Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Gul, Muhammet(86)
- Güler, Ömer(69)
- Akkurt, Nevzat(68)
- Baskonus, Haci Mehmet(53)
- Tekin, H.O.(52)
- Bulut, Hasan(50)
- ALMisned, Ghada(49)
- Serdar, Osman(43)
- Yucesan, Melih(43)
- Paksoy, Mehmet Yavuz(42)
- Yildirim, Numan(41)
- Zengin, Gokhan(40)
- Yildirim, Nuran Cikcikoglu(39)
- Ince, Muharrem(37)
- Kocabaş, Mehmet(37)
- Celik, Erkan(35)
- Benzer, Fulya(33)
- Sulaiman, Tukur Abdulkadir(29)
- Aslan, Naim(27)
- Can, Erkan(27)
- Kutlu, Banu(27)
- Kök, Mediha(27)
- Tanyol, Mehtap(27)
- Danabas, Durali(26)
- Kutluyer, Filiz(26)
- Özkul, İskender(26)
- Ates, Mehmet(25)
- Yildirim, Ozal(25)
- Onat, Onur(23)
- Topal, Murat(23)
- Demir, Veysel(22)
- Erten, Fusun(22)
- Guler, Omer(22)
- Say, Yakup(22)
- Yaman, Mehmet(22)
- Alataş, Mevlüt(21)
- Güler, Seval Hale(21)
- Çimen, Okay(21)
- Baykal, Duygu Sen(20)
- Mete, Suleyman(20)
Yayınlar
- MakaleYalnız künye2023Scopus SJRQ2New Deep Learning-Based Passenger Flow Prediction Model
Utku, Anıl; Kaya, Sema Kayapinar
The ability to predict passenger flow in transport networks is an important aspect of public transport management. It helps improve transport services, aids those responsible for management to obtain early warning signals of emergencies and unusual circumstances and, in general, makes cities smarter and safer. This paper develops a long short-term memory-based (LTSM-based) deep learning model to predict short-term transit passenger volume on transport routes in Istanbul. This prediction model has been created using a dataset that included the number of people who used different transit routes in Istanbul at one-hour intervals between January and December 2020. The proposed multilayer LSTM-based deep learning model has been compared with popular models such as random forest (RF), support vector machines, autoregressive integrated moving average, multilayer perceptron, and convolutional neural network. The experimental findings showed that the proposed multilayer LSTM-based deep learning model outperformed the other models with regard to prediction for each transfer route. Furthermore, RF, one of the machine learning models used, produced remarkably successful results.
AtıfScopus19WoS12OpenAlex16
İncele - MakaleAçık Erişim2023Scopus SJRQ1Numerical study for battery thermal management system improvement with air channel in electric vehicles
Tuğan, Volkan; Yardımcı, Uğurcan
In order to ensure the safe and efficient operation of the battery system in electric vehicles, the heat generated in the batteries must be rapidly removed from the system. Therefore, a battery thermal management system is needed to ensure that the battery pack operates at appropriate temperatures. This study focuses on improving the battery thermal management system in electric vehicles. For this purpose, two different types of battery modules with new air channel design were created. The temperature distribution, maximum temperature difference and pressure drop in the battery modules were numerically investigated with computational fluid dynamics. In addition, the effect of three different air velocities (1 m/s, 2 m/s and 3 m/s) on the battery temperature was evaluated. The results showed that the maximum temperature and maximum temperature difference in the battery decreased with the increase of the air inlet velocity. It was observed that the maximum temperature difference obtained for design 2 and design 3 decreased in the range of 15.01–17.93 % and 7.25–12.22 %, respectively, compared to Design 1.
