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 SJRQ2CropHealthNet: Potato Disease Detection Using Depthwise Separable Convolutional Neural Networks
Catal Reis, Hatice
Plant diseases are one of the primary factors that threaten food security, crop yields, harvesting, and sustainable production in the agricultural sector. In this context, early disease diagnosis is essential for enhancing agricultural productivity and reducing crop losses. In modern agricultural practices, machine learning-based approaches offer effective and innovative solutions for detecting and classifying plant diseases. These modern and innovative methods generally reach high accuracy rates with large-scale image datasets. In particular, deep learning algorithms have achieved significant success in modeling disease’s spread dynamics and detecting early disease symptoms. In this study, a convolutional neural network (CNN)-based, lightly parallel deep learning model called CropHealthNet is proposed for classifying potato leaf diseases. The model is designed with special depthwise separable convolution-based convolution layers to reduce the computational cost of CNN. CropHealthNet is a low-parameter model suitable for real-time operation, capable of recognizing disease-specific patterns with high accuracy. CropHealthNet aims to achieve deep and comprehensive feature extraction through its parallel structure and varying channel numbers. The features from each parallel structure are combined at multiple levels, increasing the model’s ability to detect abstract and deep patterns. Moreover, the proposed model has extremely low computational complexity with only 0.47 million parameters and 0.59 GFLOPs, thus offering high efficiency compared to existing approaches. The effectiveness of the proposed model was evaluated using the PlantVillage Potato Dataset. Since the PlantVillage Potato Dataset has an unbalanced data distribution, the number of data for each class has been equalized using the Synthetic Minority Over-sampling Technique (SMOTE) to evaluate the model’s performance against data imbalance. The proposed model succeeded in achieving 99.30% and 99.50% accuracy rates in the tests conducted with unbalanced and balanced datasets, respectively. Experimental findings show that the proposed model generalizes well despite data imbalance and correctly classify diseases on potato leaves. Therefore, the model can demonstrate strong performance in agricultural practices and can detect plant diseases under real-world conditions.
AtıfScopus3WoS2OpenAlex3
İncele - MakaleAçık Erişim2026Scopus SJRQ1The impact of addictive substances on employees’ job performance and workplace safety: A phenomenologi̇cal study
Doğan, Onur
This study aims to explore the impact of substance addiction on employees’ job performance and workplace safety through a phenomenological lens. The research focuses on how individuals with substance use disorders perceive their professional experiences, emotional states, and social interactions within the work environment. The study was designed using a qualitative phenomenological method. Semi-structured in depth interviews were conducted with 15 mining employees selected via criterion sampling. The participants, all of whom had a history of substance use, were interviewed across different regions in Turkey. Audio recorded interviews were transcribed and analyzed through thematic analysis. The study adhered to ethical standards and was reported according to the COREQ checklist. Three main themes and related subthemes emerged from the analysis: (1) The impact of substance use on job performance and safety attitudes; (2) Alienation and loss of professional identity in the workplace; and (3) Inner emotional challenges and individual coping strategies. Participants described cognitive difficulties, emotional exhaustion, increased workplace errors, weakened safety compliance, social isolation, and loss of belonging. Some individuals also reported efforts to recover and reestablish self control through personal strategies and peer support. The findings reveal that substance use significantly disrupts professional functionality, emotional stability, and organizational connectedness. The study emphasizes the need for empathy driven, context sensitive support strategies to improve employee well being and workplace safety. By bringing forward the lived experiences of affected workers, this research contributes valuable insights for developing preventive approaches and reinforcing safety culture within occupational settings.
