The separation and purification of carbon dioxide (CO2) from sour gas streams is critical for emission reduction and industrial reuse. This study presents a chemical absorption-based process simulation of CO2 and H2S separation using Aspen Plus, focusing on solvent-based treatment with several solvents. The process was modeled for two gas streams originating from the Shurtan Gas Chemical Complex: a raw feed stream containing 3.42% CO₂ and 0.09% H₂S, and a treated dry gas containing 2.1% CO₂. The goal was to achieve high-purity CO2 recovery (≥99.5%) with flow rates of 30 t/h and 20 t/h, respectively. Rate-based modeling was employed to simulate mass transfer and chemical kinetics in the absorber and regenerator columns. The simulation results indicated that at optimal solvent flow and absorber temperature (40–45 °C), over 98.6% CO₂ and 99.9% H₂S removal could be achieved. The specific energy requirement for solvent regeneration was estimated at 2.3 GJ per ton of CO₂, aligning with industrial efficiency benchmarks. The purified CO₂ is intended for use in the production of sodium carbonate (Na₂CO₃) at the Dehkanabad Potash Plant, which converts 20 t/h of CO₂ into 296,000 tons/year of calcined soda with 77% process efficiency. This approach enhances gas resource utilization while reducing atmospheric emissions. The model serves as a techno-economically viable foundation for scaling up CO₂ capture and utilization (CCU) in the Uzbek chemical industry.

Introduction: Consumers are sticking to nutritional guidelines on fat consumption and demanding healthier gluten-free food products, resulting in pressure on industries to produce such food products. This study aims to develop the process of making gluten-free cupcakes by substituting wheat flour with a gluten-free composite flour blend and traditional butter with seed mucilage.

Methods: Gluten-free cupcakes (GFCs) were developed using the composite flour blend (amaranth, barnyard, and soyabean flours at 1:1:1). Lepidium sativum seed mucilage (LSM) mimics fat's properties; it was extracted using centrifugation–separation technology. The GFCs were optimized through a one-factor at a time (OFAT) optimization technique to see the effect of LSM as a single variable when used in different proportions: 0%, 25%, 50%, 75%, and 100%. The 100%-fat-replaced GFCs were further evaluated for moisture, ash, protein, fat, fiber, and carbohydrate content (AOAC 2023), fatty acid profiling (GC-FID), and sensory evaluation (on a 9-point hedonic scale), and various health lipid indices were also calculated.

Results: The replacement of 100% fat in the GFCs shows a reduction of 88.74% in fat. The optimized product has moisture% = 26.31±0.07, ash% = 1.45±0.13, protein = 8.43±0.07 gm/100 gm, fat = 2.19±0.23 gm, fiber = 4.28±0.12 gm, and carbohydrate = 39.83±0.09 gm. The fatty acid profiling comparison of GFCs with butter and 100% of the fat substituted shows values for UFA:SFA = (2.3:1)(1.95:1), PUFA:SFA = (0.66:1)(1.02:1), and omega 6:omega 9 = (0.34:1)(1.1:1), respectively. An optimized GFC has an atherogenicity-index = (0.78), a thrombogenic index = (1.06), a health-promoting index = (1.36), and a ∆desaturase-index = (16) (0.022), which indicates good values, while the overall sensory acceptability is 8.2±0.21.

Conclusion: This study indicates that optimized GFCs with incorporated composite flour and 100% of the fat replaced by LSM had an improved overall proximate, sensory, and nutritional matrix. Thus, the results demonstrate the possible potential of these ingredients to improve functionality, consumer acceptance, and industrial applications.

