Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Uzun, Sevda(62)
- Merdan, Mehmet(58)
- Duran, Celal(50)
- Ozdes, Duygu(47)
- Kaygusuz, Abdullah(43)
- Ashyralyyev, Charyyar(38)
- Karsli, Orhan(33)
- Öztürk, Serkan(32)
- Araz, Onur(31)
- Demir, Selim(29)
- Kulakaç, Nurşen(29)
- Dokuz, Abdurrahman(28)
- Arslan, Mehmet(27)
- Baltacı, Cemalettin(27)
- Maden, Nafiz(27)
- Sipahi, Ferkan(27)
- Topal, Fevzi(27)
- Turan, Ibrahim(27)
- Kandemir, Raif(25)
- Kurt, Kemal(24)
- Ozturk, Samet(24)
- Peker, Iskender(24)
- Vural, Alaaddin(24)
- Reis, Hatice Catal(23)
- Yücel, Cem(23)
- Aydin, Faruk(22)
- Baltaci, Cemalettin(22)
- Gücer, Mehmet Ali(22)
- Günen, Mehmet Akif(22)
- Kankal, Murat(22)
- Topal, Meryem(22)
- Karimullah, Suud Sarim(21)
- Uysal, Ibrahim(20)
- Kurnaz, Muammer(19)
- Tuncer, Metin(19)
- Yolcu, Halil(19)
- Çelik, Necati(19)
- Ürkek, Bayram(19)
- Şan, Murat(19)
- Aliyazicioglu, Yuksel(18)
Yayınlar
- MakaleAçık Erişim2026Core–Periphery Organization and Spatial Heterogeneity in Pseudopus apodus (Anguidae) Across Its Western Palearctic Range
Şahin, Mehmet Kürşat; Topal, Azra; Kurnaz, Muammer
Understanding the internal spatial structure of widely distributed species is fundamental for biogeographic theory and conservation practice, yet such structure is often masked by extent-based range metrics. We investigated the spatial organisation of Pseudopus apodus (Pallas, 1775), the largest limbless lizard of the Western Palearctic, using 3967 occurrence records spanning 1843–2025. Spatial point pattern analysis revealed a pronounced deviation from complete spatial randomness (Clark–Evans R = 0.105, p < 0.001), with strong fine-scale clustering. Kernel density estimation identified a clear core–periphery organisation: high-density core areas accounted for 30% of records but occupied only 22% of the total extent of occurrence (EOO). The discrepancy between EOO (~8.9 million km2) and area of occupancy (AOO; ~8944 km2) spanned three orders of magnitude, emphasising that only a small fraction of the species’ geographic envelope is actively occupied. Spatial heterogeneity was high (coefficient of variation ≈ 0.99), and core and peripheral occurrences were significantly segregated along both latitudinal and longitudinal gradients. The proportion of core records showed a weak positive temporal trend most plausibly attributable to sampling effort, particularly the recent expansion of citizen-science contributions, rather than to ecological processes. These findings demonstrate that P. apodus exhibits a compact spatial core embedded within a broad, sparsely occupied periphery, underscoring the limitations of EOO-based metrics in the conservation assessment of widely distributed reptiles. We emphasise that this structure is characterised using the density of occurrence records and therefore describes the observed spatial organisation of the available data rather than directly measured population density; ecological interpretations are accordingly framed as hypotheses requiring independent validation.
- MakaleYalnız künye2026Cultural adaptation and psychometric validation of the Azerbaijani version of the Optimism Scale among university students
Güngör, Sunay; Karimi, Kambiz
In a dynamic society, instilling a sense of positive attitudes is crucial. Yılmaz and Balcı's (2002) The Optimism Scale was translated into Azerbaijani and its construct validity and reliability were tested using a convenience sample of university students (n = 300, 18–24 years). cities. The sample was split for exploratory and confirmatory factor analysis. Findings showed cultural commonalities between Azerbaijani and Turkish societies, attested through shared factors such as religion and language. The scale showed high construct validity, high internal consistency (Cronbach's alpha =.869; McDonald's omega =.867), and convergent validity (r =.41 with measures of happiness). It supports usability of the scale in Azerbaijan. Future studies should explore structural characteristics of the scale among different populations and age brackets.
