Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Uzun, Sevda(11)
- Gül, Abdulkadir(10)
- Baltacı, Cemalettin(9)
- Kaya, Selim(9)
- Kurnaz, Muammer(9)
- Ozturk, Samet(9)
- Çelik, Necati(9)
- Tuncer, Metin(8)
- Altuner, Elif Esra(7)
- Aydin, Aydanur(7)
- Barut, Abdulkadir(7)
- Cin, Aynur(7)
- Günen, Mehmet Akif(7)
- Ozdes, Duygu(7)
- Zaman, Tolga(7)
- Araz, Onur(6)
- Baltaci, Cemalettin(6)
- Bayrakdaroglu, Serdar(6)
- Bozbeyoglu, Pinar(6)
- Demirağ, Hatice(6)
- Karpuz, Ömer(6)
- Liu, Shuxiang(6)
- Merdan, Mehmet(6)
- Yilmaz, Coskun(6)
- Duran, Celal(5)
- Gulcin, Ilhami(5)
- Koçak, Tevfik(5)
- Pala, Fahrettin(5)
- Pilatin, Abdulmuttalip(5)
- Söyler, Mehmet(5)
- Topal, Fevzi(5)
- Tuncer, Gülsüm Zekiye(5)
- Türkkan, Tuğba(5)
- Uysal, Turan(5)
- Yapici, Ismail(5)
- Zengin, Gokhan(5)
- Çam, Alper Veli(5)
- Öztürk, Serkan(5)
- Şan, Murat(5)
- Şimşek, Ahmet Bahadır(5)
Yayınlar
- MakaleYalnız künye2026Scopus SJRQ1A novel neutrosophic estimation method for handling uncertainty in population mean estimation
Yadav, Akhilesh; Yadav, Dharmendra Kumar; Yadav, Subhash Kumar; Zaman, Tolga
Estimating the population mean using auxiliary information has been extensively explored within the classical framework. While point estimators offer simplicity, they provide only a single value without reflecting the uncertainty or variability inherent in real-world data. This shortcoming is particularly critical in high-precision applications and decision-making contexts. Moreover, classical estimators are often vulnerable to the influence of outliers, which can distort results and introduce significant bias. To address these limitations, this study introduces a novel estimator grounded in neutrosophic theory, which is specifically designed to handle imprecise, vague, and incomplete information-conditions frequently encountered in practical sampling scenarios. The proposed neutrosophic estimator incorporates auxiliary information expressed in neutrosophic terms, offering a more flexible and resilient estimation strategy. We derive expressions for the bias and mean square error of the proposed estimator under a first-order approximation. A comprehensive theoretical analysis, supported by simulation studies, confirms that the neutrosophic estimator consistently outperforms classical estimators in terms of accuracy and robustness, especially in uncertain environments. These findings underscore the potential of neutrosophic approaches as powerful alternatives to conventional estimation techniques in modern statistical inference.
AtıfScopus2OpenAlex3
İncele - MakaleAçık Erişim2026Scopus SJRQ2When the Human Firewall Fails: Techno-Strain as the Hidden Link Between Technostress and Information Security Policy Violations
Demirbağ, Orkun; Kaymak, Halil İbrahim; Alan, Hale; Akdeniz, Ferhan
In today’s dynamic business environment, organizations are increasingly investing in strategies to protect themselves against information system violations. While these technologies offer remarkable benefits—boosting efficiency, productivity, and overall performance—they also bring significant risks, particularly regarding information security breaches. This study delves into the critical connections between technostress, techno-strain, and the violation of information security policies. Our research aims to shed light on how technostress, which is commonly experienced by engineers working in technology-intensive environments within the IT sector, drives information security violations. Importantly, we will also explore how techno-strain mediates this relationship. By focusing on engineers who are consistently engaged with advanced technology, we seek to answer essential questions about their experiences. It is worth noting that the requirements for information security technology can widely vary based on factors such as industry type, organizational structure, departmental roles, and cultural norms. Therefore, this study examines how technostress increases the likelihood of information security policy violations and how techno-strain mediates this relationship. Looking ahead, future research should consider both the broader institutional contexts and the individual characteristics that may shape the relationship between information security violations and technostress. Furthermore, understanding the repercussions of information security violations—stemming from technostress—on a company’s financial health is vital for organizations aiming to safeguard their assets and maintain a competitive edge. Emphasizing these insights can lead to more effective strategies for managing both technology and talent in the workplace.