The article analytically and experimentally presents the possibilities for the synthesis of 2-naphthyl 2-chloroacetate. Particular attention is given to the reaction conditions. Based on the literature review, the selective insecticidal activity and chemical properties of 2-naphthol, as well as the features of its nucleophilic substitution reactions with citric acid, are studied. The aim of the research is to develop an efficient method for the synthesis of O-chloroacetylated naphthol and to investigate the nucleophilic substitution reactions of the O-chloroacetylation product with citric acid. The chloracetylation of 2-naphthol in dichloroethane solution without a catalyst leads exclusively to O-acylation, resulting in the formation of 2-naphthyl 2-chloroacetate with a 95% yield. The composition and structure of the synthesized compounds were confirmed by spectroscopic methods. Since the reaction proceeds in dichloroethane without a catalyst, no acylium cation (ion pair) is formed. Therefore, the reaction follows a nucleophilic substitution mechanism at the carbonyl group of the chloroacetyl chloride molecule, yielding an ester product. The oxygen atom in the naphthol molecule serves as the nucleophilic reagent. The nucleophilic substitution products of 2-naphthyl 2-chloroacetate with citric acid were studied using thin-layer chromatography (TLC), and their composition was confirmed with reference substances. The physical constants of 2-naphthyl 2-chloroacetate were determined, and its composition and structure were verified using TLC, IR, and NMR spectroscopy.

This study presents a comprehensive computational and experimental investigation of a cabinet-type solar dryer specifically designed for the dehydration of Plantago major leaves, a widely used medicinal plant. A detailed three-dimensional transient model was developed using ANSYS Fluent to simulate airflow behavior, solar radiation heat transfer, and temperature distribution within the drying chamber under natural convection conditions, considering solar irradiance levels ranging from 600 to 850 W/m² and ambient temperatures of 28–35°C. The initial CFD results revealed temperature gradients of up to 18.2°C between trays and the formation of stagnant airflow zones, leading to uneven drying and significant moisture variation of up to 11.8% across trays. To address these limitations, the design was iteratively optimized by repositioning air inlets/outlets, integrating deflector plates, and adjusting tray spacing from 8 cm to 5 cm. The improved configuration resulted in a 25.4% enhancement in thermal uniformity (measured as standard deviation of tray temperature), a 22.1% reduction in total drying time (from 6.8 hours to 5.3 hours), and a 17.3% increase in overall energy efficiency. Experimental validation was conducted using 1.5 kg batches of freshly harvested Plantago major leaves, with moisture content monitored using gravimetric methods. The improved dryer reduced final moisture content variation between trays to less than 2.5%, ensuring more uniform drying and improved retention of bioactive compounds such as aucubin and flavonoids. These results confirm the predictive power of CFD modeling for solar dryer optimization and validate the practical benefits of the improved design. The integration of simulation and field data highlights the viability of deploying sustainable, energy-efficient, and low-cost drying solutions for medicinal plant processing, particularly in off-grid and rural communities.

The present study aimed to evaluate the antioxidant activity and perform high-performance thin-layer chromatography (HPTLC) analysis of the ethyl acetate fraction of the acetone extract of Hardwickia binata Roxb. The ethyl acetate fraction was assessed for in-vitro antioxidant activity using various methods, including the Cupric Reducing Antioxidant Capacity (CUPRAC) assay, 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging assay, hydroxyl free radical scavenging assay, reactive nitrogen oxide scavenging assay, superoxide anion radical scavenging assay, ABTS radical scavenging assay, and Ferric Reducing Antioxidant Power (FRAP) assay. The half-maximal inhibitory concentration (IC₅₀) values were determined for each assay: CUPRAC (4.9 ± 1.1 µg/mL), DPPH (39.05 ± 0.09 µg/mL), hydroxyl free radical scavenging (11.62 ± 0.0931 µg/mL), reactive nitrogen oxide scavenging (435.2 ± 0.01 µg/mL), superoxide anion radical scavenging (16.89 ± 0.06 µg/mL), ABTS radical scavenging (14.9 ± 1.1 µg/mL), and FRAP (2.442 ± 0.12 µg/mL).. HPTL Among these, the CUPRAC and FRAP assays exhibited the most significant antioxidant activity C fingerprinting of the ethyl acetate fraction under UV light revealing the presence of seven components with retention factor (Rf) values of 0.012, 0.073, 0.12, 0.18, 0.569, 0.658, and 0.935. The ethyl acetate fraction was further analyzed for quercetin content using HPTLC densitometric analysis with a solvent system comprising toluene: ethyl acetate: methanol: glacial acetic acid (5:4:0.5:0.5, v/v). The analysis was performed on precoated silica gel 60F254 plates, and densitometric detection of quercetin was conducted at 254 nm and 366 nm. The amount of quercetin was quantified by comparing with a standard calibration curve (linear range: 200–600 ng/spot, r² = 0.9989). The concentration of quercetin in the ethyl acetate fraction was 43.41 µg/mg of the dry fraction. The results indicate that Hardwickia binata contains natural antioxidants.

