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 Erişim2025Antigenotoxic Effects of Stachys viscosa (Lamiaceae), a potential medicinal plant in Drosophila melanogaster
Karabulut, Aygul Kilic; Açar, Mikail
This research aimed to examine the anti-genotoxic properties of Stachys viscosa, a plant of the Lamiaceae family, which has medicinal and aromatic properties and is widely used in cosmetics, food, and pharmaceutical industries. The Drosophila wing somatic mutation and recombination test (SMART), an in vivo tool for evaluating somatic mutation and recombination, was employed. The antigenotoxic effect of the S. viscosa plant against mitomycin C (MMC) mutagen was investigated. The study evaluated doses of 5 mg, 15 mg, 45 mg, and 60 mg of S. viscosa, concluding that doses of 45 mg and 60 mg effectively mitigated DNA damage induced by MMC. At doses of 45 mg and 65 mg, the total number of spots caused by MMC was suppressed by 8.21% and 13.17%, respectively. The data collected indicate that the S. viscosa plant possesses certain anti-genotoxic properties.
AtıfWoS2OpenAlex2
İncele - MakaleAçık Erişim2025Scopus SJRQ3A never-ending story of an identity crisis or a creative reformulation of an Alevi-mindset? What the case of Alevi youth in the German diaspora suggest today?
Gueltekin, Ahmet Kerim
The Alevi movement, originating more than three decades ago in Turkey and the Western European diaspora, has led to significant social and cultural shifts within Alevi communities. This movement witnessed the emergence of Alevi associations, increased religio-political activities, and a fervent search for a redefined Alevi identity. The quest for a comprehensive understanding of Alevi identity remains a contested debate, prominently reflected within Alevi youth, who navigate complex socio-cultural landscapes and encounter challenges in defining their identity amidst competing narratives and associations. This paper examines the identity formation strategies of young Alevis in Berlin, drawing on ethnographic fieldwork conducted between 2021 and 2023. Contrary to mainstream portrayals of Alevi youth experiencing a loss of identity, this study argues for the presence of continuity dynamics, emphasising inherited Alevi mindsets and emotions. Through interviews and analysis of a documentary produced by Berlin Alevi youth, the paper explores new narratives about Alevi history, sociology, and theology constructed by young Alevis, highlighting their role in shaping contemporary Alevism in Germany. This research contributes original data and discussions to the existing literature on Alevi youth, shedding light on their evolving identities and the dynamics of Alevi discourse in diasporic settings.
AtıfWoS4OpenAlex3İncele - MakaleAçık Erişim2025Does Nepotism Trigger Quiet Quitting? A Research on Local Governments
Uyan, Umut; Ibin, Adil
The concept of quiet quitting, which denotes a cognitive and/or emotional, if not physical, detachment, has recently become one of the most frequently studied topics in organizational psychology. The term refers to performing only the tasks stipulated in job description with minimum organizational commitment and not going beyond that. Due to the detrimental effect of quiet quitting on both individual and organizational performance, it is crucial to study the phenomenon in depth. By referring to the organizational justice perspective, the study is designed to determine whether one of the negative employee experiences, nepotism, in local governments trigger quiet quitting. The main assumption of the research is that nepotism deteriorates the sense of justice, which leads employees to quit quietly. Structured questionnaires were administered to 259 local government workers in Adana. The results suggest that exposure to nepotism triggers quiet quitting in local governments where preferential treatments are allegedly pervasive. The study is expected to guide managers in establishing effective human resources practices in such institutions.
AtıfWoS4OpenAlex3TR Dizin1İncele - MakaleAçık Erişim2025Scopus SJRQ1Rejuvenation of Recycled Asphalt Binders with Bio-Oils from Waste Biomass Pyrolysis
Yalcin, Beyza Furtana; Yilmaz, Mehmet; Yalçin, Erkut; Altundogan, Hamdi Soner
This study evaluates the effects of using bio-oil obtained from waste biomass on the physical properties, rheology, fatigue, and rutting of recycled asphalt binder. In addition, the aim of this study is to provide benefits to the environment and the economy by reusing waste materials. The bio-oils produced were produced by the pyrolysis method. B70/100 pure bitumen was chosen as the reference binder for the rejuvenation of the selected RAP binder. To ensure its properties, five different rejuvenators (two commercial + three bio-based rejuvenators) were added to the aged bitumen obtained from recycled asphalt pavement (RAP) at different rates. The produced bio-oils were compared with commercial products. The first goal of the study is to produce rejuvenators from waste materials, and the second is to achieve similar or better results with commercial rejuvenators by producing rejuvenators from waste materials. When the test results are examined, it can be seen that the aged binder was rejuvenated to the desired hardness by adding rejuvenator to it. It is seen that the penetration value of the aged binder increased by the addition of rejuvenator, whereas the softening point and viscosity values decreased.