AtıfScopus2WoS2OpenAlex3İncele - MakaleAçık Erişim2026Scopus SJRQ3Phenolic and antioxidant assessment of the flowers, stems, leaves, and fruits of Rosa pimpinellifolia and Rosa canina at different growth time
Öz, Mehmet; Okan, Onur Tolga; Baltaci, Cemalettin
Natural plants are abundant in their native habitats and are traditionally used to treat a variety of health conditions. The Rosa genus stands out as an important species rich in bioactive compounds. This study, conducted in Türkiye, aimed to analyse the antioxidant and phenolic profiles of methanolic extracts obtained from different parts of Rosa canina (R.c.) and Rosa pimpinelifolia (R.p.) collected in 2021 and 2022. The antioxidant activity values of R.c. collected in 2021 and 2022 were found to be between 5 102.31–46 396.36 mmol Fe(II)/100 g in ferric reducing antioxidant power (FRAP), 141.92–377.54 mg ascorbic acid equivalents (AA)/kg in total antioxidant capacity (TAC), 2.18–24.68 µg/g in 2,2-diphenyl-1-picrylhydrazyl [DPPH (EC50)] and 34.31–75.77% in DPPH (% inhibition). Antioxidant activity of R.p. collected in 2021 and 2022 ranged from 17 258.44–71 903.20 mmol Fe(II)/100 g, 271.69–479.19 mg AA/kg, 1.02–8.32 µg/g and 50.98–85.57% for FRAP, TAC, DPPH (EC50) and DPPH (% inhibition), respectively. The R.p. extracts generally exhibited higher antioxidant activity than those of R.c. Considering the total identified phenolic compounds achieved from different plant parts of rosehip for both years, the highest values of total phenolic compounds were determined in R.c. leaves (222.08 mg/100 g) in 2021, and R.p. leaves (5 465.95 mg/100 g) in 2021.
- MakaleYalnız künye2026Scopus SJRQ3Optimal approach to enhancing population mean estimation using auxiliary parameters
Kumar, Surendra; Bari, Tarushree; Yadav, Subhash Kumar; Zaman, Tolga
This study presents an efficient method for estimating the population mean of a study variable using a Searls exponential ratio estimator. The approach is based on simple random sampling and leverages known population parameters of an auxiliary variable for enhanced estimation of population mean. Using large sample approximations up to the first order, the expressions for the bias and mean squared error of the proposed estimator are derived. To evaluate its performance, the estimator is compared conceptually and mathematically with several existing estimators. Theoretical results are further validated through both simulated and real-world data sets. Findings from these evaluations demonstrate that the proposed estimator consistently outperforms many competing estimators, particularly at higher population mean values. Therefore, it holds promise for improving population mean estimation across a range of practical applications.
AtıfWoS1İncele - MakaleYalnız künye2026Scopus SJRQ2Emergency Nurses’ Experiences of Digital Silence: A Qualitative Study
Bal, Betül; Kulakaç, Nurşen
This study aimed to explore emergency department nurses’ perceptions and experiences of digital silence. A qualitative study was conducted with 14 emergency department nurses from two public hospitals in Turkey. Data were collected through semistructured in-person interviews and analyzed using the Framework Method for qualitative data analysis. Four overarching themes were identified: (i) awareness of digital silence, (ii) types of digital silence, (iii) causes of digital silence, and (iv) strategies for prevention. Digital silence manifests in several forms, including failure or partial completion of data entry, the use of alternative communication channels in place of official digital systems, and disregard for system alarms or alerts. The reasons underlying digital silence stem from both individual factors and organizational factors. Strategies to reduce digital silence involved training, development of user-friendly systems, establishment of nonpunitive reporting environments, and workload management. The results revealed that digital silence extends beyond individual attitudes, representing a multidimensional phenomenon closely associated with institutional structures, organizational culture, and the design features of digital systems. Enhancing system usability, reinforcing technical infrastructure, and promoting digital literacy were identified as key strategies for reducing digital silence behaviors.
- MakaleYalnız künye2026Scopus SJRQ1Children's voices in disaster recovery: Lessons from the 2023 Turkey-Syria earthquake
Yildiz, Ayse; Simsek, Nurcan; Boluk, Aysegul
Disasters have a devastating impact on populations, with children being one of the most at-risk groups. Although their vulnerability in disasters is widely recognised, children's own voices are still largely missing from disaster recovery research and planning. This study aims to address that gap by listening directly to the experiences and perspectives of children aged 11 to 14 in Nurdağı, Gaziantep, one of the hardest-hit areas in Türkiye, on disaster relief and recovery. Using a qualitative, child-centred approach, grounded in a socio-ecological, rights-based framework, we conducted interviews with 58 children, alongside 47 additional interviews with parents, teachers, and first responders, to understand how young people coped with life after the earthquake, what challenges they faced, and what they believe would support recovery. The findings show that children struggled with difficult living conditions, trauma, disrupted education, and changing social relationships, but they also demonstrated remarkable insight, emotional intelligence, and a desire to be involved in rebuilding their communities. Many children questioned the fairness of aid distribution and called for more attention to mental health and safer schools. Rather than portraying children as passive victims, the study highlights their capacity to reflect, adapt, and contribute. It calls for more inclusive, responsive recovery strategies that treat children as active participants in disaster planning and post-disaster rebuilding. The study offers actionable recommendations for policymakers, educators, and humanitarian practitioners to better integrate children's perspectives into long-term recovery planning and resilience-building initiatives.
