Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
Browse
7 results
Search Results
Article Machine Learning Integrated Solvothermal Liquefaction of Lignocellulosic Biomass to Maximize Bio-Oil Yield(Elsevier Sci Ltd, 2025) Ocal, Bulutcem; Sildir, Hasan; Yuksel, AsliAccelerating consumption of limited fossil-based for economic growth and simultaneously mitigating greenhouse gas emissions create a dilemma that is waiting to be solved by researchers. In this context, solvothermal liquefaction of lignocellulosic biomass to produce bio-oil is a promising way to obtain green energy. However, maximizing bio-oil is challenging to optimize the operating parameters employing conventional techniques due to the complexity and non-linearity of the process. Lately, machine learning approaches have become powerful tools for addressing complex nonlinear problems by predicting process behavior and regulating operating parameters for optimization by learning from datasets. The current research demonstrates integrating experimental and a developed artificial neural network model to optimize solvothermal liquefaction of pinus brutia, based on temperature, water fraction, and biomass amount in maximizing bio-oil generation for the first time. The highest bio-oil yields were obtained at 31.40 %, 18.68 %, and 39.69 %, respectively, with 4 and 8 g biomass in the presence of water, ethanol, and water/ethanol mixture at 240 degrees C. Under the model conditions, the maximum biooil yield was experimentally verified at 46.20%, which was predicted at 48.8 %. Beyond providing accurate yield predictions, the approach highlights the potential of date-driven modeling to reduce experimental workload and cost while aiding parameter selection to improve efficiency. These outcomes emphasize the importance of machine learning integration into liquefaction process, providing remarkable results for future process design, optimization, and scalability. On the other hand, the study also includes characterization results (ultimate, proximate, FTIR, and GC-MS) of selected products and pinus brutia.Article Citation - WoS: 1Citation - Scopus: 1Dealing With Divergent Feedback Trajectories in Video-Mediated, Transnational, and Collaborative Task Design Meetings(Elsevier Sci Ltd, 2025) Colak, Fulya; Balaman, UfukThis study investigates mutual pedagogical decision making among transnational groups of preservice teachers (from Austria and T & uuml;rkiye) involved in finalizing the design of telecollaborative tasks after receiving multimodal feedback from different teacher educators. Within the scope of a Virtual Exchange project, while the teacher educator from the Turkish university conducted a large-group, whole-class, video-mediated meeting offering feedback, the teacher educator from the Austrian university preferred delivering written feedback. Examining the screen-recordings of pre-service teachers' video-mediated meetings and the diverse feedback sources, we found that the divergent feedback trajectories provide opportunities for pedagogical design-related decision making and meaning negotiation for pre-service teachers. The findings also show the synergies between the multilayered frameworks of participation and engagement in situ and bring new insights into the interactional management of video-mediated learning environments.Article Citation - WoS: 2Citation - Scopus: 3Unlocking the Biological Potential of Emulsion-Templated Matrices Through Surface Engineering for Biomedical Applications(Elsevier Sci Ltd, 2025) Sert, Emircan; Ozmen, Ece; Owen, Robert; Dikici, Betul AldemirEmulsion templating is a highly advantageous route for the fabrication of porous materials, enabling the development of matrices with high porosity, high interconnectivity, and precise morphological control. Synthetic polymers are most widely used in the fabrication of emulsion-templated tissue engineering scaffolds due to their superior mechanical strength, ease of fabrication, control over polymer properties, and batch-to-batch stability. The biological response is strongly associated with the surface properties of the biomaterials; however, scaffolds constructed from synthetic polymers often lack cell recognition sites and exhibit limited bioactivity. Thus, synthetic polymer-based porous matrices commonly require surface post-modification to improve cell adhesion, proliferation, migration, gene expression, and differentiation processes. To date, extensive work has been carried out investigating surface modification of scaffolds fabricated via traditional scaffold fabrication techniques. Still, studies addressing the post-modification of emulsion-templated matrices are comparatively limited