Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Article
    A Multidimensional Comparative Analysis of Human Expert vs. AI-Driven Feedback Approaches on Learner-Centered and Collaborative Groups
    (Routledge, 2026) Yıldız Durak, H.; Onan, A.
    The aim of this study is to examine the multidimensional effects of AI-based feedback in learner-centered and collaborative learning environments among university students. The study employed a five-group experimental design: two individual learning groups receiving either AI-based feedback(G1) or human expert feedback(G2), two collaborative learning groups receiving either AI(G3) or human expert feedback(G4), and control group(G5). According to the research results, G4 showed the highest level of development in the areas of creative problem solving, internal-external motivation, and critical thinking. G1 was the group with the highest performance, particularly in terms of system interaction, completed activities, and assignments. In contrast, G2 showed the lowest results in terms of both cognitive development and learning analytics. AI-based feedback in collaborative learning environments provided the highest development in cognitive skills, while AI-based in individual work was more effective in increasing system participation. Factorial MANCOVA indicated significant interactions between learning environment and feedback type on posttest outcomes, with strongest effects on self-efficacy, intrinsic motivation, and flexibility. These results show that AI-based feedback has different effects in both individual and collaborative learning contexts. Qualitative thematic analysis highlighted themes of cognitive facilitation, creativity enhancement, feedback quality perceptions, and environment preferences. © 2026 Informa UK Limited, trading as Taylor & Francis Group.
  • Article
    Valorization of Recycled Waste in Green/White Purification and LC-QTOF/MS Analysis of Beverages Adulterated with Incapacitating Drugs
    (Elsevier B.V., 2026) Anilanmert, Beril; Yonar, Fatma Cavus; Er, Elif Ozturk; Pekcaliskan, Elif Yılmaz; Cengiz, Salih
    Incapacitating drugs constitute a growing threat for the community, since victims may drink adulterated beverages without noticing. A validated eco-friendly/economical purification/analysis kit prototype, along with an LC-QToF/MS method has been developed in coke and mixed fruit-juice, for simultaneous determination of 10 drugs used for incapacitating victims (zaleplone, zolpidem, zopiclone, mephedrone, fentanyl, phenytoin, thiopental, sertraline, ketamine and GHB). A combination of two different waste nut-shells which yielded the highest recovery for these drugs were directly used as adsorbent after grinding and modification and a reusable separation apparatus recycled from waste were utilized for the first time in a toxicological analysis. In the method, after adding the adsorbent on to the sample, pH was adjusted. Following 25-min (min) automatic vortexing for adsorption, matrix was removed easily, using the separation apparatus. After 25-min desorption via cold ultrasonication using 500 μL methanol, a 9.5-min LC-QToF/MS analysis was performed. The validated method in fruit-juice and coke, extraordinarily gave successful results also in urine and saliva. Assessment tools for greenness/whiteness and pictograms confirmed the environmental friendliness of the method kit. © 2025 Elsevier B.V.
  • Article
    Reduced Phase Space Quantization and Quantum Corrected Entropy of Schwarzschild-De Sitter Horizons
    (Elsevier B.V., 2026) Jalalzadeh, S.; Moradpour, H.
    This paper investigates the quantization of the Schwarzschild–de Sitter (SdS) black hole (BH) using the Misner–Sharp–Hernandez (MSH) mass as the internal energy in a reduced phase space framework. After introducing the canonical variables of the reduced phase space, we derive a discrete spectrum for the surface areas of the BH event horizon (EH) as well as MSH masses. We utilized the MSH mass spectrum to obtain the entropy of the BH. The entropy of the BH and cosmic EHs reveals a logarithmic correction to the Bekenstein–Hawking term. Our results support the robustness of the logarithmic form of quantum corrections in SdS thermodynamics. © 2026 The Authors.
  • Article
    Interpretable Structural Modeling of MR Images Using Q-Bezier Curves: A Geometry-Aware Paradigm Beyond Deep Learning
    (Elsevier Science Inc, 2026) Ozger, Faruk; Onan, Aytug; Turhan, Nezihe; Ozger, Zeynep Odemis
    Magnetic resonance (MR) imaging plays a critical role in diagnostic workflows, yet its reliability is frequently compromised by scanner-dependent bias, contrast variability, and intensity drift. Although deep learning methods achieve high performance, they generally require extensive supervision and demonstrate limited robustness across diverse clinical settings. To address these challenges, we propose a transparent, geometry-aware framework for annotation-free MR enhancement based on q-B & eacute;zier curves. This model incorporates an adaptive deformation parameter q(x) that modulates local curvature, facilitating flexible adaptation to complex anatomical boundaries. The framework comprises three principal mechanisms: (i) adaptive q(x) for local responsiveness, (ii) monotone q-Bezier tone curves for intensity standardization, and (iii) Tikhonov-regularized optimization for smooth mapping. As a result, the operator remains interpretable, operates in linear time, and provides explicit control over smoothness. The proposed approach was validated across five public cohorts (BraTS, ACDC, PROMISE12, fastMRI, IXI), demonstrating significant improvements in image fidelity (SSIM, CNR, NIQE) and downstream segmentation accuracy (Dice, HD95) relative to variational filters and state-of-theart foundation models. Additionally, cross-vendor experiments confirm its robustness without the need for retraining. Collectively, these findings establish q-Bezier modeling as a principled, lightweight, and clinically interpretable alternative that complements deep learning by providing a geometry-aware pathway to robust MR representation.
