Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Bulut, Hasan(53)
- Baskonus, Haci Mehmet(52)
- Alataş, Mevlüt(39)
- Gul, Muhammet(39)
- Serdar, Osman(38)
- Güler, Ömer(37)
- Akkurt, Nevzat(31)
- Benzer, Fulya(30)
- Sulaiman, Tukur Abdulkadir(29)
- Yucesan, Melih(29)
- Zengin, Gokhan(29)
- Kocabaş, Mehmet(28)
- Topal, Murat(26)
- Batan, Nevzat(25)
- Kök, Mediha(25)
- Ezer, Tülay(24)
- Paksoy, Mehmet Yavuz(24)
- Yildirim, Ozal(23)
- Tekin, H.O.(22)
- Utku, Anıl(22)
- ALMisned, Ghada(21)
- Ince, Muharrem(21)
- Öbek, Erdal(21)
- Erten, Fusun(20)
- Aslan, Naim(19)
- Celik, Erkan(19)
- Yildirim, Numan(19)
- Cakilcioglu, Ugur(18)
- Dal, Murat(18)
- Dal, Nursel Alp(18)
- Sahin, Kazim(18)
- Özkaynak, Fatih(18)
- Aslan, Alper(17)
- Erata, Hüseyin(17)
- Orhan, Cemal(17)
- Ergen, Burhan(16)
- Tanyol, Mehtap(16)
- Demir, Yakup(15)
- Etli, Serkan(15)
- Işık, Erdem(15)
Yayınlar
- MakaleAçık Erişim2025Scopus SJRQ1Hybrid GA-ConvLSTM for data-driven prediction of climate variables: a case study of the most biodiverse cities in India
Utku, Anıl; Akyol, Sinem
Climate variables affect ecosystems’ structure, sustainability, and biodiversity. Monitoring and analysis of climate variables are essential for the management of ecosystems and the conservation of biodiversity. Temperature affects the distributions, habitats, and phonological events of living things in ecosystems. Humidity is essential for meeting plants’ water needs and the habitat’s quality and health. Dew point is essential for water quality, balance, plant health, and microclimate. Wind speed is essential for pollinating plants, microhabitats, and the health of living things. For such reasons, accurate prediction of climate variables using artificial intelligence methods can effectively predict the future of ecosystems and biodiversity and develop future strategic plans. This study aimed to predict the climate variables of temperature, humidity, dew point, and wind speed of Bhubaneshwar, Dehradun, Guwahati, Mysore, and Nagpur, among the cities with the highest biodiversity in India. It aimed to determine the long-term impacts of climate change on managing ecosystems and biodiversity protection. The hyperparameters of the ConvLSTM model, developed using CNN and LSTM, were optimized with a genetic algorithm, and the GA-ConvLSTM hybrid model was created. GA-ConvLSTM was tested with XGBoost, SVM, ANFIS, CNN, LSTM, and base ConvLSTM using approximately 15 years of hourly, up-to-date, and real-time climate variable data of cities. This work is one of the pioneering studies using GA to optimize deep learning hybrid models for multi-city climate prediction through extensive long-term high-resolution datasets. The experimental results reveal that GA-ConvLSTM outperforms conventional models, producing an R2 score exceeding 0.9 for each city across all climate variables. GA-ConvLSTM produced temperature predictions with 0.833 RMSE and 0.995 R2 for Bhubaneswar, humidity predictions with 3.461 RMSE and 0.990 R2, dew point predictions with 0.632 RMSE and 0.995 R2, and wind speed predictions with 2.278 RMSE and 0.993 R2. The experimental findings confirm the improved performance over conventional models due to SVM and XGBoost failing to achieve these R2 values and high RMSE scores. The research meets three principal obstacles because of the combination of stochastic climate datasets and complex nonlinear patterns, which also encounter limitations in conventional methods for managing scale-dependency relationships and manual parameter adjustments. This approach delivers three main strengths because it combines CNN and LSTM networks through genetic programming while tracking temporal and spatial relationships and processing noisy data automatically, leading to improved results compared to other methods. Unlike other published models in the field, the hybrid model GA-ConvLSTM combines optimized CNN and LSTM elements with genetic algorithm elements. The proposed model received its first application in this research for multi-city climate prediction through training with 15 years of hourly data. Standard methods encounter challenges when detecting long-term dependencies, but GA-ConvLSTM successfully addresses this issue.
