Sürdürülebilir Kalkınma Amaçları

Yazarlar

  • MakaleYalnız künye2026
    A 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.

    • SDG 2 · Açlığa Son
  • MakaleYalnız künye2026
    CropHealthNet: 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.

    • SDG 2 · Açlığa Son
  • MakaleAçık Erişim2026
    The 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.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
    • SDG 8 · İnsana Yakışır İş ve Ekonomik Büyüme
  • MakaleAçık Erişim2026
    Phenolic 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 künye2026
    Optimal 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 künye2026
    Children'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.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
    • SDG 10 · Eşitsizliklerin Azaltılması
    • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
    • SDG 16 · Barış, Adalet ve Güçlü Kurumlar
  • MakaleYayıncıda açık erişim2026
    The 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.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
  • MakaleAçık Erişim2026
    Place 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.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
    • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
  • MakaleYalnız künye2026
    Effects 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.

    • SDG 9 · Sanayi, Yenilikçilik ve Altyapı
    • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
  • MakaleYalnız künye2026
    Reflections 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.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
    • SDG 8 · İnsana Yakışır İş ve Ekonomik Büyüme
  • MakaleAçık Erişim2026
    A 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.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
  • MakaleYalnız künye2026
    Germination 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.

    • SDG 2 · Açlığa Son
  • MakaleYalnız künye2026
    Utilizing 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.

    • SDG 6 · Temiz Su ve Sanitasyon
    • SDG 12 · Sorumlu Üretim ve Tüketim
  • Editöre MektupAçık Erişim2026
    Reply 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

    • SDG 3 · Sağlık ve Kaliteli Yaşam
  • MakaleAçık Erişim2026
    The Effect of Fatigue During Search and Rescue Efforts in Debris on the Quality of Cardiopulmonary Resuscitation

    Çavuş, Kadir; Tiryaki, Oğuzhan; Tiryaki, Elif; Çelik, Suat; Saçar, Hüseyin Bora

    Objectives: Cardiopulmonary resuscitation (CPR), which is used in cases of life-threatening cardiopulmonary arrest, is a physically exhausting procedure. Adding to that, sometimes, even before performing CPR, interventions to rescue the injured person from a challenging environment have caused significant fatigue. In this study, taking a novel research approach, we generated a scenario of fatigue during a rescue from earthquake debris and aimed to measure the effect of that fatigue on the quality of CPR performed by paramedics. Methods: The research followed an experimental design with 2 groups (experimental/control) and 2 measurements (pretest/post-test). The study population was selected using power analysis. The sample, consisting of 84 paramedic students, was randomly divided into 42 control and 42 experimental participants. Current American Heart Association (AHA 2020) and European Resuscitation Council (ERC 2021) guidelines were strictly followed when performing CPR. In order to assess the accuracy of CPR, a General Doctor GD-CPR200S-A (2010 standard) simulator was utilized. The participants were fatigued by practicing the process of extracting and transporting earthquake victims from rubble. A personal information form with 20 questions and a CPR measurement form were used to obtain the data. Results: In the analysis performed to measure the differences between the CPR indicators for the control and experimental groups in the post-test and pretest, the difference in compression (control: 6.5 ± 50.1 and experimental: −10.3 ± 46.0) was not significant. Meanwhile, we found that the difference in ventilation (control: 0.3 ± 5.4 vs. experiment: 8.1 ± 4.6) and the difference in CPR completion times (control: 0.2 ± 1.2 vs. experiment: −0.7 ± 0.7) between the post-test and pretest were significant. Conclusions: There was no significant difference in correct compressions between the control and experimental groups, but there was a significant difference in ventilation and CPR completion times. For this reason, it is recommended to focus on the effect of fatigue on CPR quality, especially on the ventilation process. It is also recommended to include fatigue scenarios in CPR trainings.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
  • MakaleAçık Erişim2026
    Enhanced cationic dye adsorption using Stenotrophomonas indicatrix -modified MnFe2O4: performance evaluation and adsorption mechanism

