Potential Applications In Various Industries Research Articles

Acid Hydrolyzed Pearl Millet Starch Nanoparticles: Synthesis and Characterization

AbstractThe amylose content in native starch is reduced through hydrolysis, impacting its physicochemical properties. Starch nanoparticles exhibit enhanced water and oil absorption capacities, attributed to increased hydrolysis and subsequently higher solubility. Moreover, the swelling power of starch nanoparticles is notably higher, indicating improved functionality. Pasting properties are altered, with reduced peak viscosity, breakdown viscosity, and setback viscosity in modified starches. Dynamic light scattering reveals a significant reduction in particle size for starch nanoparticles compared to native starch. Morphological analysis using field emission‐scanning electron microscopy (FE‐SEM) highlights distinct granule shapes and surfaces between the two starch types. The X‐ray diffraction patterns confirm an A‐type crystalline structure in both native and modified starches. Fourier transform infrared (FTIR) spectroscopy verifies no significant difference in functional groups due to extraction or hydrolysis methods. This comprehensive investigation provides valuable insights into the chemical modification of pearl millet starch, shedding light on its potential applications in various industries, including food and pharmaceuticals.

Biological Activities of Citrus aurantium Leaf Extract by Optimized Ultrasound-Assisted Extraction

Several studies have explored the biological activities of Citrus aurantium flowers, fruits, and seeds, but the bioactivity of C. aurantium leaves, which are treated as waste, remains unclear. Thus, this study developed a pilot-scale ultrasonic-assisted extraction process using the Box–Behnken design (BBD) for the optimized extraction of active compounds from C. aurantium leaves, and their antityrosinase, antioxidant, antiaging, and antimicrobial activities were evaluated. Under optimal conditions in a 150× scaleup configuration (a 30 L ultrasonic machine) of a pilot plant, the total phenolic content was 69.09 mg gallic acid equivalent/g dry weight, which was slightly lower (3.17%) than the theoretical value. The half maximal inhibitory concentration of C. aurantium leaf extract (CALE) for 2,2-diphenyl-1-picrylhydrazyl–scavenging, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)–scavenging, antityrosinase, anticollagenase, antielastase and anti-matrix metalloprotein-1 activities were 123.5, 58.5, 181.3, 196.4, 216.3, and 326.4 mg/L, respectively. Moreover, the minimal inhibitory concentrations for bacteria and fungi were 150–350 and 500 mg/L, respectively. In total, 17 active compounds were detected in CALE—with linalool, linalyl acetate, limonene, and α-terpineol having the highest concentrations. Finally, the overall transdermal absorption and permeation efficiency of CALE was 95.9%. In conclusion, our CALE demonstrated potential whitening, antioxidant, antiaging, and antimicrobial activities; it was also nontoxic and easily absorbed into the skin as well as inexpensive to produce. Therefore, it has potential applications in various industries.

Combinations of Spent Grains as Sources of Valuable Compounds with Highly Valuable Functional and Microbial Properties

The potential of spent grains as a source of valuable compounds with various properties has gained attention. They are the by-product of the brewing process, typically resulting from the beer-making process. Five different mixed combinations of spent grains of barley, wheat, rice, maize and finger-millet were formulated and further analyzed and compared. Barley and wheat (BW), barley and rice (BR), barley and maize (BM), and barley and finger-millets (BF) were mixed in a ratio of 1:1 (w/w) and ground into a fine powder to study their techno-functional, phytochemical and in vitro properties. The techno-functional, phytochemical and in vitro properties of barley and maize (BM) were found to be the best choice, making it a promising candidate for applications in value-added products. The WAI (water absorption index) of BM (5.03 g/g) was the highest compared to BB (3.20 g/g), BF (3.56 g/g), BR (4.10 g/g) and BW (4.33 g/g), whereas the WSI (water solubility index) and OAC (oil absorption capacity) of BM (7.06% and 1.90 g/g, respectively) were lower than BW (7.60% and 2.24 g/g, respectively), BR (8.20% and 2.30 g/g, respectively), BF (9.67% and 2.57 g/g, respectively) and BB (10.47% and 2.70 g/g, respectively). A higher percentage of inhibition of DPPH (44.14%) and high phenolic and flavonoid contents (72.39 mg GAE/gm and 66.03 mg QE/gm, respectively) were observed in BM. It also showed higher in vitro properties like amylase and lipase inhibition assay (89.05% and 62.34%, respectively) than the other combinations. The present study provides valuable information about the differences between spent grain varieties and their combinations, with potential applications in various industries.