- MakaleAçık Erişim2026The Effect of a Psychiatric Nurse–Led AI-Based Online Group Guided Self-Help Program on Eating Behaviours and Body Image among Overweight and Obese Women Nurses: A Randomized Controlled Trial
Tuncer, Gülsüm Zekiye; Duman, Zekiye Çetinkaya; Tuncer, Metin
Aim: This study aimed to evaluate the effectiveness of a psychiatric nurse–led, AI-supported online group guided self-help programme on eating behaviours, body image, and body mass index (BMI) among overweight and obese women nurses. Method: A randomised controlled experimental design with pre-test, post-test, and three-month follow-up assessments was employed. Forty-four overweight and obese women nurses were randomly assigned to intervention (n = 22) and control (n = 22) groups. The intervention consisted of an 8-week online group guided self-help programme supported by a large language model (LLM), under the leadership of a psychiatric nurse. Participants did not interact directly with the LLM; all AI-generated feedback was clinically reviewed and delivered by the researcher. Results: The intervention group demonstrated significant reductions in emotional eating and external eating, along with significant improvements in body image scores and adaptive coping strategies. A significant decrease in BMI was also observed from baseline to three-month follow-up. Between-group comparisons at post-test and follow-up indicated statistically significant differences favouring the intervention for eating behaviours and selected body image–related outcomes, whereas between-group differences in BMI were not statistically significant. Conclusion: A multi-component online group guided self-help intervention incorporating structured AI-assisted feedback under psychiatric nurse leadership may represent a promising approach to improving eating behaviours, body image, and weight-related outcomes among overweight and obese women nurses.
- MakaleYalnız künye2026Purification of catalase enzyme from Thymus nummularius and examination of the effects of varying glucose concentrations on catalase activity
Toprak, Esma; Güleşci, Nuri
Catalase (EC 1.11.1.6), an antioxidant enzyme, breaks down reactive oxygen species, hydrogen peroxide (H2O2), into water and oxygen. In this study, the partial purification of catalase was obtained from Thymus nummularius M. Bieb. through ammonium sulfate (NH4)2SO4 precipitation, dialysis, and desalting/buffer exchange by using a PD-10 Sephadex G-25 M column. The isolated enzyme had a specific activity of 1294.45 U/mg protein and a purification fold of 7.80. The SDS-PAGE analysis indicated a molecular weight ranging between 37 and 50 kDa. The optimal pH and temperature for catalase activity were determined to be pH 8.0 and 25 °C, respectively. The kinetic parameters, maximum velocity (Vmax) 277.78 U/mL and Michaelis constant (KM) 34.17 mM were estimated from Lineweaver-Burk plots. Furthermore, catalase activity was evaluated at glucose concentrations ranging between 25 and 500 ppm. Enzyme activity increased at 25–100 ppm, significantly decreased at 250 ppm, and then increased again at 500 ppm. These results suggest that glucose may modulate catalase activity in a concentration-dependent manner. Even though the exact regulatory mechanism remains unclear, this effect could have potential implications for glucose-sensitive metabolic systems.
