WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/4465

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When Care Faces Violence: Anticipatory Grief, Chronic Vigilance, and Ambiguous Loss Among Street Dog Care-Givers in Istanbul
(MDPI, 2026) Yildirim, Mine
This article examines how Turkey's 2024 amendment to the Animal Protection Law reshapes volunteer caregiving for free-roaming dogs in Istanbul by reconfiguring the practical conditions under which care is sought, coordinated, and sustained. Drawing on 43 in-depth interviews and five months of fieldwork (1 July-30 November 2025), this study combines constructivist grounded theory with reflexive thematic analysis to trace how legal change is encountered through everyday governance interfaces and how these encounters reorganize caregivers' routines, capacities, and moral worlds. The analysis yields four interlocking findings. First, caregivers describe a temporality of living in pre-loss, in which anticipated removal, disappearance, and uncertain outcomes generate chronic vigilance, anticipatory grief, and ambiguous loss without closure. Second, caregiving is increasingly recalibrated as risk management: commitments persist, but intervention narrows through heightened exposure to complaints, reputational scrutiny, and fears that help-seeking may backfire. Third, institutional pathways-hotlines, shelter intake, and municipal responses-are experienced as discretionary and opaque, producing a fluctuating threshold between assistance and harm that conditions whether caregivers engage official systems at all. Fourth, this study identifies a recurring veterinary bottleneck at the street-clinic-recovery handover, where limited short-term holding capacity stalls treatment trajectories and displaces recovery labor into precarious domestic and informal spaces. Together, these findings argue that caregiver well-being is not ancillary to animal welfare governance but constitutive of it. It shapes the continuity of monitoring, the timeliness of intervention, and the everyday mediation through which coexistence is maintained under intensified legal and political pressure.
Tourism Marketing: The Experiential Perspective Conclusion
(Goodfellow Publishers Ltd, 2026) Kozak, Metin; Correia, Antonia
The Relationship between Orthographical Depth and Language Similarity / Dissimilarity and Bilingual Cognitive Advantages
(Hogrefe AG-Hogrefe AG suisse, 2025) Jeong, Haegwon; Sirolu, Demet; Secer, Ilmiye; Kiziloz, Burcu Kaya; Vurgun, Rozelin; Aktan-Erciyes, Asli; Ozalp, Dilara
The 2020 Sivrice Earthquake (MW6.8) and Its Seismotectonic Linkage to the 2023 Kahramanmaraş Earthquakes (MW7.8 and 7.6)
(Springer, 2026) Yalcin, Hilal Domac; Gunes, Yavuz; Kurcer, Akin; Budakoglu, Emrah; Elmaci, Hasan; Ozalp, Selim; Kayadibi, Onder
A series of earthquakes along the East Anatolian Fault Zone (EAFZ) started with the January 24, 2020, Sivrice (Elazığ) Earthquake (MW6.8) and culminated in the the catastrophic Kahramanmaraş Earthquakes (MW7.8 and MW7.6) on February 6, 2023. This study explores how the 2020 Sivrice event influenced the 2023 Kahramanmaraş earthquakes using field surveys and seismotectonic analyses.The 2020 earthquake, occurring in the northeastern part of Pütürge Segment, was followed by field surveys and Differential interferometry (DInSAR) analysis to determine fault geometry and slip distribution. Seismological studies, including moment tensor solutions, stress tensor analysis, and Coulomb stress changes, provided insights into the fault dynamics. Surface deformations were observed in a 50 km section of the Pütürge segment, showing R, R', T, P, and Y fractures typical of a left-lateral deformation zone. The moment tensor analysis revealed a left-lateral strike-slip fault trending N65 degrees E, with a minor normal component. The timing and location of the earthquakes, suggest that the rupture progresses bilaterally. The analysis of Coulomb stress changes showed that the 2020 event transferred stress to the Arıkonak sub-segment, the Yarpuzlu restraining double-bend, the Erkenek Segment of the EAFZ, as well as the Gerger and Narince Segments of the Southeastern Anatolian Thrust Zone. These areas were further stressed by the 2020 earthquake, setting the stage for the February 2023 Kahramanmaraş events. Thus, the 2020 Sivrice earthquake served as a trigger for the catastrophic 2023 earthquakes. The Arıkonak sub-segment, Gerger, and Narince segments are still potential sources of earthquake hazard.