- MakaleYalnız künye2026Scopus SJRQ2Optimizing compton suppression systems: A parametric monte carlo study of NaI scintillator geometry
Kaya, Ali; Çelik, Necati; Kaya, Selim
Compton suppression systems are widely used to enhance gamma-ray spectral quality in applications such as nuclear safeguards and environmental radioactivity measurements. Although optimization of high-purity germanium (HPGe) detectors has been extensively reported, the geometric optimization of secondary sodium iodide [NaI(Tl)] scintillation detectors remains less studied. This work investigates the influence of annular and plug NaI(Tl) detector geometry—length, thickness, and radius—on Compton suppression performance using Monte Carlo simulations. Performance is evaluated in terms of the peak Compton suppression factor (CSFpeak) and total Compton suppression factor (CSFtotal). The results show that CSFpeak and CSFtotal increase with plug length (2–10.2 cm) and annular thickness (1–5.85 cm), with saturation observed beyond approximately 8–10 cm and 4–5 cm, respectively, due to reduced incremental photon absorption. The plug detector radius (3.72–5.1 cm) exhibits a nonlinear effect, with optimal performance achieved at 4.55–4.83 cm, beyond which gains are marginal (<5%). Suboptimal geometries (plug length <6 cm, annular thickness <3 cm, plug radius <4.28 cm) result in 20–60% lower suppression performance, increasing Compton continuum contributions in 662 keV spectra. The optimal configuration—plug length of 8–10 cm, plug radius of 4.55–4.83 cm, and annular thickness of 4–5 cm—achieves more than 90% of maximum CSFpeak and CSFtotal while maintaining a balance between performance and detector volume. These results provide quantitative design guidelines for optimizing NaI(Tl)-based Compton suppression systems for improved gamma-ray spectrometry performance.
- MakaleYalnız künye2026Scopus SJRQ1A regulated many-to-one two-sided matching model for emergency teams: a university case study
Şimşek, Ahmet Bahadır; Göktekin, Zekiye; Şimşek, Tuğçe; Tunçer, Dilara
In workplaces, emergency teams comprised of employees play a critical role in minimising damage during emergencies through rapid response. This study introduces a multi-objective employee-team matching model that optimally assigns employees to emergency teams, balancing stakeholder preferences and physical requirements. Using a regulated many-to-one matching framework, this model accounts for employee preferences, decision-maker evaluations, and team-specific physical standards, addressing limitations in current manual matching practices. Tested through a real case study in a university setting, the model demonstrates its efficacy by achieving stable, satisfactory matches that outperform traditional methods. Sensitivity analysis across multiple scenarios further illustrates the model’s adaptability, providing decision-makers with a systematic tool for improving team stability, performance, and flexibility in various emergency preparedness contexts. The main contribution of this study is the reconciliation of preference-based assignments with performance requirements through a tuneable objective function. By jointly considering soft (preferences) and hard (physical) constraints in a single framework, the model allows decision-makers to balance satisfaction and operational feasibility–an integration that existing approaches typically overlook. This approach presents a robust, data-driven solution to enhance organisational resilience and efficiency in critical situations.
- MakaleYayıncıda açık erişim2026Scopus SJRQ2Innovation adoption of artificial meat among academic consumers in Turkey
Dişli Bayraktar, Eda; Öztürk, Zeynep; Öztürk Küçük, Hilal
Artificial meat has emerged as a promising sustainable food technology with the potential to mitigate environmental impacts associated with conventional livestock production. However, its societal diffusion largely depends on consumer acceptance and the adoption of this innovation. This study examines academics’ attitudes and consumption intentions toward artificial meat in Turkey by focusing on two innovation adoption tendencies novelty seeking and independent decision making and testing the mediating role of attitude within the Theory of Planned Behavior framework. Data were collected via an online questionnaire distributed through social media and email, yielding 277 valid responses from academics across different regions and faculties. Analyses were conducted using SPSS and Hayes’ PROCESS macro (Model 4) with 5,000 bootstrap samples (95% confidence intervals). Results indicate that attitude toward artificial meat is the strongest predictor of consumption intention. Novelty seeking positively predicts attitude, which in turn increases intention; when attitude is included, the direct effect of novelty seeking on intention becomes non-significant, indicating full mediation. In contrast, independent decision-making negatively predicts attitude and indirectly reduces consumption intention through attitude, also reflecting a full mediation structure. Descriptive findings further show high awareness but low willingness to try artificial meat among academics. Overall, the study highlights the central role of attitude in the adoption of innovative food technologies and suggests that communication strategies should prioritize attitude formation, particularly by addressing skepticism among autonomous decision-makers while engaging novelty-seeking individuals as potential early adopters.