- MakaleAçık Erişim2026Integrated MCDM-based evaluation of urban intersection congestion
Tona, Aziz Ugur; Maraş, Erdem Emin
This study aimed to systematically evaluate the factors affecting traffic congestion at urban intersections and rank them based on congestion levels. Three multi-criteria decision-making (MCDM) techniques—Content validity method (CVM), best-worst method (BWM), and technique for order preference by similarity to ideal solutions (TOPSIS)—were used in an integrated framework. First, 15 potential congestion-related criteria were identified through literature and expert input. Using CVM, 8 key criteria were selected based on field-measured traffic data, official accident records obtained from relevant authorities, and structured on-site observational measurements. Their optimal weights were then calculated via a linear optimization model within the BWM. These weights were fed into TOPSIS for estimation and ranking of junction congestion. The examination also showed the Karayolları intersection to be the most congested (score: 0.711) and Toplu Konut Boulevard Intersection to be the least congested (score: 0.140). The findings provide essential information for decision-makers, aiding initiatives to enhance urban traffic flow by pinpointing crucial crossings and suggesting alternative geometric configurations. In addition, a sensitivity analysis across different weight conditions has confirmed the reliability and practical usefulness of the model. This proposed approach serves also as a tactical tool to prioritize interventions and improve the efficacy of transportation networks in urban environments.
- MakaleYalnız künye2026Evaluation of family-centered care from the perspectives of pediatric nurses, nursing students and parents: A mixed-methods study
Çolak, Bahar; Güner, Yasemin; Goger, Berrin; Kahriman, İlknur; Dal Sevim, Şura
Introduction This study aimed to evaluate family-centered care (FCC) practices in pediatric units from the perspectives of pediatric nurses, nursing students, and parents. Methods A convergent parallel mixed-methods design was employed. Quantitative data were collected using a cross-sectional design, while qualitative data were obtained through a case study approach. The sample consisted of 338 parents, 221 nursing students, and 10 pediatric nurses. Parents completed the FCC Assessment Scale and the PedsQL Healthcare Satisfaction Module, nursing students completed the Caring Behaviors Inventory, and pediatric nurses participated in semi-structured interviews. Results Parents reported high scores in the FCC dimensions of “support,” “collaboration,” and “respect,” which significantly predicted parental satisfaction. The “support” dimension was the strongest predictor of satisfaction with information, family participation, and technical skills. Nursing students rated pediatric nurses' caring behaviors highly. Qualitative analysis identified five major themes: (1) Perception of FCC, (2) Role of the Nurse, (3) Role of the Physician, (4) Benefits of FCC, and (5) Barriers to FCC. These themes highlighted the importance of family participation, the nurse's leadership role, gaps in physician communication, the multifaceted benefits of FCC at the child, family, and system levels, and barriers including workload, physical environment limitations, and family-related challenges. Conclusion Perceived FCC practices significantly predicted parental satisfaction. However, improvements are needed in information sharing, family participation, and physical environment conditions. Implications to practice These findings provide valuable insights for developing educational, clinical, and policy strategies to strengthen the implementation of FCC in pediatric nursing practice.
- Kitap BölümüYalnız künye2026Artificial Intelligence Nanocomposite Synergy for Next-Generation Fuel Desulfurization
Kostas, Rabia Yasa; Bozbeyoglu, Pinar; Altuner, Elif Esra; Elmas, Muzaffer
Fuel desulfurization is crucial due to the harmful effects of acid rain, air pollution, and health issues associated with sulfur compounds from fossil fuel combustion. Stricter international regulations require reducing sulfur content in fuels to ultra- low levels (<15 ppm), which current hydrodesulfurization (HDS) technology struggles to achieve due to high energy costs and inefficiencies with refractory aromatic sulfur compounds, such as dibenzothiophene (DBT). This gap in technology is driving the development of new solutions. This study explores the integration of materials science, chemical engineering, and artificial intelligence (AI) to meet ultra- low sulfur targets. It highlights alternative strategies, such as adsorptive (ADS) and oxidative (ODS) desulfurization, using advanced nanocomposite materials, including MetalOrganic Frameworks (MOFs), graphene hybrids, and zeolites. These innovative materials focus on “precision targeting” and “molecular recognition,” offering greater efficiency under milder conditions compared to traditional HDS methods AI and computational science are crucial for identifying the most suitable materials among a vast array of candidates. Combining Density Functional Theory (DFT) with Machine Learning (ML) accelerates material discovery by transitioning from a trial- and- error approach to an “inverse design” method. Successful AI tools, including Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs), have been proven effective in optimising desulfurization processes through real- world examples. In summary, achieving cleaner fuels requires innovative materials guided by AI. The study also addresses the challenges of scaling this interdisciplinary approach and envisions the potential for transforming desulfurization from a cost centre into a profit centre through precise molecular separation.
