The present article reports the applications of Caputo-Fabrizio time-fractional derivatives. This article generalizes the idea of unsteady MHD free convective flow in a Walters.-B fluid with heat and mass transfer study over an exponential isothermal vertical plate embedded in a porous medium. The governing equations are converted into dimensionless form and extended to fractional model. The generalized Walters-B fluid model has been solved analytically using the Laplace transform technique. From the general solutions we reduce limiting solutions when to the similar motion for Newtonian fluid. The corresponding expressions for and Nusselt and Sherwood numbers are also assessed. Numerical results for velocity, temperature and concentration are demonstrated graphically for various factors of interest and discussed. As a result, we have plotted the influence of fractional parameter on fluid flow and drawn comparison between fractional Walters’-B and fractional Newtonian fluid and found that fractional Newtonian fluid is faster than fractional Walters’-B fluids.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.

In this study, robust and defect-free thin film composite (TFC) forward osmosis (FO) membranes have been successfully fabricated using ceramic hollow fibers as the substrate. Polydopamine (PDA) coating under controlled conditions is effective in reducing the surface pores of the substrate and making the substrate smooth enough for interfacial polymerization. The pure water permeability (A), solute permeability (B), and structural parameter (S) of the resultant FO membrane are 0.854 L·m^–2·h⁻¹·bar⁻¹ (LMH/Bar), 0.186 L·m^–2·h⁻¹ (LMH), and 1720 µm, respectively. The water flux and reverse draw solute flux are measured using NaCl and proprietary ferric sodium citrate (FeNaCA) draw solutions at low and high osmotic pressure ranges. As the osmotic pressure increases, a higher water flux is obtained, but its increase is not directly proportional to the increase in the osmotic pressure. At the membrane surface, the effect of dilutive concentration polarization is much less serious for FeNaCA-draw solutions. At an osmotic pressure of 89.6 bar, the developed TFC membrane generates water fluxes of 11.5 and 30.0 LMH using NaCl and synthesized FeNaCA draw solutions. The corresponding reverse draw solute flux is 7.0 g·m^–2·h⁻¹ (gMH) for NaCl draw solution, but it is not detectable for FeNaCA draw solution. This means that the developed TFC FO membranes are defect-free and their surface pores are at the molecular level. The performance of the developed TFC FO membranes is also demonstrated for the enrichment of BSA protein.

This study investigates the performance assessment of methanol and water as working fluid in a solar-powered vapour absorption refrigeration system. This research clarifies the system’s performance across a spectrum of operating conditions. Furthermore, the HAP software was utilized to determine and scrutinize the cooling load, facilitating a comparative analysis between software-based results and theoretical calculations. To empirically substantiate the findings, this research investigates methanol-water as a superior refrigerant compared to traditional ammonia- water and LiBr-water systems. Through experimental analysis and its comparison with previous research, the methanol-water refrigeration system demonstrated higher cooling efficiency and better environmental compatibility. The system’s performance was evaluated under varying conditions, showing that methanol-water has a 1% higher coefficient of performance (COP) compared to ammonia-water systems, proving its superior effectiveness in solar-powered applications. This empirical model acts as a pivotal tool for understanding the dynamic relationship between methanol concentration (40%, 50%, 60%) and system performance. The results show that temperature of the evaporator (5–15 ℃), condenser (30 ℃–50 ℃), and absorber (25 ℃–50 ℃) are constant, the coefficient of performance (COP) increases with increase in generator temperature. Furthermore, increasing the evaporator temperature while keeping constant temperatures for the generator (70 ℃–100 ℃), condenser, and absorber improves the COP. The resulting data provides profound insights into optimizing refrigerant concentrations for improved efficiency.

This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance in the context of urban modernization and digital transformation. The research is anchored in the quest to understand how specific technological factors influence the formation of smart cities within the region. To this end, the study adopts a Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, and electronic invoicing practices across various Kazakhstani cities. The crux of the research revolves around assessing the impact of these selected technological variables on the smart city development process. The SAR model’s application facilitates a nuanced understanding of the spatial dynamics at play, offering insights into how these factors vary in influence across different urban areas. A key finding of this investigation is the significant positive correlation between the adoption of electronic invoicing and smart city development, a result that stands in contrast to the relatively insignificant impact of server density and cloud service usage. The conclusion drawn from these findings underscores the pivotal role of digital administrative processes, particularly electronic invoicing, in driving the smart city agenda in Kazakhstan. This insight not only contributes to the academic discourse on smart cities but also holds practical implications for policymakers and urban planners. It suggests a strategic shift towards prioritizing digital administrative innovations over mere infrastructural or technological upgrades. The study’s outcomes are poised to guide future smart city initiatives in Kazakhstan and offer a reference point for similar emerging economies embarking on their smart city journeys.