despite an exponential increase in the number of publications on emulsion templating for tissue engineering in recent years. This review will first examine the fundamentals of emulsion templating, then describe cell adhesion and the characteristics of scaffolds that influence cell-material interactions. It will then provide a comprehensive analysis of surface modification techniques and recent advancements in surface-modified emulsion-templated matrices for tissue engineering applications. Finally, we address the challenges and future directions in this rapidly evolving field. We anticipate that this comprehensive literature review will present the current state-of-the-art and serve as a valuable roadmap for researchers seeking to enhance the biological performance of their emulsion-templated scaffolds through surface modifications. Such scaffold optimisation strategies not only improve cell-material interactions but also hold translational potential for advancing human healthcare through more effective regenerative therapies.Article Citation - WoS: 1Citation - Scopus: 2Scalable Growth of Optically Uniform Mows2 Alloys by Sulfurization of Ultrathin Mo/W Stacks(Elsevier Sci Ltd, 2025) Panasci, Salvatore Ethan; Schiliro, Emanuela; Koos, Antal; Kutlu, Tayfun; Sahin, Hasan; Roccaforte, Fabrizio; Giannazzo, FilippoTwo-dimensional (2D) transition metal dichalcogenides (TMDs) ternary alloys, such as MoxW1-xS2, are very appealing for the possibility of continuously tuning their excitonic bandgap by the composition. However, the deposition of ultra-thin (monolayers or few-layers) alloys with laterally uniform composition on large area represents a main challenge of currently adopted synthesis methods. In this work, we demonstrated the growth of highly uniform Mo0.5W0.5S2 bi-layers on cm2 size SiO2/Si substrates by employing a simple and scalable approach, i.e. the sulfurization of a pre-deposited ultra-thin Mo/W stack at a temperature of 700 degrees C. Comparison of Mo(1.2 nm)/SiO2, W(1.2 nm)/SiO2, and Mo(1.2 nm)/W(1.2 nm)/SiO2 samples after identical sulfurization conditions revealed very different results, i.e. (i) a uniform monolayer (1L) MoS2 film, (ii) separated multilayer WS2 islands, and (iii) a uniform bilayer (2L) Mo0.5W0.5S2 film. This indicates how W surface diffusion and coalescence on SiO2 surface plays a main role in WS2 islands formation, whereas the reaction between S vapour with Mo films or Mo/W stacks represents the dominant mechanism for the formation of MoS2 and the MoWS2 alloy. Micro-photoluminescence (PL) mapping of the obtained 2L-Mo0.5W0.5S2 film showed an excellent uniformity of light emission on large area with an exciton peak at 1.97 eV, significantly blue-shifted with respect to PL emission of 1L-MoS2 at 1.86 eV. Such highly uniform optical properties make the grown MoWS2 alloy very promising for optoelectronic applications.Article Citation - WoS: 4Citation - Scopus: 4Surface Modification Via Alkali Treatment and Its Effect on the Physicochemical and Biological Properties of Emulsion Templated Scaffolds(Elsevier Sci Ltd, 2025) Kocagoz, Mehmet; Tihminlioglu, Funda; Dikici, Betul AldemirEmulsion templating is an advantageous scaffold fabrication technique that provides high interconnectivity, high porosity, and control of the scaffold architecture. Polymerised emulsions with an internal phase ratio greater than 74 % are named Polymerised High Internal Phase Emulsions (PolyHIPEs). Polycaprolactone (PCL) is a synthetic, biodegradable, and biocompatible polymer widely used in tissue engineering, but the material-cell interaction of PCL-based biomaterials has been found to be limited due to the material's high hydrophobicity. This study aims to develop emulsion-templated polycaprolactone tetramethacrylate (4PCLMA)-based scaffolds and improve their biological performance using an alkaline surface modification method. For this purpose, 4PCLMA was successfully synthesised, and highly porous scaffolds were developed. PolyHIPEs were incubated in three different sodium hydroxide (NaOH) concentrations for three different incubation times. Chemical, morphological, mechanical characterisation, mass loss, water absorption capacity, water contact angle, Brunauer-Emmett-Teller analyses and biological investigations were conducted on NaOH-treated scaffolds in comparison with the control. The chemical changes induced by NaOH treatment in PolyHIPEs were confirmed by Fourier-transform infrared spectroscopy. NaOH treatment increased the water absorption capacity, hydrophilicity, surface area, and protein adsorption but decreased the weight and mechanical strength of the scaffolds. In vitro results showed that NaOH treatment