Structural characterization, biofunctionality, and environmental factors impacting rheological properties of exopolysaccharide produced by probiotic Lactococcus lactis C15

Exopolysaccharides (EPSs) possess distinctive rheological and physicochemical properties and innovative functionality. This study aimed to investigate the physicochemical, bioactive, and rheological properties of an EPS secreted by Lactococcus lactis subsp. lactis C15. EPS-C15 was found to have an average molecular weight of 8.8 × 105 Da and was identified as a hetero-EPS composed of arabinose, xylose, mannose, and glucose with a molar ratio of 2.0:2.7:1.0:21.3, respectively. The particle size and zeta potential represented 311.2 nm and − 12.44 mV, respectively. FITR exhibited that EPS-C15 possessed a typical polysaccharide structure. NMR displayed that EPS-C15 structure is → 3)α-d-Glcvi (1 → 3)α-d-Xylv (1 → 6)α-d-Glciv(1 → 4)α-d-Glc(1 → 3)β-d-Man(1 → 2)α-d-Glci(1 → . EPS-C15 scavenged DPPH and ABTS free radicals with 50.3% and 46.4% capacities, respectively. Results show that the antiproliferative activities of EPS-C15 revealed inhibitions of 49.7% and 88.1% against MCF-7 and Caco-2 cells, respectively. EPS-C15 has antibacterial properties that inhibited Staphylococcus aureus (29.45%), Salmonella typhimurium (29.83%), Listeria monocytogenes (30.33%), and E. coli O157:H7 (33.57%). The viscosity of EPS-C15 decreased as the shear rate increased. The rheological properties of the EPS-C15 were affected by changes in pH levels and the addition of salts. EPS-C15 is a promising biomaterial that has potential applications in various industries, such as food, pharmaceuticals, and healthcare.

Natural convection of hybrid nanofluid with magnetic and thermal effects over an inclined needle

Hybrid nanofluids have several potential applications in various industries, including electronics cooling, automotive cooling systems, aerospace engineering, and biomedical applications. The primary goal of the study is to provide more information about the characteristics of a steady and incompressible stream of a hybrid nanofluid flowing over a thin, inclined needle. This fluid consists of two types of nanoparticles: non-magnetic nanoparticles (aluminium oxide) and magnetic nanoparticles (ferrous oxide). The base fluid for this nanofluid is a mixture of water and ethylene glycol in a 50:50 ratio. The effects of inclined magnetic fields and joule heating on the hybrid nanofluid flow are considered. The Runge-Kutta fourth-order method is used to numerically solve the partial differential equations and governing equations, which are then converted into ordinary differential equations using similarity transformations. Natural convection refers to the fluid flow that arises due to buoyancy forces caused by temperature differences in a fluid. In the context of an inclined needle, the shape and orientation of the needle have significantly affected the flow patterns and heat transfer characteristics of the nanofluid. These analyses protest that raising the magnetic parameter results in an increase in the hybrid nanofluid thermal profile under slip circumstances. Utilizing the potential of hybrid nanofluids in a variety of technical applications, such as energy systems, biomedicine, and thermal management, requires an understanding of and ability to manipulate these effects.