- MakaleYalnız künye2026A Dense and Sparse Attention in Vision Transformer for Remote Sensing Image Classification
Celik, Kemal
Satellite imagery plays a crucial role in various applications, such as environmental monitoring, urban planning, and disaster response. Previously, Convolutional neural networks have played a crucial role in improving remote sensing scene classification by effectively capturing spatial features. However, they often struggle with long-range dependencies and complex spectral patterns in satellite images. Recently, transformer-based architectures, initially designed for natural language processing, have been adopted in computer vision to leverage self-attention mechanisms for capturing long-range dependencies. To effectively extract the long-range dependencies and complex patterns, this paper proposes a novel method combining dense and sparse attention mechanisms to enhance remote sensing scene classification in different scales. The dense attention mechanisms capture comprehensive connections within satellite images, followed by sparse attention mechanisms applied at both tile and patch scale levels. This multi-scale attention strategy allows the model to efficiently focus on important spatial and spectral features while managing computational complexity. Extensive experimental evaluations on three benchmark datasets, such as Merced, AID, and Optimal-31, demonstrate significant improvements in classification accuracy, achieving 98.9, 97.5, and 97.8, respectively. Experimental results show that the proposed framework outperforms CNN and Transformer baselines, enhancing the accuracy and robustness of remote sensing scene classification for geospatial analysis.
- MakaleAçık Erişim2026The novel conformable methods to solve conformable time- fractional coupled Whitham-Broer-Kaup equation
Alkan, Aslı; Avit, Özkan; Anaç, Halil
This study employs two innovative techniques, namely the conformable q-homotopy analysis transform method (Cq-HATM) and the conformable Elzaki Adomian decomposition method (CEADM), to investigate the numerical solutions for the conformable time-fractional coupled Whitham-Broer-Kaup problem. One of the two novel approaches offered is Cq-HATM, which is a hybrid approach that integrates the q-homotopy analysis transform method with Laplace transform using the concept of conformable derivative. The CEADM method, like the aforementioned approach, is a hybrid method that integrates the Adomian decomposition method and Elzaki transform by utilizing the concept of conformable derivative. The computer simulations were conducted in order to provide empirical evidence supporting the efficacy and reliability of the recommended methodologies. Upon comparing the precise solutions with the obtained solutions, it becomes evident that both of the novel methodologies exhibit simplicity, efficacy, and proficiency in addressing nonlinear conformable time-fractional partial differential equations.
- MakaleAçık Erişim2026The effect of behavioral factors related to cashlessness on the perception of green finance
Özbek, Adem; Çam, Alper Veli; Soydaş, Şafak Sönmez; Barut, Abdulkadir; Sharabati, Abdel-Aziz Ahmad
This study aims to examine the effects of behavioral factors shaping cashless payment behaviors in Turkey on green finance perception. The study focuses on subconscious factors such as functional benefit, economic benefit, psychological benefit, attitude toward technology, and perceived behavioral control. Data were collected from 520 participants aged 18 and older via an online survey and analyzed using Structural Equation Modeling (SEM). The findings reveal that functional benefit, perceived behavioral control, and attitudes toward technology significantly and positively influence perceptions of green finance, while economic and psychological benefits do not have a significant effect on behavioral control. The results reveal that behavioral factors such as ease of use and attitudes toward technology play a more significant role in individuals’ adoption of cashless payment systems than rational economic gain expectations. The study contributes to the literature by showing that cashless payment behaviors contribute to the development of sustainable finance and environmental awareness. It also provides practical recommendations for policymakers and financial institutions on improving digital payment infrastructure and user experience to promote green finance.
