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  • Öğe
    Molecular Mechanism of the Protective Effect of Tianeptine Against Ketamine-Induced Cardiac Injury in Rats
    (2021-10-26) Yıldız, Sevler; Uğur, Kerim; Taş, Hakan; Özçiçek, Fatih; Kuyrukluyıldız, Ufuk; Mendil, Ali; Çankaya, Murat; Mamedov, Renad; Süleyman, Halis
    Ketamine is a short-acting anesthetic drug that is derived from phencyclidine. Ketamine is used to treat depression and chronic pain disorders, as well as for anesthesia, analgesia, and sedation. Ketamine’s sympathomimetic characteristic causes cardiotoxicity. The pathophysiology of ketamine’s harmful impact has been linked to reactive oxygen species (ROS) and proinflammatory cytokines such as interleukin 1 beta (IL-1), interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-?). Tianeptine is an antidepressant that works similarly to tricyclic antidepressants. According to studies, tianeptine reduces the production of proinflammatory cytokines such as ROS, IL-1, IL-6, and TNF-?. Tianeptine has a sympatholytic action as well. All of this evidence suggests that tianeptine might help to reduce ketamine cardiotoxicity. The goal of our research is to use biochemical and histological techniques to see how tianeptine affects ketamine-induced cardiotoxicity in rats.
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    Recommendations for Hepatitis B Immunoglobulin and Antiviral Prophylaxis Against Hepatitis B Recurrence After Liver Transplantation
    (Murat Aladag, 2021) Mesut Akarsu; Soner Onem; Ilker Turan; Gupse Adali; Meral Akdogan; Murat Akyildiz; Murat Aladag; Yasemin Balaban; Nilay Danis; Murat Dayangac; Genco Gencdal; Hale Gokcan; Elif Sertesen; Merve Gurakar; Murat Harputluoglu; Gokhan Kabacam; Sedat Karademir; Murat Kiyici; Ramazan Idilman; Zeki Karasu
    The combination of hepatitis B immunoglobulin and potent nucleos(t)ide analogs after liver transplantation is considered as the standard of care for prophylaxis against hepatitis B virus recurrence. However, the recommended doses, route of administration, and duration of HBIG administration remain unclear. Moreover, hepatitis B immunoglobulin-free prophylaxis with potent nucleos(t)ide analogs has shown promising disease outcomes in preventing hepatitis B virus recurrence. The current recommendations, produced by the Turkish Association for the Study of the Liver, Acute Liver Failure and Liver Transplantation Special Interest Group, suggest a reduced need for hepatitis B immunoglobulin administration with effective long-term suppression of hepatitis B virus replication using potent nucleos(t) ide analogs after liver transplantation.
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    COVID-CCD-Net: COVID-19 and colon cancer diagnosis system with optimized CNN hyperparameters using gradient-based optimizer
    (Malatya Turgut Özal Üniversitesi, 2022) Sert,Eser; Kızıloluk,Soner
    Coronavirus disease-2019 (COVID-19) is a new types of coronavirus which have turned into a pandemic within a short time. Reverse transcription-polymerase chain reaction (RT-PCR) test is used for the diagnosis of COVID-19 in national healthcare centers. Because the number of PCR test kits is often limited, it is sometimes difficult to diagnose the disease at an early stage. However, X-ray technology is accessible nearly all over the world, and it succeeds in detecting symptoms of COVID-19 more successfully. Another disease which affects people's lives to a great extent is colorectal cancer. Tissue microarray (TMA) is a technological method which is widely used for its high performance in the analysis of colorectal cancer. Computer-assisted approaches which can classify colorectal cancer in TMA images are also needed. In this respect, the present study proposes a convolutional neural network (CNN) classification approach with optimized parameters using gradient-based optimizer (GBO) algorithm. Thanks to the proposed approach, COVID-19, normal, and viral pneumonia in various chest X-ray images can be classified accurately. Additionally, other types such as epithelial and stromal regions in epidermal growth factor receptor (EFGR) colon in TMAs can also be classified. The proposed approach was called COVID-CCD-Net. AlexNet, DarkNet-19, Inception-v3, MobileNet, ResNet-18, and ShuffleNet architectures were used in COVID-CCD-Net, and the hyperparameters of this architecture was optimized for the proposed approach. Two different medical image classification datasets, namely, COVID-19 and Epistroma, were used in the present study. The experimental findings demonstrated that proposed approach increased the classification performance of the non-optimized CNN architectures significantly and displayed a very high classification performance even in very low value of epoch.