A user review data-driven supplier ranking model using aspect-based sentiment analysis and fuzzy theory

Background:The supplier selection problem is a sophisticated decision-making process that involves evaluating multiple factors. While previous research has primarily focused on objective attributes, such as supplier qualifications, product quality, and price, the subjective opinions of users have often been overlooked. However, with the growing importance of user reviews and sentiment analysis in e-commerce, incorporating users’ opinions on supplier products can provide valuable insights. Purpose:This study aims to address the limitations of existing supplier selection approaches by proposing a comprehensive framework that integrates aspect-level sentiment analysis and a fuzzy multi-attribute decision model. The goal is to enhance the decision-making process by considering both objective attributes and subjective opinions. Methods:To achieve this, we develop a novel convolutional neural network (CNN) model with a gating mechanism to perform aspect-level sentiment analysis. Furthermore, we propose a fuzzy multi-attribute decision model that combines the predefined sentiment aspects with traditional evaluation criteria. The model is applied to a dataset specifically designed for automotive component supplier selection. Results:Experimental results demonstrate the superior performance of our approach compared to existing methods and datasets. A case study demonstrates the combination of aspect-level sentiment analysis and the fuzzy decision model allows for a more comprehensive evaluation of suppliers. Conclusion:By integrating aspect-level sentiment analysis and the fuzzy multi-attribute decision model, our proposed framework offers a novel perspective on supplier selection problems. The results highlight the feasibility and superiority of our approach, providing valuable insights for management in making informed decisions. This research contributes to the fields of supplier selection, sentiment analysis, and decision-making, with potential applications in various industries beyond the automotive sector.

Understanding hot deformation behavior and microstructural evolution in a novel Fe50(CoCrMnNi)50 medium entropy alloy

This study investigates the hot deformation behavior and microstructural evolution of a novel medium entropy alloy subjected to low strain rates and temperatures ranging from 650 °C to 850 °C. The alloy was subjected to hot compression testing under various conditions to observe its response. At all deformation condition, discontinous dynamic recrystallization was the main restoratory mechanism. After full recrystallization, grain sizes ranged from 1 to 5 μm, accompanied by an average hardness of 250 HV. The flow curves demonstrated a typical three-stage work hardening behavior across all deformation conditions, indicative of dynamic recrystallization. It is found that the deformation activation energy (Q) exhibited a negative slope with increasing strain, with an average value of Q = 267.7 kJ/mol. Zener-Hollomon parameter was determined from the experimental results and effectively used to simulate deformation, demonstrating good agreement with experimental findings. Remarkably, following the initial cycle of recrystallization, the deformation process shifted towards grain boundary sliding instead of secondary recrystallization, displaying characteristics reminiscent of superplastic behavior. Further analysis revealed a high strain rate sensitivity (m > 0.3) at 750 °C and 850 °C, with grain sizes lower than anticipated values. In summary, this study provides a comprehensive understanding of the hot deformation behavior and microstructural evolution in the Fe50-(CoCrMnNi)50 alloy. The findings shed light on dynamic recrystallization, deformation activation energy, and the unexpected shift to grain boundary sliding. These insights are valuable for advancing the knowledge of medium entropy alloys and their potential applications in various industries.

Film-shaped reusable smart polymer to produce lactose-free milk by simple immersion

In this study, we report the synthesis and characterization of a highly manageable polyacrylic film material for enzyme immobilization, using β-galactosidase (β-gal) as a model enzyme. The material is based on commercially available monomers and achieves efficient immobilization of β-gal through the formation of azo linkages between amino styrene groups in the polyacrylic material and the enzyme. The immobilized enzyme demonstrates superior performance compared to free enzyme in lactose hydrolysis of UHT milk, achieving lactose concentrations below 0.1% (<1 mg/mL), indicating its potential for lactose hydrolysis in dairy products. The film-shaped material is designed for easy submersion and removal, similar to a smart card, and offers reusability, with the ability to be reused at least 10 times without loss of enzymatic activity. Characterization of the immobilized enzyme on the polymeric material was performed using various techniques, including scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FT-IR), and Raman spectroscopy. Protein release studies confirmed the stability of the immobilized enzyme during prolonged incubation in aqueous solution without significant enzyme leakage. Overall, the polyacrylic film material demonstrates promise as a simple and efficient approach for enzyme immobilization, with potential applications in various industries, including the food industry.