AtıfWoS1OpenAlex1İncele - MakaleAçık Erişim2025Earthquake Hazard in Urban Areas of Bursa Province: Paleosismological Properties of the Ulubat, Bursa and İnegöl Active Faults
Karabacak, Volkan; Sançar, Taylan
This study provides a detailed mapping of active fault segments in Bursa and its surrounding regions, along with a comprehensive analysis of seismic behavior derived from paleoseismological data. As one of T & uuml;rkiyes' strategic economic centers with a dense population and industrial infrastructure, Bursa requires a holistic seismic risk assessment for effective disaster preparedness and mitigation. Paleoseismological analyses of the eastern segment of the Ulubat Fault indicate that it has been in a seismic quiescence period for approximately 1855 years. This prolonged period of inactivity highlights the potential for a large earthquake in the future around the Nil & uuml;fer Region of Bursa. Trench investigations conducted in Bursa city-centre reveal that the Bursa Fault has produced at least six surface ruptures over the past 12000 years, recurring approximately every 2000 years. Additionally, trench studies on the & Idot;neg & ouml;l Fault indicate that the & Idot;neg & ouml;l Fault has produced at least five surface ruptures over the last 12000 years, with the most recent major earthquake occurring more than 2500 years ago. Obtained results emphasize the potential for the Bursa and & Idot;neg & ouml;l faults to rupture simultaneously or in close succession, possibly triggering one another. Thus, the surface rupture caused by the 1855 Bursa earthquake is evaluated to have potentially triggered stress accumulation along the & Idot;neg & ouml;l Fault. This situation reveals a high probability of a surface-rupturing earthquake (M=6.2-6.9) occurring at any time on the & Idot;neg & ouml;l Fault, after 2500 years of seismic silence. Overall, these findings underscore the critical role of the faults in Bursa and its surroundings within the regional seismicity. In particular, the potential for sequential ruptures along the Bursa and & Idot;neg & ouml;l faults presents a significant earthquake hazard. This comprehensive analysis contributes to a deeper understanding of the seismotectonic dynamics of the region, providing valuable insights for seismic hazard assessment and risk mitigation efforts.
AtıfWoS2OpenAlex3İncele - MakaleAçık Erişim2025EFFECT OF GRAPHITE AND MAX PHASE ON THE THERMAL AND DIELECTRIC PROPERTIES OF N-VINYL CARBAZOLE AND BENZYL METHACRYLATE COPOLYMER
Barim, Esra; Gundogdu, Emrah
In this study, the P(N-vinyl carbazole-co-benzyl methacrylate) copolymer was synthesized, characterized by FT-IR/1H-NMR spectroscopic methods, and its composition was calculated from 1H NMR spectra. Composites of the copolymer with four different ratios of graphite (GR) and MAX phase (Ti3AlC2) by weight were prepared to obtain functional and novel electronic components for energy storage applications. Scanning electron microscopy, X-ray diffraction analyses were performed for some samples. Differential scanning calorimetry, thermogravimetric analysis curves were used to determine the thermal behavior of the materials. It was concluded that the composite with the highest glass transition temperatures and thermal stability was the composite with 10wt%GR/10wt%MAX additive. The thermal degradation kinetics of the copolymer and the composite containing 10wt%GR/10wt%MAX were investigated by applying the Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS) methods and it was found that the thermal degradation activation energy of the composite was lower than that of the polymer. The dielectric properties of the materials were investigated at room temperature and between 0.1 kHz and 5 kHz. At 1 kHz the dielectric constants of the copolymer and 10wt%GR-doped composite were found to be 2.22 and 12.31, respectively. The composites doped with 10wt%GR and 10wt%GR/10wt%MAX were confirmed to be semiconductors.