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    Stability regions in time delayed two-area LFC system enhanced by EVs
    (TÜBİTAK / Türkiye Bilimsel ve Teknik Araştırma Kurumu / Scientific and Technical research Council of Turkey, 2022) Naveed, Ausnain; Sönmez, Şahin; Ayasun, Saffet
    With the extensive usage of open communication networks, time delays have become a great concern in load frequency control (LFC) systems since such inevitable large delays weaken the controller performance and even may lead to instabilities. Electric vehicles (EVs) have a potential tool in the frequency regulation. The integration of a large number of EVs via an aggregator amplifies the adverse effects of time delays on the stability and controller design of LFC systems. This paper investigates the impacts of the EVs aggregator with communication time delay on the stability. Primarily, a graphical method characterizing stability boundary locus is implemented. The approach is based on the stability boundary locus that can be easily determined by equating the real and the imaginary parts of the characteristic equation to zero. For a given time delay, the method computes all the stabilizing proportional-integral (PI) controller gains, which constitutes a stability region in the parameter space of PI controller.The effects of communication delay and participation factor of EVs aggregator on the obtained stability regions is thoroughly examined. Results clearly illustrate that stability regions become smaller as the time delay and participation factor of EVs increase. Finally, the accuracy of region boundaries known as real root boundary and complex root boundary is confirmed by time-domain simulations along with an independent algorithm, quasipolynomial mapping-based root finder (QPmR) algorithm.
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    Sinovac vaccination and the course of COVID-19 disease in hospitalized patients in Turkey
    (King Faisal Specialist Hospital and Research Centre, 2022) Acun Delen, Leman; Öterkuş, Mesut
    BACKGROUND: The Alpha variant of SARS-CoV-2 has a higher transmission rate than the first variant identified. The efficacy of vaccines is affected by the characteristics of SARS-CoV-2 variants. OBJECTIVE: Investigate the relationship of vaccination and virus variant on the course of the disease in patients who were hospitalized with a diagnosis of COVID-19. DESIGN: Retrospective, cohort study SETTING: Tertiary health institution PATIENTS AND METHODS: The study included patients older than the age of 18 years who were hospitalized in a COVID-19 service or the intensive care unit with a diagnosis of COVID-19 between 1 January 2021 and 30 April 2021. Demographic characteristics, vaccination and the Alpha virus variant status, comorbidities, and information about hospitalization were obtained from the hospital automation system and patient files. MAIN OUTCOME MEASURES: Vaccination rate and relationship with course of disease. SAMPLE SIZE: 608 RESULTS: Most of the patients (n=482, 79.3%) were admitted to the COVID-19 service. More of the COVID-19 service patients had the Alpha variant than the patients admitted to ICU (P<.009). The Alpha variant was also more common in younger patients (P<.001). There was no relationship between the Alpha virus and comorbid diseases such as diabetes mellitus and hypertension. Mortality was lower in the patients who had received a second dose of the Sinovac vaccine (P=.004) compared with unvaccinated patients. CONCLUSION: Although the Alpha variant spreads faster, it has a milder course. If only the Sinovac vaccine is available, we recommend that the two doses of the Sinovac vaccine be administered. LIMITATIONS: Our study is single-center and did not include pregnant and pediatric patients. CONFLICT OF INTEREST: None.
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    Enhancement of Heat Transfer Performance of a Heat Pipe by Using Calcium Magnesium Carbonate-Ethylene Glycol/Water Nanofluid with Sodium Dodecylbenzene Sulfonate
    (Budapest University of Technology and Economics, 2022) Yılmaz Aydın, Duygu; Gürü, Metin; Sözen, Adnan
    In this paper, the effect of using CaMg(CO3)2/Ethylene Glycol-water (50:50%) as a working fluid on the thermal performance of thermosyphon heat pipe was experimentally studied. Nanofluid was prepared by two-step method using 2% concentration of CaMg(CO3)2 nanoparticle and 0.05% surfactant (Sodium dodecylbenzene sulfonate). For the experimental set-up, a straight copper pipe of one-meter length was used. The inner diameter of the pipe is 13 mm, and the outer diameter is 15 mm. Experiments were conducted at three different cooling water mass flow rates (5, 7.5, and 10 g/s) and different heating powers (200, 300, 400 W) to test heat pipe performance. It was observed that the CaMg(CO3)2 nanofluid reduced the average wall temperature of the heat pipe according to the base fluid. Furthermore, the efficiency and thermal resistance of the heat pipe were investigated separately for EG/water and CaMg(CO3)2 nanofluid. The maximum heat transfer enhancement was obtained as 9.55% under 400 W heating power and 10 g/s cooling water mass flow rate conditions and the maximum improvement in thermal resistance was observed as 21% at 200 W and 10 g/s cooling mass flow rate. Viscosity and specific heat of base fluid and CaMg(CO3)2 nanofluid were also determined and compared to each other.
