This study comparatively evaluated the physicochemical properties, color parameters, water and oil holding capacities, bulk densities, total phenolic contents, and antioxidant activities of orange blossom powder (OBP) and chamomile flower powder (CFP). OBP exhibited a higher total phenolic content (9.30 mg GAE/g) compared with CFP (2.81 mg GAE/g), whereas CFP demonstrated stronger antioxidant activity, reflected by its lower IC₅₀ value (0.54 mg/mL) relative to OBP (0.82 mg/mL). Color measurements indicated that CFP had higher b, hue, and chroma values, indicating more intense yellow pigmentation, while the higher a value of OBP was consistent with red–orange pigment characteristics. Differences in water and oil holding capacities and bulk densities supported the distinct techno-functional behaviors of the two powders. Overall, the results highlight the distinct techno-functional and bioactive characteristics of OBP and CFP, demonstrating their potential as natural functional ingredients for the development of health-oriented and value-added food products.
This study evaluated the impact of incorporating Rheum ribes L. (Işkın) at different levels (5–20%) on the chemical, functional, structural, and sensory properties of tarhana. The incorporation of Rheum ribes L. exerted a pronounced influence on the compositional and functional attributes of the tarhana formulations. Notably, substantial elevations were detected in total phenolic content and overall antioxidant capacity, accompanied by significant increases in key bioactive constituents such as gallic acid, caffeic acid, ferulic acid, quercetin, luteolin, and catechin hydrate (p < 0.05). Parallel to these biochemical enhancements, the levels of essential minerals including potassium, magnesium, calcium, and phosphorus also rose markedly following enrichment. Insights obtained from FTIR spectroscopy revealed that Rheum ribes L. supplementation induced meaningful alterations in the interactions among proteins, carbohydrates, and phenolic molecules, indicating a more organized and cohesive structural arrangement within the tarhana matrix. Sensory assessments further demonstrated that formulations containing 10–15% Rheum ribes L. achieved the highest acceptability scores, suggesting that this concentration range offers an optimal balance between nutritional enhancement and sensory integrity. Collectively, these outcomes underscore the potential of Rheum ribes L. fortification to substantially improve the nutritional profile, bioactive composition, and consumer appeal of traditional tarhana, thereby reinforcing its value as a promising functional fermented food.
This paper presents a numerical study on the enhancement of heat transfer in a solar air heater (SAH) duct using winglet-type longitudinal vortex generators (WLVGs). Delta (DW), trapezoidal (TW1, TW2), and rectangular (RW) winglets are examined in pointing-up (PU) and pointing-down (PD) orientations, with the span-wise spacing ratio (S/H) varied to determine the optimal layout (S/H = 1.43, b/H = 0.50). Computational Fluid Dynamics (CFD) simulations using the GEKO turbulence model in ANSYS Fluent are performed for Reynolds numbers (Re) ranging from 5,000 to 22,500. Flow structures are analysed via Q-criterion isosurfaces, Nusselt number distributions, and streamwise vorticity contours. Results show that PU orientations generally outperform PD due to closer vortex–wall interaction. The RW configuration exhibits the highest Nusselt number, achieving a maximum Nusselt number of 114.37 at Re = 22,500, primarily attributed to the persistence of its generated vortices. However, it also results in the greatest frictional penalty, with a maximum friction factor of 0.1562 at Re = 5,000 and a corresponding normalized value of 𝑓/𝑓₀ = 5.21 at Re = 22,500. Consequently, the RW configuration yields the lowest thermal enhancement factor (TEF) at high Reynolds numbers, reaching a minimum value of 1.050 at Re = 22,500, despite its strong heat transfer rate. In contrast, the highest TEF is achieved with the PU TW1 configuration (TEF = 1.473 at Re = 5,000), which offers the most favourable balance between enhanced heat transfer and acceptable frictional losses. These results provide design-oriented implications for solar air heater (SAH) systems, identifying PU TW1 as the most energy-efficient configuration, whereas RW may be more suitable for applications where maximizing heat transfer rate is prioritised over minimising frictional losses.