- MakaleAçık Erişim2025Scopus SJRQ2Enhanced In Vitro Bioaccessibility and Anticancer Activity of Brazilian Propolis Extracted with L-Lactic Acid Caglar Doguer
Doguer, Caglar; Ceylan, Fatma Duygu; Capanoglu, Esra; Adrar, Nabil; Boeluek, Esra; Atayoglu, Ali Timucin; Uzun, Suzan; Palabiyik, Ibrahim
AtıfOpenAlex7İncele - MakaleAçık Erişim2025On Wijsman fρ-Statistical Convergence of Order α of Modulus Functions
Turan, Gulcan Atici; Et, Mikail
In the present paper, we introduce and investigate the concepts of Wijsman f rho-statistical convergence of order alpha and Wijsman strong f rho-convergence of order alpha. These notions are defined as natural generalizations of classical statistical convergence and Wijsman convergence, incorporating the tools of modulus functions and natural density through the function f. We provide a detailed analysis of their structural properties, including inclusion relations, basic characterizations, and illustrative examples. Furthermore, we establish the inclusion relations between Wijsman f rho-statistical convergence and Wijsman strong f rho-convergence of order alpha, showing conditions under which one implies the other. These notions are different in general, while coinciding under certain restrictions on the function f, the parameter alpha, and the sequence rho. The results obtained not only extend some well-known findings in the literature but also open up new directions for further study in the theory of statistical convergence and its applications to analysis and approximation theory.
AtıfWoS1OpenAlex1İncele - MakaleAçık Erişim2025Advanced Classification of Poxvirus-Based Skin Diseases Using Deep Learning Techniques
Arik, Kaan; Agdas, Mehmet T.; Korkmaz, Adem; Kosunalp, Selahattin; Iliev, Teodor
Viral infections, especially those of the poxvirus family, present significant diagnostic challenges due to their similar clinical symptoms. This study proposes an innovative deep learning-based approach to classify six categories of poxvirus-related skin diseases: chickenpox, cowpox, healthy, measles, monkeypox, and smallpox. A dataset of 9,120 augmented images was used to train, validate, and test three advanced deep-learning models-YOLOv8, YOLOv5, and ResNet32. Among the models, YOLOv8 demonstrated superior performance, achieving an accuracy of 99.80%, precision of 99.28%, and recall of 99.14%, significantly outperforming YOLOv5 and ResNet32. The results underscore the potential of YOLOv8 in medical image analysis, providing a robust and efficient tool for the early detection and accurate classification of viral skin diseases. Comparisons with related studies highlight the effectiveness of the proposed approach, making it a state-of-the-art solution for improving diagnostic accuracy in healthcare. Future work will focus on extending the dataset and evaluating the model's applicability in real-time clinical environments.
AtıfOpenAlex1İncele - BildiriAçık Erişim2025LLM-Based Video Analytics Test Scenario Generation in Smart Cities
Yilmazer, Merve; Karakose, Mehmet
Rapid advances in the field of artificial intelligence have made significant contributions to the automation of software development and testing stages. Software created for use in various fields is tested with test scenarios created manually by software test experts or using test automation. Testing large-scale software with these methods complicates the testing phases because it requires increased human intervention and includes complex applications. In this study, an LLM-based scenario generation framework enhanced with prompt engineering is proposed for testing software to be used for video analysis in smart cities and smart campus areas. Thus, software test scenarios are created by strengthening large language models that are fast, flexible and have high learning ability using prompt engineering techniques. Test scenarios produced through LLM reinforced with prompt engineering techniques were evaluated with rarity and reality metrics and it was determined that more robust scenarios were produced compared to randomly generated test scenarios in the relevant field.