Intensification and techno-economic analysis of a biocatalytic process for coniferol production from ferulic acid: An innovative strategy for lignin valorization

Coniferol, as a natural monolignol, acts as a chemical building block for various high-value compounds. However, the current petrochemical synthesis of coniferol and its limited scalability raise environmental and cost concerns. A biocatalytic method for coniferol production from its natural precursor, ferulic acid, was previously developed using an engineered cell factory that co-expresses carboxylic acid reductase and aldo-keto reductase. The present study focused on investigating the limiting factors of coniferol production and optimizing the process using the design of experiments and fed-batch approaches. By introducing novel parameters, including an inoculum of 0.25 g/L cells and a starting concentration of 5.0 mM ferulic acid, followed by two fed-batch additions of 2.0 mM ferulic acid and 3.7 g/L glycerol, coniferol production was enhanced by a factor of 2 (reaching 1.6 g/L). The scale-up process in a 1 L bioreactor and its intensified technical and economic analysis demonstrated its cost-effectiveness. Considering two different purchase prices for the ferulic acid of $5.0 and $650.0 per kg, the payback time was estimated at 3.3 and 3.2 years, respectively, and the minimal selling price of coniferol to obtain a IRR of 30% was calculated as $4.2 and $5.0 per gram, which is significantly lower than the current market price. In conclusion, the findings illustrate a biocatalytic approach for producing valuable compounds with potential applications in various industries, including cosmetics and pharmaceuticals. Furthermore, this approach contributes to developing sustainable and profitable biorefinery processes, paving the way for future initiatives focused on biocatalytic lignin valorization.

Recovery of superbase ionic liquid using aqueous two-phase systems

Aqueous two-phase systems (ATPS) have been widely used for the purification and separation of biomolecules. However, recent studies have shown that ATPS can also be effective in the purification and recovery of other compounds, such as ionic liquids (IL). Here, we investigated the liquid-liquid phase equilibria of ATPS consisting of 5-methyl-1,5,7-triaza-bicyclo[4.3.0]non-6-enium acetate ([mTBNH][OAc]) and potassium salts (K2CO3 and K3PO4) at 293.2 K and 323.2 K. Our results indicate that both systems exhibited a high IL partition coefficient (k), exceeding 9.5, and achieved a 99.5% recovery of ionic liquid. Moreover, we found that the presence of potassium salt in the ionic liquid-rich phase had a negative impact on the IL cellulose dissolution capability. Therefore, we investigated the removal of potassium salt from the IL and successfully achieved it by using a nanoporous sodium zirconium cyclosilicate (ZS-9 or AV-13). Overall, our study suggests that ATPS can be a promising technique for the purification and recovery of ionic liquids, with potential applications in various industries.

Cloning, expression, and biochemical characterization of β-etherase LigF from Altererythrobacter sp. B11

Lignin, a complex heteropolymer present in plant cell walls, is now recognized as a valuable renewable resource with potential applications in various industries. The lignin biorefinery concept, which aims to convert lignin into value-added products, has gained significant attention in recent years. β-etherases, enzymes that selectively cleave β-O-4 aryl ether bonds in lignin, have shown promise in lignin depolymerization. In this study, the β-etherase LigF from Altererythrobacter sp. B11 was cloned, expressed, purified, and biochemically characterized. The LigF-AB11 enzyme exhibited optimal activity at 32 °C and pH 8.5 when catalyzing the substrate PNP-AV. The enzyme displayed mesophilic behavior and demonstrated higher activity at moderate temperatures. Stability analysis revealed that LigF-AB11 was not thermostable, with a complete loss of activity at 60 °C within an hour. Moreover, LigF-AB11 exhibited excellent pH stability, retaining over 50 % of its activity after 1 h under pH conditions ranging from 3.0 to 11.0. Metal ions and surface impregnation agents were found to affect the enzyme's activity, highlighting the importance of considering these factors in enzymatic processes for lignin depolymerization. This study provides valuable insights into the biochemical properties of LigF-AB11 and contributes to the development of efficient enzymatic processes for lignin biorefineries. Further optimization and understanding of β-etherases will facilitate their practical application in the valorization of lignin.

