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Öğe Automated Age Estimation from OPG Images and Patient Records Using Deep Feature Extraction and Modified Genetic-Random Forest(2025) Uçan, Gülfem Özlü; Gwassi, Omar Abboosh Hussein; Apaydın, Burak Kerem; Uçan, BahadırBackground/Objectives: Dental age estimation is a vital component of forensic science, helping to determine the identity and actual age of an individual. However, its effectiveness is challenged by methodological variability and biological differences between individuals. Therefore, to overcome the drawbacks such as the dependence on manual measurements, requiring a lot of time and effort, and the difficulty of routine clinical application due to large sample sizes, we aimed to automatically estimate tooth age from panoramic radiographs (OPGs) using artificial intelligence (AI) algorithms. Methods: Two-Dimensional Deep Convolutional Neural Network (2D-DCNN) and One-Dimensional Deep Convolutional Neural Network (1D-DCNN) techniques were used to extract features from panoramic radiographs and patient records. To perform age estimation using feature information, Genetic algorithm (GA) and Random Forest algorithm (RF) were modified, combined, and defined as Modified Genetic-Random Forest Algorithm (MG-RF). The performance of the system used in our study was analyzed based on the MSE, MAE, RMSE, and R2 values calculated during the implementation of the code. Results: As a result of the applied algorithms, the MSE value was 0.00027, MAE value was 0.0079, RMSE was 0.0888, and R2 score was 0.999. Conclusions: The findings of our study indicate that the AI-based system employed herein is an effective tool for age detection. Consequently, we propose that this technology could be utilized in forensic sciences in the future.Öğe Performance analysis of input power variations in high data rate DWDM-FSO systems under various rain conditions(Springer, 2025) Abdulwahid, Maan Muataz; Kurnaz, Sefer; Kurnaz Türkben, Ayça; Hayal, Mohammed R.; Elsayed, Ebrahim E.; Juraev, Davron AslonqulovichThis paper investigates the performance of a 32-channel Dense Wavelength Division Multiplexing Free-Space Optical (DWDM-FSO) system under various rain conditions and transmission distances ranging from 5 to 20 km. The study aims to identify optimal input power levels across different rain scenarios (-10 dBm, -5 dBm, 0 dBm, 5 dBm, and 10 dBm) to enhance the reliability and efficiency of optical communication in adverse weather. Findings indicate that for light rain conditions, input power levels of -10 dBm are suitable for distances up to 15 km. In moderate rain scenarios, -5 dBm is optimal for reliable communication up to 10 km, while higher input powers of 5 dBm are necessary to maintain performance in heavy rain conditions beyond 5 km. This study highlights the critical relationship between input power and atmospheric conditions, confirming that higher power levels can effectively mitigate the effects of rain-induced attenuation and scattering. Key parameters such as transmitter and receiver configurations, atmospheric attenuation, scattering, and turbulence were analyzed, demonstrating the importance of selecting appropriate power levels to ensure successful data transmission. Additionally, the research suggests future explorations into adaptive modulation techniques and quantum applications to further enhance system resilience and performance. The results provide valuable insights for system designers, enabling the adaptation of FSO systems to meet the challenges posed by varying environmental conditions and guiding developments in robust optical communication technologies.Öğe A hybrid model using 1D-CNN with Bi-LSTM, GRU, and various ML regressors for forecasting the conception of electrical energy(World Scientific Publishing, 2025) Abdulameer, Yahya Hafedh; Ibrahim, Abdullahi AbduTo solve power consumption challenges by using the power of Artificial Intelligence (AI) techniques, this research presents an innovative hybrid time series forecasting approach. The suggested model combines GRU-BiLSTM with several regressors and is benchmarked against three other models to guarantee optimum reliability. It uses a specialized dataset from the Ministry of Electricity in Baghdad, Iraq. For every model architecture, three optimizers are tested: Adam, RMSprop and Nadam. Performance assessments show that the hybrid model is highly reliable, offering a practical option for model-based sequence applications that need fast computation and comprehensive context knowledge. Notably, the Adam optimizer works better than the others by promoting faster convergence and obstructing the establishment of local minima. Adam modifies the learning rate according to estimates of each parameter's first and second moments of the gradients separately. Furthermore, because of its tolerance for outliers and emphasis on fitting within a certain margin, the SVR regressor performs better than stepwise and polynomial regressors, obtaining a lower MSE of 0.008481 using the Adam optimizer. The SVR's regularization also reduces overfitting, especially when paired with Adam's flexible learning rates. The research concludes that the properties of the targeted dataset, processing demands and job complexity should all be considered when selecting a model and optimizer.