Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Uzun, Sevda(67)
- Merdan, Mehmet(59)
- Duran, Celal(49)
- Ozdes, Duygu(46)
- Kaygusuz, Abdullah(45)
- Demir, Selim(37)
- Turan, Ibrahim(37)
- Karsli, Orhan(36)
- Öztürk, Serkan(35)
- Dokuz, Abdurrahman(34)
- Araz, Onur(32)
- Kandemir, Raif(31)
- Kulakaç, Nurşen(29)
- Sipahi, Ferkan(29)
- Arslan, Mehmet(27)
- Baltaci, Cemalettin(27)
- Baltacı, Cemalettin(27)
- Kurt, Kemal(27)
- Topal, Fevzi(27)
- Gücer, Mehmet Ali(25)
- Peker, Iskender(25)
- Aydin, Faruk(24)
- Bayrakdaroglu, Serdar(24)
- Maden, Nafiz(24)
- Ozturk, Samet(24)
- Vural, Alaaddin(24)
- Yolcu, Halil(24)
- Yücel, Cem(24)
- Aliyazicioglu, Yuksel(23)
- Kankal, Murat(23)
- Reis, Hatice Catal(23)
- Ürkek, Bayram(23)
- Günen, Mehmet Akif(22)
- Kurnaz, Muammer(22)
- Topal, Meryem(22)
- Karimullah, Suud Sarim(21)
- Uysal, Ibrahim(21)
- Ashyralyyev, Charyyar(20)
- Aydin, Aydanur(20)
- Bayraktar, Alemdar(20)
Yayınlar
- MakaleYalnız künye2026Scopus SJRQ1Determining 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.
AtıfScopus1WoS1OpenAlex3
İncele - MakaleYalnız künye2026Scopus SJRQ2Influence 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 künye2026Scopus SJRQ2Natural 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 künye2026Scopus SJRQ1Local 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 künye2026Scopus SJRQ3Investigation 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.
AtıfScopus2WoS1OpenAlex3İncele - MakaleAçık Erişim2026Scopus SJRQ1The effect of hawthorn vinegar, black mulberry syrup, and green tea on oral mucositis and oral health-related quality of life in individuals with diabetes: a single-blind, randomized controlled trial
Demiraǧ, Hatice; Akeren, Zahide
Objective – This study was designed as a single-blind randomized controlled trial to investigate the effects of hawthorn vinegar, black mulberry syrup, and green tea on oral mucositis and quality of life related to oral health in individuals with diabetes. Methods – Total of 120 participants were divided into four groups (hawthorn vinegar, black mulberry syrup, green tea, control; n = 30 each) and the study was completed. All participants completed the “Patient Information Form, ” “Oral Assessment Guide (OAG/ADR), ” and “Oral Health-Related Quality of Life Scale (OHQoL-UK)” before the study, on the 7th day, and after the study. In the experimental groups (hawthorn vinegar group, black mulberry syrup group, green tea group). In addition to routine oral mucositis treatment, patients with DM gargled for 1 min with diluted hawthorn vinegar [1 tablespoon (10 cc) mixed with 40 cc of water], pure black mulberry syrup, or green tea solution three times a day for 14 days, 15–20 min before meals. Results – Patients in the hawthorn vinegar group showed a decrease in oral mucositis and an increase in oral health-related quality of life at the interim measurement (day 7) and final test (day 14) measurements (p < 0.05). A negative correlation was found between the severity of oral mucositis and quality of life (p < 0.05). Conclusion – Although there was no difference between hawthorn vinegar and black mulberry syrup, they were found to be more effective than green tea in reducing oral mucositis and improving oral health-related quality of life, and all three complementary treatments were found to be effective. Clinical Trial Registration – identifier [NCT06481254]. https://register.clinicaltrials.gov/prs/beta/studies/S000E5O000000043/recordSummary.
- MakaleYalnız künye2026Scopus SJRQ2Synthesis, 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).
- MakaleAçık Erişim2026Scopus SJRQ2Climate Change Impacts on Worldwide Cotton Productivity and Agricultural Income: Physiological, Econometric, and Precision Agriculture Perspectives
Zuhal, Mustafa; Erkencioglu, Bedriye Nazli; Tokel, Dilek; Senol, Celal; Demir, Hacer Handan; Ozyigit, Ibrahim Ilker
Climate change is expected to affect all sectors of the global economy, with agriculture being particularly vulnerable due to its dependence on temperature and precipitation. Cotton is especially sensitive to these changes as its productivity relies on suitable thermal conditions, water availability, and stable reproductive development. This study investigates the effects of climate change on cotton productivity and agricultural income in seven major cotton-producing countries, including Australia, Brazil, China, India, Pakistan, Türkiye, and the United States, over the period 1971-2023. Long-run relationships were examined using the Westerlund cointegration test, country-specific effects were estimated with the Augmented Mean Group (AMG) estimator and verified using Common Correlated Effects (CCE) approach, while short-run dynamics were assessed through the Dumitrescu-Hurlin panel causality test. Results reveal significant long-run relationships between climate variables, cotton productivity, and agricultural income, although the magnitude and direction of these effects vary across countries. In contrast, short-run effects appear limited and heterogeneous. To strengthen the interpretation of the econometric findings, the results are compared with experimental evidence on cotton heat stress and physiological responses. Together, the evidence indicates that climate change influences cotton productivity mainly through temperature-sensitive processes such as photosynthesis, reproductive development, and fiber formation, underscoring the need for country-specific adaptation strategies and climate-resilient agricultural policies.
