2025-10-27
Nuklukaba Longkumer, Ardhendu Sekhar Khound
The investigation explains the mixed convective Casson fluid flow behavior passed an exponentially stretching porous surface in the presence of radiation and chemical reaction under the influence of mixed convection. Perpendicular to the flow a uniform magnetic field Bo is applied. The controlling equations are mathematically turned into ordinary differential equations by implementing appropriate similarity transformations. The MATLAB built-in bvp4c approach is then used to solve the equations numerically. The results are graphically examined for a range of flow parameter values. Special attention is paid to how the mixed convection parameters (Gr/(Re^2) and Gc/(Re^2)) affect entropy production, as well as how the magnetic parameter (M) affects the temperature profile of the system. We have demonstrated that the mixed convection parameters and magnetic parameter have a positive impact on the entropy and temperature of the system, respectively. The increase of 200 % (approximately) in (Gr/(Re^2) and Gc/(Re^2)) there is an increment in the entropy by 113 % (approximately) and 84 % (approximately), respectively. Also, with the increase of 400 % (approximately) in magnetic parameter (M) there is an increase of 34 % (approximately) in the temperature profile.
2025-10-27
K.S. Yamuna, Sanjeev Sharma, R.J. Anandhi, B. Sangeetha, S. Sivakumar
Lung sound analysis has emerged as a promising non-invasive method for the early detection and diagnosis of pulmonary diseases. However, the presence of noise, such as ambient sounds, heartbeats, and motion artifacts, often distorts the lung sounds, making accurate diagnosis challenging. This study aims to address these challenges by proposing a novel approach for pulmonary disease classification through the analysis of lung sounds using machine learning algorithms. In this research, the lung sound signals are denoised using an Adaptive Variational Mode Decomposition (AVMD) technique. Additionally, a novel multifractal detrended fluctuation analysis (MFDFA)-based feature extraction method is proposed to enhance the analysis of lung sounds. Machine learning algorithms, specifically K-Nearest Neighbors (KNN) and Random Forest classifiers, are then employed to detect lung diseases. The study utilizes the publicly available ICBHI 2017 challenge database for analysis. Results indicate that the Random Forest classifier outperforms other models, achieving an accuracy of 99.10 %, precision of 96.15 %, and specificity of 98.75 %. These findings suggest that the combination of AVMD-based denoising, MFDFA-based feature extraction, and machine learning classification significantly enhances the performance of pulmonary disease diagnosis, offering a reliable and efficient tool for clinical applications.
2025-07-15
María Fernanda Laborde, Mariana Belén Laborde, Yanina Soledad Suarez, Ana María Pagano
Food industries aim to optimize processes for quality products in shorter times. For fruits, specific storage and transport conditions are essential to maintain quality, extend shelf life, and preserve sensory and nutritional properties. This study aims to maximize honey incorporation into banana slices during osmotic dehydration, assisted by ultrasound, while minimizing processing time. The process includes three stages: 1) 20 min ultrasound-assisted immersion in distilled water, 2) osmotic dehydration in hypertonic honey solution, and 3) hot air drying. The second and third stages were mathematically modeled using a multi-objective MINLP optimization in GAMS with the Baron solver. Optimal conditions achieved an 8.75% gain in soluble solids (SG) in 11.48 h, reducing processing time by 64% with a 70% honey solution. This optimization allows a compromise solution between two contradictory objectives for planning the production process: maintaining product quality and reducing production time. The process leads to lower total costs.
2025-07-15
Fladna Moura, Angela Figueiredo, Suélen M de Amorim, Joel G Teleken, Jhony T. Teleken
This study aimed to apply a numerical/experimental approach to determine the moisture diffusion coefficient in chickpeas during the soaking and cooking processes, considering the seed swelling. The mathematical model combines Fick's second law to describe moisture transfer with the Peleg model to describe the expansion of the seed. It was solved numerically using finite differences method and fitted to experimental data of hydration kinetics at different temperature conditions (26, 40, 50, 63, 74, and 86 ºC). The numerical results showed that the D-values estimated considering deformable seeds were around 25-30 % greater than those estimated considering non-deformable seeds. This modeling approach could be useful in analyzing legumes' soaking and cooking process, but further studies are necessary to confirm its efficacy in different seed types and experimental conditions.