AtıfScopus3OpenAlex3
İncele - MakaleAçık Erişim2025Scopus SJRQ1Seismic Foresight: A Novel Multi-Input 1D Convolutional Mixer Model for Earthquake Prediction Using Ionospheric Signals
Uyanik, Hakan; Kokum, Mehmet; Senturk, Erman; Freeshah, Mohamed; Ozcelik, Salih T. A.; Halil Akpinar, Muhammed; Celik, Serenay; Sengur, Abdulkadir
This study proposes a novel deep learning approach for predicting significant earthquakes (Mw ≥ 5.0 ) in Turkey using ionospheric Total Electron Content (TEC) data and space weather indices. ConvMixer is a lightweight CNN architecture that blends spatial and channel information using depthwise convolutions and pointwise layers. Inspired by vision transformers, it offers efficient image classification with fewer parameters and high performance. We developed a multi-input one-dimensional convolutional mixer (MI-1D-ConvMixer) model to classify TEC data from the preceding five consecutive days as either precursory to an earthquake on the 6th day or normal. The model incorporates six inputs: five 1D TEC signals and one 1D space-weather index array, including the global geomagnetic index (Kp), storm duration distribution (Dst), sunspot number (R), geomagnetic storm index (Ap-index), solar wind speed (Vsw), and solar activity index (F10.7) are also utilized to reveal non-seismic related pre-earthquake ionospheric variations. Our methodology involves two stages: 1) a preprocessing stage to enhance TEC signals and 2) an end-to-end training of the MI-1D-ConvMixer model. The model architecture features depth-wise and point-wise convolutions with patch embedding, utilizing uses four tunable hyperparameters: network depth, hidden dimension size, kernel size, and patch size. We used 196 earthquakes data from Turkey from 2010-2023, and TEC data from the TNPGN-Active GNSS stations. The dataset was split into 75% for training and 25% for testing. Performance metrics, including classification accuracy, sensitivity, specificity, and F1-score, are used for evaluation. Our model achieved a classification accuracy of 97.49%, demonstrating its potential for earthquake prediction systems. This research contributes to the field by introducing a novel deep learning architecture specifically designed for integrating TEC and space weather data for earthquake prediction. Future work should focus on validating the model’s performance in different geographical regions and investigating its limitations.
AtıfScopus7OpenAlex5İncele - MakaleAçık Erişim2025Scopus SJRQ4A research on effect of certificate trainings on pre-service teachers' awareness of psychological resilience
Çankaya, Ibrahim; Balikçi, Servet; Bek, Hafiz
The aim of this research is to determine whether certification training has a significant effect on pre-service teachers' awareness. In the research, the awareness level of pre-service teachers who participated in psychological resilience training was compared. The research is a one-group pre-test post-test quasi-experimental research design. The research group consisted of 25 pre-service teachers who participated in the psychological resilience trainings organized by Uşak University Lifelong Learning Center in the spring semester of the 2024-2025 academic year. The research group received resilience awareness training consisting of two sessions and lasting 1.5 weeks. Data were collected using the brief psychological resilience scale developed by Doğan. It was determined that there was a significant difference (p < .05) between the psychological resilience awareness levels of the students before and after the certificate training. In the 21st century, certificate trainings will be provided in addition to the university diploma in order to provide the skills that institutions and the business world care about. Certificates will be among the primary reasons for teacher selection.
AtıfScopus2OpenAlex2İncele - MakaleAçık Erişim2025Scopus SJRQ4Comparison between traditional models and artificial neural networks as estimators of the growth of the Tigris scraper Capoeta umbla (Teleostei: Cyprinidae) in the Munzur River, Turkey; [Comparación entre modelos tradicionales y redes neuronales artificiales como estimadores del crecimiento del raspador del Tigris Capoeta umbla (Teleostei: Cyprinidae) en el río Munzur, Turquía]
Ozcan, Ebru Ifakat; Serdar, Osman
In this study, a comparison of traditional growth methods (lengthweight relationships and von Bertalanffy growth function) with artificial neural networks in growth models was carried out in the growth of 783 specimens of Capoeta umbla from the Munzur River, Turkey from September 2019 to May 2021. The lengthweight relationships of C. umbla W = 0.0085L3.013 R2=0.943 was determined for all individuals. The ages of the specimens were from 0 to 11 years old. The von Bertalanffy growth function was Lt = 46.15 [1-e-0.139 (t + 2.57)] and Wt = 856.32 [1-e-0.139 (t + 2.57)]3.013 for all individuals. Ф’ value was 2.471 all individuals. The training stopped and the best validation performance was fixed at 8.1473 × 10-5 at epoch 42. The validation checks were reached as 6, at epoch 48 and the gradient = 5.6566 × 10-5, at epoch 48. The target output R value was 0.98584 for training, 0.98969 for validation, 0.98757 for testing and 0.9868 for all. The calculated MAPE values were 0.140 and 0.578 for artificial neural networks, 1.168 and 2.726 for length–weight relationships, 5.721 and 4.013 for von Bertalanffy growth function, respectively. The calculated SSE values for length and weight were 0.0128 and 30.864 for artificial neural networks, 1.3985 and 350.786 for length–weight relationships. The results of the present show that artificial neural networks can be superior estimators than length–weight relationships and von Bertalanffy growth function. Therefore, artificial neural networks models are an effective tool to describe body weight and length in fish.