- MakaleYalnız künye2026Spatial heterogeneity of microscopically detected Nosema spp. infection in honeybees: Climate-associated patterns in the Eastern Black Sea Region of Türkiye
Tosun, Onur; Bekircan, Çağrı; Kurnaz, Muammer
Nosemosis has emerged as the predominant microsporidian infection of honeybees (Apis mellifera L.) in many regions, including Türkiye, yet the climatic drivers of its epidemiology remain insufficiently quantified. This study assessed the effects of temperature and relative humidity on nosemosis prevalence across seven provinces in the climatically diverse Eastern Black Sea region. A dataset of 2688 colony-level observations was analyzed using generalized linear models, mixed-effects models, beta regression, generalized additive models, and spatial autocorrelation. Both temperature and humidity were consistently significant predictors (p < .001). Quadratic temperature terms and nonlinear GAM smooths were consistent with a thermal performance pattern, with infection peaking at intermediate ranges. Humidity exerted threshold-like effects, with disproportionately higher prevalence at upper quantiles. Province-level random effects accounted for ∼18% of variance, underscoring spatial heterogeneity, while elevation was not significant once climatic variables were included. Exploratory spatial analysis (Global Moran's I = −0.476, p = 0.043) tentatively suggested dispersion rather than clustering; however, given the very small number of spatial units (n = 7), this result should be regarded as hypothesis-generating only. The beta mixed-effects model achieved moderate predictive accuracy under cross-validation (RMSE ≈ 0.109). Collectively, these findings indicate that nosemosis prevalence in the region is strongly associated with climatic variability, exhibits nonlinear and threshold-like responses, and shows pronounced spatial heterogeneity. We emphasize that these are statistical associations and that unmeasured factors (e.g., colony strength, nutrition, pesticide exposure, management practices, and co-infections) likely contribute to the unexplained variance. By integrating hierarchical, nonlinear, and spatial approaches, this study establishes a climate-associated epidemiological assessment of nosemosis risk in A. mellifera and highlights the importance of localized climatic suitability under ongoing climate change.
- MakaleAçık Erişim2026A Deep Learning–Based Framework for Automatic Determination of Developmental Dysplasia of the Hip from Graf Angles
Taşolar, Sevgi; Günen, Mehmet Akif; Sığırcı, Ahmet; Taşolar, Hakan
Developmental dysplasia of the hip (DDH) is a common neonatal condition that necessitates early diagnosis to ensure effective treatment. The traditional Graf method, while widely used for evaluating infant hips via ultrasound, is limited by operator dependency and measurement variability. This research has proposed a framework using deep learning network, morphological operation and local maxima method to diagnose DDH in newborns using ultrasound images. The method utilizes DeepLabv3 + for image segmentation, evaluating multiple backbone architectures (ResNet50, InceptionResNetV2, MobilenetV2, and Xception) to identify the region of interest accurately. Local maxima method was used to determine the extremum points of the line defining the Graf angles. Denoising filters, including mean, median, and Wiener, are applied to determine local maxima points accurately. The evaluation comprises two stages: first, assessing the performance of DeepLabv3 + backbones in producing masks for Graf angles determination, and second, comparing the angles obtained through proposed framework with those determined by expert radiologists. Comparative analysis demonstrates that MobileNetV2 (94.64 accuracy, 86.99 Cohen’s kappa, 94.31 F-score) surpasses other models in segmentation accuracy and measurement reliability. This conclusion is backed by key performance metrics such as accuracy, IoU, PSNR, F-score, SSIM, Cohen’s kappa, as well as by the intraclass correlation coefficient and Bland–Altman analyses. The proposed framework shows considerable promise in automating hip ultrasound analysis for DDH diagnosis, minimizing operator dependency while enhancing measurement consistency.