Öğe Development and Evaluation of Drone Based Spraying System for Precision Agriculture Application(International Information and Engineering Technology Association, 2025) Yousfi, Ayoub El; Alawi, YaserUnmanned aerial vehicles (UAVs), also known as drones, are increasingly used for various purposes such as photography, surveillance, mapping, inspection, and agriculture. This research specifically focuses on agricultural drones, which have the potential to address challenges encountered by farmers, ultimately positively affecting crop yields. Their ability to apply pesticides accurately and autonomously, without direct human involvement, is crucial for modern farming practices. This study aims to design and simulate a quadcopter specifically tailored for pesticide spraying. The design process involves careful selection of components and simulation using both SolidWorks and MATLAB Simulink. In SolidWorks, design the frame and components, while MATLAB Simulink is used to simulate trajectory tracking using PID controllers. The key finding is the integration of a multispectral camera to capture images and analyze data using Pix4Dfields and Agremo software. This analysis helps pinpoint specific areas requiring treatment, thereby minimizing pesticide and water usage while maximizing profitability. By targeting exact locations in the field based on data analysis, this approach improves efficiency. The research focuses on evaluating the quadcopter’s performance and trajectory accuracy, offering valuable insights into its potential agricultural impact, and assisting farmers in enhancing their profits through improved spraying techniques and resource management.Öğe Exploring the structural basis of crystals that affect nonlinear optical responses: An experimental and machine learning quest(Elsevier B.V., 2025) Hassan, Abrar U.; Güleryüz, Cihat; El Azab, Islam H.; Elnaggar, Ashraf Y.; Mahmoud, Mohamed H.H.Machine learning can enable a computational framework to learn from data, thereby enhancing decision-making for targeted properties. Based on the significance of nonconjugated crystals as effective switches, an ML based approach has been applied to evaluate driving forces behind their polarizability/hyperpolarizability related hyper-Rayleigh Scattering (βHRS). For this, a dataset of relevant 1,3,5-triazine-2,4,6-triamine related structures in collected from peer reviewed literature to design its molecular descriptors. The designed dataset is trained on different regression models along with their cross-validation techniques include K-Fold and Leave One Group Out. It shows that Random Forest Regression can predict their polarizabilities with a fair accuracy (R2 = 0.83). Additionally, it shows its energy gaps (Egaps) ranging from 4.62 to 4.89 eV, with the smallest gap observed in ethanol. Understanding both these theoretical and experimental calculations can significantly help in selecting materials for targeted purposes, including sensors, electronic devices, and catalysis. Furthermore, insights into nucleophilic tendencies and charge distributions aids in designing new materials with tailored properties, expanding their use in various applications across chemistry, materials science, and other fields. The ML techniques prove its effectiveness to predict polarizabilities in response to its computational realm due to feature design, regression models with their cross-validations.Öğe A Novel Flip-Filtered Orthagonal Frequency Division Multiplexing-Based Visible Light Communication System: Peak-to-Average-Power Ratio Assessment and System Performance Improvement(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Hujijo, Hayder S. R.; Ilyas, MuhammadFiltered orthogonal frequency division multiplexing (F-OFDM), employed in visible light communication (VLC) systems, has been considered a promising technique for overcoming OFDM’s large out-of-band emissions and thus reducing bandwidth efficiency. However, due to Hermitian symmetry (HS) imposition, a challenge in VLC involves increasing power consumption and doubling inverse fast Fourier transform IFFT/FFT length. This paper introduces the non-Hermitian symmetry (NHS) Flip-F-OFDM technique to enhance bandwidth efficiency, reduce the peak–average-power ratio (PAPR), and lower system complexity. Compared to the traditional HS-based Flip-F-OFDM method, the proposed method achieves around 50% reduced system complexity and prevents the PAPR from increasing. Therefore, the proposed method offers more resource-saving and power efficiency than traditional Flip-F-OFDM. Then, the proposed scheme is assessed with HS-free Flip-OFDM, asymmetrically clipped optical (ACO)-OFDM, and direct-current bias optical (DCO)-OFDM. Concerning bandwidth efficiency, the proposed method shows better spectral efficiency than HS-free Flip-OFDM, ACO-OFDM, and DCO-OFDM.