WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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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 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 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.Article 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 Three-Dimensional Culture Enhances the Antimicrobial Activity of Mesenchymal Stem Cells against Shiga Toxin-Producing Escherichia Coli O157:H7 in Vitro(Oxford Univ Press, 2026) Fidan, Özkan; Türkyılmaz, Süheyla; Bicer, Mesude; Öztürk, Esengül; Sener, FatmaAims This study examines the in vitro antibacterial activity of palatal adipose tissue-derived mesenchymal stem cells (PAT-MSCs) and the expression of antimicrobial peptide LL-37, with a particular focus on the effect of three-dimensional (3D) nanofibrillar cellulose-based hydrogel against Shiga toxin-producing Escherichia coli (STEC) harboring stx1 and/or stx2 genes isolated from mastitis milk in Turkey.Methods and results The antibacterial activity of conventionally cultured PAT-MSCs and 3D-cultured PAT-MSCs (PAT-MSCs-3D) was evaluated against STEC isolates and Escherichia coli ATCC 35150 using quantitative colony-forming unit (CFU) assay. The expression levels of antimicrobial peptide (AMP)-encoding genes were evaluated by quantitative real-time PCR, and AMP production was further validated by immunocytochemical staining. The results indicated that PAT-MSCs-3D exhibited significantly enhanced antibacterial efficacy, resulting in marked bacterial inhibition of all tested STEC strains, with bacterial reductions reaching up to 6-7 log under specific experimental conditions. Molecular and immunocytochemical analyses demonstrated increased expression of the antimicrobial peptide LL-37 in PAT-MSCs-3D compared to 2D cultures.Conclusions Our results show that culturing PAT-MSCs in 3D conditions leads to a significant enhancement in their antimicrobial properties, which could be linked to the upregulation of LL-37.Article Radar Resolution Enhancement Based on Burg-Aided MIMO-DBS and Burg-Aided MIMO-SAR †(MDPI, 2026) Bekar, Muge; Bekar, Ali; Baker, Christopher John; Gashinova, Marina; Pirkani, AnumAutonomous systems require sensors that provide high-resolution imagery in adverse lighting and weather conditions for advanced situational awareness. In this regard, radars are a mandatory component of autonomous systems. Although Multiple-Input Multiple-Output (MIMO) radars provide high angular resolution beyond that of their actual physical dimension, much higher cross-range resolutions are required, especially in traffic congested areas, to differentiate and recognize closely positioned targets. The motion of the MIMO radar platform can be exploited to obtain higher cross-range resolution in the off-boresight direction, using Synthetic Aperture Radar (SAR) and Doppler Beam Sharpening (DBS) techniques, but improvements in the boresight direction, the most crucial direction for path planning, require the use of super-resolution techniques. This paper proposes a technique that combines the Burg algorithm with MIMO-SAR and MIMO-DBS radar data to enhance the cross-range resolution in the boresight direction and to achieve further enhanced cross-range resolution in off-boresight directions. The proposed technique is applied to both frequency domain and time domain data in back-projection (BP) and DBS image formation processing. A comprehensive comparison is made, with evaluation of corresponding performance and operational complexity. The performance of the technique is validated through simulation, lab-based and real-world experiments at a frequency of 77 GHz.Article Novel Statistical Approaches for Survival Analysis of RNA-Sequencing Data(Bentham Science Publ Ltd, 2026) Cephe, Ahu; Karabulut, Erdem; Zararsız, Gözde Ertürk; Sezgin, Ahmet; Koçhan, NeclaIntroduction/Objective Accurate patient survival predictions are vital for effective cancer treatments. Precision medicine uses gene expression data to improve prognosis by considering genetic variability. Predicting survival in cancer patients using high-dimensional gene expression data, such as RNA-sequencing (RNA-seq), attracted much attention in recent years. However, the literature contains limited algorithms for survival modeling that account for the high dimensionality, heterogeneity, and correlated genes of RNA-seq data. This study aims to develop novel approaches for predicting survival and identifying biomarkers using RNA-seq data.Introduction/Objective Accurate patient survival predictions are vital for effective cancer treatments. Precision medicine uses gene expression data to improve prognosis by considering genetic variability. Predicting survival in cancer patients using high-dimensional gene expression data, such as RNA-sequencing (RNA-seq), attracted much attention in recent years. However, the literature contains limited algorithms for survival modeling that account for the high dimensionality, heterogeneity, and correlated genes of RNA-seq data. This study aims to develop novel approaches for predicting survival and identifying biomarkers using RNA-seq data.Methods Survival data of RNA-seq is first transformed into binary classification data using a stacking algorithm. Then, block-based priority-Lasso and IPF-Lasso algorithms are applied to the dataset, which includes two distinct types of variables. Additionally, sample weights obtained from the voom transformation are incorporated. Our approaches, named voomStackLasso, are tested on 12 real datasets from the TCGA database. We used Harrell's concordance index and the integrated Brier score to evaluate model performance, and the number of selected features to assess model sparsity.Results The results indicated that the voomStackLasso algorithms demonstrated comparable or superior performance compared to other existing survival algorithms. Furthermore, we have introduced an R package called MLSeqSurv, which allows for the utilization of both established survival algorithms from the literature and voomStackLasso algorithms for RNA-seq data.Conclusion This study introduces two new algorithms for the survival analysis of RNA-seq data. Additionally, this study has led to new research directions for applying both existing and newly developed classification algorithms to the survival analysis of RNA-seq data.