AtıfScopus1OpenAlex1
İncele - MakaleAçık Erişim2025Scopus SJRQ1Thermophysical properties and Optimization of modified palm Oil-Amine reinforced biocomposites for lightweight and insulating applications
Şahal, Hakan; Aydoğmuş, Ercan; Arslanoğlu, Hasan
The aim of this study is to investigate various thermophysical properties of modified palm oil-amine (MPOA) reinforced biocomposites to optimize these materials to meet the requirements of lightness and insulation. The effects of MPOA addition to biocomposites on bulk density, surface hardness, thermal conductivity coefficient, and activation energy have been evaluated. In addition, the structural and physical properties of these biocomposites are aimed to determine their potential use as lightweight and thermal insulation materials. The results show that MPOA incorporation significantly affects the bulk density, Shore A hardness, thermal conductivity, and thermal stability of biocomposites. The addition of MPOA provides significant benefits for lightweight biomaterials by reducing bulk density. However, high MPOA content decreases the surface hardness of the biocomposite, and with zirconium silicate (ZrSiO4), this drawback is eliminated and the curing time is reduced. Increasing MPOA ratios also improve the insulation properties of biocomposites by reducing the thermal conductivity coefficient. Thermal decomposition experiment results show that higher MPOA content reduces thermal stability. Scanning electron microscopy (SEM) reveals that high levels of MPOA lead to increased surface porosity and irregularities, negatively affecting surface morphology. An optimal MPOA reinforcement level of 5 wt% provides a balance between desirable properties such as reduced density and improved thermal insulation while minimizing adverse morphological effects. Fourier-transform infrared spectroscopy (FTIR) confirms the presence of epoxy resin and the successful chemical modification of palm oil to create bioepoxy feedstock. MPOA reinforcement offers benefits such as reduced bulk density and improved thermal insulation while addressing challenges in surface morphology, mechanical properties, and thermal stability. The study concludes that biocomposites with 5 wt% MPOA provide optimum stability, making them suitable for applications requiring lightweight and thermally insulating materials without significantly compromising structural integrity. This research, the long-term performance of biocomposites, and future investigations into their potential applications will further expand their practical applicability.
AtıfScopus2WoS2OpenAlex2
İncele - MakaleAçık Erişim2025Scopus SJRQ1High-Entropy Alloys and Oxides as Supercapacitor Electrodes: A Structural and Electrochemical Perspective for Energy Storage
Başgöz, Öyküm; Güngör, Ahmet; Güler, Ömer; Erdem, Emre
This study investigates the performance of high entropy alloys [Fe3Cr3Mn2NiV, HEA)] and high entropy oxides [(Fe3Cr3Mn2NiV)O4, HEO)] as electrode materials for supercapacitors. HEA is synthesized through mechanical alloying, followed by HEO forming via an oxidation process. XRD results demonstrate HEA comprises both amorphous and crystalline phases, whereas HEO has an entirely crystalline structure. SEM analyses showed HEA exhibits larger and irregular particles, whereas HEO displays a smaller and spherical morphology. EPR analyses revealed significant changes in defect structures and unpaired electron configurations during the transition from HEA to HEO. HEA is prone to diffusion-controlled processes due to their regular structure and strong magnetic interactions; however, HEO exhibits capacitive behavior based on surface redox reactions and pseudo-capacitive mechanisms due to their irregular structure and oxygen vacancies. CV analyses revealed that HEO contributes more capacitive via surface redox reactions, while GCPL results suggested that HEO demonstrated superior energy density (40.8 Wh kg−1) and power density (14.3 kW kg−1). Impedance analyses revealed that HEO exhibited reduced internal resistance and enhanced ion conductivity, whereas HEA demonstrated higher resistance and diffusion-controlled processes. In conclusion, HEA and HEO exhibit distinct energy storage mechanisms, and these materials can be optimized for supercapacitor applications.
AtıfScopus36WoS34OpenAlex18İncele - MakaleAçık Erişim2025Scopus SJRQ2An investigation on microstructural, physical, and radiation shielding properties Yb2O3 oxide dispersion-strengthened 316L-SS alloys
ALMisned, Ghada; Yayla, Nihal; Albayrak, M. Gökhan; Güler, Ömer; Sen Baykal, Duygu; Alkarrani, Hessa; Susoy, Gulfem; Tekin, H.O.