- MakaleAçık Erişim2026Scopus SJRQ2An Approach to the Evaluation of Spent Coffee Grounds: Use in Functional Apricot Bar Formulation
Berktaş, Serap; İncegül, Yasemin; Çam, Mustafa
Fruit bars are snack products obtained by mushing fruit, adding sugar, pectin, and other ingredients, and drying the resulting mixture. The aim of this study was to investigate the effects of spent coffee grounds (SCGs), a valuable waste product of the coffee industry, on the physicochemical and bioactive properties of a snack fruit bar enriched with bioactive properties after mushing apricot fruit. Results showed that apricot bars containing 2.5%, 5%, and 7.5% SCGs had higher phenolic, flavonoid, antioxidant activity (ABTS and DPPH), ascorbic acid, and total carotenoid contents compared to the control group. Especially, the fruit bar containing 7.5% SCG stood out in terms of tested bioactive properties. Therefore, it has been determined that the antioxidant and phenolic compounds found in SCGs are also reflected in fruit bars. Furthermore, α-amylase and lipase inhibition values were increased in the enriched fruit bars, and the potential of the developed fruit bars to exhibit antidiabetic and antiobesity properties was improved. Furthermore, the intestinal phase phenolic compound bioaccessibility values of the enriched fruit bars (87.40%–133.3%) were higher than the SCG-free control fruit bar (91.7%). The potential for creating an alternative product with improved nutritional and economic benefits by adding a waste product rich in bioactive compounds such as SCGs to the fruit bar formulation was evaluated. Such products could be considered a new alternative to a functional snack product group rich in bioactive substances that could be incorporated into today's diet.
- MakaleAçık Erişim2026Scopus SJRQ1Measuring Perceived Social Support After Disaster: Development and Validation of the Perceived Social Support in Disasters Scale (PSSDS-28)
Oruç, Abdurrahman; Cengiz, Ekrem
Background/Objectives: Measuring perceived social support after disaster remains an unresolved psychometric problem. Most instruments do not jointly capture the source of support (from whom it comes) and its function (how it operates). None has been validated in a disaster-survivor sample with retrospectively framed items. We developed and validated the Perceived Social Support in Disasters Scale (PSSDS-28), a 28-item measure integrating both dimensions. Methods: In Phase 1, a PRISMA 2020-guided systematic review; a two-round Delphi with eight experts, cognitive interviews (n = 12); and a pilot study (N = 150) produced a 31-item form. In Phase 2, face-to-face data were collected from 607 adults affected by the 6 February 2023 Kahramanmaraş earthquakes (Türkiye). Multiple analytic frameworks converged on a five-factor, 28-item structure comprising family–relative, social environment, institutional, emotional, and instrumental–informational support. Results: The correlated five-factor model fit the independent validation sample well (CFI = 0.954, RMSEA = 0.076, and SRMR = 0.072) and outperformed a one-factor alternative (ΔCFI = 0.222). Blocks showed strong internal consistency (ordinal α = 0.852–0.949), composite reliability (0.865–0.950), and adequate test–retest stability (ICC = 0.542–0.909). Scalar measurement invariance held across six groupings, with no meaningful differential item functioning. Convergent and discriminant evidence supported construct validity, and common-method variance was negligible. Institutional (M = 3.29) and instrumental–informational support (M = 2.99) scored lowest—a profile a global score would conceal. Conclusions: The PSSDS-28 provides promising initial psychometric evidence for a multidimensional post-disaster assessment instrument situated at the perceived–received interface, a target that general-purpose scales are not designed to capture. Criterion-related validity, cross-cultural validity, and cross-disaster replicability remain to be demonstrated.