Determination of groundwater potential in the western part of Rezevi Khorasan (Mashhad city), located in the arid and semi-arid region of Iran, has a critical importance in terms of water resources management and sustainable development. The majority of the study area is located on Quaternary alluvium. Vertical electrical sounding (VES) measurements were taken at 51 locations using Schlumberger configuration to determine the hydrogeological characteristics of the region. The evaluation of the VES curves revealed that the area is characterised by four layers. The resistivity values of the first layer, which has a wide resistivity range, vary between (64.3 and 720 Ω m). The resistivity values of the second layer vary between (55.9 and 549 Ω m), the resistivity range of the third layer (50 to 560 Ω m) and the fourth layer (12.9 to 626 Ω m). Dar- Zarrouk parameters were calculated using the resistivity and thickness parameters. Evaluation of the result indicates that the alluvium units that can provide groundwater. The permeability is high in sandy and gravelly units.
In this study, a highly sensitive and selective gas sensor was developed for detecting hazardous analytes, including ethanol, acetone, hydrogen sulfide (H2S), and hydrogen cyanide (HCN). ZnO thin films were deposited as the sensing layer using atomic layer deposition (ALD), while Au interdigitated electrodes with 5 µm width and spacing were fabricated on SiO2/Si substrates via photolithography. The fabricated sensor exhibited a sensitive response to the target gases even at part-per-billion (ppb). However, it was observed that as the operating temperature decreases, the sensor signal's noise level increases. Additionally, the recovery time for the sensor to return to its baseline value after gas exposure was significantly affected by the operating temperature. The detection limits for ethanol, acetone, H2S, and HCN were 14.6, 35, 115, and 115 ppb, respectively, confirming the sensor's ability to detect all analytes at concentrations well below their threshold limit values. Principal Component Analysis (PCA) revealed well-separated clusters for each analyte, particularly for ethanol and acetone, suggesting that the sensor can effectively discriminate between these two gases. These results demonstrate the sensor’s excellent sensitivity and selectivity supporting its potential for real-time monitoring of toxic gases in environmental and industrial applications.
This study investigated the morphological, magnetic, mechanical, and thermal properties of Fe-28.2%Ni-0.5%Ti, Fe-26.8%Ni-1.5%Ti, and Fe-27.6%Ni-4.2%Ti alloys. Scanning Electron Microscope (SEM), Mössbauer Spectrometer, Differential Scanning Calorimetry (DSC), and Vickers hardness were used to determine the physical properties of the alloys. In SEM examinations, a high amount of lath (rod) type martensite formation was observed in Fe-28.2%Ni-0.5%Ti, Fe-26.8%Ni-1.5%Ti alloys. In contrast, in Fe-27.6%Ni-4.2%Ti alloy, lenticular (spindle) type martensite formation with partial twinning was observed in addition to rod (lath) martensites. We determined Mössbauer parameters such as Hyperfine Magnetic Field (Heff), Quadrupole Shift (Q.S), Isomer Shift (I.S), Line Width (W), and percent fraction fields of phases. It has been found that Mössbauer spectra at room temperature are formed by the overlap of two sextet spectra belonging to the ferromagnetic or antiferromagnetic martensite phase and one single spectrum belonging to the paramagnetic austenite phase. We determined morphological change, martensitic transformation start temperature (Ms), austenite phase transformation start temperature (As), and hardness values depending on Ti amount.
This paper presents a novel framework for a decentralized social network that integrates blockchain technology, natural language processing (NLP), and deep learning (DL) to address critical vulnerabilities in traditional centralized online social networks (OSNs). Blockchain ensures data integrity, transparency, and decentralized governance, mitigating risks associated with data manipulation and privacy breaches. Deep learning algorithms, including Bidirectional LSTM for post-category prediction and LSTM for suicide detection, enhance content management by capturing nuanced language cues and identifying distress signals. NLP techniques, such as TF-IDF vectorization and cosine similarity, further improve content originality and moderation by detecting duplicates, preventing plagiarism, and fostering diverse content. This paper also elaborates on the implementation of these technologies, demonstrating how blockchain-based smart contracts manage secure interactions, deep learning models categorize content, and NLP techniques ensure content authenticity. This comprehensive integration of blockchain, deep learning, and NLP offers a transformative approach to social networking, promoting transparency, security, and ethical standards, while creating a safer, more trustworthy digital environment.