  • Article
    FTIR Spectroscopy Coupled With Chemometrics for Evaluating Functional Food Efficacy in an in Vitro Model of Iron Deficiency Anemia
    (Elsevier Science Ltd, 2026) Dalyan, Eda; Cavdaroglu, Cagri; Ozen, Banu; Gulec, Sukru
    Vibrational spectroscopy offers a rapid, cost-effective approach for studying biological systems. This study employs Fourier Transform Infrared (FTIR) spectroscopy, combined with Soft Independent Modeling of Class Analogy (SIMCA), to evaluate treatment outcomes for iron deficiency anemia (IDA). The model was built using spectra from healthy and anemic cells, then validated with cells treated with commonly used iron supplements. In calibration, 9 of 10 control and all IDA samples were correctly classified; 14 of 15 validation samples were identified as healthy. The model was applied to cells treated with protein-iron complexes. All samples treated with a 60:1 protein-iron ratio matched the healthy group, while 3 of 4 treated with a 10:1 ratio matched the IDA group. These results were further supported by iron-regulated gene expression of transferrin receptor (TFR) and (Ankyrin Repeat Domain 37) ANKRD37. FTIR coupled with chemometrics enables rapid assessment of functional effects and shows potential for screening functional ingredients in anemia-targeted food products.
  • Article
    Ten Questions Concerning Circularity in the Built Environment
    (Pergamon-Elsevier Science Ltd, 2026) Kayacetin, N. Cihan; Aslanoglu, Rengin; Piccardo, Chiara; Afacan, Yasemin; Masera, Gabriele; Li, Qiuxian; Van Hoof, Joost
    The rapid urbanisation of our societies calls for an urban renewal movement, including developing new areas to accommodate housing facilities and services and regenerating existing urban areas. Yet, urban renewal projects pose trade-offs impacting both environmental and socio-economic aspects. The renovation and new construction of buildings can escalate the use of energy and material resources as well as increasing greenhouse gas emissions. The European Union plays a leading role in promoting the transition towards sustainable and inclusive cities, whereas other regions such as North America, Australia and Asia follow suit via Circular Economy Action Plans or Frameworks, highlighting the need to enhance resource efficiency in buildings through the use of durable and circular materials. Current research on resource efficiency in buildings follows the Circular Economy concept, which aims to reduce the use of raw materials and the waste of existing materials while retaining their value for as long as possible. However, the role of the circular economy in sustainable transition and the adoption of its principles in urban contexts remain unclear while its practical implementation still faces significant challenges, including the lack of analytical instruments and assessment methods as well as co-creative approaches. This 'Ten Questions contribution' provides an overview of the pressing issues concerning circularity in the built environment, the state-of-the-art and best practices, challenges and benefits, policies and regulations, as well as numerous strategies applied on the building and neighbourhood level, assessment methodologies and future trends.
  • Article
    AI-Supported Seismic Performance Evaluation of Structures: Challenges, Gaps, and Future Directions at Early Design Stages
    (Elsevier Sci Ltd, 2026) Ak, Fatma; Ekici, Berk; Demir, Ugur
    This study reviews 91 journal articles that intersect with earthquake-resistant building design and artificial intelligence (AI)- based modeling, utilizing machine learning, deep learning, and metaheuristic optimization algorithms. Previous reviews on AI applications have examined engineering problems without considering the impact of architectural design parameters and structural irregularities on seismic performance. This review discusses the role of AI in integrating architectural design variables and seismic performance objectives, highlighting challenges, gaps, and future directions in the early design phase. The reviewed articles demonstrate that AI is successful in addressing seismic performance objectives; however, a holistic framework for assessing architectural and structural variables has not been presented. The review highlights key findings, gaps, and future directions for those involved in earthquake-resistant building design utilizing AI.