- MakaleAçık Erişim2026Scopus SJRQ1Non-Alcoholic Beer Production Using Ohmic Heating-Assisted Vacuum Distillation Method
Akdoğan, Arda; Baltacı, Cemalettin
In this study, non-alcoholic beer was produced with an ohmic heating-assisted vacuum distillation system (ODVD) and vacuum rotary distillation (VDD). The processes were conducted at three vacuum pressure levels (100, 150, and 200 mbar). Corresponding operating temperatures were 50, 58, and 67°C for the VDD system, while the ODVD system operated at in-situ-ohmic heating without an external heating medium. In ODVD, three voltage gradients (15, 20, and 25 V/cm) were applied. The two systems were compared in terms of processing time, energy efficiency, aroma profile, antioxidant capacity (ABTS, DPPH, TAC, FRAP), total phenolic (TPC) and total flavonoid content (TFC), vicinal diketone (VDK), pH, color, and bitterness value. The ODVD system showed significantly shorter processing times and energy efficiency than VDD. While the pH values of dealcoholized beer increased slightly compared to the original beer, color and bitterness values were higher in VDD samples. Aroma compounds such as ethyl acetate, isoamyl acetate, and ethyl caproate were lost during both processes. Overall, the findings demonstrate that ODVD is a promising and energy-efficient alternative for the production of non-alcoholic beer, with comparable product quality to VDD.
AtıfScopus4WoS4
İncele - MakaleYalnız künye2026Scopus SJRQ2Effects of mandatory schooling expansion on upward educational mobility among women in Türkiye
De, Prabal K.; Tümay, Muhammed
Using data from the Turkish Demographic Health Survey and a Regression Discontinuity Design, we estimate the effects of an exogenous increase in mandatory schooling on educational mobility among women in Türkiye. Our findings indicate that compulsory schooling may increase upward educational mobility where women attend education levels higher than their parents, particularly mothers. Additionally, we find such effects not only for the level at which schooling became compulsory but also at higher levels, showing a magnification of the initial impact.
- Kitap BölümüYalnız künye2026Remuneration and Duties in Ottoman Waqfs: The Case of Hafsa Sultan Waqf (Sixteenth to Eighteenth Centuries)
Karademir, Ayşenur
Ottoman charitable endowments, known as waqfs, were established by the sultan, his family, and the members of the ruling class, serving as primary employment institutions during the classical period. These waqfs offered a broad range of social services through various public structures, thereby employing a vast number of individuals with diverse skills and educational backgrounds across the empire. This study focuses specifically on wage determination within the Manisa Waqf of Hafsa Sultan, the mother of the renowned Sultan Süleyman the Magnificent, established in 1523. The waqf complex outlined in the endowment deed, comprised a mosque, a primary school, a madrasa, a dervish lodge (hankah) and a soup-kitchen (imaret). Subsequently, it expanded to include a hospital (dârüşşifâ) and a Turkish bath (hamam). Starting with an analysis of the endowment deed, this study further examines the seventeenth and eighteenth-century accounting books retrieved from the Ottoman Archives. These records reveal various aspects, including the waqf’s expansion, the increasing employment individuals, changes in daily wages over time, in-kind payments, challenges encountered during inflationary periods, and practical measures implemented to mitigate these issues.
- MakaleAçık Erişim2026Scopus SJRQ1Drivers’ Perceptions of Vertical Traffic Signs and Their Implications for Road Safety: Evidence from a Field Survey
Durmus, Tahsin; Coruh, Emine
Accurate perception and interpretation of the road environment are essential for safe driving. Vertical traffic signs play a key role in communicating warnings, regulations, and guidance to road users, thereby supporting safe and efficient traffic flow. However, their effectiveness depends not only on proper design and placement but also on how accurately and promptly they are perceived by drivers, which may be influenced by factors such as attention, cognitive workload, physical and mental condition, and fatigue. This study evaluates the contribution of selected vertical traffic signs to driving safety along a designated roadway section in Şanlıurfa, Türkiye. Face-to-face surveys were conducted with 480 active road users. Drivers’ knowledge, compliance behavior, safe route preferences, perceived visibility, and the effects of missing or inadequate signage were analyzed. The results indicate that driving exposure, education level, and experience significantly influence knowledge and perception of traffic signs, while compliance shows limited variation. These findings suggest that knowledge alone does not necessarily translate into behavioral compliance and underscore the importance of considering both driver-related factors and infrastructure characteristics in traffic safety strategies. The study provides practical insights for improving the visibility, placement, and overall effectiveness of vertical traffic signs in rapidly developing urban environments.