Computational insights into deep eutectic solvent design: Modeling interactions and thermodynamic feasibility using choline chloride & glycerol

To address climate change and environmental concerns, the chemical process industries are increasingly adopting green technology and exploring eco-friendly waste management practices. Deep Eutectic Solvents (DES) have emerged as promising green solvents with diverse applications in the industries in separation processes, catalysis, drug design, and a lot more. However, the ideal way for modeling ionic interactions within the hydrogen-bond acceptor (HBA) during DES synthesis remains uncertain, and theoretical insight on the formation mechanism of energetically stable DESs from choline chloride (CHL) and urea (URE) is yet to be explored. In this study, we investigate different modeling approaches (no bond, generic bond, or single bond) for ionic interactions in hydrogen-bond acceptor (HBA) molecules during DES synthesis and the thermodynamic feasibility of forming an energetically stable DES using choline chloride (CHL) and urea (URE) through theoretical calculations (PM3, HF, and DFT). Our findings indicate that the choice of modeling approach does not significantly affect the outcomes across calculation levels. The H-X DES formation pathway emerges as the most viable route for CHL: GLC DES synthesis, offering strong binding energy and high exothermicity. This pathway provides a robust solution for synthesizing energetically stable DES with potential applications in various industries. Researchers can consider alternative calculation levels when DFT becomes cost-prohibitive to optimize computational costs. Our study contributes valuable insights into DES design and synthesis, promoting environmentally sustainable and cost-effective processes.

Mechanical & metallurgical properties of dissimilar joining of P91 ferritic steel: A review

Dissimilar joints of P91 ferritic steel and other materials had been widely studied for their potential applications in various industries. The mechanical and metallurgical properties of these joints can be affected by various factors such as the microstructure, composition, and thermal treatment of the materials being joined. The welding techniques and the heat affected zone playing a important role in the properties of the joints. The main concern when joining these dissimilar materials is the interface reaction and stress corrosion cracking. The hardness, tensile strength, fatigue strength, creep strength, and impact toughness of the joints are also important properties that need to be considered. The brittle fracture and diffusion bonding are also important factors that affect the mechanical and metallurgical properties. Tungsten Inert gas welding, resistance spot welding, Laser welding, Electron Beam welding, and other welding techniques have been used for joining P91 ferritic steel and other materials. The properties of the joints produced using these techniques must be thoroughly evaluated to ensure their suitability for specific applications. This review paper is focused mainly on the dissimilar joining of the P91 Ferritic steel its mechanical, corrosion properties and microstructure.

Numerical study on the anisotropy in thermo-fluid behavior of triply periodic minimal surfaces (TPMS)

Porous structures are frequently utilized as thermal conductivity enhancers in the realm of heat transfer enhancement. Triply Periodic Minimal Surface (TPMS) has gained significant attention in recent years due to its favorable performance in many fields including mechanics and thermodynamic. The exceptionally large specific surface area grants it promising performance in heat transfer enhancement. However, the angular effect on thermal-fluid characteristics are not understood and requires further investigation. In this work, Gyroid and Diamond with various rotating angles used as sandwich cores were designed utilizing the implicit function method. Then, the discussions on thermal and hydraulic behaviors in the TPMS-based sandwich panels under an isothermal condition were systematically conducted by means of computational fluid dynamics. After that, the fluid flow mechanisms and heat transfer properties were visually investigated according to the comparative analysis of velocity fields, pressure drops, vortices inducing, and Nusselt number distribution. The results showed that the flow field characteristics and the heat transfer performance exhibited an apparent 45° symmetry in both Gyroid and Diamond. Moreover, the pressure gradient exhibited evident dependence on the rotating angle in both Gyroid and Diamond groups. The 45° rotated Gyroid structure case had the most extensive pressure gradient of 11.4 kPa/m; to the contrary, the 45° rotated Diamond structure had the smallest one of 9.9 kPa/m in their respective group. Nonetheless, the angular difference in heat transfer rate (HTR) is not significant, and the maximum total HTR in Gyroid and Diamond groups was 8.25 W and 9.43 W, respectively. Overall, this work contributes to a better understanding of the angular behavior of TPMS-based sandwich panels and provides valuable information for their potential applications in various industries.

