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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 An advanced mixed finite element formulation for flexural analysis of laminated composite plates incorporating HSDT and transverse stretching effect(Springer, 2025) Kanığ, Doğan; Kutlu, AkifThe modeling and analysis of laminated composite plates are performed using a unified Higher Order Shear Deformation Theory (HSDT) that accounts for transverse stretching effect. The adopted unified HSDT formulation allows the implementation of various shear functions. To derive a weak form from the generalized displacement fields of HSDTs, a variational principle is applied within a two-field mixed approach. The stationarity of the functional for laminated plate structures is obtained through the application of the Hellinger-Reissner variational principle. Hence, displacements and stress resultants, namely two independent fields, are included in finite element equations. Four-noded, quadrilateral elements are employed for the discretization of the plate's domain. While the generated functional initially had C1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$C<^>{1}$$\end{document} continuity, benefiting from the two-fields property of the mixed finite element formulation, integration by parts is performed that results with a functional requiring only C0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$C<^>{0}$$\end{document} continuity. To effectively capture the nonlinear and parabolic variation of transverse shear stress, it is determined that even with varying functions, the results are theoretically consistent with the elasticity method and the employed HSDT model. Also, when compared to the theories that are already accessible in the literature, for the bending behavior of composite plates, incorporating the stretching effect converges the exact results for laminated composite plates more than the studies where that effect is neglected.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 Benzothiophene semiconductor polymer design by machine learning with low exciton binding energy: A vast chemical space generation for new structures(Elsevier Ltd, 2025) Mallah, Shaimaa H.; Güleryüz, Cihat; Sumrra, Sajjad H.; Hassan, Abrar U.; Güleryüz, Hasan; Mohyuddin, Ayesha; Kyhoiesh, Hussein A.K.The development of new organic semiconductors with low exciton binding energies (Eb) is crucial for improving the efficiency of organic photovoltaic (PV) devices. Here, we report the generation of a chemical space of benzothiophene (BDT)-based organic semiconductors with lowest Eb energies using machine learning (ML). Our study involves the design of over 500 organic semiconductor structures with low Eb energies and their synthetic accessibility scores. For this, we collect 1061 BDT based compounds from literature, calculated their Eb energies, and predicted them using ML with Random Forest (RF) regression, yielding the best results. Our analysis, using SHAP values, reveals that heavy atoms are the main factors in lowering Eb values. Furthermore, we tested new organic chromophore structures, which showed an efficient shift of their molecular charges. The UV–Vis spectra of these structures exhibits a redshift in the range of 358–667 nm, while their open-circuit voltage (Voc) and light-harvesting efficiency (LHE) ranges from 1.64 to 1.954 V and 52–91 %, respectively. Current study provides a valuable chemical space for the development of new organic semiconductors with improved efficiency. © 2025 Elsevier LtdÖğe REAL LIFE MANAGEMENT OF ANTIBIOTIC THERAPY IN HSCT RECIPIENTS - FOCUS ON DE-ESCALATION IN PRE-ENGRAFTMENT NEUTROPENIA, THE STUDY FROM THE EBMT INFECTIOUS DISEASES WORKING PARTY (IDWP)(Springernature, 2024) Mikulska, Malgorzata; Wendel, Lotus; Tridello, Gloria; Kulagin, Alexander; Czyz, Anna; Yafour, Nabil; Ciceri, Fabio[No abstract available]Öğe Evaluation of clinical pharmacy services in pediatric nephrology service(Springer, 2021) Gun, Zeynep Ulku; Aksoy, Nilay; Tabel, Yilmaz; Sancar, Mesut[No abstract available]Öğe Effect of dose dependent organophosphate compound on interleukin-6 and insulin receptor substrate-1 levels in rat liver(Wiley, 2021) Ekremoglu, M.; Gomleksiz, O. Kurnaz; Eren, Z.; Severcan, C.; Pasaoglu, O. T.; Pasaoglu, H.[No abstract available]Öğe Inflammatory rheumatic diseases developed after COVID-19 vaccination: presentation of a case series and review of the literature(Verduci Publisher, 2023) Akkuzu, G.; Bes, C.; Ozgur, D. S.; Karaaliolu, B.; Mutlu, M. Y.; Yildirim, F.; Atagunduz, P.OBJECTIVE: An increasing number of new on-set autoimmune-inflammatory rheumatic diseases (AIRD) after COVID-19 vaccination has begun to be reported in the literature. In this article, we present our patients with new-onset AIRD after vaccination for COVID-19 and review the literature on the subject. PATIENTS AND METHODS: We investigated the clinical characteristics and laboratory parameters of previously described newly developed AIRD in individuals recently vaccinated for COVID-19, in 22 cases vaccinated with one of the COVID-19 vaccines (BNT162b2 or CoronaVac) approved in our country. RESULTS: We collected 22 cases (14 female, 63.6%) that developed an AIRD after COVID-19 vaccination. Mean age was 53 +/- 14.4 (24-87) years. The interval between the last dose of vaccination and the development of the first complaint was 23.9 +/- 19.5 (4-90) days. CoronaVac was administered to four patients, and the BNT162b2 to 18 patients. AIRD-related symptoms developed in 12 patients after the first dose, in 8 patients after the second dose, and in two patients after the third dose. Twelve out of the 22 (54.5%) cases were diagnosed with rheumatoid arthritis, two with SLE, and the remaining eight patients each with leukocytoclastic vasculitis, Sjogren's syndrome, psoriatic arthritis, ankylosing spondylitis, systemic sclerosis, mixed connective tissue disease, eosinophilic granulomatosis with polyangiitis, and inflammatory myositis, respectively. Six patients had a history of documented antecedent COVID-19 infection. CONCLUSIONS: Autoimmune/inflammatory rheumatic diseases may develop after COVID-19 vaccinations. In the era of the COVID-19 pandemic, vaccination should be questioned carefully in newly diagnosed AIRD patients.