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    Deep learning model developed by multiparametric MRI in differential diagnosis of parotid gland tumors
    (Springer, 2022) Gündüz, Emrah; Alçin, Ömer Faruk; Kızılay, Ahmet; Yıldırım, İsmail Okan
    Purpose: To create a new artificial intelligence approach based on deep learning (DL) from multiparametric MRI in the differential diagnosis of common parotid tumors. Methods: Parotid tumors were classified using the InceptionResNetV2 DL model and majority voting approach with MRI images of 123 patients. The study was conducted in three stages. At stage I, the classification of the control, pleomorphic adenoma, Warthin tumor and malignant tumor (MT) groups was examined, and two approaches in which MRI sequences were given in combined and non-combined forms were established. At stage II, the classification of the benign tumor, MT and control groups was made. At stage III, patients with a tumor in the parotid gland and those with a healthy parotid gland were classified. Results: A stage I, the accuracy value for classification in the non-combined and combined approaches was 86.43% and 92.86%, respectively. This value at stage II and stage III was found respectively as 92.14% and 99.29%. Conclusions: The approach presented in this study classifies parotid tumors automatically and with high accuracy using DL models.
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    Inductive Power Transfer for Electric Vehicle Charging Applications: A Comprehensive Review
    (Multidisciplinary Digital Publishing Institute (MDPI), 2022) Aydın, Emrullah; Aydemir, Mehmet Timur; Aksöz, Ahmet; Hegazy, Omar
    Nowadays, Wireless Power Transfer (WPT) technology is receiving more attention in the automotive sector, introducing a safe, flexible and promising alternative to the standard battery chargers. Considering these advantages, charging electric vehicle (EV) batteries using the WPT method can be an important alternative to plug-in charging systems. This paper focuses on the Inductive Power Transfer (IPT) method, which is based on the magnetic coupling of coils exchanging power from a stationary primary unit to a secondary system onboard the EV. A comprehensive review has been performed on the history of the evolution, working principles and phenomena, design considerations, control methods and health issues of IPT systems, especially those based on EV charging. In particular, the coil design, operating frequency selection, efficiency values and the preferred compensation topologies in the literature have been discussed. The published guidelines and reports that have studied the effects of WPT systems on human health are also given. In addition, suggested methods in the literature for protection from exposure are discussed. The control section gives the common charging control techniques and focuses on the constant current-constant voltage (CC-CV) approach, which is usually used for EV battery chargers.
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    An Accurate Multiple Sclerosis Detection Model Based on Exemplar Multiple Parameters Local Phase Quantization: ExMPLPQ
    (Multidisciplinary Digital Publishing Institute (MDPI), 2022) Macin, Gulay; Taşçı, Burak; Taşçı, İrem; Faust, Oliver; Barua, Prabal Datta; Doğan, Şengül; Tuncer, Türker; Tan, Ru-San; Acharya, U. Rajendra
    Multiple sclerosis (MS) is a chronic demyelinating condition characterized by plaques in the white matter of the central nervous system that can be detected using magnetic resonance imaging (MRI). Many deep learning models for automated MS detection based on MRI have been presented in the literature. We developed a computationally lightweight machine learning model for MS diagnosis using a novel handcrafted feature engineering approach. The study dataset comprised axial and sagittal brain MRI images that were prospectively acquired from 72 MS and 59 healthy subjects who attended the Ozal University Medical Faculty in 2021. The dataset was divided into three study subsets: axial images only (n = 1652), sagittal images only (n = 1775), and combined axial and sagittal images (n = 3427) of both MS and healthy classes. All images were resized to 224 × 224. Subsequently, the features were generated with a fixed-size patch-based (exemplar) feature extraction model based on local phase quantization (LPQ) with three-parameter settings. The resulting exemplar multiple parameters LPQ (ExMPLPQ) features were concatenated to form a large final feature vector. The top discriminative features were selected using iterative neighborhood component analysis (INCA). Finally, a k-nearest neighbor (kNN) algorithm, Fine kNN, was deployed to perform binary classification of the brain images into MS vs. healthy classes. The ExMPLPQ-based model attained 98.37%, 97.75%, and 98.22% binary classification accuracy rates for axial, sagittal, and hybrid datasets, respectively, using Fine kNN with 10-fold cross-validation. Furthermore, our model outperformed 19 established pre-trained deep learning models that were trained and tested with the same data. Unlike deep models, the ExMPLPQ-based model is computationally lightweight yet highly accurate. It has the potential to be implemented as an automated diagnostic tool to screen brain MRIs for white matter lesions in suspected MS patients.