- MakaleAçık Erişim2026Scopus SJRQ1Weekly Fluctuations in Internal Load and Neuromuscular Performance Across a 10-Week Training Period in Elite Female Boxers
Aydın, Ahmet Serhat; Altuğ, Tolga; Yılmaz, Coşkun; Badau, Adela; Söyler, Mehmet
This study examined weekly internal load and neuromuscular performance in elite junior female boxers over 10 weeks. Internal load was quantified using session rating of perceived exertion (sRPE), from which weekly monotony and strain were derived. Neuromuscular performance was assessed weekly using wall-sit endurance and a repetitive jump test. Twenty elite junior female boxers (Mean ± SD: 18.9 ± 1.2) were monitored during regular training without experimental manipulation. Weekly sRPE-derived training load, monotony, and strain showed statistically significant week-to-week fluctuations (p < 0.001). Neuromuscular performance improved in week 2, declined during weeks 3–5, and partially recovered in week 6. The findings demonstrated consistent temporal alignment between internal-load indices and week-to-week neuromuscular performance changes within an observational monitoring framework. Inter-individual variability was observed across athletes. Overall, sRPE-derived indices reflected training stress patterns and were aligned with neuromuscular performance changes in elite female boxers, supporting their use for contextual monitoring of weekly training responses. These findings support the practical integration of internal-load and performance monitoring in elite female combat-sport settings. Future research incorporating boxing-specific external-load metrics, physiological markers, and longer monitoring periods may further refine individualized load-management strategies.
AtıfScopus1İncele - MakaleAçık Erişim2026Scopus SJRQ1Structural joint modeling of magnetotelluric data and Rayleigh wave dispersion curves using Pareto-based particle swarm optimization: an example to delineate the crustal structure of the southeastern part of the Biga Peninsula in western Anatolia
Büyük, Ersin; Zor, Ekrem; Tapırdamaz, Mustafa Cengiz
It is widely acknowledged that the joint inversion of magnetotelluric and seismological datasets enhances the quality of the crustal structure solution, even when the physical correlation between electrical resistivity and seismic velocity is weak or indirect. The structurally coupled joint inversion approach has received considerable attention over the past two decades for its ability to estimate such parameters by penalizing their cross-gradient vectors at similar spatial positions. Despite this interest, various structural couplings and different physical directions (incremental or decremental) have been partially overlooked. We hereby propose an approach for the joint inversion of magnetotelluric (MT) and Rayleigh wave dispersion (RWD) data to estimate uncorrelated parameters by integrating particle swarm optimization (PSO) and the Pareto optimality approach. We used the optimality framework of these methods to overcome the difficulties associated with traditional joint inversion algorithms and to obtain optimal solutions that account for both similar and contrasting physical sensitivities. The significant correlation between the inverted and synthetic models under both noise-free and noisy datasets, together with the consistent results obtained from comparison with a traditional derivative-based joint inversion algorithm, further strengthened our confidence in applying the proposed modeling approach to the field data from the southeastern Biga Peninsula, western Anatolia. The models inverted from the field data corroborate the efficacy of the presented method. A notable characteristic of the proposed methodology is its capacity to estimate uncorrelated physical parameters, such as electrical resistivity and seismic velocity, without the imposition of penalties. Therefore, the presented method not only offers advantages in joint inversion but also allows modelers to observe and analyze model parameters having different sensitivities that may indicate different physical directions.
