Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Unsettled Grounds, Enduring Bonds: A Literature Review on Employee Engagement during Organizational Change(Routledge Journals, Taylor & Francis Ltd, 2026) Abbas, Alhamzah F.; Ahmed, Ayesha; Usman, Muhammad; Shah, Syed Haider AliThis systematic review critically examines how employee engagement is conceptualized and operationalized within the context of organizational change, aiming to uncover prevailing themes, highlight conceptual inconsistencies, and identify gaps in the literature to advance understanding in evolving organizational settings. Guided by the the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA framework, the study analyzes 29 peer-reviewed journal articles published between 2006 and 2025, retrieved from the Scopus database, employing thematic synthesis and citation mapping to explore both organizational and individual-level influences on engagement during change. The findings reveal a dual-level framework: at the organizational level, leadership, organizational support, communication, and cultural and contextual dynamics play a central role, while at the individual level, psychological and emotional factors, behavioral patterns, attitudes toward change, and opportunities for skill development and career progression are key drivers. This review contributes by clarifying conceptual boundaries, identifying underexplored dimensions, and providing actionable insights for leaders and HR practitioners to sustain and enhance employee engagement during periods of organizational transition.Conference Object Sustainable Approach to Fabricating Flat Micro Ribbon Electric Wires Directly from Turning Process Chips(Elsevier B.V., 2026) Kesriklioglu, Sinan; Sivesoglu, AbdurrahmanArticle Predicting Respiratory Infection and Symptoms Development Using Gene Set Enrichment Scores and Machine Learning(Elsevier Sci Ltd, 2026) Aydin, Zafer; Isik, Yunus EmreRecent advancements in precision medicine enable personalized predictions grounded in individual-level genetic data. However, relying solely on a single type of data can decrease prediction accuracy and limit the biological interpretability of the resulting models. Incorporating predefined genetic knowledge, such as derived gene sets, can improve performance and provide deeper biological insights for complex diseases, including respiratory infections. This study aimed to evaluate the usability of enrichment scores (ES), calculated using gene sets from the Molecular Signatures Database (MSigDB), as a feature representation for machine learning models to predict respiratory viral infections and symptom development. In addition, the proposed feature representation approach was extensively compared with the de facto gene-level expression representation. A total of 36,834 predefined gene sets were compiled from the MSigDB, and their ES values were calculated. Experiments used the GSE73072 dataset from Gene Expression Omnibus, containing gene expression profiles before and after virus exposure. Various machine learning and feature selection algorithms were applied to ES-based and probe-level feature sets. The results showed that both feature representation approaches achieved an area under the precision-recall curve (AUPRC) value greater than 0.90 for all tasks. Compared with the Respiratory Viral DREAM Challenge leaderboard phase, our models showed a 14.8% improvement in pre-exposure predictions (T0) and a 17.4% improvement in symptom classification. Using enrichment scores as a feature representation generally resulted in better performance than probe-level representation when predicting respiratory infections and symptom development. Identifying key gene sets through feature selection and comparing them with essential genes for respiratory viruses enabled a more comprehensive analysis, providing deeper insights into the pathways that contribute to these predictions.Article Probing Adversarial Robustness of Protein Language Models: A Reproducible Case Study of ESM-2 Under Substitution-Based Attacks(AIUB Office of Research and Publication, 2026) Aydin, Zafer; Niloy, Md. Robiul Islam; Moazzam, Md. GolamArticle Modeling Commuter Mobility in Stockholm: A Spatial Panel Approach Using Mobile Phone Data(Springer Heidelberg, 2026) Fischer, Manfred M.; Osth, John; Toger, Marina; Turk, UmutThis paper examines the sociodemographic and socioeconomic determinants of regional commuter mobility in the Greater Stockholm Area using a heteroscedastic spatial Durbin panel data model estimated via Bayesian Markov Chain Monte Carlo methods. Drawing on mobile phone-derived origin-destination flows from the MIND database, the analysis exploits unusually fine spatial and temporal granularity across a balanced panel of 675 regions over the period 2018-2023. A k-nearest neighbor spatial weight matrix (k = 18), selected via Bayesian model comparison, captures the topological structure of interregional connectivity. By modeling spatial lags in both the dependent and independent variables, the framework enables explicit recovery of direct (own-region) and indirect (spillover) effects from scalar summary measures of the matrix of partial derivatives - providing robust posterior inference on how sociodemographic and socioeconomic conditions propagate through space. This approach addresses a key limitation of conventional non-spatial methods, which risk producing biased estimates by ignoring spatial interdependence. Empirical results confirm that spatial spillovers predominate over direct effects, with educational attainment and car ownership emerging as the principal determinants of commuter mobility, while age composition plays a comparatively modest role. These findings underscore that evaluating direct effects in isolation systematically underestimates the broader societal returns to mobility-enhancing regional policies.Article Electrospun PCL/PEG Nanofibers Incorporating Plantago Lanceolata Extract and Clove Oil for Dual-Function Wound Dressings(IOP Publishing Ltd, 2026) Teke, Selin Nur; Yuruk, Adile; Isoglu, Ismail AlperIn this study, we developed electrospun polycaprolactone/polyethylene glycol (PCL/PEG) nanofibers loaded with Plantago lanceolata (P. lanceolata) extract and clove oil to evaluate their combined potential for wound healing and antibacterial activity. PCL/PEG nanofibers were electrospun and post-loaded with P. lanceolata extract at 5%, 10%, and 15% (w/v), together with 1% (v/v) clove oil. Scanning electron microscope analysis showed a uniform, bead-free nanofibrous structure, with fiber diameters ranging from 768 +/- 140 nm to 892 +/- 206 nm and pore sizes from 3.93 +/- 0.97 & micro;m to 6.20 +/- 1.16 & micro;m. The nanofibers exhibited swelling ratios between 103.23 +/- 16.42% and 133.93 +/- 40.45% within 1 h and showed gradual degradation ranging from 25.92 +/- 2.84% to 57.76 +/- 0.92% over 21 d, with cumulative extract release approaching a plateau by day 28 under the experimental conditions. The incorporation of plant extract and essential oil initially increased the water contact angle from 15.97 +/- 1.07 degrees to 48.61 +/- 7.85 degrees, indicating that the nanofiber surface remained hydrophilic; at higher extract contents, the nanofibers transitioned to a superhydrophilic state. Antibacterial activity was primarily governed by clove oil, yielding up to 85.16 +/- 0.36% efficacy against E. coli (E. coli) and 79.90 +/- 0.29% against S. aureus (S. aureus). While P. lanceolata extract alone showed limited antibacterial activity, its presence within clove oil-loaded nanofibers consistently enhanced antibacterial performance at the composite level. In vitro scratch assays demonstrated pronounced wound closure at later time points (72-96 h), particularly for nanofibers containing higher extract concentrations, confirming the dominant contribution of P. lanceolata to the healing response. Overall, the electrospun PCL/PEG nanofibers represent a dual-function wound dressing, with clove oil contributing antibacterial protection and P. lanceolata extract supporting wound healing.Article Effects of Group Aerobic Exercise on Health and Social Adaptation in Earthquake Survivors: A Qualitative Study(Lippincott Williams and Wilkins, 2026) Yardimci, Fatma Betul; Kaya, M. Siyabend; Anaforoglu, Bahar; Altay Ili, Hafize; Apak, HidirArticle Comprehensive Evaluation of Microstructure–Property Relationships in Al-Added Sn-Zn Eutectic Solder Alloys from Thermal, Electrical, and Mechanical Perspectives(Springer, 2026) Bayram, Ümit; Şahin, Mevlüt(Sn-8.8Zn)-XAl (X = 0, 0.5, 1.0, 2.5, 5.0 wt.%) solder alloys were produced using a vacuum muffle furnace. The microstructural images, chemical compositions, and phase structures of the alloys were characterized by field emission scanning electron microscopy (FESEM), field emission scanning electron microscopy-energy dispersive x-ray spectroscopy (FESEM-EDX), and x-ray diffraction (XRD) analyses, respectively. According to FESEM images, a fully eutectic microstructure was observed in the Sn-8.8Zn alloy. With increasing Al content, dendritic structures formed and became denser. The mechanical properties of the alloys (ultimate tensile strength sigma UT, tensile yield strength sigma TY, compressive yield strength sigma CY, and Vickers hardness HV) were measured as a function of composition. The highest strength and hardness values were obtained for the (Sn-8.8Zn)-2.5Al alloy, whereas the (Sn-8.8Zn)-5.0Al alloy exhibited the highest ductility. The melting enthalpies (Delta H) and the specific heat differences between the solid and liquid phases (Delta CP) of the alloys were measured by differential scanning calorimetry (DSC) analysis. It was determined that an increase in the Al content of the eutectic alloy resulted in higher measured thermophysical properties. Finally, electrical resistivity (rho) values at T = 300 K, measured using the standard four-point probe method (FPPM), revealed an increase in resistivity up to 1.0 wt.% Al content, followed by a decrease beyond this value. In contrast, thermal conductivity values calculated using the Wiedemann-Franz law exhibited an opposite trend, decreasing up to 1.0 wt.% Al, and increasing thereafter. Based on microstructure-property relationships, the results were compared with previous studies, highlighting that (Sn-8.8Zn)-XAl alloys represent promising alternatives to lead-free solders.Article Dissecting the Strain and Sex Specific Connectome Signatures of Unanesthetized C57BL/6J and DBA/2J Mice Using Magnetic Resonance Imaging(Wiley, 2026) Neuberger, Thomas; Kamens, Helen M.; Zhang, Nanyin; Ünsal, Hayreddin Said; Arefin, Tanzil M.Mouse models are an essential tool for understanding behavior and disease states in neuroscience research. While genetic and sex-specific effects have been reported in many neurodegenerative and psychiatric illnesses, these factors may also alter baseline neuroanatomical features of mice. This raises the question of whether the observed changes are related to the disease being studied (i.e., pathological differences) or if there are baseline strain or sex differences that may predispose animals to different responses. Over the past decade, tremendous effort has been made to map neural architecture at various scales; however, the complex relationships, including identifying genetic and sex-specific differences in brain structure and function, remain understudied. To bridge this gap, we used C57BL/6J and DBA/2J mice, two of the most widely used inbred mouse strains in neuroscience research, to investigate strain and sex-specific features of the brain connectome in awake animals using magnetic resonance imaging (MRI). By combining resting-state functional MRI and diffusion MRI, we found that the motor, sensory, limbic, and salience networks exhibit significant differences in both functional and structural domains between C57BL/6J and DBA/2J mice. Further, functional and structural properties of the brain were significantly correlated in both strains. Our results underscore the importance of considering these baseline differences when interpreting brain-behavior interactions in mouse models of human disorders.Conference Object AI Explainability for Adaptive Mmwave Beam Configuration in Dynamic Vehicular Environments(Institute of Electrical and Electronics Engineers Inc., 2026) Foh, Chuan Heng; Kose, Abdulkadir; Yigit, Ugur; Akbas, Ayhan; Shojafar, Mohammad