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    An efficient fault classification method in solar photovoltaic modules using transfer learning and multi-scale convolutional neural network
    (Elsevier, 2022) Korkmaz, Deniz; Açıkgöz, Hakan
    Photovoltaic (PV) power generation is one of the remarkable energy types to provide clean and sustainable energy. Therefore, rapid fault detection and classification of PV modules can help to increase the reliability of the PV systems and reduce operating costs. In this study, an efficient PV fault detection method is proposed to classify different types of PV module anomalies using thermographic images. The proposed method is designed as a multi-scale convolutional neural network (CNN) with three branches based on the transfer learning strategy. The convolutional branches include multi-scale kernels with levels of visual perception and utilize pre-trained knowledge of the transferred network to improve the representation capability of the network. To overcome the imbalanced class distribution of the raw dataset, the oversampling technique is performed with the offline augmentation method, and the network performance is increased. In the experiments, 11 types of PV module faults such as cracking, diode, hot spot, offline module, and other classes are utilized. The average accuracy is obtained as 97.32% for fault detection and 93.51% for 11 anomaly types. The experimental results indicate that the proposed method gives higher classification accuracy and robustness in PV panel faults and outperforms the other deep learning methods and existing studies
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    NCA-based hybrid convolutional neural network model for classification of cervical cancer on gauss-enhanced pap-smear images
    (Wiley-Blackwell, 2022) Bingöl, Harun
    Cervical cancer is a very serious disease that deeply affects women's lives, often resulting in death. This type of cancer, which is very common in women, is diagnosed at an early stage and is of vital importance for the success of the treatment. Pap-smear tests are used by physicians as the primary diagnostic tool to diagnose the disease. In this study, a hybrid deep model is proposed to classify pap-smear images to detect cervical cancer. In addition, the Gaussian method was applied to improve the images in the original dataset. Feature maps were taken from both the original dataset and the Gaussian-enhanced dataset in the built hybrid architecture, which used Darknet53 and Mobilenetv2 models as the base. After these obtained feature maps were combined, useless features were extracted and the number of features was reduced by using the Neighborhood Component Analysis (NCA) dimension reduction method. Finally, this optimized feature map was classified into different classifiers. As a result of the experimental studies, it was determined that the proposed hybrid model performed better when compared to other studies in the literature and the accuracy rate was 98.90% in the Support Vector Machines (SVM) classifier.
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    A comparative melissopalynological study of royal jelly from Turkey
    (Taylor & Francis, 2022) Yıl, Gülşah; Karlıdağ, Semiramis; Akyol, Abuzer; Köseman, Abdurrahman; Uyumlu, Ayşe Burçin; Yılmaztekin, Murat; Erdoğan, Selim; Şeker, İbrahim
    Three treatments (Glucose, Sucrose, Bee Feed Syrup) were used to examine the influence of supplementary feeding on the pollen spectrum of the royal jelly produced by Apis mellifera L. colonies. Apis mellifera colonies were located in the Battalgazi and Dogansehir districts of Malatya province in Turkey. In total 255 royal jelly samples were investigated and the analysis recorded over 30 taxa. In both sites the control group heavily utilised Quercus, Verbascum, Astragalus, and Lamiaceae. The feeding treatments saw Quercus, Verbascum, and Astragalus still being used but in different proportions. The utilisation of Lamiaceae was much reduced and Echium became an important component in colonies that had supplementary feeding. © 2022 Collegium Palynologicum Scandinavicum.