- MakaleAçık Erişim2026Scopus SJRQ4GREEN SYNTHESIS AND STRUCTURAL CHARACTERIZATION OF IRON OXIDE NANOPARTICLES FROM ROBINIA PSEUDOACACIA L. FRUITS FOR DYE REMOVAL FROM AQUEOUS SOLUTIONS
Demir, Semra; Akar, Bülent; Baltaci, Cemalettin
In this study, iron oxide nanoparticles were produced and characterized using a green synthesis method with Robinia pseudoacacia fruits. The structural and functional properties of the nanoparticles were investigated using XRD, TEM/EDX, and FTIR analyses. The results indicated that the produced iron oxide nanoparticles had nanoscale particle sizes and exhibited a poorly crystalline (predominantly amorphous) structure according to XRD analysis. The comparative adsorption performance of the synthesized FeONPs and fruit powder in the removal of malachite green (MG), phenol red (PR) and methylene blue (MB) from aqueous solutions was evaluated. According to the results, the adsorption capacity followed the order MB> MG > PR. FeONPs exhibited consistently higher Qₑ values across all dye systems compared to the fruit powder. High removal efficiencies were obtained at low and moderate initial concentrations, while increasing the adsorbent dose enhanced the overall removal but resulted in a reduction in the adsorption capacity per unit mass. The obtained findings indicate that biosynthesized iron oxide nanoparticles can be used as an efficient and environmentally friendly adsorbent for eliminating environmental pollutants.
- MakaleYalnız künye2026Scopus SJRQ1Optic disc segmentation: Improved U-Net model and hyperparameter optimization with harmony search algorithm
İncir, Ramazan; Bozkurt, Ferhat
Vision loss negatively impacts individuals quality of life, creating a societal issue. As stated by the World Health Organization, vision loss is significant concern among health problems. Glaucoma and Diabetic Retinopathy are among the primary causes of vision impairment and loss. Early diagnosis of these diseases is crucial for guiding appropriate treatment. Optical disc segmentation plays a key role in diagnosing these diseases and helps in effectively detecting them through the analysis of retinal images. This study proposes method based on the automatic processing of fundus images to contribute to the early diagnosis of eye diseases. Improved U-Net architecture developed for optical disc segmentation is used. To enhance the models performance, the improved U-Net architecture has been strengthened with residual and custom convolution blocks. Genetic Algorithm, Particle Swarm Optimization Algorithm, Ant Colony Optimization and Harmony Search Algorithm were used for hyperparameter optimization. Comparisons showed that the Harmony Search Algorithm achieved better results, improving overall model performance and providing more accurate segmentation outcomes. The models performance has been tested on the IDRiD and DRISHTI-GS datasets. The improved architecture outperformed existing methods in the literature. Significant improvements were observed in key segmentation metrics such as IoU and Dice coefficient. In experimental studies using the IDRiD and DRISHTI-GS datasets, the proposed model achieved IoU scores of 93.65% and 95.20% and Dice scores of 96.72% and 97.54% respectively. The model was able to accurately define optical disc boundaries even in low contrast and complex images. The obtained success demonstrates the models potential as valuable tool for the early diagnosis of vision loss causing diseases.
AtıfScopus1WoS1İncele - MakaleYalnız künye2026Scopus SJRQ1Optimal design of a novel enhanced inerter-based tuned mass damper in seismic-excited structures considering SSI effects
Araz, Onur; Shahraki, Mohammad Alibabaei
This paper proposed a novel enhanced inerter-based tuned mass damper (E-TMDI) for the control of damped single-degree-of-freedom structures due to ground acceleration. The apparatus represents an energy-dissipating passive absorber assembled from a pair of inerter elements, a pair of springs, a single mass, and a single damper. The present work directly integrates soil-structure interaction (SSI) effects within the optimization process, thereby yielding more accurate and dependable outcomes. For a clearer insight into the control mechanism of E-TMDI, the frequency-domain transfer function for responses is derived, while the influences of various model parameters on the displacement amplitude magnification factor of the superstructure both considering and neglecting SSI are examined. Four design parameters (i.e., f 1 first frequency ratio, f 2 secondary frequency ratio, ξ1 damping ratio, and κ inertance ratio of the second inerter to the first) of E-TMDI are obtained using particle swarm optimization (PSO) algorithm to minimize peak displacement amplitude of the structure. Results from the frequency domain analyses in this research indicate that the proposed E-TMDI has better efficiency and frequency band property both traditional TMD and TMDI configurations when equipped with same total mass (μ) and inertance ratio (β) in suppressing structural vibrations. Additionally, the stability of the proposed device is examined through simulations of the E-TMDI-equipped structure under a range earthquake record. The findings reveal that the E-TMDI maintains superior effectiveness even when the host structure experiences diverse earthquake events. This validation, conducted under real earthquake records, confirms the reliability of this design framework, filling a significant gap in determining the seismic control performance of E-TMDI under varying soil conditions.