AtıfScopus34WoS35İncele - MakaleAçık Erişim2023Scopus SJRQ2ResMIBCU-Net: an encoder–decoder network with residual blocks, modified inverted residual block, and bi-directional ConvLSTM for impacted tooth segmentation in panoramic X-ray images
Imak, Andaç; Çelebi, Adalet; Polat, Onur; Türkoğlu, Muammer; Şengür, Abdulkadir
Objective: Impacted tooth is a common problem that can occur at any age, causing tooth decay, root resorption, and pain in the later stages. In recent years, major advances have been made in medical imaging segmentation using deep convolutional neural network-based networks. In this study, we report on the development of an artificial intelligence system for the automatic identification of impacted tooth from panoramic dental X-ray images. Methods: Among existing networks, in medical imaging segmentation, U-Net architectures are widely implemented. In this article, for dental X-ray image segmentation, blocks and convolutional block structures using inverted residual blocks are upgraded by taking advantage of U-Net’s network capacity-intensive connections. At the same time, we propose a method for jumping connections in which bi-directional convolution long short-term memory is used instead of a simple connection. Assessment of the proposed artificial intelligence model performance was evaluated with accuracy, F1-score, intersection over union, and recall. Results: In the proposed method, experimental results are obtained with 99.82% accuracy, 91.59% F1-score, 84.48% intersection over union, and 90.71% recall. Conclusion: Our findings show that our artificial intelligence system could help with future diagnostic support in clinical practice.
AtıfScopus21OpenAlex23
İncele - MakaleYalnız künye2023Scopus SJRQ2Numerical investigation of the effect of using louver baffles on thermal performance in solar air collectors
Tuğan, Volkan; Işık, Erdem
Conventional flat plate solar air collectors have advantages such as low cost and simple design. However, their thermal efficiency is lower than that of other designs. The thermal efficiency of these collectors can be increased by detailed examination of parameters such as the shape, size, arrangement and material of the air duct. In this study, it is aimed to improve the thermal efficiency of solar air collectors. The effect of louver baffles, which were not previously used in solar air collectors, on thermal efficiency was investigated numerically via computational fluid dynamics. Three different solar air collectors with flat plates, segmented baffles, and louver baffles were compared in terms of thermal efficiency. In addition, pressure drops in solar air collectors were investigated. The mass flow rate of the air in all collectors is assumed to be 0.04 kg/s. Analyzes were carried out between 09:00 and 16:00. The thermal efficiency values obtained during the day for solar air collectors with flat plate, segmented baffles and louver baffles are 27.66%–56.35%, 29.57%–58.82% and 30.09%–59.47%, respectively. The daily thermal efficiency values obtained for solar air collectors with flat plate, segmented baffles and louver baffles are 46.98%, 49.18% and 49.87%, respectively. The pressure drop for solar air collectors with flat plate, segmented baffles and louver baffles were found to be 4.62, 18.82 and 5.96 Pa, respectively. Based on the data obtained from this study, louver baffles are recommended for use in solar heating applications due to their high thermal efficiency and low pressure drop.
AtıfScopus5WoS5OpenAlex5İncele - MakaleYayıncıda açık erişim2023Scopus SJRQ1Soil-dependent β and γ shape parameters of the Haverkamp infiltration model for 3D infiltration flow
Yilmaz, D.; Lassabatere, L.; Moret-Fernandez, D.; Rahmati, M.; Angulo-Jaramillo, R.; Latorre, B.
Estimating of soil sorptivity ((Figure presented.)) and saturated hydraulic conductivity ((Figure presented.)) parameters by field infiltration tests are widespread due to the ease of the experimental protocol and data treatment. The analytical equation proposed by Haverkamp et al. (1994) allows the modelling of the cumulative infiltration process, from which the hydraulic parameters can be estimated. This model depends on both initial and final values of the soil hydraulic conductivity, initial soil sorptivity, the volumetric water content increase ((Figure presented.)) and two infiltration constants, the so-called (Figure presented.) and (Figure presented.) parameters. However, to reduce the number of unknown variables when inverting experimental data, constant parameters such as (Figure presented.) and (Figure presented.) are usually prefixed to 0.6 and 0.75, respectively. In this study, the values of these constants are investigated using numerical infiltration curves for different soil types and initial soil water contents for the van Genuchten-Mualem (vGM) soil hydraulic model. Our new approach considers the long-time expansions of the Haverkamp model, the exact soil properties such as (Figure presented.), (Figure presented.) and initial soil moisture to derive the value of the (Figure presented.) and (Figure presented.) parameters for each specific case. We then generated numerically cumulative infiltration curves using Hydrus-3D software and fitted the long-time expansions to derive the value of the (Figure presented.) and (Figure presented.) parameters. The results show that these parameters are influenced by the initial soil water content and the soil type. However, for initially dry soil conditions, some prefixed values can be proposed instead of the currently used values. If an accurate estimate of (Figure presented.) and (Figure presented.) is the case, then for coarse-textured soils such as sand and loamy sand, we propose the use of 0.9 for both constants. For the remaining soils, the value of 0.75 can be retained for (Figure presented.). For (Figure presented.) constant, 0.75 and 1.5 values can be considered for, intermediate permeable soils (sandy loam and loam) and low permeable soils (silty loam and silt), respectively. We clarify that the results are based on using the vGM model to describe the hydraulic functions of the soil and that the results may differ, and the assumptions may change for other models.