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    Evaluation of the relationship between nasal septal deviation and development of facial asymmetry with anthropometric measurements depending on age: The effect of nasal septum deviation on craniofacial asymmetry and somatotype
    (Elsevier, 2022) Arpacı, Muhammed Furkan; Özbağ, Davut; Aydın, Şükrü; Şenol, Deniz; Baykara, Rabia Aydoğan; Çiçek, İpek Balıkçı
    Aim: It was aimed to determine the change of facial asymmetry resulting from nasal septal deviation (SD) depending on age, gender, degree of deviation and the affected area besides the effect of SD on somatotype and craniofacial morphology. Materials and methods: 171 volunteers (90 males, 81 females), 27 individuals aged 9–13, 44 individuals aged 14–18, 44 individuals aged 19–23 and 56 individuals in control group participated in the study conducted in otorhinolaryngology polyclinic.11 photometric, 16 anthropometric measurements were taken from the participants. Results: SD affects facial asymmetry formation, although not statistically significant compared to healthy individuals asymmetry rates (p?0.05). It was determined that the degree of SD affected asymmetry only between the ages of 14–18 (in adolescence) and the development of asymmetry in all SD patients was not statistically dependent on age and gender (p?0.05). Photometric measurements demonstrated asymmetries in horizontally-extending parameters of 1/3 middle part of face. There was no statistically significant difference in the cranial anthropometric measurements of the upper and lower 1/3 of the face compared to the control group (p?0.05). The order of the most asymmetrical parameters is Alare-Zygion, Alare-Subnasale, Cheilion-Gonion, Exocanthion-Cheilion, Midsagittal plane-Zygion, Zygion-Cheilion, Zygion-Gonion, Subalare-Cheilion, Glabella-Exocanthion. In all participants were determined that endomorph somatotype was dominant in female and mesomorph somatotype was dominant in male besides SD did not affect somatotype and somatotype did not alter with age. Conclusion: The development of facial asymmetry due to SD is not affected by age and gender furthermore SD does not affect craniofacial asymmetry and somatotype.
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    Clinical and Molecular Findings in a Turkish Family Who Had a (c.869-1G>A) Splicing Variant in PSEN1 Gene with A Rare Condition: The Variant Alzheimer's Disease with Spastic Paraparesis
    (Bentham Science, 2022) Doğan, Mustafa; Eröz, Recep; Tecellioğlu, Mehmet; Gezdirici, Alper; Çevik, Betül; Barış, İbrahim
    Background: Early-onset Alzheimer's disease (EOAD) is commonly diagnosed with an onset age of earlier than 65 years and accounts for 5–10% of all Alzheimer's disease (AD) cases. To date, although only 10-15% of familial EOAD cases have been explained, the genetic cause of the vast proportion of cases has not been explained. The variant Alzheimer's disease with spastic paraparesis (var- AD) is defined as a rare clinical entity characterized by early-onset dementia, spasticity of the lower extremities, and gait disturbance. Although the disease was first associated with variants in exon 9 of the PSEN1 gene, it was later shown that variations in other exons were also responsible for the disease. Objective: The current study aims to raise awareness of varAD, which occurs as a rare phenotype due to pathogenic variants in PSEN1. In addition, we aimed to evaluate the spectrum of mutations in varAD patients identified to date. Methods: Detailed family histories and clinical data were recorded. Whole exome sequencing was performed and co-segregation analysis of the family was done by Sanger sequencing. Also, a review of the molecularly confirmed patients with (varAD) from the literature was evaluated. Results: We identified a heterozygous splicing variant (c.869-1G>A) in the PSEN1 gene, in a family with two affected individuals who present with varAD. We reported the clinical and genetic findings from the affected individuals. Conclusion: We present the detailed clinical and genetic profiles of a Turkish patient with the diagnosis of varAD together with subjects from the literature. Together, we think that the clinical characteristics and the effect of the (c.869-1G>A) variant will facilitate our understanding of the PSEN1 gene in AD pathogenesis.
