Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Kaygusuz, Abdullah(35)
- Sipahi, Ferkan(35)
- Karsli, Orhan(34)
- Dokuz, Abdurrahman(30)
- Duran, Celal(30)
- Kandemir, Raif(29)
- Ozdes, Duygu(28)
- Maden, Nafiz(27)
- Uzun, Sevda(27)
- Merdan, Mehmet(26)
- Vural, Alaaddin(26)
- Öztürk, Serkan(25)
- Araz, Onur(24)
- Kulakaç, Nurşen(24)
- Ashyralyyev, Charyyar(23)
- Yildiz, Salih(23)
- Yilmaz, Ozgur(23)
- Doğan, Kadir Caner(21)
- Arslan, Mehmet(20)
- Aydin, Faruk(20)
- Doğru, Bülent(20)
- Bayraktar, Alemdar(19)
- Kankal, Murat(19)
- Ayaydin, Hasan(18)
- Baltaci, Cemalettin(18)
- Yolcu, Halil(18)
- Cakir, Tufan(17)
- Cengiz, Ekrem(17)
- Demir, Selim(17)
- Gücer, Mehmet Ali(17)
- Akaryali, Enver(16)
- Artan, Seyfettin(16)
- Hayaloğlu, Pınar(16)
- Kaya, Afşin Ahmet(16)
- Tosunoğlu, Büşra(16)
- Uysal, Ibrahim(16)
- Kurt, Kemal(15)
- Ozturk, Samet(15)
- Reis, Hatice Catal(15)
- Aksakal, Vecihi(14)
Yayınlar
- MakaleYalnız künye2026Determining the effect of blockchain technology on the medical waste management process in the circular economy framework using integrated FUCOM-ARAS methods
Batar, Bilge; Peker, İskender
Background: The circular economy concept aims to reduce environmental impact by promoting resource reuse, minimizing waste through input reduction, and lowering costs. Rising costs are leading healthcare facilities and other organizations to prioritize medical waste management. Blockchain technology, introduced in 2008, functions as a database of auditable and traceable transactions built on a network of trust-based blocks. Key features such as transparency, reliability, accessibility, flexibility, and automation can significantly enhance the efficiency of medical waste management processes, thereby contributing to the circular economy. Objective: This study aims to evaluate the effectiveness of medical waste management—critical for healthcare institutions and sustainable development—within the framework of the circular economy. Multi-criteria decision-making (MCDM) techniques are used to assess the contributions of blockchain technology to this process. Methods: A literature review was conducted to identify relevant criteria and alternatives. The Full Consistency Method (FUCOM), an MCDM technique, was used to calculate the weight of each criterion. The Additive Ratio Assessment (ARAS) method was applied to rank the alternatives. Conclusion: According to the analysis's findings, transparency, traceability, and dependability are the three most important criteria, respectively. The stages of medical waste storage, disposal, and transportation have the highest priority ratings among the available options. According to these results, incorporating blockchain technology into medical waste management can significantly improve system traceability and reliability, enhancing its role in the circular economy. Notably, the storage phase is the most appropriate for implementing blockchain. However, the other phases’ comparatively high appropriateness scores attest to the technology's capacity to be used efficiently across the waste management cycle. This integration promotes traceable and transparent procedures, guaranteeing dependable waste management procedures in healthcare facilities and supporting the objectives of the circular economy and sustainability. Additionally, the sensitivity analysis shows that when the weighting of criterion is altered, the ranking of alternatives changes as well. This dynamic interaction emphasizes how blockchain technology may be successfully integrated into all phases rather than being restricted to just one because waste management is cyclical and holistic.