Robust HMM-Based Remaining Useful Life Estimation Using a Ridge-Regularized EM Algorithm
(MDPI, 2026) Kucukdag, Halime Beyza; Kirkil, Gokhan; Hekimoglu, Mustafa
Estimating the remaining useful life (RUL) of engineering systems is crucial for maintenance planning and the reliability of complex mechanical units. Accurate RUL predictions support timely interventions and help to prevent unexpected failures. This study proposes a statistically robust framework that models degradation signals up to the end of life using a hidden Markov model (HMM) with a simple-failure structure and an absorbing terminal state. The proposed method estimates state-dependent linear emission parameters and transition probabilities using a ridge-regularized expectation-maximization (EM) algorithm. The ridge penalty stabilizes slope estimates under limited data, while a robust Huber-based scale estimator reduces sensitivity to outliers in the sensor-derived health indicator. RUL is computed as a weighted expected time to absorption, combining transient-state survival characteristics with smoothed posterior-state probabilities obtained via the forward-backward algorithm. This yields a low-variance state-aware estimator that preserves the probabilistic structure of the HMM. Simulation studies show that the proposed ridge-regularized EM significantly reduces parameter variance and improves predictive accuracy compared with the baseline weighted least squares EM (WLS-EM). A real-data case analysis demonstrates further improvements in RUL estimation accuracy and smoother, more reliable prediction trajectories. Overall, the framework provides a robust and interpretable approach for practical prognostics applications.
Quantum Information Flow in Microtubule Tryptophan Networks
(MDPI, 2026) Craddock, Travis J. A.; Gassab, Lea; Pusuluk, Onur
Networks of aromatic amino acid residues within microtubules, particularly those formed by tryptophan, may serve as pathways for optical information flow. Ultraviolet excitation dynamics in these networks are typically modeled with effective non-Hermitian Hamiltonians. By extending this approach to a Lindblad master equation that incorporates explicit site geometries and dipole orientations, we track how correlations are generated, routed, and dissipated, while capturing both energy dissipation and information propagation among coupled chromophores. We compare localized injections, fully delocalized preparations, and eigenmode-based initial states. To quantify the emerging quantum-informational structure, we evaluate the L1 norm of coherence, the correlated coherence, and the logarithmic negativity within and between selected chromophore sub-networks. The results reveal a strong dependence of both the direction and persistence of information flow on the type of initial preparation. Superradiant components drive the rapid export of correlations to the environment, whereas subradiant components retain them and slow their leakage. Embedding single tubulin units into larger dimers and spirals reshapes pairwise correlation maps and enables site-selective routing. Scaling to larger ordered lattices strengthens both export and retention channels, whereas static energetic and structural disorder suppresses long-range transport and reduces overall correlation transfer. These findings provide a Lindbladian picture of information flow in cytoskeletal chromophore networks and identify structural and dynamical conditions that transiently preserve nonclassical correlations in microtubules.
pH-Driven β2AR Dynamics Reveal Loop-Mediated Allosteric Communication
(Amer Chemical Soc, 2026) Sogunmez Erdogan, Nuray; Akten, E. Demet
Membrane protein structure and dynamics are highly sensitive to environmental conditions, including changes in pH that can alter the protonation states of ionizable residues and, in turn, influence local electrostatics and stability. Constant-pH molecular dynamics (CpHMD) provides a framework to explore such effects by allowing dynamic proton exchange during simulations. Here, we applied CpHMD at pH:6.5, 7.0, and 8.0, alongside conventional MD, to examine how pH variations may influence the local conformational behaviors of the beta 2-adrenergic receptor (beta 2AR). During the 1.2-mu s-long total simulation, loop regions rich in titratable residues, particularly ICL3 and ECL2, showed the strongest responses to protonation changes. CpHMD trajectories suggested a pH-dependent redistribution of loop flexibility and hydrogen-bonding patterns, producing a see-saw-like effect, while fixed-protonation Control runs showed more constrained behavior. Across all simulations, the key GPCR microswitches, such as the ionic lock, the Y-Y gate, the NPxxY and PIF motifs, and the Trp286-Phe290 toggle pair, stayed within the ranges expected for an inactive receptor. This suggests that pH changes mainly influence local loop motions in the inactive receptor without pushing it toward activation-like states. Finally, mutual information analysis on both C alpha atoms and dihedral angles revealed altered communication between the extracellular and intracellular loops under different pH environments. While limited in time scale, these results provide a computational perspective on how protonation dynamics can modulate the GPCR behavior and highlight the value of incorporating pH effects in molecular-level investigations.