With the increasing number of network users, intrusion detection systems (IDS) have become a critical area of focus. The deployment of machine learning (ML)-based systems is crucial due to their ability to learn from data. However, the network data often contains both numerical and categorical features. This presents a significant challenge as some ML algorithms, such as Support Vector Machine (SVM) and k-Nearest Neighbour (kNN), require encoding before using categorical features. Here, we investigate the impact of One-Hot Encoding (OHE) on the classification performance and time complexity of ML algorithms, including Decision Trees (DTs) (which accept categorical features), SVM, kNN, and others. In this study, intrusion datasets such as NSLKDD and UNSWNB15, which contain categorical features, are used. The performance of DTs and other classifiers was compared on encoded and unencoded datasets. Our findings are: (1) OHE can improve the classification performance of DT classifiers, and it does not negatively affect DT classifiers. However, OHE increases the time complexity due to increased dimensionality; (2) comparing the performance of DT with other classifiers showed that DT achieve a comparable performance with less time complexity. (3) OHE can help to transform complex categorical features to eliminate irrelevant categories. The results of this experiment are presented to visualise the importance of the properties of DTs. This study shows that DTs are promising in developing time-efficient and accurate IDS.
Global warming has become a worldwide problem in recent years, and authorities are taking action to overcome this problem. Refrigerants with high global warming potential (GWP) are continuously prohibited, and as a result, ultra-low GWP refrigerants stand out in the heating, cooling, refrigeration, and air conditioning (HVAC-R) industry. This paper presents a theoretical analysis of air-to-air heat pump cycles using 2024 F-Gas regulation-compliant ultra-low GWP refrigerants, including hydrocarbons and transcritical CO2, with three different configurations. Annual energy consumption and total equivalent warming impact (TEWI) values were calculated for three provinces in Türkiye with different climates using bin-hour data. The results were compared in both cooling and heating modes with R410A and R32 cycles as well. Up to 11.7% and 14.5% improvement in annual energy consumption was achieved using parallel compression and booster cycle, respectively. Cycles with booster configuration using R290 and R600a refrigerants achieved the best performance.
The thermal safety of lithium-ion batteries (LIBs) is a crucial challenge for electric vehicles and stationary energy storage systems, as excessive heat generation may cause accelerated aging, capacity loss, or catastrophic thermal runaway (TR). This study develops and validates a coupled electrochemical–thermal model to investigate the heat generation, temperature response, and TR behavior of cylindrical 18650-type LIBs. Experimental discharge tests (1C and 2C) were performed on a 1S14P battery module, and the results were compared with numerical simulations in STAR-CCM+ and an Arrhenius-based TR model implemented in MATLAB Simulink. The model accurately captured the onset of exothermic reactions, with a maximum deviation of ~5% from experimental data. Parametric analyses revealed that higher ambient convection coefficients delay TR initiation and reduce its severity, highlighting the importance of forced-air cooling in thermal management systems. Furthermore, the effect of different enclosure materials on TR propagation was investigated. While ceramic fiber and aerogel provided the most effective thermal insulation, polystyrene demonstrated the best overall balance between heat dissipation under normal operation and insulation during TR events. The findings confirm that material selection and thermal management design play a decisive role in preventing TR propagation and ensuring battery safety. This work contributes practical guidelines for the safe and efficient design of next-generation battery systems.