did not cause cytotoxicity in L929 cells and positively affected the cell adhesion and proliferation behaviour of Saos-2 cells. This study suggests surface modification of biodegradable synthetic polymer-based PolyHIPEs by NaOH treatment as a simple, scalable and cost-effective approach to enhance cell-material interactions of the material without causing a significant change in the overall morphology, contributing to the advancement of next-generation healthcare technologies.Article Citation - WoS: 2Citation - Scopus: 2Temporal Electroencephalography Features Unveiled Via Olfactory Stimulus as Biomarkers for Mild Alzheimer's Disease(Elsevier Sci Ltd, 2025) Olcay, Bilal Orkan; Pehlivan, Murat; Karacali, BilgeAim: Our primary aim is to capture and use the timings of the characteristic brain responses to olfactory stimulation for mild Alzheimer's disease diagnosis purposes. Proposed method: Our method identifies the timings of short-lived signal segments where characteristic distances between pre- and post-stimulus relative spectral energies are attained for each EEG channel and frequency band. These timings and timing-derived features were subsequently used in a leave-one-subject-out cross-validation scenario to assess the diagnostic performance of our framework. We evaluated seven distinct statistical distance measures to determine the most effective one for characterizing the neurological conditions of the subjects. Results: The average cross-validation performance shows that our framework achieved 87.50% diagnosis performance. The frequently used features were mainly derived from the delta and alpha activity of the prefrontal region (Fp1) and the beta activity of the parietal region (Pz), which agree with the current findings of olfaction biophysics. Comparison with existing methods: We compared the performance of our method with that of four existing methods in the literature. Our method outperformed these four methods. Moreover, our method elicited the highest accuracy when the clinical olfactory score (UPSIT) was included as a feature. Conclusions: Our analysis framework reveals a significant alteration of the timing organization of the brain that emerged upon olfactory stimulation in Alzheimer's patients. The timings of characteristic response and the features calculated via these timings contribute to Alzheimer's disease diagnosis performance remarkably. The perspective proposed here may facilitate early diagnosis, thereby facilitating the exploration of novel therapeutic and treatment strategies.Article Citation - WoS: 6Citation - Scopus: 10Using Chemosensory-Induced Eeg Signals To Identify Patients With <i>de Novo</I> Parkinson's Disease(Elsevier Sci Ltd, 2024) Olcay, Orkan; Onay, Fatih; Ozturk, Guliz Akin; Oniz, Adile; Ozgoren, Murat; Hummel, Thomas; Guducu, CagdasObjective: Parkinson's disease (PD) patients generally exhibit an olfactory loss. Hence, psychophysical or electrophysiological tests are used for diagnosis. However, these tests are susceptible to the subjects' behavioral response bias and require advanced techniques for an accurate analysis. Proposed Approach: Using well-known feature extraction methods, we characterized chemosensory-induced EEG responses of the participants to classify whether they have PD. The classification was performed for different time intervals after chemosensory stimulation to see which temporal segment better separates healthy controls and subjects with de novo PD. Results: The performances show that entropy and connectivity features discriminate effectively PD and HC participants when olfactory-induced EEG signals were used. For these methods, discrimination is over 80% for segments 100-700 and 200-800 milliseconds after stimulus onset. Comparison with Existing Methods: We compared the performance of our framework with linear predictive coding, bispectrum, wavelet entropy-based methods, and TDI score-based classification. While the entropy- and connectivity-based methods elicited the highest classification performances for olfactory stimuli, the linear predictive coding-based method elicited slightly higher performance than our framework when the trigeminal stimuli were used. Conclusion: This is one of the first studies that use chemosensory-induced EEG signals along with different feature extraction methods to classify healthy subjects and subjects with de novo PD. Our results show that entropy and functional connectivity methods unravel the chemosensory-induced neural dynamics encapsulating critical information about the subjects' olfactory performance. Furthermore, time- and frequency-resolved feature analysis is beneficial for capturing disease-affected neural patterns.