    Ozdes, Duygu; Dede, Alper; Turfan, Fatma Asya; Seker, Serdal

    In this study, MnFe2O4 magnetic nanoparticles were modified with the Stenotrophomonas indicatrix bacteria for the first time in the literature to develop an effective and novel bio-adsorbent for the remediation of toxic cationic dyes, specifically Rhodamine 6G (R6G) and Methylene Blue (MB), from contaminated aqueous media. MnFe2O4 and bacteria-loaded MnFe2O4 were thoroughly characterized using FTIR, XRD, and SEM-EDX analyses. XRD results confirmed that the cubic spinel structure of MnFe2O4 was preserved after bacterial modification, while FTIR spectra evidenced the successful incorporation of biological functional groups, including –NH, –OH, amide, and phosphate moieties, onto the nanoparticle surface. Adsorption performance of the dyes was evaluated in terms of parameters including aqueous solution pH, equilibrium time, bacteria-loaded MnFe2O4 dosage, and initial R6G and MB concentration. After investigating the effect of salt on adsorption efficiency, the applicability of the proposed adsorbent was assessed using real water samples. According to the experimental results, the optimum pH and equilibrium period for the uptake of both dyes were determined to be 8.0 and 60 min, respectively. Kinetic analyses showed that the pseudo-second order kinetic model exhibited a superior fit in representing the adsorption rates of both dyes, while isotherm studies indicated that both Langmuir and Freundlich isotherm models fit the experimental data well. While the adsorption capacities of pure MnFe2O4 for MB and R6G were 19.5 mg g− 1 and 15.3 mg g− 1, respectively, these values reached 67.6 mg g− 1 and 59.5 mg g− 1 for the bacteria-loaded MnFe2O4. The obtained data revealed that bacterial modification significantly increased the adsorption capacity of MnFe2O4, suggesting that the developed bio-adsorbent stands out as an effective and promising candidate for the remediation of dye-contaminated effluents.

    • SDG 6 · Temiz Su ve Sanitasyon
  • MakaleYalnız künye2026
    Phytochemical profiling, biological activities, and molecular docking analysis of Dorycnium pentaphyllum subsp. haussknechtii

    Ayna, Adnan; Hakan, Oguzhan; Yapıcı, İsmail; İzol, Ebubekir; Yılmaz, Mustafa Abdullah; Necip, Adem; Yapar, Yakup

    BACKGROUND: In the current study, the biological activity fingerprint of Dorycnium pentaphyllum subsp. haussknechtii was investigated by an interdisciplinary approach through analysis of its phytochemical content, antioxidant capacity, enzyme inhibitory potential and molecular docking. RESULTS: The analysis of the phytochemical content by liquid chromatography–tandem mass spectrometry was characterized by the presence of flavan-3-ols, such as epicatechin, epigallocatechin, and catechin, as well as quercetin-derived flavonoids such as isoquercitrin. Analysis of the antioxidant capacity by 2,2-diphenyl-1-picrylhydrazyl, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), ferric reducing antioxidant power, Fe3+–Fe2+ reducing and cupric reducing antioxidant capacity methods indicated the strong antioxidant capacity of the plant extract. In addition, the plant extract was able to modulate biological enzyme activity effectively, with IC50 values of 111.78 μg mL−1 for acetylcholinesterase, 22.07 μg mL−1 for butyrylcholinesterase, 1.39 μg mL−1 for α-glucosidase, 7.34 μg mL−1 for carbonic anhydrase I, and 17.41 μg mL−1 for carbonic anhydrase II. To have a better understanding of the molecular mechanism for the plant extract's properties, the major phenolic compounds present in the plant extract were investigated for molecular docking with their respective enzymes. As such, the results revealed a strong binding affinity and conformational stability, with strong hydrogen bonding and π–π interactions. CONCLUSION: Generally, the properties revealed by the plant extract indicate that the phenolic content, strong antioxidant properties, and enzyme inhibition activity of D. pentaphyllum subsp. haussknechtii have shown great potential for being a useful natural source for therapeutic lead compounds.