Background:
The growing demand for sustainable and health-promoting functional foods has led to the exploration of novel lipid sources. Algal oil, particularly rich in omega-3 long-chain polyunsaturated fatty acids (LC-PUFAs), offers a promising alternative to conventional fats. This study aims to integrate fatty acid profiling and mineral composition analysis into the development and optimization of an algal-oil-based chocolate spread, emphasizing its nutritional enhancement and potential health benefits.

Methods:
A chocolate-based spread emulsion was developed using Schizochytrium sp.-derived algal oil as the primary lipid source. The formulation was optimized using response surface methodology (RSM) based on texture, spreadability, and sensory acceptability. Fatty acid methyl esters (FAMEs) were analyzed using Gas Chromatography–Flame Ionization Detection (GC-FID), while mineral composition was determined through Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). The spread's physicochemical properties, including pH, moisture content, water activity, and oxidative stability (MDA assay), were also assessed.

Results:
The optimized formulation exhibited high sensory acceptability, with a desirable spreadability index and stable emulsion properties. Fatty acid analysis revealed significant enrichment in docosahexaenoic acid (DHA, 37.64 ± 1.12%), followed by eicosapentaenoic acid (EPA, 12.08 ± 0.84%), indicating a strong omega-3 profile. Saturated and monounsaturated fatty acids were present in balanced proportions. Mineral analysis demonstrated elevated levels of magnesium (34.6 ± 2.3 mg/100g), calcium (28.1 ± 1.7 mg/100g), and iron (4.2 ± 0.3 mg/100g), contributing to the functional benefits of the product. The final spread exhibited low malondialdehyde levels (0.78 ± 0.04 nmol/g), confirming oxidative stability during storage.

Conclusion:
This study successfully demonstrates that the integration of fatty acid and mineral profiling into the product development phase enables the creation of a nutritionally dense and sustainable algal-based functional spread. The findings support the potential of algal oil as a viable alternative fat source in functional food formulations, with implications for cardiovascular and neuroprotective health outcomes.

The rapidly growing global population and evolving consumer preferences have intensified challenges in managing perishable food inventories and minimizing post-harvest losses. “Advanced Deep Learning Techniques for Shelf-Life Estimation and Food Waste Reduction” presents a comprehensive investigation into state-of-the-art neural network architectures and methodologies designed to accurately forecast the remaining usable life of fresh and processed food products. By integrating multimodal data sources—encompassing physicochemical quality indicators, environmental storage conditions, and real-world supply-chain variables—this research demonstrates how deep learning models can transform traditional shelf-life prediction and demand-planning practices, yielding substantial reductions in food spoilage and waste. Finally, we discuss broader implications for sustainable food systems and circular economy practices. By providing granular, product-level shelf-life insights, advanced deep learning enables more precise allocation of near-expiry goods to secondary markets (e.g., discount retail and food bank donations) and optimizes routing to minimize carbon emissions associated with spoilage-induced inefficiencies. Life cycle assessment (LCA) modeling of the pilot studies estimates a 7% reduction in greenhouse gas emissions per unit of food distributed, driven by lower waste volumes and reduced need for expedited transport of replaced stock.

In conclusion, this research substantiates that advanced deep learning techniques—particularly hybrid CNN-LSTM architectures integrated with reinforcement learning–driven decision systems—offer a transformative approach to shelf-life estimation and food waste reduction. The demonstrated improvements in predictive accuracy, operational waste savings, and environmental benefits underscore the potential for wide-scale adoption in commercial food supply chains. Future work will explore federated learning strategies to enable collaborative model training across organizations without sharing proprietary data and the extension of these methodologies to additional food categories and distribution modalities.

Deep eutectic solvents (DES) and natural deep eutectic solvents (NADES) are promising alternatives to traditional organic solvents for the extraction of polyphenols. They provide multiple advantages, such as improved extraction efficiency and increased solubility of the target compounds. These solvents are formed by mixing hydrogen bond donors and acceptors in specific molar ratios, which lowers their melting points. DES and NADES effectively dissolve a wide range of polyphenolic compounds that possess antioxidant and anti-inflammatory properties.