Oxide dispersion-strengthened alloys have emerged as a highly effective solution to address the physical, structural, and shielding challenges faced by traditional alloys in nuclear environments. This study presents a comprehensive evaluation of the microstructural, mechanical, and radiation shielding properties of Yb2O3 oxide dispersion-strengthened 316L stainless steel composites at varying Yb2O3 concentrations such as 1%, 5%, 10%, and 20% by weight. XRD analysis revealed lattice distortions, with crystallite sizes decreasing from 11.2267 nm to 9.3351 nm. SEM/EDX analyses confirmed homogeneous Yb2O3 dispersion at lower concentrations, with agglomeration at 20% Yb2O3. The mass attenuation coefficient increased from 56.103 cm2/g to 65.919 cm2/g at 0.015 MeV, marking a 17.5% enhancement. HVL decreased by 40.68% at 0.2 MeV for the 20% Yb2O3 sample. Additionally, the 20% Yb2O3 composite showed nearly 33% lower transmission factor at 3.0 cm thickness and 0.662 MeV. It can be concluded that Yb2O3 reinforcement significantly enhances the microstructural, and gamma-ray attenuation properties of 316L-SS composites, positioning them as promising materials for advanced nuclear shielding and structural applications.
AtıfScopus5OpenAlex5İncele - MakaleAçık Erişim2025Scopus SJRQ1Spring-Based Soil–Structure Interaction Modeling of Pile–Abutment Joints in Short-Span Integral Abutment Bridges with LR and RSM
Polat, Erkan; Göçmen Polat, Elifcan
Integral abutment bridges (IABs) are increasingly adopted in transportation infrastructure due to their durability, reduced maintenance needs, and cost-effectiveness compared to conventional bridges. However, their reliable performance under live loads is strongly influenced by the nonlinear soil–structure interaction (SSI) at the pile–abutment joint, which remains challenging to quantify using conventional analysis methods. This study develops simplified spring-based models to capture the SSI behavior of pile–abutment joints in short-span IABs. Predictive equations for joint rotation, deflection, moment, and shear are formulated using Linear Regression (LR) and Response Surface Methodology (RSM). Unlike prior studies relying solely on FEM or traditional p–y curves, the novelty of this work lies in deriving regression-based spring constants calibrated against FEM analyses, which can be directly implemented in standard structural software. This approach significantly reduces computational demands while maintaining predictive accuracy, enabling efficient assessment of pile contributions and global bridge response. Validation against finite element method (FEM) results confirms the reliability of the simplified models, with RSM outperforming LR in representing nonlinear parameter interactions.
AtıfScopus2WoS2OpenAlex3İncele - MakaleAçık Erişim2025Scopus SJRQ4Is There a Difference Between Postpartum Depression and Mother-baby Bonding in Pregnant Women Who Had and Did Not Have COVID-19? A Comparative and Cross-sectional Study; [COVID-19 Geçiren ve Geçirmeyen Gebelerde Doğum Sonrası Depresyon ve Anne-bebek Bağlanması Arasında Fark Var mıdır? Karşılaştırmalı ve Kesitsel Bir Çalışma]
Karatay, Gülnaz; Gürarslan Baş, Nazan; Yüksekol, Aslı
Objective: This study was conducted to examine the effect of being diagnosed with coronavirus disease-2019 (COVID-19) during pregnancy on postpartum depressive symptoms and infant-mother bonding. Method: This comparative cross-sectional study was conducted in a city in southeastern Turkey. Using the purposeful sampling method, 210 postpartum women (106 had COVID during pregnancy, 104 did not) constituted the sample of the study. The data were collected through face-to-face interviews between 15 March and 30 May 2022. Data were collected using the mother introductory information form, mother-infant bonding scale, and Edinburgh postnatal depression scale. The obtained data were analyzed using percentages, means, t-test, chi-square, Mann-Whitney U, and regression analysis. Results: According to the findings of the study, a significant relationship has been observed between contracting COVID-19 and both the birth weight of the baby and the week of birth. Moreover, having COVID-19 negatively affected infant-mother bonding and increased postpartum depressive symptoms. Conclusion: According to the findings of the study: it was observed that the babies of mothers who had COVID-19 had lower birth weight, were born before the full term, mother-baby bonding was lower, and postpartum depression was higher in mothers.