AtıfScopus19WoS19OpenAlex20İncele - MakaleAçık Erişim2026Scopus SJRQ1The Mediating and Moderating Roles of Innovation Climate in the Relationship Between Nurses’ Attitudes Toward Artificial Intelligence, Creative Self-Efficacy, and Clinical Competence
Karakaya Suzan, Ozge; Gül, Uğur; Koyuncu, Oğuz; Akdeniz, Canberk
Background: Artificial intelligence (AI) is increasingly integrated into health care; however, how nurses’ attitudes toward AI and creative self-efficacy are associated with perceived clinical competence within different organizational contexts remains unclear. Aim: To examine whether perceived climate for innovation statistically mediates the association between nurses’ attitudes toward AI and perceived clinical competence and moderates the association between creative self-efficacy and perceived clinical competence. Methods: This cross-sectional study included 233 nurses recruited online by convenience sampling from hospitals in Türkiye between January and March 2026. Self-report measures assessed attitudes toward AI, creative self-efficacy, perceived climate for innovation, and perceived clinical competence. Pearson correlations and PROCESS Models 4 and 1 with 5000 bootstrap samples tested statistical mediation and moderation. Adjusted analyses included age, gender, previous AI-related training and AI use, educational level, professional experience, and institution type. Results: Attitudes toward AI were indirectly associated with perceived clinical competence through perceived climate for innovation; the adjusted indirect association remained significant (B = 0.0700, SE = 0.0333, 95% CI [0.0173, 0.1453]), consistent with partial statistical mediation. Perceived climate for innovation also moderated the association between creative self-efficacy and perceived clinical competence after adjustment (interaction B = −0.1672, SE = 0.0447, 95% CI [−0.2552, −0.0792]). This positive association became weaker as perceived climate for innovation increased. Conclusion: Attitudes toward AI, creative self-efficacy, perceived climate for innovation, and perceived clinical competence were significantly associated, and the statistical mediation and moderation patterns remained after adjustment. The cross-sectional, self-report data do not establish temporal or causal mechanisms or effects on objectively measured clinical performance or patient outcomes. Implications for Nursing Management: Nurse managers may consider supporting AI literacy, safe AI use, team-based learning, and innovation-supportive work environments. These strategies should be evaluated prospectively using objective clinical and patient outcomes before their effectiveness is inferred.
- MakaleYalnız künye2026Scopus SJRQ2Honeybee Silk: A Promising Value-Added Biomaterial with Antioxidant, Antimicrobial, Antihyaluronidase, and Microstructural Characteristics
Yildiz, Oktay; Değirmenci, Atiye; Boyraci, Gulsum Merve; Aksoy, Canan
Bee products with their huge potential are becoming more valuable beyond food industry. Honeybee silk is non-utilized biomaterial in any commercial applications and even burned during the processing of beeswax. Although studies concerning insects silks are commonly on spider and silkworm silks, honeybee silk remains unexplored. Scanning electron microscope and energy dispersive X-ray spectroscopy (SEM–EDX) were used to identify chemical composition via elemental mapping of the native form of honeybee silk. Honeybee silk, in the form of thin layer inside the honeycomb cells, was processed through a series of steps to separate it from beeswax. Protein content was evaluated and revealed a composition of approximately 11.69%, indicating its strong biopolymeric origin. Amino acid analysis of honeybee silk performed by RP-HPLC revealed the presence of both polar and nonpolar amino acids, indicating a well-balanced amino acid profile. Antioxidant, antimicrobial, and anti-hyaluronidase properties of processed honeybee silk were presented. The methanolic extracts of honeybee silk were found to have higher total phenolic content (TPC) and antioxidant activity as assessed by DPPH (2,2-diphenyl-1-picrylhydrazyl) and FRAP (ferric reducing antioxidant power) assays than the aqueous extracts. While no antimicrobial activity was found for aqueous extracts, methanolic honeybee silk extract exhibited antimicrobial activity against Escherichia coli, Staphylococcus aureus, Bacilluscereus, Staphylococcus epidermidis, and Candida albicans. The hyaluronidase inhibition values (IC50) were found as 0.0094 and 0.0079 g/mL for aqueous and methanolic honeybee silk extracts, respectively. The aforementioned findings indicate that honeybee silk as a promosing value-added product is worthy of attention from pharmaceutical industries and future studies.