Öğe A fast and efficient machine learning assisted prediction of urea and its derivatives to screen crystal propensity with experimental validation(Elsevier Ltd, 2025) Güleryüz, Cihat; Sumrra, Sajjad H.; Hassan, Abrar U.; Mohyuddin, Ayesha; Noreen, Sadaf; Elnaggar, Ashraf Y.Predicting crystal propensity is crucial yet challenging in various industries where it significantly influences product stability, performance, and efficacy. Predicting a crystal propensity identifies their optimal chemical structures for desired properties including solubility, bioavailability, shelf-life stability etc. Herein, A machine learning (ML) assisted analysis is performed to predict their crystal propensity by collecting a dataset of 6000 non-crystalline and over 200 crystalline urea and its derivatives. The data is trained by employing a Support Vector Machine (SVM) with its Radial Basis Function (RBF) and linear kernels along with Random Forest regression analysis. The trained data is compared with four other ML models, including Linear Regression, Gradient Boosting, Random Forest and Decision Tree Regressions to predict their crystal propensity. It yields an accuracy of 79 % for identifying their non-crystalline compounds and 59 % in predicting crystallization failure. Their dimensionality reduction via t-SNE reveals their distinct clustering patterns to underscore their complex interplay between molecular structure and crystal propensity. Their experimental validation also corroborates the current findings to demonstrate their efficacy to streamline their crystal engineering for pharmaceutical formulation-based workflows. Notably, the number of rotatable bonds and molecular connectivity index (χov) emerges as pivotal descriptors for enabling their accurate classification with minimal input features. This study elucidates its quantitative structure-crystallinity relationship to provide a valuable tool for crystal design and optimization.Öğe Activation of Proteolysis During Oocyte In Vitro Maturation(2025) Tepeköy, Filiz; Bulut, Berk; Karaöz, ErdalIn vitro maturation (IVM) is a form of assisted reproductive technology (ART) applied to obtain mature oocytes in culture. Decline in IVM success rates by age has led consideration of novel approaches based on cellular dynamics. Our aim was to achieve proteostasis in old bovine oocytes from 13 to 16-year-old bovine with a lower potential for fertilization. Lysosomal activation was achieved through increasing concentrations of proton pump activators PIP2 (0.1, 0.5, 1, and 5 μM), PMA (0.1, 1, 10, and 50 μM), and DOG (0.1, 1, 10, and 50 μM) at 6, 12, 18, and 24 h of IVM in old bovine oocytes. Morphological analysis was performed and IVM rates were determined. DQ-Red BSA was applied to live oocytes to determine proteolytic activation while lysosome density was determined by Lysotracker probe. Protein carbonylation was detected through oxyblot analysis. Polar body extrusion (PBE), through which a haploid nonfunctional polar body is released in the perivitelline space after completion of the first meiotic division, was observed in PIP2-0.1 μM, -0.5μM-6h; PIP2-5μM-12h; PMA-0.1μM-18h; PIP2-0.1μM, -0.5μM-24h groups. Oocyte diameter was the highest in DOG-1μM-6h, PMA-0.1μM-12h, PIP2-1μM-18h, and PIP2-0.5μM-24h groups. Morphological scores of oocytes were higher in young and old control groups. PIP2, PMA, and DOG affected oocyte quality positively after 6 h of IVM yielding in oocyte scores similar to the control group oocytes. However, they had a negative impact on the oocyte scores in longer periods of IVM, except for lower doses PMA (0.1 and 1 μM) at 12 h and PIP2 (0.5 μM) and PMA (0.1 μM) at 18 h, which were able to maintain the scores relatively closer to the control oocytes. Proteolytic activation was achieved in all groups at 6 h of culture. At all other time points PIP2 and PMA groups showed a better response to proteolytic activation. Lysosome density was increased in PIP2-5μM-6h; PIP2-0.1μM, -1μM-12h; PIP2-1μM, -5μM-18h as well as PMA-0.1μM-6h; PMA-1μM, -10μM-12h; PMA-1μM-18h; DOG-50μM-6h and DOG-0.1μM-12h. Protein carbonylation was the lowest in PIP2-0.1 μM groups at 12, 18, and 24 h. This study suggests that proton pump activators PIP2 and PMA was found to have a positive impact on IVM in terms of both morphological scores and proteolytic activation in a time and dose dependant manner.