
Water scarcity remains one of the most pressing constraints to agricultural productivity in the Aral Sea region. Dehkan farms operate under limited irrigation resources, making efficient input allocation essential for sustainable production. However, empirical evidence on whether digital agri-food technologies improve farm-level efficiency in water-constrained environments is still limited. This study aims to evaluate the technical efficiency of dehkan farms and examine the impact of digital technology adoption on production performance under water scarcity conditions. The analysis is based on primary survey data collected from 120 farms in Karakalpakstan during the 2025 agricultural season. An input-oriented Data Envelopment Analysis (DEA) model under variable returns to scale is applied to estimate technical efficiency. Farms are classified into digital adopters and conventional producers for comparative assessment. Results indicate that digitally oriented farms demonstrate higher average efficiency scores and improved irrigation water use compared to conventional farms. The findings suggest that digital irrigation practices and improved farm management systems contribute to enhanced resource efficiency. Strengthening institutional support and expanding access to digital technologies can improve agricultural sustainability in the Aral Sea region.
This paper introduces and investigates some properties of algebras constructed from the algebra of polynomials via derivation and integration operators using a process presented by Dzhumadildaev in a previous work. In particular, we discover new classes of infinite-dimensional simple conservative algebras and describe derivations of these algebras of ranks 1 and 2.