SCARA robots are widely used in industrial automation due to their high precision and speed, particularly in pick-and-place operations. In addition to conventional programming approaches, alternative vision-based control methods have gained interest to enhance flexibility and efficiency in robotic applications. This study presents the design and implementation of a Position-Based Visual Servoing (PBVS) for the SCARA robot system capable of detecting and manipulating objects in real-time. The proposed system consists of a fixed overhead camera, a SCARA robot, and Python-based control software. The software integrates image processing algorithms, kinematic calculations, and motor control, enabling the robot to autonomously identify objects, compute their positions, and execute pick and place tasks. To enhance object detection accuracy, Kuwahara filtering, Canny edge detection, morphological transformations, and connected component analysis were applied. Experimental results demonstrated that the combination of Kuwahara filtering and Canny edge detection achieved the lowest MSE error (8.45%), ensuring precise object localization. Furthermore, inverse kinematics was employed to generate accurate joint movements, allowing smooth and reliable grasping operations. The system was tested through 100 pick-and-place trials, achieving a 100% grasping success rate when Kuwahara filtering was applied. The experimental findings confirm that vision-based control significantly improves SCARA robot performance, making it suitable for automated assembly, material handling, and quality control applications.
Today’s marine oil spills are causing environmental concerns on a global scale. In order to effectively remove such pollutants, various absorbent materials with two-dimensional (2D) and three-dimensional (3D) structures and super-wetting properties have been developed. However, there are significant difficulties in desorption of the absorbed oil from these materials. The strong adsorption of oil components on the surface of the material limits both the efficiency of sorbent materials and the potential for reuse. In this study, polyurethane (PU) sponge adsorbents coated with different silane agents were fabricated to treat oil spills. Four different types of silanes Polydimethylsiloxane (PDMS), Octadecyltrichlorosilane (ODTCS), Methyltrichlorosilane (MTCS) and Dodecyltrimethoxysilane (DTMS) were used as silane agents. For the prepared test specimens; silane binder ratios of 0.1%, 0.5% and 1% were used in three different ways, respectively. The coating temperatures were 25°C, 40°C and 55°C and the coating times were 15 minutes, 30 minutes and 45 minutes. The contact angles and absorption capacities of the obtained PU sponge adsorbents with water were measured. In addition, their surface morphologies were examined by SEM analysis. The data obtained showed that the best absorption capacity for 81 g was achieved in the coating with PU-MTCS silane agent when 1% silane agent, 25 °C reaction temperature and 30 minutes time were applied.
nula helenium L. (Elecampane) leaves are an underutilized source of natural antioxidants due to their rich phenolic content. Although most studies have investigated roots or other aerial parts, limited information is available on phenolic extraction from I. helenium leaves. This study aimed to optimize the solvent concentrations for phenolic compound extraction from I. helenium leaves using D-Optimal Mixture Design and to evaluate the total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activities of the extracts. Various solvent mixtures (ethanol, methanol, and water) were tested, and the optimal composition was determined as 42.40% ethanol, 0.00% methanol, and 57.60% water. Under these conditions, TPC and TFC were found to be 28.12 mg gallic acid equivalent (GAE)/g dry sample and 27.74 mg quercetin equivalent (QE)/g dry sample, respectively. Antioxidant activities measured by ABTS, DPPH, and FRAP assays were 19.73, 1.42, and 6.10 mg Trolox equivalent (TE)/g dry sample, respectively. These results indicate that I. helenium leaf extracts, with high phenolic content and potent antioxidant activity, represent a promising natural antioxidant source, particularly for applications in the food industry.