2025-07-15
Leandro Nicolás Bengoa, Paola Pary, Pablo Ricardo Sere, María Susana Conconi, José Fernando Bengoa, Walter Alfredo Egli
An eco-friendly alkaline glutamate-based electrolyte was used to produce copper-carbon nanotubes composite coatings with improved tribological properties. Experiments were performed at different current densities to deposit pure Cu, Cu-CNT and Cu-activated CNT coatings. The electrolyte was agitated by low frequency ultrasound to disperse the particles and consequently, help their incorporation in the Cu matrix. The coatings were characterized by SEM and XRD. The wear resistance and coefficient of friction were evaluated with tribological tests. Cu-CNT and Cu-activated CNT composites were successfully produced with improved tribological properties respect to those of pure Cu. It was found that the codeposition modified the morphology of the coatings as well as their crystallographic orientation. These modifications were more noticeable when the CNT were activated by acid-treatment.
2025-07-15
Cagin Bolat, Ilker Gur, Abdulkadir Çebi
In recent years, parallel to the new industrial trends, the applicability of novel artificial neural network systems and machine learning techniques in the manufacturing and metallurgy sectors has risen due to the increasing competitiveness among steel, pipeline, and construction firms. This work focuses on estimating the hardness of high-carbon martensitic stainless steels depending on the heat treatment media, austenitizing temperature (AT), and secondary annealing temperature using different machine-learning methodologies for the first time in the literature. The attained outcomes indicated that the highest average hardness level was found in the medium-level tempering temperature and low AT in brine. As the tempering temperatures rose to the upper limits, measured hardness results diminished in both quenching media. Besides, according to all fold types and error metrics, the random forest (RF) machine-learning model was the strongest approach to estimate the final hardness values of the heat-treated samples whereas the Bayesian ridge (BR) was the poorest way.
2025-07-15
Ayca Gülhan, Oguz Çakir, Cihan Dusgun, Mehmet Fuat Gülhan
Edible flowers, demanded by consumers for their distinct sensory properties and health benefits, have a short shelf life. This study aimed to apply the brine method to extend the shelf life of zucchini ( Cucurbita pepo L.) flowers, one of the edible flowers. The phytochemical profile of the samples was determined using LC-MS/MS, a method that allows the amount of 56 different phytochemicals to be determined. In this context, zucchini flowers were stored in brines containing 5% and 10% NaCl for the 7th, 14th, 21st and 28th days. The highest antioxidant activities were found in DPPH (19.23±0.74 mgTE/g extract) and CUPRAC (181.43±1.08 mmol Trolox Eq/g) on the 7th day of brining at 10% salt concentration. The highest TPC (32.10±0.33 mg GAE/g) was determined on 7th day of brining and at 10% salt concentration. The dominant phytochemicals were determined as quinic acid, fumaric acid, protocatechuic acid, 4-OH-benzoic acid, routine, hesperidin, isoquercitrin, nicotifluorine, quercetin and kaempferol at 10% salt concentration on the 7th and 14th days. This study demonstrates that the brine method can be used as an appropriate processing technology to extend the shelf life of zucchini flowers and also to broaden their application. Additionally, the findings of this study contributed to optimizing the storage time and salt concentration of brined zucchini flowers. It is thought that brined flowers can gain a place in the market as a commercial food product .
2025-07-15
M. Karthikraja, P. Kalidoss, S Anbu, P. Prabakaran
The manufacturing industry has thoroughly Examined the use of cutting fluids improved by nanotechnology that have higher heat conductivity to increase the efficiency of drilling operations. Due to their diverse physical & chemical characteristics and environmental compatibility, ionic liquids show significant promise for use as cutting fluids. This study examines how well different combinations of ionanofluids with nanoparticles perform as cutting fluids in drilling, by analyzing heat transfer through computational fluid dynamics and Ansys Fluent software. The thermal properties of a mixture containing TiO 2 , Al 2 O 3 , and Multi-walled carbon nanotube (MWCNT) nanoparticles are studied by mixing them with the ionic fluid 1-ethyl-3-methylnidazolium tetra-fluoroborate at various Reynolds numbers and particle volume fractions. Inconel 718 titanium alloy is used to make the workpiece, and tungsten carbide-cobalt is used to make the drill bit. The drilling temperature of the pure ionic liquid decreases by 23.18% with the addition of MWCNT and ionic coolant. While the particle volume (%) remains higher. For pure ionic coolant, the Al 2 O 3 , TiO 2 , and MWCNT ionanofluids improve the mean heat transfer coefficient by 33.44%, 44.32%, and 59.05%, respectively. When it comes to thermal efficiency and rate of heat dissipation, MWCNT nanocoolants outperformed Al 2 O 3 and TiO 2 ion nanocoolants.