- MakaleAçık Erişim2025Scopus SJRQ1Effect of neuro-linguistic programming on comfort after cesarean: a randomized controlled trial neuro-linguistic programming comfort level cesarean
Doğan, Aysel; Dal, Nursel Alp; Beydag, Kerime Derya
Background: Due to the deterioration in comfort experienced after cesarean section, mothers go through troubled hours, have problems with breastfeeding, and cannot even meet their own and their baby’s needs. This study was conducted to determine the effect of neuro-linguistic programming on mothers’ comfort levels following cesarean section in the postpartum period. Methods: This study was performed from 1 January to 1 September 2023 as a prospective randomized controlled single-blind clinical trial with 100 participants (50 experimental, 50 control). The research data were collected using the Personal Information Form and the Postpartum Comfort Scale. The dependent samples t test and independent samples t test were used in the analysis of research data as well as numbers, percentages, and means. Analysis of covariance (ANCOVA) was used to evaluate the effect of the NLP more accurately by controlling the pre-test scores. Results: There were statistically significant differences between the mean pretest and posttest postpartum comfort scale scores, physical comfort scores, psycho-spiritual comfort scores, and sociocultural comfort scores of mothers in the intervention group. In this regard, mothers in the intervention group had higher mean postpartum comfort scale scores, physical comfort scores, psycho-spiritual comfort scores, and sociocultural comfort scores in the posttest phase than in the pretest phase. Conclusions: This study revealed that neuro-linguistic programming enhanced the postpartum comfort levels of mothers who underwent cesarean delivery. In this context, it is recommended that nurses and midwives enhance participants’ comfort through the use of neuro-linguistic programming techniques in care processes. Trial registration: NCT05646537.
AtıfScopus3WoS2OpenAlex2
İncele - MakaleAçık Erişim2025Scopus SJRQ1A novel s-box generation method based on metastable inducing over FPGA for block ciphers
Garipcan, Ali Murat; Aydın, Yılmaz; Özkaynak, Fatih
Substitution boxes (s-boxes) providing the nonlinearity property are fundamental components of modern encryption systems. The security of these systems directly depends on the quality of the s-boxes ensuring a high level of resistance to advanced attacks. Although there is no perfect method in the literature, improving the cryptographic properties of s-boxes, such as nonlinearity and differential independence remains an important area of interest for many researchers. In this paper, we propose a new s-box generation method based on the reinforcement of the randomness obtained from the metastable states of the R-S latch. In the proposed method, a Field Programmable Gate Array (FPGA) chip is used to obtain design inputs based on physical reality obtained from the hardware level. Design inputs with poor statistical adequacy are transformed into s-boxes by passing them through four different hash functions (Blake2b, Blake2 s, SHA3 and Shake). A total of 333,328 s-boxes are generated with the proposed method for four different scenarios and widely used evaluation metrics such as bijectivity, nonlinearity (NL), strict avalanche criteria (SAC), bit independence criteria (BIC), differential probability (DP) and linear probability (LP) are considered for the analysis. Taking into account these metric values, the study also presents a detailed performance comparison of the proposed s-boxes with recent studies from the last 5 years in the literature. The fact that the nonlinearity degree of 75 % of the produced s-boxes is higher than 103, which is the average limit value in the literature, also confirms the method's efficiency, proven reliable by the analysis results. When all these results are evaluated together, they confirm that the proposed method is highly effective in generating robust s-boxes and that these s-boxes can be reliably used in modern cryptographic systems.
AtıfScopus21WoS23İncele - MakaleAçık Erişim2025Scopus SJRQ2Modeling and analysis of WEDM with a new deep neural network
Mahmat, Aybars; Dogan, Gurkan; Ergen, Burhan; Tosun, Nihat
In some cases, the models targeted in machining processes are difficult to apply to industrial production. Artificial intelligence techniques applied to industrial production methods in recent times eliminate these problems in machining. The use of deep learning methods in solving these problems has recently increased. In this study, a new deep neural network (DNN) based on artificial neural networks is proposed to model the machining of AISI4140 steel by wire electrical discharge machining (WEDM). The proposed DNN model predicts surface roughness (SR) and wire wear ratio (WWR), which are the most important inferences in cutting with WEDM. Obtaining inferences such as SR and WWR in a real experimental environment means a lot of time and cost. With the proposed model, there is a significant reduction in time and cost factors. The dataset used to train and test the proposed model was obtained from the real experimental environment. For training and testing the model, the data set is divided into two parts: 20% test data and 80% training data. In the experimental tests carried out with the proposed model, error rates such as Mean Absolute Error (MAE), R2, and Mean Squared Error (MSE) accuracy rate between SR and WWR values estimated according to the SR and WWR values obtained from the real environment were examined. MAE, MSE, and R2 for SR reached 0.0495, 0.0005, and 98.48%, respectively, while MAE, MSE, and R2 for WWR reached 0.0156, 0.0036, and 98.39%, respectively. These results of the proposed model provided a lower error rate and higher accuracy than the state-of-the-art models in the literature.