Öğe Enhancing Content-Based Image Retrieval with a Stacked Ensemble of Deep Learning Models(Institute of Electrical and Electronics Engineers Inc., 2024) Zeain, Abdulrahman; Ibrahim, Abdullahi AbduOur research paper delves into an innovative exploration of content-based image retrieval (CBIR), harnessing the capabilities of deep learning models to transform the way images are searched and accessed in extensive databases. The primary goal of our study is to create an ensemble stacking model that synergizes the strengths of various deep learning architectures, thereby boosting the accuracy and efficiency of image retrieval processes. We utilize the Corel Images dataset, rich in diverse visual themes, to test and validate our model's efficacy. Our research methodology encompasses four key stages: data preprocessing, model training with DenseNet, MobileNet, and Inception-ResNet, followed by an in-depth evaluation of the model. The approach demonstrates the effectiveness of our ensemble model as it achieves a high accurate rate of 97 % exceeds the benchmarks set by the individual models in our compare and differential analyses. Moreover, the manuscript investigates the model's technical detail, such as the feature extraction, runtime with different images, and scalability to more massive datasets. The eulogy for the model's performance in the performance evaluation section encapsulates the functional performance and the practicality of CBIR efficacy.Öğe Diagnosis of Epileptic seizures and Hypoxic-ischemic encephalopathy using Artificial Intelligence based on EEG signal: A review(Institute of Electrical and Electronics Engineers Inc., 2024) Kadhim, Ezzaddin; Al-Jumaili, Saif; Uçan, Osman NuriThe brain is the nucleus for cognition and controls voluntary and involuntary activities inside the human body. Any neurological illness, regardless of its cause, will impair the brain's functionality. Certain neurological illnesses manifest symptoms as seizures. Epilepsy and Hypoxic-ischemic Encephalopathy (HIE) are the most similar disorders in symptoms, but at the neurological level, they are two completely different disorders. This difference is measured at the level of neural activity, as Electroencephalography (EEG) is one of the most distinctive tools used to measure neural activity in the brain. Experts use EEG to diagnose disorders through recorded brain activity, including seizures, but the diagnosis process consumes much time and effort. Adopting Artificial Intelligence (AI) techniques to extract the patterns of brain illnesses is a more efficient process for diagnosing disorders because it depends on computing and, thus, has high accuracy in diagnosing brain illnesses. In this research, we reviewed the most effective stages and methods adopted by researchers to diagnose brain disorders based on EEG and artificial intelligence techniques.Öğe Islamkoy traditional houses and investigation of building materials: Okul street example(Peter Lang AG, 2020) Besir, Sebnem Ertas; Sonmez, ElifI˙slamköy town of Isparta, which is also located at the intersection of important historical roads, has hosted different civilizations and many societies. Traditional houses that are in I˙slamköy with its past are among the which bear the traces of the past to the present. In this respect, these houses are among the important cultural heritages that need to be improved and preserved with their unique architectural characteristics, influenced by local values. Today, it is a necessity to transfer traditional houses to future generations in terms of their historical value and importance. In terms of ensuring cultural continuity, I˙slamköy houses that reflect the traditional lifestyle is important to protect and maintain. For this purpose, in the study, examples of traditional residential architecture of I˙slamköy have been handled within the scope of Okul Street, and construction techniques and material usage of existing structures are determined. © Peter Lang AG 2020.Öğe Addressing the gap between pharmacy education and practice(Nova Science Publishers, Inc., 2020) Aksoy, NilayThe heath care process is straggling with complexity, yielding the necessity for multidisciplinary approaches involving all health care providers as well as social scientists and well-rounded pharmacists. The discrepancy between training and practice makes it difficult to undertake these approaches. It has become apparent that pharmacy education needs to respond to professional and social changes and renew its mission in terms of students and learning objectives. "In theory, there is no difference between theory and practice, but in practice there is," stated Manfred Eigen. This chapter will focus on approaches for bridging the theory-practice gap. First of all, these differences can be resolved by carrying out realistic research. Pharmacy institutions should perform advanced research to determine the needs and to promote and support the practice. Numerous literature studies support the proposition to include pharmacists in inter-professional primary health care teams. Country-based research will help confirm whether the training system and education obtained by pharmacy students is sufficient to promote a positive attitude toward potential integration into primary health care. Second, common, clear, and compelling outcomes should be established based on previous studies, and education should be standardized accordingly. A well-rounded student of pharmacy is created by a high-quality pharmacy school, a well-formed curriculum that meets the requirements, and a highly effective style and method of education. The