AtıfScopus12OpenAlex10İncele - MakaleYalnız künye2023Scopus SJRQ1An efficient hybrid weather prediction model based on deep learning
Utku, A.; Can, U.
Weather events directly affect human activities. In particular, extreme weather events with global warming, forest fires, and high air temperatures that cause drought make human life difficult. Effective and accurate weather prediction models are needed to take precautions against such climatic events. Therefore, it is essential to develop models that make precise weather predictions. Technological developments contributed significantly to developing successful deep learning-based weather prediction models. With a high success rate, this study proposed a hybrid weather prediction model based on Convolutional Neural Networks and Recurrent Neural Networks models. The proposed hybrid model was applied to the Jena dataset, which contains 14-parameter, large-scale meteorological data that were never utilized for weather prediction. The experimental results were compared with popular deep learning, machine learning, and statistical methods such as Auto-Regressive Integrated Moving Average, Convolution Neural Networks, Long-Short Term Memory, Multilayer Perceptron, Random Forest, Recurrent Neural Networks, and Support Vector Machine. As a result of these comparisons, the proposed hybrid model obtained the best prediction result for all metrics. For example, according to the weather prediction results for Jena, Germany, the proposed hybrid model got the results of Mean Squared Error: 0.035, Root-Mean-Squared Error: 0.189, Mean Absolute Error: 0.126, and R-Squared: 0.987.
AtıfScopus15WoS11OpenAlex11İncele - MakaleAçık Erişim2023Scopus SJRQ1Adding New Scientific Evidences on the Pharmaceutical Properties of Pelargonium quercetorum Agnew Extracts by Using In Vitro and In Silico Approaches
Chiavaroli, Annalisa; Libero, Maria Loreta; Di Simone, Simonetta Cristina; Acquaviva, Alessandra; Nilofar; Recinella, Lucia; Leone, Sheila; Brunetti, Luigi; Cicia, Donatella; Izzo, Angelo Antonio
Pelargonium quercetorum is a medicinal plant traditionally used for treating intestinal worms. In the present study, the chemical composition and bio-pharmacological properties of P. quercetorum extracts were investigated. Enzyme inhibition and scavenging/reducing properties of water, methanol, and ethyl acetate extracts were assayed. The extracts were also studied in an ex vivo experimental model of colon inflammation, and in this context the gene expression of cyclooxygenase-2 (COX-2) and tumor necrosis factor α (TNFα) were assayed. Additionally, in colon cancer HCT116 cells, the gene expression of transient receptor potential cation channel subfamily M (melastatin) member 8 (TRPM8), possibly involved in colon carcinogenesis, was conducted as well. The extracts showed a different qualitative and quantitative content of phytochemicals, with water and methanol extracts being richer in total phenols and flavonoids, among which are flavonol glycosides and hydroxycinnamic acids. This could explain, at least in part, the higher antioxidant effects shown by methanol and water extracts, compared with ethyl acetate extract. By contrast, the ethyl acetate was more effective as cytotoxic agent against colon cancer cells, and this could be related, albeit partially, to the content of thymol and to its putative ability to downregulate TRPM8 gene expression. Additionally, the ethyl acetate extract was effective in inhibiting the gene expression of COX-2 and TNFα in isolated colon tissue exposed to LPS. Overall, the present results support future studies for investigating protective effects against gut inflammatory diseases.