AtıfWoS1OpenAlex2İncele - MakaleYalnız künye2026Scopus SJRQ2Integrating Artificial Intelligence Into Nursing Care Planning: A Comparative Evaluation of Psychosocial Care for Patients With a Stoma
Kulakaç, Nurşen; Tuncer, Metin
This methodological study evaluated and compared the content quality and appropriateness of nursing care plans developed by nurses and artificial intelligence (AI) for addressing the psychosocial problems of patients with stomas. Two nursing care plans addressing the psychosocial needs of a patient with a stoma were developed: 1 generated by nurses and 1 generated by an AI system. The content quality and appropriateness of the care plans were independently evaluated by 12 experts, including nursing academics and clinical nurses, using the DISCERN measurement tool. Inter-rater reliability was assessed using the intraclass correlation coefficient (ICC). The mean DISCERN score of the nurse-generated care plan was significantly higher than that of the AI-generated care plan (P=.008). Inter-rater agreement demonstrated good agreement. The findings indicate that nurse-generated care plans demonstrate superior content quality and overall integrity compared to AI-generated plans. AI-generated care plans exhibit potential as supportive tools in nursing care planning.
- Kitap BölümüYalnız künye2026Fungi-Derived Food Additives and Flavors
Arpa Zemzemoğlu, Tuba Eda; Eker, Tülin
The growing global population, the decline in edible food sources, technological advancements, and limited time have led to significant changes in society's eating habits. The increasing preference for ready-to-eat and semi-prepared foods has also resulted in higher consumption of food additives. In today's conditions, food additives are used at various stages of the food supply chain, from farm to fork, for different purposes. However, excessive intake of food additives may have negative health effects. For this reason, there has been a growing interest in natural food additives in recent years. Due to their functional properties, edible mushrooms are widely used as versatile ingredients in food product development. This chapter aims to determine the potential of edible mushrooms as food additives. Edible mushrooms can be used as meat substitutes in various food products, reducing fat and animal protein content while increasing dietary fiber and amino acid levels. When used as fat replacers, they lower fat levels in processed foods and enhance sensory properties. When incorporated as flour substitutes in baked goods, they boost dietary fiber, protein content, and antioxidant capacity. Additionally, mushrooms act as natural salt and phosphate substitutes, reducing sodium levels in meat products and replacing synthetic additives while maintaining sensory acceptability and product quality. Mushrooms also have great potential as natural colorants. Their natural origin, low-cost and high-yield production, and wide color spectrum make them suitable for use as food additives. These multifunctional roles of edible mushrooms highlight their potential to enhance nutritional profiles and promote sustainability in food formulations.
- MakaleYayıncıda açık erişim2026Scopus SJRQ3The Effect of Music-Repeating Robotic Parrot Therapy and Different Instrumental Live Music Therapies on Anxiety and Fatigue Levels in Hemodialysis Patients: A Randomized Controlled Trial
Demirağ, Hatice; Cin, Aynur; Aktepe Coşar, Dilan; Uzun, Sevda; Türkmen, Osman Oğulcan
Aim: This study aimed to evaluate the effects of three different music-based interventions on anxiety and fatigue levels in patients undergoing hemodialysis, compared to a concurrent control group receiving standard care. Methods: This randomized controlled trial involved 64 patients receiving maintenance hemodialysis. They were randomly assigned to four equal groups (n = 16 each): live music, live ney sound therapy (using a traditional reed flute known for its soothing, breath-like tones), a music-repeating robotic parrot therapy (an interactive robotic parrot that repeats music or sounds provided by the patient), or a control group (no intervention). The experimental groups received 30-min sessions 3 days per week for 2 months. The “Beck Anxiety Scale” and “Fatigue Severity Scale” were used to measure anxiety and fatigue, respectively. Assessments were performed before the intervention, immediately after the 2-month intervention period, and at 2 months after the end of the intervention period. Results: Before the intervention, there were no significant differences in anxiety or fatigue scores across the four groups (p > 0.05). After the interventions, all three groups exposed to music therapy showed significant reductions in both anxiety and fatigue scores compared to the control group (p < 0.001). Conclusion: All three therapies were effective in managing anxiety and fatigue symptoms in hemodialysis patients. Among them, music-repeating robotic parrot therapy demonstrated the most superior and longest-lasting effects in reducing both anxiety and fatigue levels. Trial Registration: ClinicalTrials.gov identifier: NCT07238374.