  • MakaleYalnız künye2026
    Improving the hydrothermal reduced graphene oxide supercapacitor with heat-moisture-treated potato starch as binder

    Daulay, Amru; Yassaroh, Yassaroh; Samada, Lukmanul Hakim; Amrulloh, M. Hanif; Kumaş, Cavit; Nariswari, Mentari Kirana; Putri, Devi Mariska; Chambioso, Yugo

    Alternative binders that can be processed in water are still in the early stages of development for more efficient and sustainable supercapacitors. However, their electrochemical performance is still below average. This study uses heat-moisture-treated starch (starch HMT) as a binder for reduced graphene oxide (rGO) supercapacitors. Starch HMT has been fabricated at 120 °C. The XRD diffractogram exhibits peaks at 2θ angles of 15°, 17°, 22°, and 24°. The 2θ values indicate that potato starch is of type B. FTIR spectra show the formation of OH, C–O–C, C-O, C–O–C, and C-H bonds. SEM images show cracks in the morphology. Electrochemical testing shows a specific capacity of 230 F/g at a current density of 1 A/g. The charge–discharge stability of the electrodes at 5000 cycles is 90%. These results offer a framework for developing electrode materials and binders for supercapacitors.

    • SDG 7 · Erişilebilir ve Temiz Enerji
    • SDG 9 · Sanayi, Yenilikçilik ve Altyapı
    • SDG 12 · Sorumlu Üretim ve Tüketim
  • MakaleYalnız künye2026
    Multi-scale deep fusion architecture for brain tumor detection via local-contextual feature integration

    Reis, Hatice Catal; Turk, Veysel

    Early detection of brain tumors is crucial for enhancing treatment strategies and improving clinical prognosis. However, current conventional methods limit diagnostic accuracy and slow down diagnostic processes due to subjective interpretations and dependence on experts. Deep learning-based approaches have the potential to enhance diagnostic accuracy and facilitate early diagnosis by mitigating current limitations in automatic learning techniques for feature extraction and modeling processes. In this study, an advanced deep learning model, Multi-Scale Local-Context Fusion Network (MSLCFNet), is proposed for automatic diagnosis of brain tumors within the scope of oncological diseases. The proposed model evaluates local spatial features, global patterns, and long-range contextual relationships holistically through multi-layered representations, enabling effective identification of complex structures of tumor morphology. This architecture has the potential to increase diagnostic consistency and minimize the risk of misdiagnosis by reducing inter-observer variability, especially in cases where limited contrast and unclear boundaries lead to diagnostic uncertainty. The proposed model achieved accuracy rates of 96.51% and 98.17% on two different MRI brain tumor datasets, respectively. Additionally, a hybrid model based on MSLCFNet+ResNet50 was proposed in the study to obtain high-level feature representations for brain tumor diagnosis. The model offers a significant improvement in the diagnosis process by reducing misdiagnosis rates to 98.86% and 99.50% accuracy. The proposed methods make a significant contribution to enhancing diagnostic accuracy in clinical decision support systems, as they enable the efficient processing of complex morphological structures.

    • SDG 3 · Sağlık ve Kaliteli Yaşam
  • MakaleAçık Erişim2026
    Synthesis, Characterization, Biological Properties, and Sensor Applications of Novel Thiosemicarbazone Derivatives

    Gezegen, Hayreddin; Özbek, Oguz; Topal, Meryem; Şahin, Hatice; Koçyiğit, Ümit M.

    In this study, novel thiosemicarbazone derivative molecules (5a–j) were synthesized. The characterization of the synthesized molecules was carried out using 1H–, 13C–NMR, FT–IR, and Q–TOF spectroscopic techniques. Then, the inhibitory effect of these compounds was examined for human carbonic anhydrase I and II (hCA I, and II) and acetylcholinesterase (AChE). The hCA I II, and AChE were efficiently inhibited by synthesized thiosemicarbazone derivatives, with Ki values in the range of 0.293–1.666 µM for hCA I, 0.298–1.332 µM for hCA II, and 52.51–138.63 µM for AChE, respectively. Finally, the sensor properties of the synthesized thiosemicarbazone derivatives were investigated. The newly synthesized thiosemicarbazone derivative molecules exhibited high selectivity towards Pb2+ ions. The sensor prepared with 5a from these molecules had a Nernstian behavior of 28.8 ± 1.5 mV/decade and a low detection limit of 2.86 × 10−6 M in a wide concentration range of 1.0 × 10−1–1.0 × 10−5 M. The newly proposed sensor also had a wide pH working range (5.0–10.0), a very fast response time (5 s), and good reproducibility. The newly fabricated sensors were used as indicator electrodes for the potentiometric titration of Pb2+ ions with ethylenediaminetetraacetic acid (EDTA) and were successfully applied for the determination of Pb2+ ion content in different water samples.