AtıfScopus35OpenAlex35İncele - Derleme MakaleYalnız künye2023Scopus SJRQ1A review of advances in mechanical behaviors of the underground energy transmission pipeline network under loads
Zheng, Qiang; Xu, Qian; Shu, Zekai; Yang, Di; Chen, Weiwang; Akkurt, Nevzat; Zhang, Hui; Lin, Lin; Zhang, Xinxin; Ding, Yulong
The safety of underground energy transmission pipeline network is threatened by traffic, earthquakes, explosions, and other stresses. To solve the problem of damage to the underground energy transmission pipeline networks by external loads, this study analyzed the mechanical properties of the Pipe-Soil Coupling System (PSCS) under external loads from a mechanical perspective. The pipeline constitutive model, the soil constitutive model, the internal effect of the PSCS, the influence of external stresses on the PSCS, and the dynamic response of the PSCS under various research methodologies were all studied. First, different mechanical features of the pipes and soil were employed to investigate the pipe and soil constitutive models. Second, based on the different force directions within the PSCS, the earth pressure and axial friction of the PSCS were investigated to clarify the interaction between the pipe and soil. For the purpose of to better understand the degradation of the underground pipeline state, the impacts of man-made and natural stresses on the PSCS failure were explored. Finally, the results of the investigation of the dynamic response of the PSCS were examined for their applicability using three research methods: theoretical analysis, numerical simulation, and experimental analysis. It is found that the existing constitutive models of pipeline and soil are lack of basis, which increases the difficulty of the selection of constitutive models in the process of research. In the analysis of load effect, earth pressure plays a dominant role in affecting the local stability of pipeline, but the calculation accuracy of soil pressure needs to be improved. Due to the lack of experimental guidance for complex damage phenomena under external loads, it is impossible to accurately determine the limit state parameters of pipelines under complex damage modes. It is critical to create and refine the theory underpinned by numerous experimental data in order to address the issue of pipeline dynamic response under multi-field coupling, including explosion and earthquake. This work is critical for analyzing existing research findings, identifying future research problems, and enhancing buried pipeline safety management.
AtıfScopus15WoS13OpenAlex14İncele - MakaleYalnız künye2023Scopus SJRQ1A long short-term memory-based hybrid model optimized using a genetic algorithm for particulate matter 2.5 prediction
Utku, Anıl; Can, Ümit; Kamal, Mustafa; Das, Narasingha; Cifuentes-Faura, Javier; Barut, Abdulkadir
Beijing, Shanghai, Singapore, and London are regions with high population density and industrial activities. In this sense, accurate prediction of the rate of particulate matter 2.5 (PM_2.5), one of the most important air pollutants, is very important for creating a healthy ecological system. This study proposes a hybrid method to predict PM_2.5 with high success. This method aims to optimize the Long Short-Term Memory (LSTM) deep learning model, which successfully solves time series problems with a Genetic Algorithm (GA). Here, the hyperparameters of the LSTM model, such as the number of layers, number of neurons, number of epochs, and kernel size, are optimized to achieve the highest prediction rate. Against this backdrop, the present study uses for the first time a hybrid GA-LSTM model to predict PM_2.5 concentrations in Beijing, Shanghai, Singapore, and London. The Beijing dataset consists of 13 attributes, the Shanghai dataset consists of 10 attributes, the London dataset consists of 5 attributes, and the Singapore dataset consists of 7 attributes. In this study, input variables such as PM_2.5, DEWP, TEMP, PRESS, WS, WD, PRE, Snowfall hours, Rain hours, and Season were used. To assess the effectiveness of this hybrid method, the developed GA-LSTM model was compared with k-Nearest Neighbors (kNN), Random Forest (RF), Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), Convolutional Neural Networks (CNN), LSTM, and Gated Recurrent Units (GRU). Experimental results showed that GA-LSTM outperformed the compared models. In addition, one of the best results was obtained compared to other models in the literature.