curriculum of apprenticeships should be improved. The enhancement of apprenticeship programs should not be limited to increasing the number of apprenticeship courses, but should also extend to the quality of their content. Simulation training can play an important role in upscaling and improving pharmacy learning productivity and in overcoming the barrier of limited real-field learning. Lastly, the disparity between community-based and hospital-based apprenticeships and the courses attributed to graduates must be reduced to provide compatibility with pharmacy practice. Inter-professional education (IPE) should be introduced into the curriculum. One of the major obstacles to the success of the pharmacist in providing primary health care is presented when the pharmacist is directly involved in patient care and this role is ignored by other health care providers. Inter-professional education prepares students for collaborative thinking and practice. Building this collaborative project through education has a major impact on bridging the gaps between different providers of primary health care. In summary, the recommendations proposed include: continuing professional development (CPD) to enhance the workforce, incorporating technologies and software in pharmacy education, evaluating the education process from different aspects (students, practitioners, primary health care providers), restructuring the curriculum according to research feedback, and finally, effectively collaborating with other health care providers ("One hand can't clap alone"). © 2020 Nova Science Publishers, Inc.Öğe THE USE OF ACTIVIN IN OVARIAN FOLLICLE CULTURE SYSTEMS(Nova Science Publishers, Inc., 2020) Tepekoy, FilizThe cancer treatment during puberty and early adulthood might have negative effects on reproductive system in women, causing premature menopause, premature ovarian failure and infertility. In order to protect germ cells from these undesirable effects without any functional loss, different experimental approaches have been developed. One of these approaches is ovarian follicle culture system which includes in vitro growth of ovarian follicles obtained from the patients before being exposed to the detrimental effects of cancer treatment. In vitro growth of the follicles starts from primordial stage and gives rise to an ovulatory follicle with a competent oocyte within a culture system supplemented with folliculogenesis activators. Activin is one of these follicle activators supporting the growth and survival of the follicles. As a member of the transforming growth factor beta (TGF-β) superfamily, activin is known to be expressed in granulosa cells and oocytes. The main role of activin is stimulation of follicle stimulating hormone (FSH) secretion from anterior pituitary and induction of follicle growth enabling granulosa cell proliferation and antral cavity formation. Exogenous activin has been considered to be one of the key components of the in vitro follicle culture. The effects of the activin during in vitro follicle growth have been evaluated through both morphological and molecular biological criteria such as oocyte and follicle diameter, oocyte integrity, expressions of proliferation markers in granulosa cells and expressions of mitogenactivated protein kinase (MAPK) and Akt signaling members in the follicles, meiotic competence of oocytes and hormone synthesis. Since, one of the most important effects of activin on granulosa cells is induction of FSH receptor expression, activin is mostly used in combination with FSH during the culture. The current literature has mainly focused on the differential effects of activin on in vitro grown follicles at different developmental stages in the presence and absence of other activators such as FSH. This review covers the key literature on the structural and functional effects of the use of activin during in vitro growth of ovarian follicles. © 2020 by Nova Science Publishers, Inc. All rights reserved.Öğe An account of the first ten years of the Turkey-European Union negotiations (2005-2015)(Ahmet Yesevi University, 2016) Erhan, Çağri; Akdemir, ErhanThis article examines the first 10 years (2005-2015) of the membership negotiations between Turkey and the European Union. The main reason for examining this period is that it covers the initial negotiations and the most recent period of the possible membership of Turkey in the EU. This article includes a brief history of the negotiations, the decision to initiate the negotiations, and the initial negotiations. In addition, the pace of the negotiations are evaluated and the future of the negotiations are predicted based on the assessment of the current stage in the negotiations. In this context, European Union progress reports will also be analysed in depth. © 2016, Ahmet Yesevi University. All rights reserved.