- MakaleYalnız künye2026Scopus SJRQ3Nurses’ 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.
AtıfScopus1WoS1OpenAlex1
İncele - MakaleYalnız künye2026Scopus SJRQ4TREE 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.
- MakaleAçık Erişim2026Scopus SJRQ1Enhanced Sensorless Current Control in Boost Converters for EV Fast Charging: Equilibrium Optimization-Tuned Cascaded ANN-Fuzzy Logic Control
Altan, Aytac; Yanarates, Cagfer; Alzaidi, Mohammed S.
Efficient current control in boost converters is critical for electric vehicle (EV) battery charging applications, where dynamic operating conditions challenge conventional control strategies. This paper presents a novel cascaded artificial neural network (ANN) and fuzzy logic (ANFIS) controller designed to enhance current regulation in boost converters. The performance of the proposed approach is validated through comparison with single PI, cascaded PI, and single ANFIS control schemes. To improve system performance, a sensorless current estimation technique is implemented, reducing hardware dependency and enhancing robustness, while lowering system cost. Experimental evaluations demonstrate that the proposed cascaded ANFIS controller maintains consistent current levels under rapid load changes, providing improved transient response and steady-state accuracy. Specifically, the proposed method achieves a settling time of 23 ms, compared to 185 ms for single PI and 66 ms for single ANFIS control, corresponding to an 87.6% improvement over PI. In addition, overshoot is reduced from 37.25% (PI) and approximately 20% (ANFIS) to negligible levels, while a fast rise time of 3.62 ms is obtained. These improvements reduce current deviation and transient stress, contributing to more stable and reliable charging operation. Although charging time, efficiency, and battery lifetime are not directly measured, the results indicate strong potential for improved practical charging performance. The proposed approach provides valuable insights into the integration of intelligent control methods in power electronics and supports the development of high-performance EV charging systems.
AtıfScopus16WoS15OpenAlex11İncele - MakaleAçık Erişim2026Scopus SJRQ1Whole-genome characterization of clinical Enterococcus faecalis and Staphylococcus epidermidis Isolates reveals mecA-positive E. faecalis and a shared lnu(A)–rep7a resistance plasmid in Türkiye
Ejder, Nebahat; Özad Düzgün, Azer
Background: This study aimed to genomically characterize clinical Enterococcus faecalis and Staphylococcus epidermidis isolates obtained from aspirate and sputum samples at Bayburt State Hospital, focusing on antimicrobial resistance genes, virulence factors, and mobile genetic elements. Methods: Whole-genome sequencing (WGS) was performed on the isolates, and antimicrobial resistance genes, virulence determinants, multilocus sequence types (MLST), plasmid replicons, and mobile genetic elements were identified using bioinformatics tools. Results: The E. faecalis E5 (ST64) isolate, recovered from an aspirate sample, carried multiple antimicrobial resistance genes, including mecA, vanT, erm(B), tet(M), and qacA, along with a diverse virulence gene repertoire (cyl, ebp, ace, and agg), mobile genetic elements (Tn6009, ISL1a3), and four plasmid replicons (rep19C, rep9C, repUS43, and rep7a). The E. faecalis E184 and E187 isolates (ST124), obtained from sputum samples, harbored fewer acquired resistance genes but shared gyrA (T672A) and parC (V307I) mutations associated with fluoroquinolone resistance. The S. epidermidis ST59 isolate carried resistance genes lnu(A), fosB, and qacD, together with the plasmid replicon rep7a and insertion sequence ISSau4. The co-occurrence of lnu(A) and the rep7a plasmid in both species suggests a potential pathway for interspecies transmission of resistance determinants. Conclusions: This study reports the genomic detection of mecA in an E. faecalis isolate from Türkiye based on WGS analysis. However, this finding is based solely on genomic data and lacks phenotypic or experimental validation. The detection of a shared plasmid-associated resistance element (lnu(A)–rep7a) in both E. faecalis and S. epidermidis highlights the potential for interspecies resistance gene flow within the hospital environment.
- MakaleAçık Erişim2026Scopus SJRQ2Aspect-Based Sentiment Analysis on Social Media Comments (Twitter) : The Attributes of Service Robots in the Hotel and Restaurant Industry
Acar, Ayşegül; Türten, Burak; Diker, Ersin
Service robots are becoming more prevalent in the service industry, yet the impact they have on customer experiences is not well-documented. This study identified consumer emotions toward service robots in hotels and restaurants, focusing on how specific attributes of these robots affect consumer emotions. Furthermore, it explored which countries generate the most comments on these service robot attributes and the nature of consumer emotions within these regions. Utilizing sentiment analysis, the study examined 52,513 English-language tweets about hotel and restaurant service robots. Additionally, logistic regression analysis helped quantify the impact of robot attributes–categorized as physical, functional, and relational–on different classes of emotions. The findings reveal that customers of restaurants and hotels were most influenced by the physical and relational attributes of service robots, respectively, with functional attributes having the least impact. The logistic regression analysis offered significant insights into how service robot attributes influence consumer experiences in hotels and restaurants.
AtıfScopus5WoS4OpenAlex5İncele - MakaleYalnız künye2026Scopus SJRQ1A 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.
AtıfScopus1WoS1İncele - 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.
AtıfScopus3WoS2OpenAlex3İncele - 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