- MakaleAçık Erişim2026Modulation of Hot Pepper Pungency by Melt Dispersion Encapsulation: Role of Wax Type on Microcapsule Structure, Bioactive Compound Content, and Antioxidant Activity
İncegül, Yasemin; Berktaş, Serap; Çam, Mustafa
In this study, it was aimed to suppress pungency and obtain a new product by using carnauba, beeswax, and their mixture in the encapsulation of hot pepper oleoresin. Melt dispersion technique was used in production and physical, chemical, and structural analyzes of the obtained capsules were examined. The suppression of the pungency sensation was determined by sensory analysis, and it was determined that the beeswax-based capsule (BW50) was the most effective formulation in suppressing pungency perception (0.83). When looking at the sensory and Scoville Heat Units (SHU) results, there is a parallelism, and it can be stated that the pungency sensation is suppressed. The highest encapsulation efficiency values were observed in CW20 (91.92%), BW20 (90.69%), BC20 (86.92%), and CW30 (86.49%) capsules. When capsule bioactivities were examined, beeswax capsules showed the highest values, while carnauba wax capsules generally showed the lowest values. As expected, as the amount of oleoresin in the capsules increased, the capsules exhibited higher phenolic, flavonoid, carotenoid, and antioxidant activity scores. SEM, FT-IR, and TGA determined that the encapsulation process did not cause any adverse structural reactions in oleoresin. This study broadened the potential application of encapsulated hot pepper oleoresin in food formulations, particularly in functional foods and products intended for consumers sensitive to pungency, by converting it into a more tolerable form.
- MakaleAçık Erişim2026Semantic Architecture and Knowledge Evolution of Endoscopic Submucosal Dissection Research: A Computational Bibliometric Analysis
Demir, Huseyin; Akar, Tuncay; Mertoglu, Suleyman; Tekinarslan, Merve
Aim: The overarching intellectual structure, dominant thematic clusters, and longitudinal evolution of the endoscopic submucosal dissection (ESD) literature have yet to be systematically mapped. This study aims to characterize the semantic and thematic architecture of ESD research through computational text analytics and to reveal latent structural patterns and temporal dynamics within this domain. Methods: A corpus of 1,000 peer-reviewed publications was processed through an eight-stage computational pipeline that incorporated word embedding-based semantic analysis, unsupervised clustering, Latent Dirichlet Allocation (LDA) topic modeling, inter-topic network analysis, and temporal trend modeling. The primary outcome was characterization of the semantic architecture of ESD research, whereas secondary outcomes included topic relationships, temporal evolution, and model performance metrics. Results: Semantic analysis revealed two dominant clusters: a technically oriented domain encompassing device innovation and procedural optimization and a clinically oriented domain addressing therapeutic outcomes, organ-specific protocols, and adverse event management. Topic modeling identified nine coherent thematic categories, with limited integration between technical and clinical research trajectories. Temporal analysis revealed a pronounced post-2024 shift toward upper-gastrointestinal applications, particularly esophageal and gastric ESD, with relative stagnation in colorectal investigations. The optimal semantic clustering solution achieved a silhouette score of 0.215, while the nine-topic LDA model demonstrated a coherence score of 0.39. Conclusion: This study provides the first data-driven macro-structural characterization of the ESD literature, revealing a persistent bifurcation between technical innovation and clinical application streams. These findings offer a strategic framework to help clinicians, investigators, and curriculum developers identify priority areas for advancement in therapeutic endoscopy.