AtıfScopus5WoS5OpenAlex7İncele - MakaleAçık Erişim2025Scopus SJRQ2HASK-Net: new hybrid attention selective kernel network for automatic colon cancer detection from colonoscopy images
Imak, Andaç; Doğan, Gürkan; Sengur, Abdulkadir; Ergen, Burhan
Colorectal cancer is a frequently analyzed cancer type seen today. It is the third leading of cancer in terms of incidence. It is among the second leading cases resulting in death. However, when detecting pre-cancerous polyps using traditional methods, the rate of being overlooked is high. Therefore, the rate of missed polyps can be greatly reduced with deep learning-based computer-aided diagnosis (CADx) methods. In this study, a novel convolutional neural network based on CADx, called HASK-Net, is proposed for automatic polyp detection. While HASK-Net uses ResNet50 as a feature extractor in the encoder network, the novely designed hybrid attention selective kernel convolution uses it in the decoder network to increase the representation power in feature maps and learn more complex features. In experimental results on the publicly available Hiper-Kvasir and EndoTech 2020 benchmark datasets, HASK-Net showed extremely promising performance with a dice similarity score of 97.02% and 84.83% and an mIoU score of 95.38% and 84.32%, respectively.
- MakaleAçık Erişim2025Scopus SJRQ2Multiscale Time Series Modeling in Energy Demand Prediction: A CWT-Aided Hybrid Model
Sezer, Elif; Yıldırım, Güngör; Özdemir, Mahmut Temel
In the contemporary energy landscape, the increasing demand for electricity and the inherent uncertainties associated with the integration of renewable resources have rendered the accurate and reliable forecasting of short- and long-term demand imperative. Energy demand forecasting, fundamentally a time series problem, can be inherently complex, nonlinear, and multi-scale. Therefore, interest in artificial intelligence–based methods that provide high performance for short- and long-term forecasting, rather than traditional methods, has increased in order to solve these problems. In this study, a hybrid artificial intelligence model based on LSTM, GRU, and Random Forest, utilizing a distinct mechanism to address these types of problems, is proposed. The Multi-Scale Sliding Window (MSSW) approach was utilized for the model’s input data to capture the dynamics of the time series at different scales. The optimization of windows was conducted using the Continuous Wavelet Transform (CWT) method to determine the optimal window sizes within the MSSW structure in a data-driven manner. Experimental studies on Panama’s real energy demand data from 2015 to 2020 show that the CWT-aided MSSW-hybrid model forecasts better with lower error rates (0.007 MAE, 0.009 RMSE, 1.051% MAPE) than single models and manually determined window sizes. The results of the study demonstrate the importance of hybrid structures and window optimization in energy demand forecasting.
AtıfScopus1OpenAlex2İncele - MakaleAçık Erişim2025Scopus SJRQ1Effect of Amount of Guidance in Inquiry-Based Physics Laboratory on Conceptual Understanding and Metacognitive Awareness
Peşman, Haki; Arı, Üzeyir; Cirit, Didem Karakaya; Ayazgök, Büşra
This study explores the influences of verification and guided inquiry-based physics laboratories on preservice science teachers’ conceptual understanding of and misconceptions about simple electric circuits and their metacognitive awareness. In other words, the impact of the amount of guidance in inquiry teaching is being explored. There were two groups: (1) the experimental group, where the guided inquiry was implemented, and (2) the control group, where the verification style inquiry was implemented. The experiment was a true-experimental design because 55 pre-service science teachers were randomly assigned to the groups. This study used two pretest and posttest instruments: (1) Simple Electric Circuit Diagnostic Test (SECDT) with 11 items and (2) Metacognitive Awareness Inventory (MAI) with 52 items. The SECDT is a three-tier test to assess conceptual understanding and misconceptions of students about simple electric circuits, while the MAI assesses the metacognitive awareness of adults. The authors utilized a doubly multivariate repeated measures design, a multivariate test statistic for repeated measures, for analyzing the data. As a result, this study presents evidence of the positive effect of a guided inquiry-based physics laboratory concerning the verification-based one on preservice science teachers’ conceptual understanding of simple electric circuits and their metacognitive awareness and presents conclusions based on the discussion.