- MakaleYalnız künye2026Influence of holmium substitution on structural characteristics and radiation shielding parameters of YBCO (358) superconducting ceramics
Düzgün, İbrahim; Kaya, Selim; Gül, Osman
This study reports on the structural characterization, radiation shielding assessment, and magnetic-field response of holmium-substituted Y3-xHoxBa5Cu8O18+δ superconducting ceramics synthesized by the conventional solid-state reaction route. X-ray diffraction measurements on five compositions (x = 0, 0.75, 1.5, 2.25, 3) supported the formation of a dominant orthorhombic Y358-type matrix across the substitution range. Scanning electron microscopy (SEM) combined with energy-dispersive X-ray spectroscopy (EDS) revealed a progressive microstructural evolution with increasing Ho content, including SEM–BEC/EDS-detectable Ho-rich inclusions consistent with Ho2BaCuO5-type secondary particles at higher substitution levels. XCOM-based mass attenuation coefficients, half-value layer, mean free path, effective atomic number, radiation protection efficiency, gamma-ray kerma coefficients, and fast-neutron removal cross-sections were calculated for all five compositions over 50–2000 keV. EGS4 Monte Carlo simulations independently verified the XCOM results for three representative compositions (x = 0, 1.5, and 3). Ho-containing specimens exhibited a significant enhancement in photon absorption near 60 keV, associated with the increased photoelectric contribution of holmium in the vicinity of its K-absorption edge. Among the full five-composition series, the x = 2.25 specimen (ρ = 5.531 g cm−3) exhibited the best calculated shielding performance across the full energy range, owing to its highest bulk density combined with substantial Ho incorporation. The x = 1.5 specimen provided the most balanced calculated radiation-attenuation and hysteretic magnetic response among the three representative compositions examined by EGS4 and M–H measurements at 20 K, retaining approximately 93% of the reference M–H hysteresis area while full substitution reduces it by roughly 67%. These findings establish a multi-parametric reference dataset for Ho-substituted Y358 ceramics and demonstrate the promise of rare-earth-engineered superconducting ceramics as multifunctional materials in radiation-intensive environments.
- MakaleYalnız künye2026Natural Radioactivity and Radiological Risk Assessment of Rocks Around the Mines: A Case Study From the Mastra and Hazine Mağara Mining Areas, Northeastern Türkiye
Sipahi, Ferkan; Çelik, Necati; Gücer, Mehmet Ali; Dizman, Serdar
This study presents a comprehensive assessment of natural radioactivity levels and associated radiological hazards in rock samples collected from Mastra and Hazine Mağara mining sites in the Gümüşhane province, Türkiye. The concentrations of primordial radionuclides (226Ra, 232Th, and 40K) were measured in samples of andesite, granite, and limestone using a High Purity Germanium (HPGe) detector. Complementary whole-rock geochemical analysis (XRF and ICP-MS) was conducted to understand the geochemical controls on radioactivity concentrations. The results reveal significant heterogeneity in activity concentrations both within and between the two sites. For 226Ra, the Hazine Mağara site exhibited a wider range (2.44–22.57 Bq kg−1) with a higher maximum value compared to Mastra (2.65–13.96 Bq kg−1). Similarly, 232Th and 40K activity concentrations showed considerable variability, often linked to the presence of specific accessory minerals like zircon, monazite, and K-feldspar. Geochemical data indicated that element concentrations (K, U, Th) were generally lowest in limestone and highest in granite, showing a strong correlation with the measured activity concentration values. Radiological risk indices, including radium equivalent activity, absorbed dose rate, annual effective dose equivalent, and excess lifetime cancer risk, were calculated. While values remain below international public health safety limits, localized anomalies were identified. Multivariate statistical methods were used to determine the relationship between the 226Ra, 232Th, 40K, Raeq (Bq/kg), Ig, Hex, D (nGy/h), AEDE (μSv/y), AGDE (μSv/y), and ELCR (×10−5). The study concludes that despite these localized anomalies, both mining areas pose an overall minimum environmental radiation risk, underscoring the necessity for site-specific assessments to ensure safe resource utilization and radiation protection.
- MakaleYalnız künye2026Local differentially private multi-criteria recommender system
Demir Gül, Nurgül Nisa; Batmaz, Zeynep; Yargıç, Alper
While multi-criteria collaborative filtering (MCCF) enhances recommender systems with more accurate and personalized content, it also introduces significant privacy concerns due to the use of fine-grained personal data. Differential privacy (DP), particularly local DP (LDP), is widely used in single-criterion systems to protect privacy. However, LDP-based mechanisms remain unexplored in MCCF systems.This study introduces the first LDP-enabled MCCF framework that applies a criterion-wise perturbation procedure to preserve the structure of multi-dimensional ratings while providing formal privacy guarantees. Three Laplace-based mechanisms as Standard (SLM), Bounded (BLM), and Truncated (TLM) are integrated and evaluated on two Yahoo!Movies subsets under privacy budgets ε ∈ [0.1, 10]. The results show that BLM and TLM consistently outperform SLM, particularly under stricter privacy conditions. On YM20, the root mean squared error (RMSE) loss compared to the unmasked variant ranges from 3.92–140.62% with SLM, 3.92-69.58% with BLM, and 3.68–88.47% with TLM. For YM10, RMSE loss ranges from 1.72–130.12% with SLM, 2.09–63.25% with BLM, and 1.55–75.64% with TLM. Moreover, minimizing noise via min-max normalization generally enhances accuracy, while rating distributions and sparsity of the datasets, clipping strategies and privacy levels further affect outcomes. Overall, the proposed LDP-based MCCF framework achieves competitive prediction quality while ensuring strong privacy guarantees, advancing privacy-preserving approaches in multi-criteria recommendation.