Fabrication and characterization of superhydrophilic graphene-based electrospun membranes for efficient oil-water separation

This research article investigates the fabrication of superhydrophilic graphene-based electrospun membranes for efficient oil-water separation. The study utilizes cellulose acetate (CA) as the base material for membrane fabrication, employing an electrospinning technique followed by the electrohydrodynamic atomization of graphene oxide (GO) to enhance their hydrophilicity. The surface morphology, water contact angle, and Fourier Transform Infrared (FTIR) spectra of the fabricated membranes were analyzed to assess their properties. The membrane characterization techniques revealed the successful integration of GO nanosheets on the surface of the highly porous interconnected nanofibrous matrix. The modified membranes exhibited superhydrophilicity and underwater oleophobicity. The water contact angle of the optimized GO-based electrospun CA membrane was reduced from 110° to zero within 3 s. The performance of the membranes was evaluated through oil-water separation experiments using different types of oils (such as toluene, n-decane, and hexane) in water. The results demonstrated that the graphene-based optimized membranes exhibited high separation efficiency (3820 LMH), with a water permeation flux as high as 65.5 % compared to CA membranes (2308 LMH). The efficiency of separation while using all three different oils with DI water was calculated to be >99.9 %. The study provides valuable insights into the use of graphene-based membranes for oil-water separation and highlights the potential of the electrohydrodynamic atomization technique for the surface modification of membranes. The developed membranes have great potential applications in various industries, including oil and gas, chemical, and wastewater treatment.

Formation and structural features of micelles formed by surfactin homologues.

Surfactin, a group of cyclic lipopeptides produced by Bacillus subtilis, possesses surfactant properties and is a promising natural and biologically active compound. In this study, we present a comprehensive characterization of surfactin, including its production, chromatographic separation into pure homologues (C12, C13, C14, C15), and investigation of their physicochemical properties. We determined adsorption isotherms and interpreted them using the Gibbs adsorption equation, revealing that the C15 homologue exhibited the strongest surface tension reduction (27.5mN/m), while surface activity decreased with decreasing carbon chain length (32.2mN/m for C12). Critical micelle concentration (CMC) were also determined, showing a decrease in CMC values from 0.35mM for C12 to 0.08mM for C15. We employed dynamic light scattering (DLS), transmission electron microscopy (TEM), and density functional theory (DFT) calculations to estimate the size of micellar aggregates, which increased with longer carbon chains, ranging from 4.7nm for C12 to 5.7nm for C15. Furthermore, aggregation numbers were determined, revealing the number of molecules in a micelle. Contact angles and emulsification indexes (E24) were measured to assess the functional properties of the homologues, showing that wettability increased with chain length up to C14, which is intriguing as C14 is the most abundant homologue. Our findings highlight the relationship between the structure and properties of surfactin, providing valuable insights for understanding its biological significance and potential applications in various industries. Moreover, the methodology developed in this study can be readily applied to other cyclic lipopeptides, facilitating a better understanding of their structure-properties relationship.