- Kitap BölümüYalnız künye2026A Policy-Aligned Integrated Index Framework for Environmental Impact Assessment Monitoring and Reporting Using the Best Worst Method
Şimşek, Aybala; Şimşek, Ahmet Bahadır
Environmental Impact Assessment generates growing volumes of monitoring data, yet reporting still tends to treat indicators as separate signals rather than parts of a coherent evaluative structure. This chapter responds to that gap by developing a policy-aligned integrated index for monitoring and reporting in EIA. The proposed framework links environmental indicators to ESG themes, SDG targets, and European Green Deal priorities, then uses the Best Worst Method to derive transparent and defensible weights. Rather than presenting the index as a substitute for detailed evidence, the chapter treats it as a structured synthesis that can clarify how monitoring results relate to policy commitments and reporting needs. An illustrative application shows how the framework can organise indicators, support interpretation, and remain sensitive to alternative weighting choices. The chapter concludes by outlining the practical value and limits of using integrated indices in EIA contexts.
- MakaleAçık Erişim2026Scopus SJRQ1Place attachment of earthquake victims residing in Antakya (Hatay) after the Kahramanmaraş earthquakes on February 6, 2023
Fakıoğlu, Merve; Mızrak, Sefa
People affected economically, environmentally, physically, and psychologically by the earthquake may be reluctant to move to safer and more comfortable places for various reasons. Investigating the factors that influence people’s place attachment after devastating earthquakes will enable the creation of sustainable communities and cultures. This study examined the impact of earthquake experience, preparedness, place-protective behavior, social support, insecurity, price increase, the surrounding environment, self-efficacy, and risk perception on place attachment among earthquake victims in Antakya following the February 6, 2023, Kahramanmaraş earthquakes. Data were collected via surveys from 453 earthquake victims in the Antakya region of Hatay (Türkiye) province, one year after the earthquakes. Eleven ordered logistic regressions revealed the strength and direction of the factors affecting place attachment. Earthquake victims who were injured, lost relatives, were not evacuated, and were not disturbed by the rubble had higher place attachment. Earthquake preparedness, formal social support, post-earthquake insecurity, post-earthquake price increase, self-efficacy, and earthquake risk perception did not affect place attachment. Sustainability and place-protective behavior increased place attachment. Furthermore, place attachment was higher among men and those who lived longer in Antakya. This study is expected to guide managers, disaster experts, and non-governmental organizations who develop strategies to increase people's place attachment in disaster-affected regions.
- MakaleYalnız künye2026Scopus SJRQ1Effects of earthquake frequency content and isolation thickness on seismic behavior of a structure system resting on geotechnical seismic isolation layer
Ozturk, Kasif Furkan; Cakir, Tufan; Araz, Onur
Geotechnical seismic isolation (GSI) systems aim to partially dissipate the energy before it reaches the foundation of the structure system and are therefore regarded as an important alternative to structural seismic isolation systems. In addition, the use of petroleum-derived waste materials in the GSI systems fills a significant gap in the field of waste recovery. The present study investigates the changes in the dynamic responses of a 5-story building system with and without GSI, using a set of earthquakes classified according to their frequency content. For this purpose, parametric analyses were performed using analytical methods, considering three different earthquake frequency contents and six different GSI thicknesses. Furthermore, an approach for selecting the GSI thickness was suggested. The results generally show that, for structures founded on both natural soil (NS) and GSI systems, the earthquakes with low frequency content produce responses greater than the average responses calculated for all the investigated earthquakes. Although increasing the GSI thickness has a significant effect on attenuating structural responses, increasing this thickness beyond 3 m does not lead to a relatively significant reduction in the dynamic responses of the investigated structural system. Therefore, considering the structural system, NS, rubber-soil mixtures and earthquakes examined in this study, selecting a GSI thickness in the range of 2–3 m (inclusive) may be regarded as a practical approach for mitigating the dynamic responses of the structure since further increments in thickness beyond this range provide only progressively limited improvements in structural responses. Consequently, this research may provide meaningful data for the development of vibration control strategies to improve seismic resilience of structures, and the results are expected to be useful for better understanding of the GSI applications.