- MakaleYalnız künye2026Investigation of the adhesion properties of duplex coating on AZ91 alloy surface by MAO/HiPIMS-PVD methods
Kaplan, Emine Boynueğri; Şüküroğlu, Süleyman; Şüküroğlu, Ebru Emine
This study focuses on enhancing the surface properties and minimizing the mechanical incompatibility between the AZ91 magnesium alloy and the coating by applying CrAlYN/CrYN gradient coatings through the HiPIMS-PVD method, combined with the enlargement of a MgO intermediate layer via the Micro Arc Oxidation (MAO) method. The duplex coating approach was designed to strengthen adhesion and structural integrity between the substrate and the coating. Coating parameters for both MAO and HiPIMS-PVD processes were optimized using a Taguchi L4 orthogonal array, and the coatings were analyzed using SEM, EDS, XRD and scratch testing. MAO coatings exhibited porous and rough surfaces with volcanic morphologies. The best adhesion performance under MAO conditions was achieved with 650 V, 700 Hz, and a Type B solution, resulting in a critical load value of Lc₂ = 24 N. CrAlYN/CrYN gradient coatings alone showed coating thicknesses from 0.83 μm to 1.66 μm with compact and homogeneous microstructures. Adhesive strength was relatively low (Lc₂ = 5–10 N). In the duplex coating configuration, CrAlYN/CrYN coatings were deposited on the MAO-formed MgO layer, significantly increasing adhesion. Critical load values (Lc₂) ranged from 90 to 110 N, with the highest adhesion achieved under low CrY target voltage and current conditions. The findings demonstrate that the MAO/HiPIMS-PVD duplex coating method substantially improves adhesion and surface characteristics of AZ91 alloy, offering a promising solution for advanced surface engineering applications.
- MakaleYalnız künye2026Synthesis, characterization, and thermal-magnetic evaluation of novel triazine-derived polyamides and their metal complexes
Çanakçı, Dilek; Sarıbıyık, Oğuz Yunus
In this work, novel triazine-containing polyamide derivatives possessing thermal stability and magnetic properties were synthesized. The synthesis process involves two steps: first, the chlorination of adipic acid and succinic acid using thionyl chloride; and second, the amidation of triazine. As a result of these procedures, two different triazine-containing polyamides were synthesized. The synthesized polyamides formed complexes with Ag, Cu, and Zn ions to enhance their thermal stability and magnetic properties.The structures of the synthesized polyamides were elucidated primarily by FTIR analysis, focusing on distinctive bands corresponding to the carbonyl group. The molecular structures of the polyamides were confirmed using 1H NMR and 13C NMR spectroscopy. Scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDX) was employed to obtain information on the morphology and elemental composition of the samples. In addition, X-ray diffraction (XRD) analysis was performed to characterize the crystal structures, unit cell parameters, and orientations of the solid-state metal complexes. The thermal stability of both the polyamides and their metal complexes was investigated using thermogravimetric analysis (TGA). The magnetization of the synthesized compounds was measured as a function of temperature under zero-field-cooled (ZFC) and field-cooled (FC) conditions using a physical property measurement system (PPMS).
- MakaleYalnız künye2026Nurses’ Experiences in Preventing or Reducing Sensory Deprivation and Sensory Overload in Intensive Care Patients: A Phenomenological Study
Uzun, Sevda; Aslan, Çimen
This study aimed to assess nurses’ experiences in preventing or reducing sensory deprivation and sensory overload in intensive care unit (ICU) patients, utilizing a phenomenological approach. The qualitative research involved face-to-face, semi-structured, in-depth interviews with 15 nurses working in a general ICU in the southern region of our country. Data collection continued until data saturation was achieved, and all interviews were audio recorded and transcribed. Colaizzi’s phenomenological analysis method was employed for data analysis, and adherence to the COREQ checklist was ensured throughout the study. The data analysis revealed 2 main categories (reflection on situations that may cause sensory deprivation and sensory overload in intensive care units and practices and coping experiences of nurses to avoid sensory deprivation and overload) and 6 themes (environment, disease, and its effects, being separated from the family environment and loved ones, challenges encountered, coping, and psychosocial applications). The results indicated that patients undergo sensory deprivation or sensory overload in the intensive care environment, with nurses playing a pivotal role in addressing these situations. It was observed that nurses encountered challenges in coping with sensory deprivation or sensory overload issues in patients. Nurses are advised to regularly assess training programs to ensure the ongoing promotion of safe nursing practices aimed at minimizing sensory deprivation or sensory overload in patients.