Graphene Quantum Dots (GQDs) are gaining significant attention due to their unique optical, electronic, and biocompatible properties, making them ideal candidates for applications in bioimaging, sensing, and drug delivery. This study explores the synthesis of GQDs derived from citric acid (CA), phenylalanine (Phe), and tryptophan (Trp) using a pyrolysis method, where GQDs were synthesized using 2.0 g of CA with varying amounts of Phe (0.75 g, 0.50 g, 0.25 g) and Trp (0.25 g, 0.50 g, 0.75 g), corresponding to GQDs1, GQDs2, and GQDs3, respectively. The influence of precursor composition on the structural, optical, and physicochemical properties of GQDs was analyzed. Particle size measurements showed a hydrodynamic diameter range of 0.89 nm to 1.5 nm, with increasing Trp content leading to larger particles and a broader size distribution, reflected in polydispersity index (PDI) values of 0.221, 0.312, and 0.368 for GQDs1, GQDs2, and GQDs3, respectively. Zeta potential analysis revealed values of -21.4 mV, -12.2 mV, and -7.5 mV for GQDs1, GQDs2, and GQDs3, respectively, indicating reduced surface charge with higher Trp content, which may affect colloidal stability. Optical characterization showed π→π* (~230–270 nm) and n→π* (~300–350 nm) transitions in the UV-Vis spectra, with varying absorbance intensities across samples. Fluorescence spectroscopy confirmed strong emission properties, which were highly dependent on precursor ratios. Quantum yield (QY) values were 32.2%, 95.5%, and 75.6% for GQDs1, GQDs2, and GQDs3, respectively, highlighting the role of nitrogen doping in fluorescence enhancement. These findings demonstrate that controlled precursor composition can fine-tune GQD properties, offering potential for optoelectronic, bioimaging, and sensing applications. Further exploration of functionalization strategies could enhance their practical utility.
The effect of heat treatment (roasting and steaming) of flaxseed on physicochemical properties of mucilage and its potential to use as fat replacer in cake formulation were investigated. Flaxseeds were roasted at 100, 130, 160 °C for 5, 10, 15 min, and steamed for 5, 10, 15 min before mucilage extraction. The highest water-holding capacity (22.6%) and oil-holding capacity (4.2%) were observed in mucilage extracted from flaxseed steamed for 15 min, and roasted for 15 min at 160 °C, respectively. However, heat treatment decreased the foam capacity of the mucilage. The highest emulsion capacity (45.5%) was observed in mucilage from flaxseed roasted at 100 °C for 15 min. Mucilage was used in cake formulation at 50% replacement with fat. Heat-treated flaxseed mucilage significantly increased the cake’s specific volume, with the highest (2.52 cm3/g) was determined in the cake supplemented by 15 min steamed flaxseed mucilage. Steamed flaxseed mucilage resulted in a softer cake texture. Moreover, mucilage from steamed flaxseed generally resulted in lower color differences in cake samples compared to that from roasted flaxseed. The addition of mucilage increased total dietary fiber content of cake samples and decreased their glycemic index values. Steamed flaxseed mucilage resulted in the lowest glycemic index values. Overall, heat-treatment of flaxseed, especially steam treatment, before mucilage extraction results in mucilage with improved functional properties without resulting any adverse effects at 50% replacement with shortening in low-fat cake quality.
In this study, functionally graded (FG) porous materials containing one or more infill patterns and infill rates were designed to fabricate porous materials with high compressive properties. For the FG material design, five types of infill patterns (three 3D infill patterns: octet, gyroid, and cubic; and two 2D infill patterns: trihexagonal and concentric) and two infill rates (50% and 70%) were determined. Utilizing various combinations of different infill rates and infill patterns, a total of 21 FG porous samples and 5 control samples with uniform porous distribution were designed. The samples were produced using the Fused Deposition Modelling (FDM), and the effect of functional grading on the compressive behavior of the porous material was investigated by conducting compression tests using an Instron 8801 testing machine. The highest compressive strength was obtained in the 70%CONS sample, which was functionally graded based on infill rate, with a 54% increase compared to its corresponding control sample. By combining the concentric 2D infill pattern with the gyroid 3D infill pattern, the compressive strength of the designed GY-CONS-GY sample increased by 33% compared to the gyroid sample.