- MakaleYalnız künye2026Minimum covariance determinant-based estimators for estimating population mean using two auxiliary variables
Zaman, Tolga; Islamoglu, Ebrucan; Bulut, Hasan
This study addresses the challenge of outliers in sample surveys, a common issue that can distort results and lead to inaccurate conclusions. To tackle this problem, researchers have developed various robust regression techniques including least trimmed squares, least median of squares, least absolute deviations, Huber’s, Hample’s and Tukey’s maximum likelihood estimators, and Huber’s maximum likelihood estimator for location and scale estimators. We propose a new approach: minimum covariance determinant-based ratio estimators for estimating the population mean in sample surveys. To assess the performance of the proposed minimum covariance determinant-based estimators, we derive their mean square error expressions and determine the conditions under which they surpass existing estimators in efficiency. To validate our theoretical findings, we conduct a numerical illustration using real-world data and perform simulations with R-Programme software. The results demonstrate that our method effectively handles outliers and improves the overall accuracy of survey-based estimations, making it a valuable tool for researchers working with sample survey data.
- MakaleYalnız künye2026Challenge of existence: social anxiety in Finding Audrey
Demir, Nalan
Mental health problems affect individuals worldwide, and literature functions as a medium for both reflecting and shaping social understandings of these issues. Young adult (YA) novels that address mental health can raise public awareness, enhance mental health literacy, and support earlier diagnosis and more effective treatment. This study examines the representation of social anxiety disorder in Finding Audrey (2015) by Sophie Kinsella, focusing on the protagonist Audrey Turner. It analyses Audrey’s experience through her symptoms and treatment process, classifying symptoms into behavioural and cognitive-emotional categories. Behavioural symptoms include avoidance, limited eye contact, and physical reactions, while cognitive-emotional symptoms involve negative self-talk, shame, low self-esteem, negative self-perception, and diminished trust in others. These symptoms and the depicted therapeutic approaches are evaluated in relation to current psychological and psychiatric research. Overall, the novel presents social anxiety disorder in a realistic and psychologically coherent manner, aligning with findings in psychology and psychiatry.
- MakaleYayıncıda açık erişim2026Production and Multi-Criteria Evaluation of Healthy White Cheese Snacks Using Microwave-Vacuum Drying
Ayrancı, Vasıf Kubilay; Mzoughi, Mondher; Salum, Pelin; Zemzemoğlu, Tuba Eda Arpa; Erbay, Zafer
Microwave-assisted vacuum drying (MVD) is an emerging technology suitable for producing healthy snack foods, such as cheese snacks. This study aimed to produce a low-fat, low-salt, crunchy cheese snack using MVD. Low-fat, low-salt cheese slices were dried under seven different combinations of microwave power (5%–15%), vacuum level (220–300 Torr), and drying time (6.5–11 min), selected through preliminary trials. The resulting snacks were characterized by their physical properties and volatile compound profile. The results revealed significant differences in moisture content, water activity, bulk density, and volumetric/surface/cross-sectional expansion among the samples. Samples produced under high vacuum and long process time conditions exhibited the most favorable overall characteristics, including the lowest moisture, water activity, and density, alongside the highest volume expansion. These samples also showed a darker color and a superior crispy texture (higher fracturability with lower hardness, springiness, and chewiness). Twelve volatile compounds, with a profile limited by the low-fat content of the cheese, were detected. The TOPSIS analysis identified the sample produced under high vacuum conditions (dried at 10% power, 220 Torr, 10 min) as optimal. Practical Applications: This study provides a roadmap for producing crunchy, low-fat, and low-salt cheese snacks using microwave vacuum drying. For food manufacturers, the identified optimal conditions offer a process guideline to develop a healthier snack alternative with an appealing texture and color. The systematic TOPSIS-based evaluation method can be adopted for quality control and product development decisions. For consumers, the resulting product aligns with growing demand for nutritious, reduced-sodium convenience foods.