AtıfScopus17OpenAlex18İncele - MakaleYalnız künye2023Scopus SJRQ4The Effect of Self-Esteem on Loneliness in Individuals With Schizophrenia
Üşenmez, Tülay Yıldırım; Budak, Funda Kavak; Ayhan, Mehmet Osman
The aim of this study was to evaluate the effect of self-esteem on loneliness in persons with schizophrenia. This study was conducted between August 2020 and August 2021 at a community mental health center affiliated with a research and training hospital in Turkey. This was a cross-sectional study that included 100 individuals with schizophrenia. A Descriptive Characteristics Form (DCF), the Rosenberg Self-Esteem Scale (RSES), and the University of California Los Angeles Loneliness Scale (UCLA-LS) were used for data collection. The individuals’ total mean scores were 2.47 ± 1.24 for RSES and 56.42 ± 10.00 for UCLA-LS. A moderate negative correlation was found between these scores (r =-0.526, P < 0.01). The results revealed that the persons with schizophrenia had a moderate level of self-esteem and a high level of loneliness, possibly indicating that as self-esteem increases, loneliness levels may decrease.
- MakaleAçık Erişim2023Scopus SJRQ1Magneto-couple stress of tri-hybrid metallic oxide nanomaterials in porous media with nonlinear properties for thermal technology advancement
Salawu, S.O.; Obalalu, A.M.; Fatunmbi, E.O.; Disu, A.B.; Akkurt, Nevzat
The rising industrial demand for technological advancement in improving their working fluids and thermal augmentation has prompted studies on various non-Newtonian fluids and nanofluids. These play momentous role in many engineering devices and electronics development. Therefore, this study seeks to examine the thermal performance of ternary hybridized magneto-couple stress nanofluids in permeable media with nonlinear thermofluidic properties. The dispersion of suspended cobalt ferrite CoFe2O4, titanium dioxide TiO2 and magnesium oxide MgO nanoparticles occurs in H2O conventional solvent. With isothermal energy, the tri-hybrid nanofluid is controlled by stretchy velocity, magnetic field, gravity and Ohmic heating. An invariant transmutation of the partial derivative model is offered using similarity variables. The complete solutions to the model are obtained via Chebyshev technique coupled with integrated collocation method. From the graphically presented results, it is revealed that strong heat transfer is provided by ternary CoFe2O4+Ti02+MgO nanofluids compared to CoFe2O4+Ti02 and CoFe2O4 nanofluids. Also, the nanofluid concentration volume fraction enhanced thermal distribution and performance in the system.
AtıfScopus26WoS26OpenAlex27İncele - MakaleYalnız künye2023Scopus SJRQ1Effect of type and concentration of cryoprotectant on the motility, viability, and fertility of climbing perch Anabas testudineus Bloch, 1792 (Pisces: Anabantidae) sperm
Maulida, Siti; Eriani, Kartini; Fadli, Nur; Kocabaş, Filiz Kutluyer; Siti-Azizah, Mohd Nor; Wilkes, Martin; Muchlisin, Zainal Abidin
The climbing perch, Anabas testudineus is a freshwater fish that has economic value in Indonesia. It is cultured in the country, but the breeding technology, specifically sperm storage, is not well developed. Sperm cryopreservation is one of the preservation methods that need to be developed to support fish breeding technology. The type of cryoprotectants and its concentration are species-dependent and determines the success of this approach. Therefore, this study is aimed at determining the optimal type and concentration of cryoprotectant for sperm cryopreservation of A. testudineus. Four separate study series were performed, each of which evaluated one type of cryoprotectant at five concentration levels. The cryoprotectants used were DMSO, methanol, glycerol, and ethanol, and the tested concentrations were 0%, 5%, 10%, 15%, and 20%, which were combined with 5% egg yolks. Each treatment was conducted with three replications. The results showed that the type of cryoprotectant and its concentration significantly affected sperm motility, viability, and fertility of climbing perch (P < 0.05). The best outcome was obtained in DMSO, and methanol at a concentration of 10%, glycerol at 5%, and ethanol at 15%. However, the highest motility, viability, and fertility values were observed at 10% DMSO, indicating it is the best type and concentration for sperm cryopreservation of climbing perch A. testudineus.