2025-04-10
Huseyin Gençcelep, Aksel Aksel Efe, Abdullah Kurt
The aim of this study was to investigate the quality of beef sausages containing mushroom ( Agaricus bisporus ) powder (MP) with varying rates (0, 0.5, 1.0, and 1.5 %) under cold storage for 60 days. In particular, the study focused on changes to the jelly and fat separation (JFS) of sausage batter, as well as chemical, lipid oxidation, color, and sensory characteristics in the final product. The incorporation of MP resulted in a decline in the JFS, with the most notable reduction occurring at 1.5 % MP, from 10.92 to 7.67 % within the batter. The protein content of the sausage increased from 13.46 % to 15.76 % with the addition of 1.5 % MP. The pH level, which was elevated due to the existence of basic amino acids in MP, decreased during the storage period and reached a pH value comparable to that of the control. The considerable rise in thiobarbituric acid reactive substances (TBARS) observed in the control sausages showed a marked decrease throughout the storage period in the sausages to which MP had been incorporated. Additionally, these sausages exhibited a lower free fatty acid content than the control.
2025-04-10
Esra Sik, Gorkem Ozulku
Wheat bran (WB) has gained significant importance since containing some valuable nutritional compounds, predominantly dietary fibers (DFs). The aim of this study was to compare the brans of two different bread wheat cultivars from grain to bread in order to evaluate the effects of their chemical, functional and bioactive properties on bread making quality. Therefore, two different wheat cultivars obtained from Thrace region of Turkiye, named Tekirdag and Rumeli. These wheat grains were similar in terms of thousand grain weight, hectoliter weight, protein, and gluten content while gluten index and Zeleny sedimentation value of Rumeli wheat cultivar were higher ( p < 0.05). After milling wheat grains, the composition of WBs were determined and significant differences were observed except for moisture and protein content. Rumeli WB contained higher insoluble and total DF, leading to have higher total water retention capacity (T-WRC). Lower T-WRC of Tekirdag WB provided to have a better bread making quality than Rumeli WB since showing higher specific volume ( p < 0.05). The breads produced from these WBs were similar in terms total phenolic content (TPC) and antioxidant properties although there were significant differences between WBs in terms of TPC and antioxidant activity ( p < 0.05). The results of this study are suggestive in assessing the properties of WB from different cultivars for bread quality. It was indicated that some WB characteristics such as total DF content and T-WRC showed their effects on bread making while bioactive properties of WBs were not able to maintain in corresponding breads.
2025-04-10
Ammar Al-Maliki, Moharam Habibnejad Korayem
The paper refers to deriving dynamic equations of motion and applications to obtain dynamic load-carrying capacity (DLCC) for bipedal robots walking. The governing equations for determining the DLCC of a given end-effector trajectory are presented at the beginning. Then via an algorithm for finding the greatest load value, the DLCC for a specified trajectory is obtained for a biped robot for the curve path.10 degrees of freedom (DOF) biped is used, and a kinematic and dynamic model for this robot was obtained. Under these conditions of research, the main limiting factor to calculating the maximum allowable load for a prescribed dynamic trajectory is the constraint of the torque actuator. At the same time, the biped robot walking dictates the need for additional constraints, that is, the stability constraints of the robot. The actuator torque constraint of the joints was formulated in this study depending on typical (torque-speed) characteristics of DC motors. The study also considers the jerk limits, an important constraint in a robotic system's dynamic motion and trajectory planning. A strategy to calculate DLCC subjected to these limitations above-mentioned is formulated. Given an arbitrary path, a general computational technique for a 10 DOF biped robot case is laid out in detail. The results showed that the value of the maximum allowable load when the end-effector moved in a curve path was 0.702 kg. The path describes the strategy of dynamic motion by controlling dynamic forces on the robot's joints where the lower values of dynamic forces lead to decreasing energy consumption, which means an increased ability to lift larger loads. Lastly, the simulation results were validated by implementing an experimental biped robot.