- MakaleAçık Erişim2025Scopus SJRQ2Maximizing performance in child footballers: chronotype and time of day study
Kaba, Ilknur; Engin Çelikel, Baha; Adanur, Oğuzhan; Yılmaz, Coşkun; Yonca Sezer, Süreyya; Tan, Çetin; Durhan, Tebessüm Ayyıldız; Özer, Uğur; Ceylan, Tülay
Background: A limited number of studies have investigated the effects of circadian rhythm-based running exercise interventions on physical fitness in child athletes. This study aimed to investigate the effects of an eight-week morning and evening running program on lower extremity strength, agility and respiratory function in 10–12-year-old male footballers. Methods: Participants visited the laboratory three times, with one-day intervals before and after the training program. The assessments included maximal inspiratory pressure (MIP), maximal expiratory pressure (MEP), forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and the FEV1/FVC ratio. Additionally, agility and functional performance tests (FPTs) were conducted for both the dominant and non-dominant legs. Results: The findings indicated that morning running was more effective than evening running in enhancing respiratory function. Morning running also showed superior results in lower extremity strength tests, particularly in the single-leg (SL) and triple-leg (THD) crossover hop for distance tests (CHDs) and the 6-m timed-hop test (6 m THT). Furthermore, the agility performance of the morning running group was significantly better than that of the evening and control groups. Conclusion: Consequently, morning running interventions had a positive impact on key physical fitness parameters, including respiratory muscle strength, respiratory function, agility, and lower extremity strength in child footballers.
- MakaleAçık Erişim2025Scopus SJRQ4The effect of the pesticide Klaxon on the oxidative stress and the antioxidant responses of the Zebra mussel (Dreissena polymorpha); [El efecto del pesticida Klaxon sobre el estrés oxidativo y las respuestas antioxidantes del mejillón cebra (Dreissena polymorpha)]
Ozcan, Ebru Ifakat
Klaxon pesticide represents a novel generation of insecticide employed in the control of diseases, pests and weeds in select agricultural regions. Pesticides that enter the aquatic environment indirectly have a detrimental impact on the organisms that inhabit this environment, and humans are ultimately exposed to these chemicals through the food chain. The present study investigated the toxicity of the klaxon pesticide in Dreissena polymorpha, a suitable bioindicator of water pollution, through the analysis of oxidative stress and metabolic biomarkers. The effects of klaxon at concentrations of 0.01, 0.15 and 0.30 mg·L-1 on oxidative stress and antioxidant changes in D. polymorpha were determined over a 24 – and 96–hour period. Enzyme–linked immunosorbent assay (ELISA) kits were employed to quantify the activities of superoxide dismutase (SOD), glutathione peroxidase (GPx), catalase (CAT) and thiobarbituric acid (TBARS), as well as to assess the levels of reduced glutathione (GSH). ELISA kits were used to determine results. Statistical evaluation of biomarker analyzes was performed using the SPSS 24.0 package program one–way ANOVA (Duncan 0.05) test. Significant decreases in GSH levels (P<0.05); significant increases in TBARS levels (P<0.05) were observed. Significant decreases (P<0.05) in SOD, CAT and GPx activities were observed. Considering the study data, it was determined that the klaxon pesticide penetrating the body of the living organism caused oxidative stress and changes in enzyme activities in D. polymorpha.