  • Article
    Artificial Intelligence for Improving Thermal Comfort through Envelope Design in Residential Buildings: Recent Developments and Future Directions
    (Elsevier Science Sa, 2026) Bayraktar, Arda; Ekici, Berk
    Envelopes are vital components for improving thermal comfort in almost all building typologies. Yet, the design and analysis of envelopes are complex, as they involve multiple aspects and various parameters, ensuring comfort standards. Improving thermal comfort in residential buildings is within the scope of researchers to suggest sustainable design alternatives that consider multiple performance aspects and design parameters. Previous review articles have focused on improving thermal performance in residential buildings from the perspective of envelope technology, materials, and design strategies. However, none of them investigated current developments using artificial intelligence (AI), which inevitably supports decision-making in complex circumstances for a sustainable built environment. This review examines the contribution of AI methods, which consist of metaheuristic optimization and machine learning algorithms as sub-branches, to envelope parameters. The paper systematically reviews 95 relevant works on AI, including early approaches, to provide a comprehensive overview of current developments, following PRISMA guidelines. The results showed that early applications considered conventional approaches to improve thermal comfort and energy performance, which mostly limit the results to specified cases. On the other hand, studies utilizing AI methods dealt with numerous parameters, allowing them to cope with complex envelope systems in a reasonable amount of time. The study addresses relevant research questions related to the trends, research methods, system types, AI methods, data types, and their relation to performance and envelope parameters. The study also provides actionable insight, underlining gaps and future works for utilizing machine learning methods in the reviewed research domain.
  • Article
    Sustainable Recovery of Critical Raw Materials From Geothermal Igneous Systems: Geochemical, Mineralogical, and Techno-Economic Insights from the Dikili-Bergama Field (Western Anatolia, Turkiye)
    (Elsevier, 2026) Ayzit, Tolga; Baba, Alper
    The sustainable co-extraction of critical raw materials (CRMs) with renewable geothermal energy offers a dual pathway to support the circular economy and low-carbon transition. In this study, an integrated geochemical and mineralogical approach is used to comprehensively assess the recoverable lithium (Li) boron (B), strontium (Sr) and other critical raw materials in the geothermal reservoirs of the Dikili-Bergama region Turkiye. A geochemical analysis was carried out by systematic sampling and multi-element testing of geothermal water and reservoir rock. Hydrogeochemical studies of the geothermal fluids indicated the presence of remarkable concentrations of B (4.6 ppm), Sr (2.8 ppm) and Li (1.2 ppm), suggesting the possibility of active leaching processes in the deposit. Mineralogical studies using X-ray diffraction (XRD) have revealed a number of secondary mineral phases, such as quartz and labradorite, indicating the interaction between water and rock. These interactions affect not only the permeability and porosity of the deposit, but also the mobilization and precipitation of CRMs. A techno-economic analysis will be used to identify potential synergies that could improve the economic feasibility of geothermal projects in the region. The Monte Carlo simulation has shown that the Dikili-Bergama geothermal reservoirs have a potential of similar to 712 tons of Li. In this study, the CRM potential that emerged during the geothermal energy exploitation process in the region was calculated. The temporality and the process of obtaining are completely related to the extraction technology. This offers the dual benefit of renewable energy and strategic mineral extraction, contributing to sustainable resource management in volcanic environments.
  • Article
    The Effect of Layered Cover Plate Material on the Ballistic Performance of Ceramic Armors: Experimental and Numerical Study
    (Pergamon-Elsevier Science Ltd, 2026) Cellek, Seven Burcin; Tasdemirci, Alper; Cimen, Gulden; Yildiztekin, Faki Murat; Toksoy, Ahmet Kaan; Guden, Mustafa
    This study investigates the ballistic performance of silicon carbide (SiC) ceramic armor systems reinforced with single and hybrid metallic cover plates composed of Ti-6Al-4V (Ti64) and copper. Controlled ballistic experiments combined with validated LS-DYNA simulations were conducted to examine how cover-plate material, thickness, and stacking sequence influence penetration resistance, energy dissipation, and failure mechanisms. The experimental results revealed that metallic cover plates significantly enhance protection by improving projectile erosion and extending dwell time. While both Ti64 and copper single layers increased the antipenetration capability (APC) compared with bare SiC, hybrid configurations achieved the highest performance. The optimal design, consisting of a 2 mm Ti64 plate placed in front of a 1 mm copper plate, produced the greatest reduction in penetration depth and the highest APC value. Numerical analyses closely replicated the experimental trends and provided insight into stress-wave interactions, pressure evolution, and damage progression within the ceramic. The findings demonstrate that hybrid Ti64-Cu systems not only improve initial impact resistance but also redistribute energy toward the front layers, reducing stress transmission to the backing and mitigating catastrophic ceramic failure. The combined experimental and numerical results establish a clear design framework for developing lightweight, high-efficiency ceramic armor through tailored hybrid layering strategies.