AtıfScopus2WoS2OpenAlex3İncele - MakaleAçık Erişim2025Scopus SJRQ1Green Synthesis of Multi-Walled Carbon Nanotube-Reinforced Hydroxyapatite Doped with Silver and Silver-Core Selenium-Shell Nanoparticles: Synthesis, Characterization, and Biological Activity
Unal, İlkay
Hydroxyapatite (HAp) is widely used in biomedical applications due to its biocompatibility, osteoconductivity, and bioactivity. However, its low mechanical strength, tendency toward rapid corrosion, and lack of bactericidal properties present significant limitations in applications. This study aimed to improve the properties of HAp by reinforcing it with multi-walled carbon nanotubes (MWCNTs) and doping it with silver nanoparticles (AgNPs) and silver-core selenium-shell nanoparticles (Ag@SeNPs). Ocimum basilicum extract was used as both a reducing and stabilizing agent in the synthesis of nanoparticles using an environmentally friendly and non-toxic method as an alternative to traditional methods. The synthesized HAp, HAp/MWCNT, Ag-HAp/MWCNT, and Ag@Se-HAp/MWCNT nanocomposites were characterized by TEM, SEM, XRD, Raman spectroscopy, and BET analysis. BET analysis showed a reduction in surface area from 109.4 m2/g for pure HAp to 71.4 m2/g, 47.5 m2/g, and 35.3 m2/g for HAp/MWCNTs, Ag- HAp/MWCNTs, and Ag@Se-HAp/MWCNTs, respectively. Antimicrobial activities against P. aeruginosa, E. coli, S. aureus, E. faecalis, and C. albicans were evaluated. HAp and HAp/MWCNT did not show any antimicrobial activity, while Ag-HAp/MWCNTs showed inhibition zones of 14 mm for Escherichia coli and 18 mm for Pseudomonas aeruginosa at 5 mg/mL. Ag@Se-MWCNTs/HAp exhibited superior efficacy with inhibition zones of 18 mm, 12 mm, and 20 mm for S. aureus, E. faecalis, and Candida albicans, respectively. The incorporation of Ag@SeNPs enhanced HAp’s antibacterial and antifungal properties through a synergistic mechanism.
AtıfScopus12WoS10OpenAlex12İncele - MakaleAçık Erişim2025Scopus SJRQ4EVALUATION OF IMPLEMENTATION STRATEGIES IN THE CONTEXT OF ZERO-WASTE CITY AND CIRCULAR ECONOMY CONCEPT
Derse, Onur; Polat, Elifcan Göçmen
In recent years, there is a growing interest for waste systems in many countries around the world due to inevitable consequences of major environmental concerns. Urbanization, consumption styles, rapid developments of technologies have increased the consumption inevitably brings about the waste generation, which significantly poses risks to the environment. Although most papers have focused on waste management problems, there is a great gap of evaluation of implementation strategies for the zero-waste city and circular economy concepts. The goal “zero-waste” is strategically achieved with enriched engineering methods including all stakeholders to overcome the challenging waste issues. In this context, this study presents a systematic approach of implementing the policies and strategies focused on the most essential dimensions analysis associated with zero-waste and circular economy based on the PESTEL (political, economic, social, technological, environmental, and legal). In the study, Best-Worst Method (BWM) is first provided to evaluate a range of zero-waste implementation strategies which are essential for planners and policymakers. In addition, computational results are compared with the Stepwise Weight Assessment Ratio Analysis (SWARA), and the Fuzzy Analytical Hierarchy Process (F-AHP) methods to validate the results, and the results of the methods were found to be consistent. Environmental, economic and technological dimensions were obtained as the most influential strategies. According to the results of BWM and Fuzzy AHP methods, the four most important sub-strategies are S16 (Implementing a closed loop chain), S13 (Promoting sustainability), S5 (Investing in waste management infrastructure) and S12 (Green energy technologies). It is seen that these strategies are mostly environmental. According to the SWARA method, the most important sub-strategies under the economic dimension are S5, S4 (Providing economic incentives), and S6 (Development of green finance initiatives). The findings should also encourage the practitioners and researchers, as the detailed evaluation of strategies in terms of the zero-waste and circular economy provides a database to transform current cities into zero waste cities.
AtıfScopus3WoS1OpenAlex2İncele - MakaleAçık Erişim2025Scopus SJRQ1The effect of motivational interviewing on healthy lifestyle behaviors and quality of life in on menopausal women: a pilot randomized controlled trial
Orhan, İlksen; Yağmur, Yurdagül
Background: This study aims to determine the effect of motivational interviewing (MI), an effective communication technique, on healthy lifestyle behaviors and quality of life in menopausal women. Methods: This is a randomized controlled empirical study. The study was conducted with a total of 136 women, including 68 for experimental group and 68 for control group. The data were collected using an introductory information form, the Health Promoting Lifestyle Profile II (HPLPL II) and the Menopause-Specific Quality of Life (MENQOL). Women in the experimental group received 6 sessions of motivational interviewing and 2 follow-up interviews in two family health centers (FHCs) from the researcher. No intervention was applied to women in the control group. The data were analyzed using number, percentage, mean, standard deviation, chi-square test, Bonferroni test, independent samples t test and repeated ANOVA. Results: There was a statistically significant difference between the HPLPL II total scale and health responsibility, nutrition, spiritual development, interpersonal relationships, and stress management subscales pre-test, interim test and post-test mean scores of women in the experimental group, and their mean scores increased positively (p < 0.001). In addition, a statistically significant difference was also found between their MENQOL vasomotor, psychosocial, physical and sexual domains pre-test, mid-test and post-test mean scores (p < 0.05). Conclusion: Motivational interviewing was found to be effective in increasing healthy lifestyle behaviors and quality of life in menopausal women. Trial registration: Current Controlled Trials NCT06802458, 17/01/2025 (https//clinicaltrials.gov/study/NCT06802458), “Retrospectively registered”.