Improving Tire Specification Character Recognition in the YOLOv5 Network

The proposed method for tire specification character recognition based on the YOLOv5 network aimed to address the low efficiency and accuracy of the current character recognition methods. The approach involved making three major modifications to the YOLOv5 network to improve its generalization ability, computation speed, and optimization. The first modification involved changing the coupled head in YOLOv5 to a decoupled head, which could improve the network’s generalization ability. The second modification proposed incorporating the C3-Faster module, which would replace some of the C3 modules in YOLOv5’s backbone and head and improve the network’s computation speed. Finally, the third modification proposed replacing YOLOv5’s CIoU loss function with the WIoU loss function to optimize the network. Comparative experiments were conducted to validate the effectiveness of the proposed modifications. The C3-Faster module and the WIoU loss function were found to be effective, reducing the training time of the improved network and increasing the mAP by 3.7 percentage points in the ablation experiment. The experimental results demonstrated the effectiveness of the proposed method in improving the accuracy of tire specification character recognition and meeting practical application requirements. Overall, the proposed method showed promising results for improving the efficiency and accuracy of automotive tire specification character recognition, which has potential applications in various industries, including automotive manufacturing and tire production.

Soret and Dufour effects on MHD mixed convection flow of Casson hybrid nanofluid over a permeable stretching sheet

The use of hybrid nanofluids can improve the engine operation and fuel efficiency in automotive engineering, as well as the efficiency of cooling systems used in food processing and preservation. This study provides insight for the development of efficient heat exchangers, thermal energy storage systems and cooling systems for various industrial applications, which can improve product quality and safety. The study aims to investigate the Soret and Dufour effects in hybrid nanofluid flow, with the goal of understanding their behaviour and potential applications in various industries. The flow is over a vertically stretched permeable sheet with porous material under convective boundary conditions and a non-uniform heat source/sink. The reduced governing equations are represented by non-linear-coupled ordinary differential equations solved by means of the shooting method based on the fourth-order Runge–Kutta method. Enhancing the Casson parameter reduces the fluid velocity while enhancing the mass and thermal Grashof numbers increases the flow velocity. The Soret and Dufour effects improve temperature and concentration, and a higher Biot number increases the temperature. The novelty of this investigation lies in its incorporation of Soret and Dufour effects, porosity, heat source/sink and a more refined definition of nanoflow, which is compared to previous results.

Linear Diophantine fuzzy sets over complex fuzzy information with applications in information theory

This article aims to link AG-groupoids and complex fuzzy set theory by constructing a method to rank complex fuzzy information, provide an alternative definition of CLDFS, and an algorithm for data encryption/decryption using AG-groupoids. Achieving these objectives would enable effective handling of complex and ambiguous data and a novel approach to data security with potential applications in various industries. The authors introduce new operations and laws to explore the structural properties of CLDFS, including applying the inverse discrete Fourier transform of a CLDFS to identify a reference signal and characterizing right regular ordered AG-groupoids in terms of CLDF-score right ideals. They also demonstrate an application of utilizing an AG-groupoid as a symmetric key for encryption/decryption and CLDF-score right ideals of an ordered AG-groupoid to select a suitable signal for system analysis.

ІНТЕЛЕКТУАЛЬНИЙ АНАЛІЗ ВЕБКОНТЕНТУ ДЛЯ ФОРМУВАННЯ СОЦІАЛЬНО-ЦИФРОВОЇ ІДЕНТИЧНОСТІ ВЕБКОРИСТУВАЧА

The article discusses the growing need to analyze and understand web user behavior due to the unprecedented amount of digital content being generated and distributed on the Internet. Web content intelligence is presented as an effective way to explore and extract valuable information from online content, including websites, social media platforms, and other digital sources, to better understand web users' interests, preferences, and behaviors. The ability to identify web users based on their online behavior is important for industries such as marketing, psychology, and law enforcement. However, there are certain problems associated with this approach, such as ensuring the privacy and security of web users’ data, as well as assessing the accuracy and reliability of web content analysis tools. The purpose of the article is to review the current state of web content analysis, its potential applications in various industries, and its role in shaping the digital future. The article emphasizes the importance of an interdisciplinary approach to the study of virtual identification and self-presentation in online communities, taking into account the socio-demographic characteristics of a web personality involved in social interactions. The article also explores the latest trends and developments in the field of web data mining, including web content analysis, web structure analysis, web page usage analysis, and social media data analysis. A software solution for conducting intelligent analysis of web content is proposed to form a social and digital identity of a web user using a specialized dictionary of content markers of a web community member.