DES were prepared using urea and glycerol in a 1:2 (U¹G²) ratio in a silicone bath for 60 min at temperatures of 70–90 °C with constant stirring. The infrared spectra of the starting materials – glycerol and urea – as well as those of the resulting DES were recorded. DES was then applied in the solid-liquid extraction of polyphenols from Helichrysum italicum, with 70% methanol as a reference standard. After extraction, total phenolic content (TPC), total flavonoids (TFC), and antioxidant activity assessed by DPPH, HRSA, CPRAC, and in vitro anti-inflammatory activity assessed by albumin denaturation inhibition (IAD) were measured. The DES (U¹G²) extract demonstrated superior performance compared to the 70% MeOH extract, with higher dry yield (322.65 vs. 303.80 mg), total phenolics (178.50 vs. 142.85 mg GAE/g DW), and flavonoids (154.82 vs. 109.43 mg QE/g DW). Antioxidant activity was stronger in CUPRAC (264.67 vs. 203.46 mM TE/g DW), DPPH assays (IC₅₀ = 4.24 vs. 8.89 µg/mL), and hydroxyl radical scavenging activity (HRSA, IC₅₀ = 100.33 vs. 107.27 µg/mL). Slightly better inhibition of albumin denaturation (155.61 vs. 150.64 µg/mL) also indicates enhanced anti-inflammatory potential. The results highlight the efficacy and sustainability of DES-based extractions, suggesting that this environmentally friendly approach can be scaled up for commercial extract production.

The growing demand from consumers for wholesome food products has made it extremely difficult to create eco-friendly and sustainable solutions. Ozone treatment in the food and horticulture product capitalization sectors has been widely acknowledged as completely safe for human use based on the most recent rules of the relevant authorities. Ozone devices for research and education are known to allow the introduction of ozone gas for many uses, especially in food and agricultural applications. Despite their usefulness, their expensive cost prevents them from being widely available in research and educational institutions in underdeveloped nations, which limits practical training and the creation of local applications to support the capacities of the food and agriculture sectors. At the same time, there has been a startling rise in electronic components worldwide, and the cheap prices have raised financial concerns. In this regard, the study's goal was to create a working prototype of an ozone (O₃) generator utilizing inexpensive parts. The apparatus was constructed utilizing a pump that delivers air at varying flow rates and a high voltage principal circuit that produced O₃. An Arduino board with sensors attached was used to accomplish the control operation. To finish the device, stainless steel tube and other basic components were utilized. Performance was assessed in accordance with the calibration procedure outlined for such produced devices or comparable ones. The findings provide credence to the viability of constructing an inexpensive ozone generator using inexpensive parts, hence promoting sustainable technological advancement.

The purification of raw natural gas is critical for removing contaminants such as water vapor, gas condensates, and mechanical impurities that can impair downstream equipment and reduce gas quality. In this study, we present a comprehensive modeling, simulation, and experimental analysis of a modified three-phase gas-liquid separator tailored for high-load natural gas streams. The separator design incorporates thirty suspended baffles and a novel anti-foam mesh, which were geometrically optimized using experimental fluid dynamics principles. Aspen Plus simulations were performed using the Peng-Robinson thermodynamic model with a detailed three-phase flash separation module. Feed composition from the Somontepa gas field was used (CH₄: 89.65%; CO₂: 4.12%; H₂S: 3.00%; C₂–C₆+: 2.55%), at 5.6 MPa and 25°C. The simulation accurately predicted the phase split, showing that 98.3% of the hydrocarbon vapor was directed to the gas outlet, while >99% of condensates and water were captured in the liquid phase. Sensitivity analysis across 20–65 m/s inlet velocities revealed that the pressure drop was reduced by 27% in the enhanced baffle configuration. Furthermore, Aspen Plus predicted a 96.8% decrease in entrained liquid carryover compared to a baseline separator. The results were validated through field trials, which confirmed the simulation predictions: gas condensate content was reduced from 16.58 to 0.725 g/m³, moisture from 4.84 to 0.1 g/m³, and mechanical impurities from 1.2 to 0.0058 g/m³. This synergy of simulation and practice highlights the robustness of the improved design for deep natural gas decontamination and positions it as a scalable solution for industrial gas processing plants.