AtıfScopus3WoS3OpenAlex4İncele - MakaleAçık Erişim2025Scopus SJRQ1Maximal strength, sprint and jump performance in elite kumite karatekas
Cinarli, Fahri Safa; Aydogdu, Onur; Aydin, Yalcin; Tokgöz, Gürkan; Kahraman, Abdulselam; Beykumül, Ayşegül; Aygoren, Caner; Yılmaz, Nurkan; Ramirez-Campillo, Rodrigo
Background: Both maximal muscle strength and muscle power are independently important for karatekas. However, the relationship between strength and power in elite male kumite karatekas is under researched. This study aimed to determine the relationship between back-leg-chest (BLC) isometric muscle strength with sprint and jump variables in elite male karatekas. Methods: Male elite/international level (tier 4) kumite karatekas (n = 14; age, 20.79 ± 1.67 year; height, 1.77 ± 0.06 m; weight, 72.21 ± 5.20 kg) were recruited. BLC strength, sprint and jump values were measured with a dynamometer, a photocell, and an application, respectively. Pearson correlation (trivial r < 0.1; small r < 0.3; moderate r < 0.5; large r < 0.7; very large r < 0.9; nearly perfect/perfect r ≥ 0.9) and linear regression analyses were performed to determine the relationship and shared variance between BLC strength, sprint, and jump performance. Results: There were large to very large correlations between BLC strength and sprint time (r = − 0.930, p < 0.01), velocity (r = 0.918; p < 0.01), acceleration (r = 0.913; p < 0.01) and running momentum (r = 0.721; p < 0.01). Additionally, BLC strength correlated with jump height (moderate, r = 0.550, p < 0.05), peak anaerobic power (moderate, r = 0.672, p < 0.01) and power to body mass ratio (moderate, r = 0.545, p < 0.05). BLC strength and sprint variables showed an r2 = 0.52–0.86 (p < 0.01), while BLC strength and jump variables showed an r2 = 0.29–0.45 (p < 0.05). Conclusions: BLC strength is related to jump and sprint performance in male elite karate athletes. This relationship underscores the importance of including strength training that targets BLC muscle strength in training programs for coaches and athletes.
AtıfScopus6İncele - MakaleAçık Erişim2025Scopus SJRQ2Advanced synthesis and comprehensive characterization of nanoparticle-reinforced epoxy-based biocomposites derived from modified palm oil
Şahal, Hakan; Aydoğmuş, Ercan; Canpolat, Erdal; Kaya, Mehmet
In this research, new biocomposites were synthesized by two-step modification of palm oil (MPO). The raw material (MPOSA) was epoxidized in the first step and obtained by reacting with 4,4-diaminodiphenyl sulfone in the second step. Silicon carbide (SiC), MPOSA, bisphenol A diglycidyl ether, and epoxy resin were used to obtain the biocomposites. After this process, necessary physical tests and chemical analyses were performed. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) analyses were used to characterize the biocomposites. The research included measurements of bulk density, Shore D hardness, thermal conductivity, and thermal stability of the biocomposite. The results indicated that MPOSA reinforcement decreased the bulk density of the biocomposite in proportion to the doping level, and Shore D hardness tests revealed a decrease in hardness with the addition of MPOSA. The increase in MPOSA reinforcement also led to a reduction in the thermal conductivity coefficient. In experimental studies, the optimum reinforcement ratio was determined as 1 wt.% nano-SiC, 10 wt.% glass fiber, and 10 wt.% MPOSA. Excessive MPOSA reinforcement adversely affected the matrix structure and pore distribution of the nanocomposite due to aggregation due to increased intermolecular interaction. Thermal decomposition results showed that MPOSA reinforcement reduced the activation energy of the nanocomposite. This study successfully developed an economical, environmentally friendly, and easily processed biocomposite and contributed to the development of functional and sustainable alternatives.