- MakaleAçık Erişim2026Effect of Breastfeeding Education Delivered Through Motivational Interviewing on Breastfeeding Motivation, Self-Efficacy, and Maternal Bonding in Mothers Giving Vaginal Birth: Randomized, Controlled Trial
Palancı Ay, Özge; Aktaş, Songül
Objectives: This study examined the effect of breastfeeding education using the motivational interviewing technique on breastfeeding motivation, self-efficacy, and mother–infant bonding in mothers who gave birth vaginally. Methods: This randomized, controlled trial included 80 primiparous mothers. The experimental group received breastfeeding education with the motivational interviewing technique at four time points. Data were collected using Maternal Descriptive Information Form (MDIF), the Primiparous Breastfeeding Motivation Scale (PBMS), the Breastfeeding Self-Efficacy Scale (BSES), the Mother–Infant Bonding Scale (MIBS), and the Motivational Interviewing Importance and Confidence-Efficacy Rating Scale. Data were collected at three time points: immediately before training (pretest), 15 days following completion of the training (post-test), and 4 weeks thereafter (follow-up). Data were evaluated using Student’s t test, Mann–Whitney U test, analysis of variance, Friedman variance test, and intention-to-treat analysis. Results: In the post-test and follow-up evaluations, the experimental group had significantly higher mean scores than the control group in the “Value ascribed to breastfeeding” (p < 0.001 and p = 0.004, respectively) and “Midwife support” (p < 0.001 and p = 0.003, respectively) subdimensions of the PBMS as well as in “Motivational interviewing importance” (p < 0.005) and “Confidence-efficacy rating scale” (p < 0.001). During the follow-up period, the experimental group also showed significantly higher scores in the “Self-efficacy” subdimension (p < 0.001) and total mean scores of the BSES (p = 0.033) and MIBS (p = 0.002) than the control group. However, the “Expectation of success” subdimension score of the PBMS was not significant (p > 0.05). Conclusion: Breastfeeding education using the motivational interviewing technique enhances breastfeeding motivation (including values ascribed to breastfeeding, self-efficacy, and midwife support), breastfeeding self-efficacy, mother–infant bonding, and the importance and confidence-efficacy levels in breastfeeding. © The Author(s) 2026. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
- MakaleYalnız künye20265-Hydroxymethylfurfural and furfural levels in non-alcoholic beverages: a survey of product types
Arslan Burnaz, Nesibe; Baltacı, Cemalettin; İlyasoğlu, Huri
Toxic furanic compounds such as 5-hydroxymethylfurfural (HMF) and 2-furfural (F) can form during the processing and storage of non-alcoholic beverages (NABs). This study aimed to determine the levels of HMF and F in a wide range of NAB categories, including fruit juices and nectars, carbonated soft drinks, non-carbonated soft drinks, energy drinks, and coffee with milk drinks. The levels of HMF and F were determined using a validated analytical method. The HMF and F levels of the studied samples varied depending on the type of product. The coffee with milk drinks exhibited the highest levels, while the carbonated soft drinks exhibited the lowest. Notably, the HMF levels of most of the coffee with milk drinks exceeded 10 mg L−1. The findings provide novel insights into the presence of furanic compounds in NABs and emphasise the importance of raising consumer awareness regarding potential dietary exposure to furanic compounds, particularly from coffee drinks.
- MakaleYalnız künye2026Unraveling the Web of Marital Well-Being: Associations Among Relationship Quality, Emotion Regulation, and Cognitive Flexibility
Özer, Şükrü; Odaci, Hatice
This study aims to explore the associations among relationship quality, cognitive flexibility, cognitive emotion regulation, and subjective well-being in married individuals in Turkey. Using a cross-sectional correlational design, we collected data from 1,013 married participants (mean age = 40.65; 52.5% male). Results indicated that relationship quality was positively associated with subjective well-being, cognitive flexibility, and adaptive emotion regulation strategies and negatively associated with maladaptive emotion-regulation strategies. Cognitive flexibility and adaptive emotion-regulation strategies were positively associated with subjective well-being, whereas maladaptive strategies were negatively associated. Mediation analyses revealed significant indirect associations between relationship quality and subjective well-being through cognitive flexibility and both adaptive and maladaptive emotion-regulation strategies. These findings highlight patterns of association among relational and cognitive-emotional variables in marital well-being and may inform future research and clinical practice.