Öğe Ulubelenolide: A New triterpene lactone from Tanacetum chiliophyllum (Fisch. & Mey.) var. monocephalum Grierson(ACG Publications, 2015) Polatoğlu, Kaan; Gören, NezhunA further investigation on Tanacetum chilliophyllum var. monocephalum ethyl acetate extract afforded a new triterpene lactone Ulubelenolide (olean-12-ene-3β,10β-olide) (1).The structure of (1) was determined with spectral analysis including FTIR, 1H, 13C NMR, APT, DEPT, COSY, HMQC, HMBC, and APCI-MS. © 2015 ACG Publications. All rights reserved.Öğe The cinematic image as an architectural conductor: A mediated hint from future architecture(Intellect Ltd., 2016) Kavakoğlu, Ayşegül Akçay[No abstract available]Öğe Global risk aversion spillover dynamics and investors’ attention allocation(Central University of Finance and Economics, 2017) Ceylan, ÖzcanThis paper investigates market-wide risk aversion in an international setting. Particularly, this empirical study evaluates risk aversion spillover dynamics as an uncertainty transmission mechanism for the period 2000-2015 to reveal if there has been a significant change in these dynamics when markets are going through turbulent periods. As a plausible proxy for risk aversion, variance risk premium (VRP) is computed through the difference between expected variances under risk-neutral and physical measures for seven markets studied: United States, United Kingdom, Germany, France, Netherlands, Switzerland and Japan. Effects of a shock to U.S. VRP on the other markets’ VRPs are evaluated through Generalized Forecast Error Variance Decomposition. Results show that risk aversion spillovers from U.S. to other markets are stronger while the U.S. is going through turbulent periods confirming the intuition that investors are more focused on incidents in the turbulent market. Markets become more connected in terms of sentiments when a country is unexpectedly hit by a major crisis, limiting diversification opportunities. © 2017, Central University of Finance and Economics. All rights reserved.Öğe Graphene-based electrochemical aptasensors(Wiley Blackwell, 2019) Ozalp, V. Cengiz; Karabiyik, Göktuğ; Bayrac, A. Tahir; Uçak, Samet; Tuna, Bilge G.Graphene has remarkable electrical, thermal, and mechanical characters and has been widely used in biosensor development. Various graphene-based materials, including graphene oxide (GO), an aqueous dispersible oxygenated derivative of graphene, have been widely successfully utilized in molecular hybrids or biocompatible scaffolds or substrates, and patterned carbon films after being chemically reduced or modified to tune the material properties. Aptamers are short oligonucleotides that bind targets with high specificity and affinity (in the nanomolar or picomolar ranges). Aptamers have been selected for targets with varying degrees of complexity, from small molecules to whole cells or tissues. Aptamers have high potential as diagnostic and therapeutic tools, with many advantages when compared with antibodies, including their smaller size-which improves access to biological environments "hidden" from antibodies-their lack of immunogenicity, and the lower cost and higher reproducibility of nucleotide production. In addition, aptamers can be chemically modified to become more stable, labeled with fluorophores or other reporters, and can be easily truncated to eliminate sequences not important for interaction. These valuable properties make aptamers flexible and powerful tools for diagnostic and therapeutic purposes. In this chapter, we plan to focus on graphene-aptamer combinations in order to obtain selective and highly sensitive biosensors for medical and food safety purposes. © 2019 John Wiley & Sons, Inc. All rights reserved.Öğe The role of the clinical pharmacist in supportive care(Nova Science Publishers, Inc., 2021) Aksoy, NilaySupportive care is a multidisciplinary medical field centered around the prevention and treatment of complications and enhancing the quality of life for patients with severe or chronic disease and their families. Supportive care aims to provide appropriate pain and symptom management, to support families and enhance relationships by relieving and sharing their load, and to comprehend the advantages and disadvantages of possible care strategy and assess them in the light of the patient's priorities and values. Pharmacists can lead successfully in supportive care services through ensuring the safe compounding, preparation, and delivery of chemotherapy, by leading educational programs, by boosting and encouraging patients to adhere to chemotherapy and supportive therapy protocols, and by closely evaluating and assessing the prescribed drug to reduce drug-related problems. This chapter describes the comprehensive minutiae of supportive care for chemotherapy-induced nausea and vomiting in addition to summarizing alternative supportive care for alopecia, neutropenia, gastrointestinal toxicity, etc. and emphasizes the significant role of clinical pharmacists in providing this care. © 2021 Nova Science Publishers, Inc. All rights reserved.Öğe Political Music in Turkey: The Birth and Diversification of Dissident and Conformist Music (1920-2000)(Oxford University Press, 2020) Avcı, Mustafa[No abstract available]