- MakaleYalnız künye2026Scopus SJRQ2Reflections of Employees' Digital Addiction Experiences on Workplace Distraction, Safety Perception, and Collective Responsibility: A Phenomenological Study
Doğan, Onur
This study aims to examine how digital addiction based experiences of employees influence attention processes, safety awareness, and collective responsibility in the workplace. It particularly seeks to identify challenges in digitally intensive environments regarding cognitive load, behavioral reflexes, and institutional risk communication. The research employed a phenomenological design with semi- structured interviews conducted with 19 employees from various sectors across Turkey. Criterion sampling was used, and interviews continued until data saturation was reached. All interviews were audio recorded, transcribed verbatim, and analyzed using Colaizzi's (1978) seven step method. Reporting followed the COREQ checklist to ensure rigor and transparency. Thematic analysis revealed three main themes: Cognitive Load and Deterioration in Safety Perception, Behavioral Disconnection and Erosion in Safety Attitudes, and Organizational Silence and Collective Collapse in Risk Awareness. These findings show that digital addiction negatively affects attention, reflexes, safety behaviors, and institutional reporting processes. Digitalization influences not only work efficiency but also employees' safety behaviors and organizational risk communication. Constant digital stimuli cause distraction, disrupt safety practices, and weaken collective responsibility. The study provides insights into how digital addiction transforms workplace safety culture and recommends comprehensive prevention strategies for employers, managers, and policymakers.
AtıfScopus2WoS1OpenAlex1İncele - MakaleAçık Erişim2026Scopus SJRQ1A comparative interventional study on the effectiveness of acceptance and commitment therapy, emotion-focused therapy, and attachment-based therapy in improving emotion regulation among adolescents with digital game addiction
Güngör, Sunay
Background: Digital game addiction is a rapidly developing social and mental health concern that is closely related to emotion regulation difficulties. The present study aimed to compare the effectiveness of acceptance and commitment therapy (ACT), emotion-focused therapy (EFT), and attachment-based therapy (ABT) in improving emotion regulation among adolescents with digital game addiction. Methods: The present study was an interventional study employing a pretest–posttest design and a control group. The sample included 100 adolescents aged 13–18 years who were diagnosed with gaming disorder according to the 11th Revision of the International Classification of Diseases (ICD-11) criteria. Participants were selected using purposive sampling and were assigned to four groups of 25 individuals each, including three experimental groups and one wait-list control group. The 7-item Digital Game Addiction Scale (DGAS-7) and the Regulation of Emotions Questionnaire among Adolescents (REQ-A) were used to gather data. ACT and EFT were administered in eight sessions, whereas ABT was delivered in 10 sessions. Data were analyzed using repeated measures ANOVA in SPSS. Results: It was found that the three therapeutic strategies produced a significant increase in functional emotion regulation scores (internal and external) and a significant decrease in dysfunctional emotion regulation scores compared to the control group (p < 0.001). However, the effect sizes for the ACT and EFT groups were very large compared to the ABT group. There was no significant difference between ACT and EFT; nevertheless, both interventions were significantly more effective compared to ABT at both the posttest and follow-up stages. Conclusion: ACT and EFT are more effective interventions for improving emotion regulation among adolescents with digital game addiction because of their emphasis on psychological flexibility and emotionally profound processing. Although ABT was found to be moderately effective, it can be used as an adjunctive therapy, particularly in cases involving relational problems.