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    Preparation of 10-undecenoic acid based polyurethane/PCL fibers by electrospinning method and investigation of their antifungal properties
    (Springer, 2022) Açarı Karaca, İdil; Boran, Filiz; Kolak, Seda; Tatlıcı, Eray; Yeşilada, Özfer; Köytepe, Süleyman; Ateş, Burhan
    Nowadays, in the treatment of such fungal infections, antifungal drugs in various forms are one of the most preferred methods. These medications can be in the form of creams and lotions, shampoos, pills, suppositories, powders, or sprays. The dose of the drugs is adjusted according to the type and growth area of the fungus, the severity of the symptoms, and the medical history of the patients. Dressing materials with antifungal properties are an alternative treatment method used for the treatment of fungal skin infections. These covers not only treat fungal infections but also prevent their spread. Within the scope of this study, polyurethane-based wound dressing materials (PU-UDA/PCL) with antifungal properties were developed. Electrospining method was used to produce these dressing materials and the surface area of the wound dressing material was increased, thereby increasing the effect of antifungal property. Polypropylene glycol, glycerol, and catechin as polyol were preferred in polyurethane (PU) synthesis. These structures were polymerized with isophorone diisocyanate and modified with 10-undecenoic acid. Obtained 10-undecenoic acid modified polyurethane (PU-UDA) structures were transformed into wound dressing structure with polycaprolactone (PCL) by electrospinning method. Structural, morphological, and thermal properties of the wound dressing materials were analyzed with different instrumental analysis methods. The antifungal activities of PU-UDA/PCL were tested. Antifungal tests were performed on C. albicans and C. tropicalis. Therefore, PU-UDA/PCL series could be used as an efficient antifungal agent. Finally, it was determined that the obtained 10-undecenoic acid-based polyurethane fibers have a suitable structure and feature for the treatment of many fungal infections.
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    Synthesis and analysis of TiO2 nanotubes by electrochemical anodization and machine learning method for hydrogen sensors
    (Elsevier, 2022) Işık, Eşme; Taşyürek, Lütfi Bilal; Işık, İbrahim; Kılınç, Necmettin
    The conductometric hydrogen gas sensors were used to explore TiO2 nanotubes in this study. TiO2 nanotubes are synthesized by anodization of the titanium foils using a neutral 0.5% and 1% (wt) NH4F in glycerol solution depending on anodization time and anodization voltage at the temperature of 20 °C. The amorphous, rutile and anatase phases of TiO2 are observed for as-prepared TiO2 nanotubes, annealed at 700 and 300 °C, respectively. The diameters of the nanotubes grow as the anodization time and voltage increase, according to scanning electron microscopy (SEM) images. The inner diameter of nanotubes is changed between ~70 nm to ~225 nm. Hydrogen sensing properties of Ti/TiO2 nanotubes/Pd device has been tested at room temperature under concertation range from 0.5% to 10% depending on the crystalline phase. The highest sensor response is observed for anatase crystalline TiO2 nanotubes. Typical Schottky-type behavior is observed from the I-V measurement. All the fabricated nanotube diameters are also simulated by using Support Vector Machine and Artificial Neural Network models. And also, some of the nanotube diameters which are not obtained experimentally (anodization voltage of 70 V) are estimated using the Support Vector Machine and Artificial Neural Network models. In addition, an analytical model is also proposed using Jacobi numeric analysis method alternative to the simulation model for the nanotube diameter. Finally, the analytical, simulation, and experimental results are compared, and the best result is obtained using the 1 Hidden Layer Artificial Neural Network model.
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    Cyberchondria, Covid-19 phobia, and well-being: a relational study on teachers
    (Mattioli1885, 2022) Karakaş, Neşe; Tekin, Çiğdem; Bentli, Recep; Demir, Ekrem
    Background: This study aims at investigating level and contributor factors of Cyberchondria, COVID-19-related Phobia, and Well-Being in a sample of teachers in Turkey. Methods: The study was conducted on teachers (n=1000) working in a province in eastern Turkey. Data for the study were collected using a form that included particitest, and Kruskal Wallis analysis of variance were used to analyze the data. Results: As participant's cyberchondria levels rose, C19P-SE scores increased (r=0.271, p<0.001), and WHO-5 scores decreased (r=-0.224, p<0.05). Corona-phobia was higher in those who used social media than in those who did not (p<0.05). Cyberchondria scale scores were higher among those who had taken medications without a physician's recommendation during the pandemic. Participants who had a disabled person or a person in need of care in their household had higher scores for distrust of the physician and C19P-SE than for the cyberchondria severity scale sub-dimension, and the WHO-5 mean scores were lower (p<0.001, P=0.016, and P=0.020, respectively).Conclusions: The study results show that increasing levels of cyberchondria trigger COVID-19 phobias in teachers during the COVID-19 pandemic and negatively affect their well-being. This descriptive study can help understand the risk group for cyberchondria, the influencing factors, and the health and economic consequences, and identify strategies for effective combating with cyberchondria.