Öğe Forecasting of Twitter Hashtahg Temporal Dynamics Using Locally Weighted Projection Regression(IEEE, 2017) Alsaadi, Husam Ibrahiem; Almajmaie, Layth Kamil; Mahmood, Wisam AliPopularity of social networks opens great opportunities for market such as advertisement. Using hashtags increasingly used in twits helps us to realize popular topics on the internet. Since most of new hashtags become popular and then fade away quickly, there is a limited time to predict the trend. Therefore, this paper proposes a fast incremental method to forecast the rate of the used hashtags in hour like time series. Two main parts for forecasting system are applied Preprocessing and Supervised Learning. Normalization is one of most popular preprocessing of dataset also proposed to have larger dataset. Moreover, the efficiency of the system under changing number of input (number of past hours from hashtag history) and output (number of next hours which is going to be predicted) are evaluated. Locally Weighted Projection Regression as one of the most powerful machine learning methods with no meta-parameter are applied in this paper as real-time learning method. The performance of the system is verified by implementation of Volume Time Series of Memetracker Phrases and Twitter Hashtags. The results show that the errors of forecasting system are good enough to understand the trend of the hashtag.Öğe Relationship between serum vitamin D levels semen parameters and sperm DNA damage in men with unexplained infertility(Verduci Publisher, 2022) Gungor, K.; Gungor, N. D.; Basar, M. M.; Cengiz, F.; Ersahin, S. S.; Cil, K.OBJECTIVE: The aim of the study was to investigate the relationship between serum level of vitamin D, semen analysis parameters and sperm DNA damage in men with unexplained subfertility. PATIENTS AND METHODS: Fifty-eight men diagnosed with unexplained infertility and 50 age and BMI matched fertile men were included in the study. A participant whose semen parameter is normal but pregnancy is not achieved was accepted as unexplained male infertility. Blood samples were taken from all participants following three-day abstinence for measurement of vitamin D. Sperm DNA damage was assessed by Aniline Blue staining of the collected samples. RESULTS: Compared with the fertile men, male patients with unexplained infertility had significantly lower vit D levels (27.00 ng/mL (12.6339.3 0) vs. 23.66 ng/mL (7.50-55.00), p<0.004). While the number of patients with vitamin D levels lower than 20 ng/mL was 26 (44.8%) in the infertile group, it was recorded as 5 (10.0%) in the fertile group (p<0.001). DNA damage was found in 31.50% (9.0-71.0) of the infertile men and 26.00% (11.0-54.0) of the fertile men. DNA damage was found to be significantly higher in the unexplained infertile group (p<0.002). In men with unexplained male infertility, serum vit D levels were positively correlated with total sperm count (r = 0.527, p<0.001), total motility (r = 0.527, p<0.001) and sperm morphology (r = 0.416, p = 0.001). There was a negative and significant correlation between vit D levels and sperm DNA damage (r =-0.605, p<0.001). In the logistic regression analysis, serum vit D > 20 ng/mL led to an improvement in fertility outcome. CONCLUSIONS: Men with unexplained infertility exhibit decreased serum vit D levels and increased sperm DNA damage.Öğe BRAF V600E mutation: a significant biomarker for prediction of disease in paediatric Langerhans cell histiocytosis(Springer, 2019) Ozer, E.; Sevinc, A.; Ince, D.; Yuzuguldu, R.; Olgun, N.[No abstract available]Öğe Opportunities and Risks in Higher Education in the Postpandemic Period(Tuba-Turkish Acad Sciences, 2020) Erhan, Cagri; Gumus, SenayIn the first half of the 2020, we all have witnessed the measures taken to stop the spread of the novel Coronavirus which causes the COVID-19 disease and slow down the pandemic in almost the whole world. One of the most significant measures which was taken to prevent gatherings in public spaces is to stop in person education altogether and move education into digital platforms. On the other hand, in the second half of the 2020, we expect to observe a controlled normalization process until a vaccine is found. Considering that until a vaccine is found, the pandemic will keep affecting people and it will take time to turn back into regular social life, higher education institutions are also expected to adopt into this controlled social life which will last a while longer and keep increasing its educational and scientific activities in this environment. Although, it is still not certain how the higher education institutions will take shape and take its place in the new normal, it is possible to say that there are many risks and opportunities waiting for the higher education institutions. While developments in distance and digital learning may be considered as a big opportunity for the universities, travel restrictions, economic stagnation, problems faced in distance learning and obstacles which was encountered in the internationalization process of higher education may be considered as ominously awaiting risks for the higher education institutions.