AtıfScopus10WoS7OpenAlex11İncele - MakaleAçık Erişim2023Scopus SJRQ3Online scratch activities during the COVID-19 pandemic: Computational and creative thinking
Cırıt, Didem Karakaya; Aydemir, Selçuk
This paper investigated the effect of online Scratch activities on college students’ computational and creative thinking. The study adopted a mixed research design including one group pretest-posttest. The sample consisted of 24 child development undergraduates (23 female and 1 male) in the 2019-2020 academic year. The research was carried out in “Teaching science and mathematics in preschool education” course and lasted 12 weeks. The participants developed Scratch projects based on eight learning outcomes (four math and four science). Data were collected using the Computational Thinking Scale, the Marmara Creative Thinking Dispositions Scale, and reflective journals. The quantitative data were analyzed using a paired sample t-test. The qualitative data were analyzed using content analysis. The results showed that Scratch activities helped students develop computational and creative thinking. The results of this study provide evidence that Scratch activities develop the students’ higher order skills. Ultimately, this research study recommends that Scratch activities ought to be integrated to science and mathematics education curriculums.
AtıfScopus5OpenAlex5İncele - MakaleAçık Erişim2023Scopus SJRQ1FeCoNiMnCr high-entropy alloys (HEAs): Synthesis, structural, magnetic and nuclear radiation absorption properties
Şimşek, Telem; Kavaz, Esra; Güler, Ömer; Şimşek, Tuncay; Avar, Barış; Aslan, Naim; Almisned, Ghada; Zakaly, Hesham M.H.; Tekin, H.O.
We report the synthesis and structural, magnetic and Radiation shielding properties of High Entropy Alloy (HEA) produced through mechanical alloying method. Using an X-Ray Diffractometer (PanalyticalEmpryan) with CuK radiation at 45 kV and 40 mA, the phase identification starting elements and as-milled powders are identified. Scanning electron microscopy (SEM) equipped with energy dispersive X-ray spectroscopy (EDX), morphological and microstructural investigations were conducted (FEI Quanta FEG 450). EDX and elemental mapping analyses are conducted to assess the purity and elemental distributions of the synthesized alloys. Using the Quantum Design Physical Characteristics Measurement System (PPMS) with vibrating sample magnetometer (VSM) and a magnetic field of 30 kOe at room temperature, magnetic properties are examined. Using 137Cs radioisotope and mathematical methods, gamma-ray and neutron shielding properties of HEA are investigated in a conventional transmission setup using experimental and theoretical approaches. In the presence of a 3 T applied field, the sample exhibits a low magnetization of 5.30 emu/g at 300 K. Moreover, Ms is raised to 22 emu/g at 10 K owing to decreased thermal effects. The temperature dependence of the magnetization is recorded in the presence of a 1 T applied field. HEA exhibits superior neutron attenuation properties than conventional absorption materials such as B4C, graphite, and water. Our results showed that the synthesized HEA has superiority over other alloys and conventional neutron absorption materials. It can be concluded that the proposed novel HEA might be investigated further in terms of broadening its characterization and clarifying its other crucial properties to extend the scope of the current investigation.
AtıfScopus42OpenAlex47İncele - MakaleYalnız künye2023Scopus SJRQ3A Selective and Sensitive Electrochemical Sensor for Pyridoxine Hydrochloride (Vitamin B6) in Pharmaceutic Tablet
Koçak, Berna
In this study, a copper (II) oxide-glutardialdehyde modified boron doped diamond electrode was used as a sensor for the electroanalysis of pyridoxine hydrochloride (vitamin B6) for the first time. A copper oxide-glutardialdehyde modified boron doped diamond electrode (CuO-GA2/BDDE) was prepared by a simple drop casting method on boron diamond electrode (BDDE) by suspending CuO with glutardialdehyde (CuO-GA2). The electrochemical behavior of vitamin B6 was examined using cyclic voltammetry (CV) and its electrochemical determination was found by differential pulse voltammetry (DPV). Under optimum experimental conditions, the linear working range of vitamin B6 on CuO-GA2/BDDE via the DPV method was calculated as 5.96×10−6–3.75×10−4 mol.L−1. The limit of detection (LOD) was calculated as 1.99×10−7 mol.L−1. In order to demonstrate the selectivity of the method improved for the quantitative determination of vitamin B6 on the CuO-GA2/BDDE, the interference effect of some cations (Zn2+, Cu2+, Pb2+) and anions (NO3−, Cl−) was investigated via the DPV method. The improved electrode was successfully used for the electroanalysis of vitamin B6 in a tablet sample of the commercial Tribeksol® (deva) (250/250/1 mg B1+B6+B12).