AtıfScopus1WoS1İncele - MakaleAçık Erişim2025Scopus SJRQ4Effects of chlorpyrifos on the freshwater mussel Unio elongatulus eucirrus (Bourguignat, 1860), with a focus on neurotoxicity and oxidative stress responses; [Efectos del clorpirifos en el mejillón de agua dulce Unio elongatulus eucirrus (Bourguignat, 1860), con especial atención a la neurotoxicidad y las respuestas al estrés oxidativo]
Zorlar, Faruk; Şeker, Engin; Pala, Ayşegül
This study set out to investigate the effects of the organophosphate insecticide chlorpyrifos (CPF) on certain biochemical parameters of the freshwater mussel Unio elongatulus eucirrus. Mussels were exposed to varying concentrations of CPF (10, 20, and 40 μg·L-1) for duration of 96 hours. Samples were collected from the mussels at the 24th and 96th hours of the experiment. The results indicated that exposure to CPF concentrations led to a decline in the activities of acetylcholinesterase (AChE), superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) activities and, accompanied by an increase in malondialdehyde (MDA), and decreased reduced glutathione (GSH) levels in mussels. In conclusion, the present study demonstrates that CPF caused AChE inhibition, formation of oxidative stress, and negative effects on certain antioxidant parameters in the freshwater mussel U. elongatulus eucirrus.
- MakaleAçık Erişim2025Scopus SJRQ3Establishing a link between the chemical composition and biological activities of Gladiolus italicus Mill. from the Turkish flora utilizing in vitro, in silico and network pharmacological methodologies
Zengin, Gokhan; Cetiz, Mehmet Veysi; Abul, Nurgul; Gulcin, Ilhami; Caprioli, Giovanni; Piatti, Diletta; Ricciutelli, Massimo; Koyuncu, Ismail; Yuksekdag, Ozgur; Bahşi, Muammer
Objectives: Five solvent extracts (n-hexane, ethyl acetate, ethanol, ethanol/water (70%), and water) of Gladiolus italicus Mill. from Turkey were evaluated for chemical and biological properties. Methods: Antioxidant activities, inhibitory properties against key enzymes involved in the etiology of chronic diseases were tested, as well as cytotoxic effects on different cell lines. Chemical characterization was also carried out to determine the most abundant compounds of each extract. Results: The highest total phenolic content (TPC) was observed in the water extract while highest TFC in ethanol/water extract. The most abundant compounds in the extracts were hyperoside (69041.06 mg kg−1), isoquercitrin (46239.49 mg kg−1), delphindin-3,5-diglucoside (42043.81 mg kg−1), myricetin (21486.61 mg kg−1), and kaempferol-3-glucoside (21199.76 mg kg−1). Molecular dynamic (MD) simulations confirmed the structural stability and dynamic conformational integrity of these complexes over a period of 100 ns. In network pharmacology, A total of 657 unique target genes were screened: 52 associated with programmed cell death-1 (PD-1), 85 with vascular endothelial growth factor receptor-2 (VEGFR2), and 130 with fibroblast growth factor receptor-2 (FGFR2), identifying crucial gene interactions for these proteins. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted, revealing significant interactions and pathways such as the advanced glycation end products (AGE) and their receptors (RAGE) signaling pathway in diabetic complications and T- helper 17 (Th17) cell differentiation, among others. This elucidation of complex networks involving key genes like AKT Serine/Threonine Kinase 1 (AKT1), MYC proto-oncogene (MYC), tumor protein 53 (TP53), Interleukin 6 (IL6), and tumor necrosis factor (TNF) provides a promising foundation for the development of targeted therapies in the treatment of non-communicable diseases. Conclusion: These results show that G. italicus could be a natural source of potent antioxidants and enzyme inhibitors which need to be further explored for the development of biopharmaceuticals.
AtıfScopus15OpenAlex13
İncele - BildiriAçık Erişim2025Toplam Elektron Içeriǧi ve Uzay Iklim Verileri Kullanilarak Transfer Öǧrenme ile Deprem Öncüllerinin Analizi
Uyanik, Hakan; Şentürk, Erman; Köküm, Mehmet; Özçelik, Salih Taha Alperen; Akpinar, Muhammed Halil; Şengür, Abdulkadir
The stress changes occurring in the Earth's crust before earthquakes may cause some anomalies in the ionosphere and cause significant changes in the Total Electron Content (TEC) and Space Climate (SCC) parameters. The analysis of these changes offers a significant potential in the detection of earthquake precursors. In this study, the analysis of earthquake precursors was performed using TEC and UC data and the effectiveness of transfer learning and machine learning techniques was investigated. Features were extracted from five-day TEC and UC data using a pre-trained Multi-Input One-Dimensional Convolutional Mixer Network (ÇG-TB-EMA) and these features were classified with different machine learning algorithms. Within the scope of the study, earthquakes with a magnitude of Mw≥6.0 that occurred during the low and high solar activity periods of the 24th solar cycle were analyzed. The earthquakes were selected from the Far East region between 10°S-45°N latitudes and 120°E-160°E longitudes, where intense seismic activity is observed. Experimental studies have shown that during the low solar activity period, support vector machines (SVM) and artificial neural networks (ANN) models exhibited the highest performance with 96.04% accuracy and 96.08% F1 score, respectively. During the high solar activity period, the classification success decreased slightly, and SVM and ANN models achieved the best results with 90.28% accuracy and 89.86% F1 score. These findings reveal that the effect of solar activity on ionospheric variables should be taken into account in earthquake precursor detection. For future studies, long-term analyses are recommended to better understand the effects of solar activity.