Multi-Satellite Collaboration for Integrated Satellite Remote Sensing, Communications and Computing Networks: Usage Scenarios and Challenges
(IEEE-Inst Electrical Electronics Engineers Inc, 2026) Xiao, Ming; Lei, Lei; Panayirci, Erdal; Ma, Zheng; Lei, Xianfu; Zhang, Zhengquan
With the booming demands for real-time integrated space information services and the advanced satellite direct-to-X technology, it is a promising future to integrate satellite remote sensing, communications and computing in the form of integrated satellite networks (ISN), which directly provide space information services for users even without terrestrial networks. In this article, we firstly present typical usage scenarios and discuss the requirements for ISN. Subsequently, we present ISN architecture by considering heterogeneous satellites, homogeneous integrated satellites and their hybrid deployments. Furthermore, we study the key parts of designing ISN, including integrated satellite sensing and communications, and multi-satellite collaborative computing. To reduce computing delay, we propose a multi-satellite and satellite-terrestrial collaborative computing scheme together with partial offloading, which fully utilizes the computing capabilities of satellite edge computing, terrestrial cloud computing and user computing. Request and push modes are studied for ISN's satellite remote sensing services, where the former satisfies the personalized user service requests, while the latter actively distributes public information to users for such scenarios as public safety services. Finally, we highlight some technical challenges and future research directions.
Measurements of Acoustic Absorption of Baffles Comparing Edge Effect and Room Position
(INT Inst Acoustics & Vibration, 2025) Saher, Konca; Ozis, Feridun; Elban, Guven; Vergili, Suat
This study presents an experimental analysis of the acoustic absorption performance of suspended baffles, focusing on the influence of edge effect, and room position. Measurements were conducted in a 223 m(3) reverberation chamber according to ISO 354. The experimental setup included 120 x 20 cm baffles (spaced at every 30 cm) composed of high-density glass wool and thermally treated polyester felt. Key variables included three room positions (single wall, double wall and middle of the room), and three mounting configurations of edge cover (deep well, well and no-well) to assess performance variations. The methodology involved sound absorption measurements using pink noise excitation, eight omnidirectional microphones, and dodecahedron loudspeakers. The results revealed that the deep-well method minimized edge effects, leading to consistent absorption results across different room positions. In contrast, well and no-well configurations exhibited significant variations. Measurements at the room center consistently demonstrated higher absorption due to additional reflections, while configurations adjacent to two walls exhibited the lowest performance. Findings emphasize the importance of edge effect and mounting configurations in the measurement of acoustic efficiency. This study contributes to the understanding of baffle-based sound absorption in interior spaces.
Job Polarization: Evidence for Türkiye
(Open Library Humanities, 2026) Gulser, Evren; Yilmaz, Ensar
In this article, we examine labour market polarization dynamics in Türkiye. First, we use highly refined microdata to classify tasks - mainly abstract, routine and manual - to conduct analysis at the occupation-task level. Second, we find evidence for polarization driven by technological changes (the routinization hypothesis), education and increasing female employment in both low- and high-wage occupations. Lastly, we analyse the tasks performed by workers in their respective occupations and find that the occupational assignment of tasks determines their value, suggesting the existence of a structural task content.
