WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Widening the Moral Circle: Perceived Responsibility and Guilt as Mediators of Moral Expansiveness and pro-Environmental Behavior(Springer, 2026) Sari, Erkin; Coskun, Muhammet; Cingoz-ulu, Banu; Candanoglu, InciPrevious research has shown that moral constructs, such as personal norms, play a significant role in shaping individuals' pro-environmental engagement. However, the specific influence of moral expansiveness on such behaviors has received limited attention in the existing literature. This study aims to investigate the relationship between moral expansiveness and pro-environmental engagement within the Turkish context, which is particularly vulnerable to the impacts of climate change. It specifically examines the mediating roles of perceived environmental responsibility and environmental guilt to better understand the mechanisms underlying this association. In total, 244 undergraduate students (167 women, 76 men, 1 did not state; Mage = 21.95, SDage = 2.58) participated in the current study in exchange for course credit. Findings indicated that moral expansiveness indirectly predicted pro-environmental behaviors through both perceived environmental responsibility and environmental guilt, although its direct effect was not significant. Perceived environmental responsibility and environmental guilt both significantly predicted pro-environmental behaviors. Additionally, individuals with more left-leaning political views reported higher levels of pro-environmental behavior. This study highlights how broader moral concern can support sustainability, while contributing to the inclusion of non-Western contexts in environmental psychology.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.Article Surface Integrity and Tool Wear in S2-GFRP Milling: Experimental and Statistical Evaluation of Cutting Parameters and DLC and TiAlN Tool Coatings(Springer London Ltd, 2026) Danisman, Sengul; Yilmaz, Cagatay; Ersoy, Emin; Kesriklioglu, SinanIn this study, the surface integrity of S2-glass fiber-reinforced polymer (S2-GFRP) composites during milling with carbide cutters was investigated using a two-phase experimental design, focusing on surface roughness (Ra), burr area, and tool wear (VB). In the first phase, using a Taguchi L9 design, the effects of coating type (uncoated, TiAlN, DLC), spindle speed (2000-6000 rpm), and feed rate (0,15-0,25 mm/rev) on Ra and burr area were evaluated. In this short machining range where tool wear was negligible, the optimal combination yielding the lowest Ra (approximate to 0.97 mu m) and the minimum burr area (approximate to 231 mm & sup2;) was determined to be 4000 rpm, 0,15 mm/rev, and the DLC-coated tool. Regarding the effect of tool material on Ra, the DLC-coated tool provided approximately 4 and 2 times better results than the uncoated and TiAlN-coated tools, respectively. In the second phase, experiments extended up to 130 passes with this optimal parameter set showed that Ra increased significantly with increasing VB, and the burr area exhibited threshold-like behavior. In particular, a sudden increase in Ra and the burr area was observed when the VB approximate to threshold of approximately 100 mu m was exceeded; partial regression analyses confirmed different burr-formation tendencies in the low- and high-wear regimes. The results reveal that DLC coating initially provides superior performance in S2-GFRP milling, but surface degradation accelerates after the critical VB threshold.Article Structural Optimization for Robotic Concrete Construction: A Systematic Review(MDPI, 2026) Gürer, Ethem; Pektaş, Ömer Korkut; Alaçam, Sema; Güzelci, Orkan Zeynel; Çevik, Ayşe Nesligül; Türel, Ahmet; Özdemir, SalihConcrete construction is associated with high environmental impact and geometric limitations imposed by conventional formwork, which has led to growing interest in combining structural optimization with robotic fabrication. In this study, structural optimization refers to computational methods such as topology optimization, shape optimization, and form finding that aim to improve material efficiency and load-bearing performance by modifying the geometry of structural elements. This systematic review investigates how these optimization approaches are translated into fabrication-aware design workflows for robotic concrete construction. Following a PRISMA-based methodology, 90 peer-reviewed studies published between 2015 and 2025 were analyzed. The review focuses on fabrication routes including (i) 3D concrete printing, (ii) 3D-printed formwork, (iii) shotcrete-based additive manufacturing, and (iv) controlled casting systems, and examines how each route constrains geometry representation, design decisions, toolpath generation, and robotic execution. The review analyzes design-to-fabrication workflows that link optimized structural geometry to production logic and process control. Key findings indicate that incorporating fabrication constraints at early design stages can support buildability and potential material efficiency, while reinforcement integration and quality control remain critical challenges for structural reliability. The review also highlights the increasing role of in situ sensing and feedback-driven automation in improving process stability. Overall, the study clarifies current practices, limitations, and emerging directions for integrating structural optimization with robotic concrete fabrication.Article 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 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 From Agility to Advocacy: Exploring How Gender Moderates the Impact of Social Media Agility on Brand Trust and Influencing Behavior(Palgrave Macmillan Ltd, 2026) Bozkurt, Sıddık; Gligor, David; Hollebeek, Linda D.; Sarp, SerapThis research investigates the effect of perceived social media agility (P-SMA) on customers' influencing behavior, a theoretical subset of engagement behavior, with brand trust acting as a mediator and gender (male/female) as a moderator. It also explores how these relationships differ across age groups. Two online surveys were conducted: Study 1 with 165 younger participants and Study 2 with 178 adults. Using PROCESS Macro Models 4 and 7, we tested direct, mediated, and moderated mediation effects. Both studies found that P-SMA enhances brand trust, which subsequently mediates its influence on customer behavior. Study 2 confirmed these results, showing that gender moderates the relationship between P-SMA and both brand trust and influencing behavior, with stronger effects observed among females (vs. males) in both samples. The findings highlight the importance of tailoring social media strategies to gender-based engagement patterns. Crafting content and interaction styles that foster trust can improve influence and advocacy, especially when agility is a key element of the brand's digital presence. This research integrates P-SMA, brand trust, and customer influence behavior within a moderated mediation model. Using two age-diverse samples, it shows gender shapes reactions to brand agility, while age differences remain non-significant across both datasets.Article Driving Sustainability and Sustainable Developmental Goals in Hospitality: The Influence of Green HRM, Environmental CSR and Shared Green Vision on Pro-Environmental Behaviour(Wiley, 2026) Rafiq, Nosheen; Bulbul, Yagiz Efe; Cobanoglu, Cihan; Shah, Syed Haider Ali; Raza, GulzaibEnvironmental sustainability is highly dependent on the employees' pro-environmental behaviour (PEB) particularly in the hospitality industry context, yet there is still a gap of explanation on mechanisms that systematically improve employees' PEB. Based on Social Identity Theory, this study attempts to examine how green human resource management (GHRM) practices influence employees' PEB in two paths, directly and indirectly, through dual mediating mechanisms: environmental corporate social responsibility (ECSR) and green shared vision (GSV). Using a quantitative design, the study data were collected from 449 hotel managers through a structured questionnaire and analyzed with SmartPLS (SEM). The results show that GHRM has a significant positive effect on PEB and also through indirect effects of both ECSR and GSV. Further, the model explains the substantial amount of variance in PEB. The effect size reveals that indirect pathways are stronger mechanisms than the direct path from GHRM to PEB. Through bringing together the collective cognitive and identity based aspects into one framework, this study extends the theoretical understanding of mechanisms of how GHRM transform sustainability strategies into employee level environmental engagement, which is also aligned with the Sustainable Development Goals (SDGs). The study empirically broadens the GHRM research in the hospitality sector within developing country context and also presents multiple practical insights for hotel policymakers and managers to synchronize environmental strategies with employee conduct.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 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.