AtıfScopus7WoS6OpenAlex6İncele - MakaleYalnız künye2023Scopus SJRQ3Comprehensive Evaluation of the Relationships Between Grape Skin Color/Ripening Time and Antioxidative Capacity, Some Phytochemicals, and Fatty Acid Compositions of Their Seeds
Çakır, Atilla; Odabaşıoğlu, Mehmet İlhan; Karaca Sanyürek, Nesrin; Aydın, Sevinç
It has been proven that grapes, which are widely cultivated around the world, have positive health effects. However, the phytochemical composition of lesser-known local varieties of Vitis vinifera L., which has a very wide range of varieties, is still being studied. The aim of this study was to determine the effects of skin color and ripening time on the phytochemical compositions of grape seeds. As a plant material local grape varieties cultivated in Southeastern Anatolia (Turkey) were used. The results showed that grape skin color has an effect on vitamin K1, vitamin K2, vitamin D3, δ‑tocopherol, stigmasterol, ergosterol, myristic acid, oleic acid, trans-elaidic acid, and the monounsaturated fatty acid (MUFA) and saturated fatty acid (SFA) contents of seeds. The seeds of grape varieties with colored skins were richer in K2, D3, stigmasterol, oleic acid, trans-elaidic acid, and MUFAs, while the seeds of grape varieties with white skins were richer in K1, δ‑tocopherol, ergosterol, and SFAs. The ripening time of the grapes was found to have a partial effect on the fatty acid compositions of the seeds, but without any effect on linoleic acid contents. As the ripening time was delayed, there was an increase in oleic acid and MUFA contents of the seeds, while there was a decrease in SFA contents. In general, increased vitamin K1 contents of the seeds were parallel to decreases in vitamins K2, D2, and D3, as well as α‑tocopherol content and antioxidant activity. The seeds of grape varieties that have colored skins were found to have more suitable compound compositions for use in the production of functional foods that support human and animal health. In addition, it was concluded that grape berries that ripen late may be more favorable for grapeseed oil production.
AtıfScopus3WoS4OpenAlex3İncele - MakaleYalnız künye2023Scopus SJRQ1Energy, exergy and cost analysis of different hemispherical solar distillers: A comparative study
Hadi Attia, Mohammed El; Hussein, Ahmed Kadhim; Radhakrishnan, Ganesh; Vaithilingam, Sivakumar; Younis, Obai; Akkurt, Nevzat
The experimental study of the results of reflective aluminum foils, metal sheets, and phosphate granules on the productivity and efficiency of hemispherical solar stills was given throughout this work under the solar conditions of the city of El-Oued (Algeria). Solar stills were designed, manufactured, and tested in August 2020. A standard hemispherical solar still was made of wood and coated with black silicon. It was considered a traditional solar still. Although it was compared to traditional solar stills, it was improved by covering its side walls with reflective aluminum foil, zinc metal sheets, and copper sheets. It had been found that the productivity of the modified still was 8.67%, 29.08%, and 42.35%, respectively, on top of that of the traditional solar still. This could be due to the activity of the foils and metals, which reflect more radiation and store energy, increasing the temperature of the salt water in the basin. In the second experiment, three modified solar stills in line with aluminum foil and phosphate granules (30 g/L), zinc metal sheet and phosphate granules, and copper metal sheet and phosphate granules were collectively used. It had been found that the productivity of the modified solar still with aluminum foil and phosphate granules (the improvement rate is 30.61%) was on the far side of that with zinc metal sheets and phosphate granules (the improvement rate is 49.961%) and copper metal sheets and phosphate granules (the improvement rate is 62.24%).