- MakaleYalnız künye2026Scopus SJRQ2Impact of stress ball intervention on satisfaction, comfort and anxiety in hemodialysis patients: a randomized controlled trial
Salti, Aysun Kazak; Topali, Hasret; Turkmen, Osman Oğulcan
Hemodialysis (HD) patients commonly experience psychological distress and anxiety, which may affect their comfort and satisfaction during treatment. This study examined the overall impact of stress ball use on satisfaction, comfort, and anxiety among individuals receiving HD. A total of 46 patients were randomized between January and July 2025. Three participants in the intervention group withdrew before completing the study; therefore, the final analysis included 43 patients (20 in the stress ball group and 23 in the control group). Data were collected using the Patient Information Form (PIF), Visual Analog Patient Satisfaction Scale (VAPSS), Hemodialysis Comfort Scale (HCS), Distress Thermometer (DT), and Visual Analog Scale for Anxiety (VAS-A). Patients in the intervention group used a stress ball for at least 15 minutes during each of twelve HD sessions. Measurements were obtained at baseline, midpoint, and post-test, while the control group received standard care and was assessed concurrently. The study findings demonstrated that anxiety levels decreased over time in the stress ball group, whereas they increased in the control group. Similarly, distress levels decreased in the stress ball group, while no significant change was observed in the control group. HD comfort scores decreased in the stress ball group but increased in the control group. In contrast, no statistically significant difference was found between the groups in terms of the VAPSS scores. These results highlight the potential value of simple distraction techniques in clinical settings for further improving psychological outcomes.
- MakaleYalnız künye2026Scopus SJRQ1Classification and detection of Salmonella, Escherichia coli O157:H7, and Listeria monocytogenes using Fourier-transform near infrared spectroscopy coupled with machine learning
Ozturk, Samet; Huang, Lihan; Hwang, Cheng-An; Sheen, Shiowshuh
This study was conducted to investigate the potential use of Fourier-transform near-infrared (FT-NIR) spectroscopy combined with machine learning (ML) algorithms to accurately identify three foodborne pathogens, including Salmonella spp., Listeria monocytogenes, and Escherichia coli O157:H7. Each bacterial strain (two per pathogen) was individually cultured and purified through sequential washing using ethanol–deionized (DI) water solutions. Each purified culture was transferred into each well of a 96-well cell plate covered with custom-cut filter paper and then vacuum dried at 50 °C under 20 kPa for 1 h. The absorbance spectra of dehydrated bacterial cells were then acquired across the range of 1000–2400 nm using a diffuse reflectance probe connected to a FT-NIR process analyzer. To identify the optimal classification pipeline, the acquired spectra were analyzed using ten different pre-processing methods, three feature selection methods, and supervised algorithms including partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), random forest (RF), artificial neural network (ANN), and convolutional neural network (CNN). Furthermore, the accuracy of the developed ML pipelines was further enhanced through under-sampling and boosting steps. The results demonstrated that SVM, RF, ANN and CNN outperformed PLS-DA, where the classification accuracies were above 90%. The findings demonstrate that using Savitzky-Golay first derivative (SG1) filtering to pre-process the full spectra followed by SVM classification yielded the highest accuracy, achieving 95.3% overall accuracy in ML pipeline. This study highlights the powerful capability of FT-NIR spectroscopy coupled with ML algorithms to detect and identify foodborne pathogens on dehydrated surfaces in process environments.
AtıfScopus3WoS3OpenAlex3İncele