High-Performance and Low-Power Quantum-Dot-Based Multiply-Accumulate Design for next-Generation Supercomputing Platforms (Vol 82, 207, 2026)
(Springer, 2026) Navimipour, Nima Jafari; Ahmadpour, Seyed-Sajad; Rasmi, Hadi; Zohaib, Muhammad
Geoecono Mics of the Indo-Pacific: A Multi-Faceted Perspective for Current and Future Situation of the Region and Global and Regional Relationships
(Ideal Kultur Yayincilik, 2024) Haskan, Sinan
Fractal Analysis of Cardiac Spectra
(Symmetrion, 2024) Arsan, Taner; Pekcan, Onder
Cardiac diseases are one of the main reasons for mortality in modern, industrialized societies, and they cause high expenses in public health systems. Therefore, it is important to develop analytical methods to improve cardiac diagnostics. The heart's electric activity was first modeled using a set of nonlinear differential equations. Variations of cardiac spectra originating from deterministic dynamics are investigated. Analyzing the power spectra of a normal human heart presents the His-Purkinje network, which possesses a fractal-like structure. Phase space trajectories are extracted from the time series graph of ECG. Lower values of fractal dimension, D, indicate dynamics that are more coherent. If D has non-integer values greater than two when the system becomes chaotic or strange attractor. Recently, the development of a fast and robust method, that can be applied to multichannel physiologic signals, was reported. The convolutional Neural Networks (CNNs) method was also applied to patient-specific ECG classification for real-time heart monitoring. This manuscript investigates two different ECG systems produced from normal and abnormal human hearts to introduce an auxiliary phase space method in conjunction with ECG signals for diagnosing heart diseases. Here, the data for each person includes two signals based on V(4 )and modified lead III (MLIII), respectively. The fractal analysis method is employed on the trajectories constructed in phase space, from which the fractal dimension D is obtained using the box-counting method. It is observed that, the second signals (i.e., MLIII) have larger D values than the first signals (i.e., V-4), predicting more randomness yet more information. The lowest value of D (i.e., 1.708) indicates the perfect oscillation of the normal heart, and the highest value of D (i.e., 1.863) presents the abnormal heart's randomness. Our significant finding is that the phase space picture presents the distribution of the peak heights from the ECG spectra, giving valuable information about heart activities in conjunction with ECG.
Everyday Life, Child Rearing, and Fatherhood in Ottoman Middle Class Families at the Turn of the 20th Century
(Routledge Journals, Taylor & Francis Ltd, 2026) Ozbek, Muge
Drawing on the personal diaries of two middle-class fathers, Memduh Bey and Ahmet Nedim Bey, this article explores the lived experience of fatherhood, child-rearing, and everyday life in the late Ottoman Empire. While existing scholarship has examined the modern family primarily through public discourse and prescriptive literature, this study utilizes rare ego-documents to reconstruct the private sphere. The analysis challenges the stereotype of the distant, authoritarian Ottoman patriarch, revealing instead fathers who were emotionally expressive, deeply engaged in domestic routines, and dedicated to their children's moral instruction. However, the article argues that this intimate fatherhood cannot be understood in isolation. It demonstrates that the fathers' ability to serve as playful companions and moral guides was structurally enabled by a gendered and classed infrastructure of care. This support system included extended kin networks, which provided essential material and emotional security, and the often-invisible labor of domestic workers and mothers, who absorbed the physical burden of daily childcare. By foregrounding these dynamics, the study illustrates how late Ottoman middle-class fatherhood was not merely a matter of sentiment, but a privileged role sustained by the labor of others. Consequently, this article contributes to the history of the Ottoman family and the global history of fatherhood by offering a textured understanding of late Ottoman middle-class fatherhood.
Citation - WoS: 22
Citation - Scopus: 19
Evaluation of Public Transportation Systems for Sustainable Cities Using an Integrated Fuzzy Multi-Criteria Group Decision-Making Model
(Springer, 2023) Canakcioglu, Mustafa; Kundu, Pradip; Kucukonder, Hande; Gorcun, Omer Faruk; Garg, Chandra Prakash
In this era of increasing demand for mobility and rapid urban growth, there is a pressing need for a public transit system that is safe, fast, reliable, well-connected, and sustainable. Furthermore, it is essential to reduce the external costs associated with urban transportation, including environmental pollution, noise, congestion, and accidents, to foster sustainable cities. Choosing the right urban transportation system can meet this goal, but it is not an accessible business for decision-makers in the face of several conflicting criteria and ambiguities in the evaluation process. To cope with this, the current paper suggests a multi-criteria group decision-making (MCGDM) framework consisting of fuzzy BWM (Best-Worst method) and fuzzy MAIRCIA (Multi-Attribute Ideal-Real Comparative Analysis) techniques. This extended MCGDM approach has been applied to evaluate six urban transport systems, namely, Trams, Light Rail Trams, Metro (Subway), Bus Rapid Transport, Commuter Trains, and Public Buses based on 11 selection criteria which we have determined after consultation with highly experienced professionals. The fuzzy BWM technique is employed to identify the weights of the criteria. The fuzzy MAIRCA technique is utilized for ranking the alternatives using the calculated weights of the criteria. The proposed approach's validation has been examined with an extensive robustness check. The study is conducted from a general perspective, i.e., not restricted to a particular city. However, with the identified selection criteria, the proposed decision-making procedure can be repeated for a specific city considering any specific requirements, constraints, or limitations of that city.