AtıfScopus37OpenAlex34İncele - MakaleAçık Erişim2023Scopus SJRQ1Screening for Chemical Characterization and Pharmacological Properties of Different Extracts from Nepeta italica
Acquaviva, Alessandra; Di Simone, Simonetta Cristina; Nilofar; Bouyahya, Abdelhakim; Zengin, Gokhan; Recinella, Lucia; Leone, Sheila; Brunetti, Luigi; Uba, Abdullahi Ibrahim; Guler, Osman
Plants from the Nepeta genus have been proved to possess different pharmacological properties, among which are antimicrobial, antioxidant, anti-inflammatory, analgesic, and cytotoxic effects. Nepeta italica is a medicinal plant traditionally used for its analgesic effects, and in the present study, the phytochemical composition and biological effects of hexane, dichloromethane (DCM), ethyl acetate (EA), ethanol, ethanol-water, and water extracts of the aerial parts were investigated for determining phenolic composition, antioxidant effects, and anti-inflammatory effects in isolated mouse colon specimens exposed to lipopolysaccharide (LPS). Polar extracts were the richest in terms of phenolic compounds, especially rosmarinic acid. In parallel, ethanol, ethanol-water, and water extracts were also the most effective as scavenging/reducing and enzyme inhibition agents, especially towards cholinesterases and α-glucosidase, and in inhibiting the LPS-induced cyclooxygenase-2 (COX-2) and tumor necrosis factor α (TNFα) gene expression in mouse colon. This poses the basis for future in vivo investigations for confirming the protective effects of polar extracts of N. italica against inflammatory bowel diseases.
AtıfScopus31OpenAlex31İncele - MakaleAçık Erişim2023Scopus SJRQ1Analysis of unsteady thermo-solutal MoS2-EO Brinkman electro-conductive reactive nanofluid transport in a hybrid rotating Hall MHD generator
Shamshuddin, M.D.; Bég, O. Anwar; Akkurt, Nevzat; Leonard, Henry J.; Bég, Tasveer A.
MHD rotating generators offer a plausible renewable energy mechanism. New designs are emerging in which nanotechnology is contributing. Such systems are increasingly deploying more complex functional fluid materials such as base fluids containing magnetic nanoparticles which constitute electromagnetic nanofluids and can be tuned to enhance efficiencies. Motivated by these developments, a mathematical model is presented for the combined effects of Hall current, heat source, chemical reaction and radiative flux on the unsteady rotating thermo-solutal magnetohydrodynamic transport of a Molybdenum disulphide (MoS 2)-EO oil electroconductive Brinkman nanofluid to study the boundary layer characteristics in the vicinity of the side wall of an MHD generator system. The governing dimensional conservation equations are scaled using appropriate transformations into a system of dimensionless coupled partial differential equations. Under appropriate initial and boundary conditions, solutions are derived using the Laplace Transform Method (LTM) and complex variables. The physical impacts of the magnetic, nanoscale, thermal and species control parameters on primary and secondary velocity, temperature and concentration are visualized graphically. The judicious doping of the base fluid with MoS 2 nanoparticles is shown to achieve superior thermal performance for MHD rotating energy generators.
AtıfScopus38OpenAlex24İncele - MakaleAçık Erişim2023Scopus SJRQ3Production of SBS Reinforced Polyester Composite: Characterization of Physical and Chemical Properties
Şahal, Hakan; Aydoğmuş, Ercan
In this study, dissolved styrene butadiene styrene (SBS) copolymer is homogeneously reinforced into orthophthalic unsaturated polyester (UP) resin. Polyester composite production is carried out with the help of methyl ethyl ketone peroxide (MEKP) and cobalt octoate (Co Oc) catalysts. The density, Shore D hardness, thermal conductivity coefficient, thermal stability, morphological surface structure, and chemical bond structure of the obtained composite have been examined. According to the results, SBS reinforcement decreases the density of the composite and increases the thermal conductivity coefficient. The addition of SBS at different weight ratios (1%, 3%, 5%, 7%, and 10% w/w) reduces both the hardness and thermal stability of the polyester composite. According to the test and analysis results, 5 wt.% SBS reinforced polyester composite production is determined as the optimum ratio. 7 wt.% and above SBS reinforcement negatively affect the physical and chemical properties of the obtained composite. For example, when 10 wt. % SBS reinforced composite is examined by scanning electron microscope (SEM), and irregular pores are observed in the surface morphology. Also, it is understood by Fourier transform infrared spectroscopy (FTIR) that there is a physical interaction between SBS and polyester and that no chemical bond is formed. The thermal decomposition behavior of the composite has been determined according to the decrease in the activation energy. As SBS ratio increases, it is understood that the thermal stability of the product obtained with the decrease in the activation energy of the polyester composite weakens.
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