The effects of hydrothermal aging in distilled water (DW) and seawater (SW) environments on the water absorption behavior and crush characteristics of hybrid glass/carbon fiber-reinforced composite pipes with ±55° and ±70° winding angles were evaluated. Specimens were kept for 120 days at 30°C, and water absorption was analyzed experimentally and theoretically. Results revealed that distilled water-aged samples exhibited higher maximum water absorption rates (2.5% for DW55 and 2.62% for DW70) compared to seawater-aged samples (2.37% for SW55 and 2.44% for SW70), attributed to the inhibitory role of ionic components in seawater. Lower winding angles consistently showed greater water absorption due to increased microstructural voids, facilitating water diffusion. Quasi-static axial compression tests demonstrated significant degradation in crush performance after aging. Unconditioned samples with 70° winding angles achieved the highest initial peak load (56.9 kN) and specific energy absorption (28.89 J/g). However, aging reduced these values, with seawater-aged samples (SW55) showing a 12.32% decrease in specific energy absorption compared to unconditioned counterparts. Crushing force efficiency (CFE) also declined, correlating with matrix plasticization and fiber/matrix interface weakening. Notably, hybrid pipes with 55° winding angles exhibited superior energy absorption (30.44 J/g for U55), emphasizing the role of fiber orientation in load distribution.
As the population grows and vehicles are increasingly owned, emissions from fossil fuels are worsening environmental problems. In this context, electric vehicles (EVs) present a significant alternative for the development of sustainable transportation systems. However, for electric vehicles (EVs) to become a prevalent form of transportation, the establishment of an effective and efficient charging infrastructure is imperative. The primary objective of this study is to ascertain the most suitable location for the installation of an electric vehicle (EV) charging station within the Erzincan Binali Yıldırım University Yalnızbag Campus. During site selection, the analytical hierarchy process (AHP) and TOPSIS methods were used to evaluate the criteria. The study was conducted in two stages. In the first, seven active-use transformers on campus were weighed using the AHP method, then the most suitable one was selected using the TOPSIS method.In the second, seven parking areas were analysed using the same criteria. The parking lot selection used the AHP and TOPSIS methods, considering faculty and campus entrance distance, lot capacity and transformer preference score.
Direct current (DC) motors are widely used in industrial applications due to their numerous advantages, such as high efficiency, cost-effectiveness, and adaptability. Therefore, accurate control of these motors is equally crucial. The most popular controller for regulating the speed of a DC motor is the conventional Proportional-Integral-Derivative (PID) controller. However, determining the parameters of a DC motor, developing a mathematical model, and subsequently identifying or experimentally selecting control parameters is a laborious and time-consuming process. In this study, the coefficients of the PI controller used for speed regulation of a DC motor were determined using the Particle Swarm Optimization (PSO) and Sine Cosine Algorithm (SCA) methods. The study was conducted experimentally for three different reference values and four distinct control methods, with the resulting data visualized using MATLAB. Step, sinus with offset, and sinus without offset signals were selected as reference values. The control methods employed included open-loop control, PI control, PSO-PI control, and SCA-PI control. When the results of open-loop control and optimization-based PI control were compared, it was observed that steady-state errors decreased by 91.25% and 90.41% for step reference with PSO and SCA, respectively; by 84.7% and 80.58% for sinus with offset reference with PSO and SCA, respectively; and by 76.72% and 74.75% for sinus without offset reference with PSO and SCA, respectively. Additionally, the motor demonstrated a more stable tracking of the reference values. When the PI control results were compared with PSO-PI and SCA-PI control, the steady-state error was found to decrease by an mean of 9.74% for the same reference values.
This paper presents a nonlinear model predictive control (NMPC) framework for real-time formation control of autonomous ground vehicles (AGVs) operating under dynamic geometric patterns. The proposed method integrates a nonlinear kinematic bicycle model with a time-varying linearization strategy and constrained quadratic optimization to compute control inputs for each follower agent. Formation references are generated online using geometric transformation functions, enabling flexible spatial configurations such as line, rectangular, half-circle, and V-shaped formations. An exponential convergence model ensures smooth trajectory tracking, while input constraints are enforced at each control step. The controller is decentralized and scalable, with each agent solving its own NMPC problem using leader pose information. Extensive simulations validate the approach across multiple formations, demonstrating accurate tracking, constraint satisfaction, and real-time feasibility. The results confirm that the proposed NMPC architecture provides a unified and modular solution for multi-AGV formation control under nonlinear dynamics.