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İncele - MakaleYalnız künye2026Scopus SJRQ2Germination as a Pre-isolation Modification Method for Common Buckwheat Protein Isolate
Gülbahar, Esma; Tunç, Merve Tuğçe; Akdoğan, Arda; Baltacı, Cemalettin; Sarıcaoğlu, Furkan Türker; Parlak, Mahmut Ekrem; Aydın, Engin; Odabaş, Halil İbrahim
This study investigated germination as a pre-isolation modification method to enhance the techno-functional and nutritional properties of common buckwheat (Fagopyrum esculentum Moench) protein. Germination was conducted at two different temperatures (20 and 30 °C) for 24, 48, and 72 h, and isolated proteins were analyzed for their chemical, structural, and functional properties. Results showed that the highest protein yield was achieved at 30 °C for 24 h, though durations exceeding 48 h reduced purity. SDS-PAGE and FTIR analyses confirmed that endogenous protease activity degraded high-molecular-weight proteins and increasing random coil proportions, indicating partial unfolding. SEM imaging revealed that germination transformed the dense protein surface into a porous morphology. Increasing germination time and temperature led to decreased lightness (L*) and hue angle, along with moderate increases in redness (a*), indicating notable changes in the visual appearance of the protein isolates. DSC results showed a decrease in thermal stability (Td) due to structural changes. In addition, germination significantly improved solubility, emulsifying activity, foaming capacity, and water/oil absorption, particularly at the 24 h of germination. Most notably, germination at 30 °C for 24 h increased in vitro protein digestibility from 75.67 to 82.19%. The results show that the germination is a promising approach to enhance the functionality and digestibility of buckwheat protein for potential application in food industry.
- MakaleYalnız künye2026Scopus SJRQ2Utilizing Pollutant Waste Cheese Whey into Low-cost Broth for Bacterial Growth and Protein Production
Alkowlani, Amir Towfiq Hasan; Beldüz, Ali Osman; Çanakçi, Sabriye; Bektaş, Kadriye İnan; Ay, Fulya; Özyurt, Taner; Yıldız, Oktay
Cheese whey (CW), an abundant and nutrient-rich byproduct of cheese production, accounts for approximately 85% of milk volume and is generated globally in quantities reaching 145–200 million tons annually. Despite its biochemical complexity and high organic load, CW remains underutilized in microbial biotechnology. Its pollutant potential is up to 100 times higher than domestic sewage due to extreme biological oxygen demand (BOD), chemical oxygen demand (COD), high nutrient content, and acidity. Untreated discharge causes severe oxygen depletion, damages aquatic ecosystems, degrades soil, and contributes to climate change. This study evaluates CW as a sustainable and cost-effective alternative to synthetic bacterial growth media. Ten bacterial strains were cultured for 17 h in different forms of CW fresh, aged (up to two years), and dried and compared with standard Luria Bertani (LB) medium. Bacterial growth was assessed using optical density at 600 nm (OD₆₀₀), and protein yields were measured in µg/µL. CW supported growth ranged from OD₆₀₀ 2.36–4.46, comparable to 2.53–4.16 in LB, with protein yields between 0.19 and 0.43 µg/µL versus 0.18–0.44 µg/µL in LB. These findings demonstrate that CW can effectively support bacterial proliferation and protein production, offering a novel valorization route for a major agro-industrial pollutant while reducing environmental harm and fermentation costs.
- MakaleAçık Erişim2026Preliminary Study on the Characterization of a Novel Polysaccharide from Enterococcus faecium SL60 Isolated from Siyez Sourdough; [Siyez Ekşi Mayasından İzole Edilen Enterococcus faecium SL60'tan Elde Edilen Yeni Bir Polisakkaritin Karakterizasyonu Üzerine Ön Çalışma]
Genç, Berna
This study reports the production, structural characterization, and preliminary cytotoxicity evaluation of an extracellular polysaccharide (EPS) synthesized by Enterococcus faecium SL60, a strain isolated from traditional Siyez (einkorn) sourdough. Analytical techniques including GC-MS, FTIR, XRD, zeta potential, and elemental analysis were applied to characterize the EPS. The purified EPS was found to be a water-soluble, negatively charged, amorphous heteropolysaccharide predominantly composed of mannose and glucose, with minor proportions of rhamnose, arabinose, galactose, and xylose. The total carbohydrate yield was 7.6 g/L. FTIR confirmed the presence of typical carbohydrate functional groups, while zeta potential analysis indicated a moderate surface charge (−9.71 mV), implying colloidal stability. Cytotoxicity evaluation using the CCD-1079Sk fibroblast cell line showed no significant toxicity at concentrations up to 500 µg/mL. These findings highlight the potential of SL60-derived EPS as a safe bioactive compound with possible applications in functional food development and health-related products.