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    Determination of tensile strength of cementitious composites using fracture parameters of two-parameter model for concrete fracture
    (Elsevier, 2022) İnce, Ragıp; Fenerli, Cenk
    In this study, the formulation of the two-parameter model based on the size effect proposed by previous researchers was initially improved to be much more practical. Subsequently, six series of notched and unnotched beams with a size ratio of 1:4 and notched and unnotched square prismatic specimens with a size ratio of 1:6 were tested to verify this modified formulation. The peak loads obtained from the fracture tests of the notched specimens were examined using the two-parameter model. Then, the test results of the unnotched bending and splitting specimens were simulated according to the modified formulation. Furthermore, this formulation was applied to extensive test data obtained from the direct tension specimens with double edge notches and from the unnotched specimens in the literature to derive the direct tensile strength of concrete. Finally, when comparing the results of this study to the previous studies, there were slight differences among the other formulas, except for the one that covered splitting specimens.
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    Evaluation of the efferent auditory system in COVID-19 adult patients
    (Taylor & Francis, 2022) Emekci, Tuğba; Dündar, Mehmet Akif; Kirazlı, Gülce; Men Kılınç, Fatma; Cengiz, Deniz Uğur; Karababa, Ercan; İnceoğlu, Feyza; Arbağ, Hamdi
    Background: The short- and long-term effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the medial olivocochlear reflex and outer hair cells in the cochlea remain largely unclear. Aims: The aim of this study was to investigate the efferent auditory system effects in adult patients with COVID-19. Materials and methods: The study included 18–50 years old 44 volunteers: 26 individuals (52 ears) with COVID-19 in the study group and 18 healthy individuals (36 ears) in the control group. Otolaryngological examination, immitancemetric evaluation, distortion product otoacoustic emission (DPOAE), contralateral acoustic stimulation with DPOAE, audiometric evaluation, and high frequency audiometric evaluation were performed in all individuals participating in the study. Results: In our study, patients with COVID-19 had significantly lower DPOAE results with or without broadband noise at only 6 kHz frequency and contralateral suppression results at all frequencies compared to healthy individuals. A statistically significant difference was found between the study and control groups according to whether the participants had a response in the high frequency audiometry at 12 and 16 kHz frequencies. Conclusions: COVID-19 affects many systems in the body. As a result of the findings obtained in the present study, it is shown that the auditory efferent system may also be affected.
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    Toxic and essential elements in selected fish species from the Tigris River (Turkey) and assessment of their health risks and benefits
    (Elsevier, 2022) Varol, Memet; Kaçar, Emel; Sünbül, Muhammet Raşit
    The distribution of 18 toxic and essential elements (TEEs) (Sr, As, Ba, Cu, Fe, Ga, Ca, Cd, K, Co, Mg, Mn, Na, Ni, P, Pb, Cr and Zn) was investigated in tissues/organs of three fish species showing similar feeding habits from the Tigris River. The findings revealed that concentrations of TEEs in fish depend on the species. The highest contents of most TEEs were recorded in the gills followed by the liver, skin and muscle. Generally, inverse relationships were recorded between fish size and TEEs in tissues of fish species which may be explained by the lower metabolic rate and dilution effect of higher lipid content in the bigger fish. The average contents of Cd, Pb, Cr, Cu, Zn and inorganic As in muscle tissues of fish species were below the permissible limits. The estimated daily intakes of Ba, Cu, Fe, Mn, Ni, Sr, Zn, inorganic As, Cd, Co, Cr and Pb were much lower than the reference doses set by USEPA. The target hazard quotient and hazard index values were below 1, indicating that non-carcinogenic health effects are unlikely to occur. The carcinogenic risk values for inorganic As were below 10?6, indicating no carcinogenic health risks for consumers. It was found that daily consumption of 230 g of fish would not be expected to cause any health risks. In addition, it was found that fish species would provide great benefits considering intake of essential elements. These findings revealed that nutritional benefits from consumption of fish species outweighed the health risks posed by toxic elements in fish.