AtıfScopus3WoS3OpenAlex3İncele - MakaleAçık Erişim2025Scopus SJRQ2Investigation of the effect of the metallographic properties of vertical and horizontal cylinders made of ferrochrome with different contents on heat transfer by natural convection
Kahraman, Gökhan; Taşgın, Yahya
In this study, ferrochrome materials containing elements with different content ratios were manufactured into six-cylinder specimens, 13 mm in diameter and 16 mm in length, and heated in a furnace up to 500 °C. The heated cylinders were removed and left to cool in vertical and horizontal positions in a 16 °C environment. The temperatures were recorded using thermal cameras at certain intervals while the materials cooled down. The six specimens, whose metallographic differences were identified using SEM and XRD analysis devices, were placed vertically and horizontally, and their heat transfer by natural conviction was noted. In the calculations, each specimen’s Nusselt and Rayleigh numbers were identified based on time and then compared. The fastest cooling among the specimens occurred in the ferrochromium material with 55.93% Cr, 31.11% Fe, 11.56% C, 0.48% Si, 0.83% O, and 0.09% Al compound ratios, both in vertical and horizontal positions. Additionally, since the Nusselt number of the horizontal cylinders remained below one based on their position, their natural convection flows were not initiated. The cooling in the horizontal cylinders occurred via conduction.
- MakaleAçık Erişim2025Scopus SJRQ1ADAMTS-1, a multifunctional proteinase, in the uterus of both estrous cycle rats and ovariectomized rats can be regulated via hormones
Parlak Ak, Tuba; Yaman, Mine; Bayrakdar, Ali; Bulmus, Ozgur
Remodeling of the extracellular matrix (ECM) throughout the estrous cycle is one of the most striking features of the uterus. A disintegrin and metalloprotease with thrombospondin type I motifs (ADAMTS-1) is a metalloproteinase responsible for the degradation of some proteoglycans, which are ECM components. In this study, ADAMTS-1 distribution was analyzed in the uterus of ovariectomized rats administered 17β-estradiol (E2) and progesterone (P4) and in the uterus at different estrous stages. Ovariectomized (OVX) rats were subjected to single and combined E2 (0.2 mg/kg) and P4 (10 mg/kg) hormone replacement therapies. E2 was administered for 3 consecutive days, followed by E2, P4, or E2 + P4 for 4 consecutive days. The serum level of E2 decreased from the proestrus phase to the diestrus phase, but that of P4 was the highest in the estrus phase. During the estrus phase, the serum level of luteinizing hormone (LH) was the lowest and that of follicle-stimulating hormone (FSH) was the highest. P4 level increased significantly in the OVX + P4 and OVX + E2 + P4 groups compared with the OVX group. The serum levels of LH and FSH decreased in the OVX + E2 and OVX + P4 groups compared with the OVX group, and were the lowest in the OVX + E2 + P4 group. ADAMTS-1 immunoreactivity in luminal, glandular, and stromal cells of the uterus decreased from proestrus to diestrus. When immunoreactivity in hormone replacement groups was compared, weak immunoreactivity was observed in the OVX group. ADAMTS-1 immunoreactivity gradually increased in OVX + P4 and OVX + E2 groups, and was particularly notable in luminal, glandular, and stromal cells in the OVX + E2 + P4 group. ADAMTS-1 distribution was affected by the estrous cycle process and hormone replacement therapy in the OVX procedure.
AtıfScopus1OpenAlex1İncele - MakaleAçık Erişim2025Scopus SJRQ2Determination of cardiometabolic risk in pre- and post-menopausal women
Orhan, İlksen; Koçak, Hatice Serap; Kaplan, Emine
Objective: The study was designed to determine and compare the cardiometabolic risk in premenopausal and postmenopausal women. Methods: Data were collected using cross-sectional and correlational study. In this study, the sociodemographic characteristics, anthropometric measurements, and biochemical parameters of menopausal women were examined. Results: The average age of menopausal women is higher compared to premenopausal women. Menopausal duration, number of children, daily cigarette consumption, body weight, body mass index (BMI), waist circumference, hip circumference, waist-to-hip ratio, systolic and diastolic blood pressure, fasting blood glucose, hemoglobin, AST (aspartate aminotransferase), and Framingham risk score are higher in menopausal women compared to premenopausal women. Conversely, height, HDL (high-density lipoprotein) level, LDL (low-density lipoprotein) level, TSH (thyroid-stimulating hormone), ALT (alanine aminotransferase), HbA1c (glycated hemoglobin), serum albumin, and visceral adiposity index (VAI) values are lower in menopausal women compared to premenopausal women. Conclusion: These findings indicate changes in the metabolic profiles of menopausal women. This study could serve as an important resource for assessing the health status of menopausal women and for implementing appropriate measures. Clinical trial number: not applicable.
AtıfScopus4WoS4OpenAlex5İncele