- Editöre MektupAçık Erişim2026Scopus SJRQ4Reply to the Letter to the Editor: Assessing the Predictive Value of Kolmogorov–Arnold Networks for the No–Reflow Phenomenon in ST–Segment Elevation Myocardial Infarction: A Comparative Machine Learning Study; [Editöre Mektup Yanıtı: ST Segment Yükselmesi Miyokard Enfarktüsünde No–Reflow Fenomeni için Kolmogorov–Arnold Ağlarının Öngörü Değerinin Değerlendirilmesi: Karşılaştırmalı Makine Öğrenimi Çalışması]
Taşolar, Hakan; Bayramoğlu, Adil; Günen, Mehmet Akif; Levent, Sümeyye; Güral, Yunus; Halisdemir, Nurhan
- MakaleAçık Erişim2026Scopus SJRQ4Association Between Health Literacy and Mediterranean Diet Adherence Among Adult Women in Türkiye
Çam, Alper Veli; Şik, Elif
Objective: Health literacy is widely recognized as an important determinant of informed health-related decision-making. However, evidence regarding whether health literacy translates into healthy eating behaviors, particularly adherence to the Mediterranean diet, remains limited. This study aimed to examine the association between health literacy levels and adherence to the Mediterranean diet among adult women living in Türkiye. Methods: This cross-sectional study was conducted with 400 women aged 18 years and older residing in Türkiye. Data were collected using a sociodemographic information form, the Turkish Health Literacy Scale–Short Form, and the Mediterranean Diet Quality Index (KIDMED). Health literacy levels were categorized as inadequate, problematic–limited, adequate, and excellent, while Mediterranean diet adherence was classified as low, moderate, or optimal. Ordinal logistic regression analysis was performed to examine the association between health literacy and adherence to the Mediterranean diet, adjusting for sociodemographic variables (age, education, income, and occupation). Findings: Among the participants, 25.3% had inadequate health literacy, 31.8% had problematic–limited health literacy, 34.0% had adequate health literacy, and 9.0% had excellent health literacy. Mediterranean diet adherence was low in 34.5% of participants, moderate in 52.3%, and optimal in 13.3%. The ordinal logistic regression analysis revealed that, after adjusting for sociodemographic variables, one dimension of health literacy (Cognitive Health Literacy) was significantly associated with Mediterranean diet adherence, whereas no significant association was observed for the other dimension. Conclusion: The findings suggest that certain dimensions of health literacy may be associated with adherence to the Mediterranean diet when sociodemographic factors are taken into account. These results highlight the importance of considering both individual knowledge and contextual factors in understanding dietary behavior. Future research should further explore the role of nutrition-specific literacy and structural determinants in shaping healthy eating practices.
- MakaleAçık Erişim2026Scopus SJRQ1A leakage-free analytics framework for subject-wise electrocardiogram-based sleep apnea detection using machine learning
Melek, Negin
Sleep apnea is associated with impaired sleep quality and elevated cardiovascular risk, creating a need for reliable automated screening approaches. Although electrocardiogram (ECG)-based detection methods have shown promising results, reported performance values can be affected by evaluation strategies that allow information leakage between training and testing data. This study investigates ECG-based sleep apnea detection under strict subject-wise conditions using the PhysioNet Apnea-ECG database. Thirty-five annotated single-lead ECG recordings sampled at 100 Hz were divided into non-overlapping 60-s segments according to minute-wise apnea labels. Statistical ECG descriptors and time-domain heart rate variability features were extracted and evaluated using k-nearest neighbors (KNN), support vector machine (SVM), and Random Forest (RF) classifiers. In addition, a lightweight one-dimensional convolutional neural network (1D-CNN) was trained directly on filtered ECG segments. Repeated holdout validation with subject-level train-test separation was adopted, and normalization parameters were estimated exclusively from training data in each repetition to prevent information leakage. Model performance was assessed using accuracy, balanced accuracy, precision, recall, specificity, F1-score, ROC-AUC, Cohen's kappa, and Golden Distance (GD). In the representative subject-wise evaluation, Random Forest achieved the most balanced performance, yielding the highest balanced accuracy (0.70) together with the lowest GD (0.56). Across the repeated subject-wise holdout experiments, SVM achieved the strongest average overall performance, producing the highest mean accuracy (0.72), balanced accuracy (0.69), ROC-AUC (0.77), and Cohen's kappa (0.39), and the lowest mean GD value (0.58). The lightweight 1D-CNN converged stably during training, but its performance on unseen subjects remained lower than that of the handcrafted feature-based models.