- MakaleYalnız künye2026TREE TOPOLOGY-BASED RESOURCE ALLOCATION AND DISCOVERY ALGORITHM FOR ONE HOP
Genemo, Musa Dima; Saroja, Yalamanchili; Gopi, Kistam; Mutyam, Veeramani; Reddy, Bhargavi Peddi; Navatejareddy, Ramireddy; Madala, Srinivasa Rao; Sai, Nimmagadda Yaswanth; Koteswararao, K.
The components of a distributed system include multiple computing nodes which may use different types of hardware and connect to each other through a communication network that operates without shared memory or clock systems. The primary advantage of distributed systems enables organizations to share resources which results in faster computing times together with increased data availability and system reliability. The process of resource sharing requires organizations to first identify their resources and then assign those resources before anyone can access them. Computer systems implement caching to store frequently used data and program segments. The new caching technique called virtual caching enables a host node to delegate its cache authority for specific pages to nearby nodes who can use its partial cache space. The virtual caching protocol specifies neither the client node's process for accessing virtual cache nor its method for retrieving virtual cache from distant servers. The resource discovery and allocation problem needs us to develop a solution for this particular issue. The resource donation process requires us to find donor nodes who have extra resources while we need to assess which resources will be given to deficient nodes at each connected network point. Our goal is to achieve complete fulfillment of requests which deficient nodes make for resources. The importance of virtual caching lies in the fact that it doesn't require physical movements of cache. The requirements of the system determine when virtual cache allocation can be modified. The proposed heuristics provide efficient performance because they require minimal time and perform limited communication operations. We assess distribution quality through a comparison between heuristic distribution results and the distribution outcomes from the ILP problem solution. We present and assess several heuristics which aim to reduce unfulfilled resource requests that arise from resource-deficient nodes during their resource search process which has a maximum distance of two hops. The paper restricts its analysis to single hop operations only. The paper demonstrates through its research that this algorithm reaches optimal solution status based on our established benchmark criteria. The resource distribution for bounded hops restricts its operations to one-hop resource distribution. Every resource-surplus node transfers additional nodes to other nodes while maintaining its own resource balance without reaching resource-deficient status. Load distribution cannot be divided into infinite parts. Our research focuses on measuring the fulfillment level for each resource-deficient node request.
- MakaleYalnız künye2026A dynamic predictive model for Bacillus cereus growth from spores under temperature abuse conditions
Juneja, Vijay K.; Osoria, Marangeli; Gao, Juan; Kapoor, Harsimran Kaur; Ozturk, Samet; Purohit, Anuj; Mishra, Abhinav
Bacillus cereus, a common foodborne pathogen, can cause emetic and diarrheal food poisoning. The associated outbreaks are commonly caused by temperature abuse during food cooling, storage, and transportation. This study developed a model to predict B. cereus growth from spores based on isothermal growth data collected at 10–54.4 °C in tryptic soy broth. A four-strain spore cocktail was heated at 80 °C for 10 min and inoculated at an initial level of ∼2 log CFU/mL. Growth curves at temperatures showing growth (15–50 °C) were fitted using the Baranyi model. The average h0 value was 3.04. The temperature dependence of the maximum specific growth rate was characterized using the modified Ratkowsky model. The estimated theoretical minimum and maximum growth temperatures were 8.94 °C and 54.11 °C, respectively. The lag phase duration was related to temperature using a hyperbolic function. All models showed good agreement with the observed data, with satisfactory fit statistics (R2 = 0.953–0.998 and RMSE = 0.073–0.904). The Baranyi differential equations were solved numerically using a fourth-order Runge–Kutta method to build the dynamic model. Model validation was conducted under two sinusoidal non-isothermal temperature profiles (10–30 °C for 30 h and 25–45 °C for 23 h). The accuracy factor (Af) and bias factor (Bf) values were 1.2117 and 1.2117 for the 10–30 °C profile, and 1.1359 and 1.1288 for the 25–45 °C profile, respectively. These results demonstrated that the dynamic model could precisely predict B. cereus growth and be used as a baseline reference for food system research and risk assessment.
- MakaleYalnız künye2026CropHealthNet: 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.
- MakaleYalnız künye2026Optimal 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.
- MakaleYalnız künye2026Emergency 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 künye2026Children'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.
- MakaleYalnız künye2026Integrating 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 erişim2026The 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.
- MakaleYalnız künye2026Effects 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 künye2026Reflections 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.
- MakaleYalnız künye2026Germination 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.