- MakaleAçık Erişim2025Scopus SJRQ3Effect of polymer modification on bitumen rheology: A comparative study of bitumens obtained from different sources
Özdemir, Ahmet Münir; Yalçln, Beyza Furtana; Yllmaz, Mehmet
The rheological and mechanical properties of bituminous binders vary significantly depending on the crude oil source. Consequently, the response of binders from different sources to polymer modification also differs. This study compares the rheological performance of B160/220 penetration-grade binders sourced from the Turkey-Batman and Iraq-Lanaz refineries, modified with styrene-butadiene-styrene (SBS), the most widely used polymer additive. To evaluate high-temperature performance, performance grade and frequency sweep tests were conducted using a dynamic shear rheometer. In addition to experimental assessments, the rheological behavior of the binders was analyzed using the Christensen-Anderson, Cross, and Carreau-Yasuda models. Time-temperature superposition principle master curves were generated to characterize their viscoelastic behavior. Zero shear viscosity (ZSV) values were determined using the Cross and Carreau-Yasuda models to examine the impact of polymer modification on binder viscosity. The findings indicate that the initial rheological properties of bitumen significantly influence its response to SBS modification. For instance, the G∗/sin δvalue increased by up to 199% at 64°C with 4% SBS addition, while the softening point rose by 9.5°C compared to unmodified binders. Modelled ZSV values showed more than a sevenfold increase in some cases, especially in Iraqi binders. On the other hand, at -18°C, the m-value dropped to 0.282 in the B-SBS4 binder, indicating a potential risk of low-temperature cracking. While polymer modification improved the rheological properties of both bitumen types, its effectiveness varied depending on the source.
AtıfScopus8WoS8OpenAlex7İncele - MakaleAçık Erişim2025Scopus SJRQ2Evaluation effect of physicochemical properties of deep eutectic solvents on phenolic compounds extraction yield from Kultik seed
Aydin, Çağlar Mert
The aim of this study is to achieve maximum phenolic component extraction efficiency by using deep eutectic solvent, and to gain higher extraction efficiency than that obtained using conventional solvent from fruit waste, namely Kultik seed (Cucumis melo L.). Six DES (deep eutectic solvent) combination were formed using zinc chloride, ethylene glycerol, lactic acid, choline chloride, sorbitol and glucose. The evaluated DES properties were viscosity, pH, %brix and refractometric index, and their effect on phenolic extraction. Overall, the forming components significantly influence DES properties, indicating importance of choosing proper components in DES formation to receive desired extraction result. There was a correlation between extraction yield and DES properties (brix%, pH and viscosity), showing adjusting these properties are crucial in yield of desired phenolic extraction yield, r > 0.5. Alcohol based DESs had lower viscosity, higher brix% and pH in the range of 3–5. Sugar based DESs had higher viscosity, lower brix% and pH other than the range of 3–5. The highest phenolic extraction efficiency was obtained in extraction using alcohol based DESs as solvent, while the extraction using sugar and carboxylic acid based DESs underperformed. Furthermore, the extractions using some DES types (zinc chloride: ethylene glycerol (149.5 mg GAE 100 g−1), choline chloride: ethylene glycerol (161.5 mg GAE 100 g−1)) achieved better phenolic yield than that obtained using conventional solvents (water (7,6 mg GAE 100 g−1), methanol (80.2 mg GAE 100 g−1), ethanol (138.7 mg GAE 100 g−1)). These results indicate that DESs, as a green solvent, provide excellent alternative to organic solvents for green chemistry, and have a great potential to use in industrial applications involving extraction of bioactive compounds from plant sources.