Blume-Capel Model in D= 1 with Long-Range Interactions: Giant Reentrance in the Finite-Temperature Tricritical Phase Diagrams
(Elsevier, 2026) Berker, A. Nihat; Artun, E. Can
The Blume-Capel model in one dimension with long-range power-law interactions is studied by renormalization-group theory. A series of finite-temperature tricritical phase diagrams is found, as a function of the power-law exponent of the power-law interactions. These calculated phase diagrams exhibit a giant reentrance in the form disorder-order-disorder as temperature is lowered. The first-order transition takes over the entire phase boundary at longest-range interactions, as a near-equivalent-neighbor regime is approached.
An Integrated TFN-MARCOS-SWOT Model for Multi-Criteria Evaluation of Digital Transformation and Maturity in Higher Education Institutions
(Pergamon-Elsevier Science Ltd, 2026) Kolemen, Cansu Sahin; Tirkolaee, Erfan Babaee; Sahin, Ersin; Gorcun, Omer Faruk
Digital transformation has become critical for today's universities' competitiveness and sustainable development. However, the success of digital transformation processes is directly related to investments in technological infrastructure, the accurate measurement of corporate digital maturity, and the effective management of these processes. This study aims to comprehensively evaluate digital maturity and the effectiveness of digital transformation processes in universities with a Multi-Criteria Decision-Making (MCDM) approach. To accurately address the ambiguity arising from uncertainty and expert judgments, Triangular Fuzzy Numbers (TFNs) and the Measurement Alternatives and Ranking according to Compromise Solution (MARCOS) method are combined. In addition, a SWOT analysis is performed to systematically specify the strengths, weaknesses, opportunities, and threats that shape the strategic digital transformation directions of universities. The developed model is then applied to a set of criteria wherein universities are assessed under various dimensions, such as digital infrastructure, human resources, governance, digital culture, and innovation. The findings reveal that universities with high levels of digital maturity can carry out their digital transformation processes more effectively and sustainably. It is also demonstrated that the proposed methodology is able to efficiently deal with strategic planning of digital transformation and maturity in higher education institutions.
Citation - WoS: 1
A Hybrid Deep Learning Framework Using Synthetic Oversampling, Autoencoder, Convolutional Neural Networks, and an Attention Mechanism for Credit Card Fraud Detection
(Springer Nature, 2025) Kiaei, Ali Akbar; Navimipour, Nima Jafari; Pour, Narges Mohammadali; Heidari, Arash; Zavvar, Mohammad; Jafari, Mojtaba
Credit card fraud is still a big problem for banks and other financial organizations throughout the globe. It hurts consumer confidence and financial stability. Despite significant progress in fraud detection, existing algorithms struggle with highly imbalanced datasets dominated by legitimate transactions. This article addresses this issue by proposing by suggesting a new way to solve it that combines the Synthetic Minority Oversampling Method (SMOTE), autoencoder, Convolutional Neural Networks (CNNs), and attention mechanism into one framework (SMOTE-AE-CNN-Att). The technique starts by utilizing SMOTE to balance the dataset, then uses AE-CNN-Att models to extract features, and then uses classic Machine Learning (ML) methods to classify the data. The suggested method has been shown to be very accurate (> 99.9%) in finding faket transactions while keeping important performance metrics like precision (up to 90.07%), recall (up to 91.13%), and F1-score (up to 90.60%). When compared to other techniques, the SMOTE-AE-CNN-Att model does a better job of finding a good balance between accuracy and recall, which is very important for finding fraud. This research shows how Deep Learning (DL) methods might make it much easier to detect fraud in credit card transactions. This would lead to better security and consumer protection in financial transactions.
A Coordinate-Free Approach to Obtaining Exact Solutions in General Relativity: The Newman-Unti-Tamburino Solution Revisited
(Springer/Plenum Publishers, 2026) Bilge, Ayse Humeyra; Dereli, Tekin; Baysazan, Emir; Birkandan, Tolga
The Newman-Unti-Tamburino (NUT) solution is characterized as the unique Petrov Type D vacuum metric such that the two double principal null directions form an integrable distribution. The uniqueness of the NUT is established by evaluating the integrability conditions of the Newman-Penrose equations up to SL(2,C)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$SL(2,\mathbb {C})$$\end{document} transformations, resulting in a coordinate-free characterization of the solution.
Policy Advice and Capacity
(Edward Elgar Publishing Ltd, 2025) Bali, Azad Singh; Coban, M. Kerem

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