Öğe ENHANCING PREDICTIVE PERFORMANCE IN COVID-19 HEALTHCARE DATASETS: A CASE STUDY BASED ON HYPER ADASYN OVER-SAMPLING AND GENETIC FEATURE SELECTION(Taylors Univ Sdn Bhd, 2024) Mohammedqasim, Hayder; Jasim, Abdulrahman Ahmed; Mohammedqasem, Roa'a; Ata, OguzPredictive analytics is paramount in the health industry, where it finds its wide application, in that it helps increase the forecast's accuracy level based on big data. Most of the time, there is a tendency toward the imbalance of the datasets in healthcare. In this study, two COVID-19 datasets from Kaggle were used as a case study of dataset imbalance. In such scenarios of imbalanced datasets like COVID-19, conventional sampling methods like ADASYN (Adaptive Synthetic Sampling Approach for Imbalanced Learning) tend to yield only modest accuracy levels. To address another problem like finding the optimal features, this study proposes a novel approach that combines oversampling techniques with genetic feature selection (GFs) using laboratory data. This innovative method aims to construct machine -learning clinical prediction models for the identification of COVID-19 infected patients, leveraging two widely recognized datasets by using hyper ADASYN over -sampling and genetic feature selection, stands out for its unprecedented precision in identifying relevant features crucial for accurate predictions. Unlike the traditional approach, it can solve the class imbalance problem and tune the feature space to bring about a dramatic increase in accuracy, precision, recall, and overall predictive performance by using our hypermodel. Our approach significantly enhanced the performance of the classifier, and the Random Forest (RF) model with n trees classifies accurately to the limit of 99%, with precision 99%, recall 99%, and F1 -score 99% for each of the datasets. Decision Tree (DT) model achieved 92% with all metrics for Dataset I, and 95% with all metrics for Dataset II. Multilayer Perceptron (MLP) achieved 99% with all metrics, respectively, for both datasets. Gradient Boosting (XGB) achieved 97% for all metrics with dataset I and 98% with all metrics for dataset II. These results underscore the efficacy of our proposed method in balancing COVID-19 datasets and enhancing predictive accuracy.Öğe Successful kidney transplantation in case of completely occluded inferior vena cava and iliac veins: a case of inherited antithrombin deficiency(Asoc Regional Dialisis Trasplantes Renales, 2021) Tekin, Sabri; Erok, Berrin; Win, Nu Nu; Agolli, Elidor; Ucak, Alper; Akyol, Huseyin; el Mounjali, AssiyaProduced in the liver, Antithrombin III, now simply antithrombin (AT), is a vitamin K-independent serine protease inhibitor in the coagulation pathway. It is the most important primary physiologic inhibitor of thrombin in the human body. In addition to thrombin, AT also inhibits other coagulation serine proteases including VIIa, IXa, Xa, XIa, XIIa. (1-2) The deficiency of AT may be inherited or acquired. The incidence of inherited AT deficiency is about 1:2000-5000 in general population and is the least common of the three main anticoagulant deficiencies (the other two being protein C deficiency and protein S deficiency). (3) Its inheritance is generally in autosomal dominant fashion. The resultant procoagulant state leads to unprovoked recurrent venous thromboses and thromboembolic events such as deep vein thrombosis or pulmonary embolism which generally appear at the post-pubertal period, compared to the very low occurrence in the prepubertal period.(4) The diagnosis is based on both quantitative and qualitative measurement of AT level.(5) The measured AT activity in functional tests in healthy subjects is generally around 80% to 120%, and AT level of less than 70% is considered as being AT deficiency. This evaluation should be made while not on anticoagulation therapy, because heparin decreases AT levels for up to 10 days following its discontinuation and warfarin increases its level. (6) Patients with inherited AT deficiency rarely develops renal failure which may be caused by renal vein thrombosis or glomerular injury associated with fibrin accumulation. (7) In these young patients with end stage renal disease (ESRD), renal transplantation is currently the best therapeutic option to improve the quality of life and to avoid the risk of complications of other renal replacement treatment particularly thrombosis of the hemodialysis access. Kidney transplantation in patients with an occluded iliac veins and inferior vena cava (IVC) is a very challenging surgery to perform.(8-9) Despite the reported success in few cases for children, kidney transplant surgeries with thrombotic diseases in adults remain very limited in the literature. Herein, we present a successful kidney transplantation by using a polytetrafluoroethylene (PTFE) graft in a young male patient with AT deficiency associated with totally occluded IVC and iliac veins.Öğe The Effect of Astrocyte-Derived Fatty Acid-Binding Protein 7 on Blood-Brain Barrier Integrity in LPS-Induced Inflammation(Wiley, 2023) Altunsu, Deniz; Temizyurek, Arzu; Ayvaz, Ecem; Kaya, Mehmet; Ahishali, Bulent[No abstract available]Öğe Management of medication adherence across ENABLE COST countries: a pilot study(Springer, 2022) Mucherino, Sara; Aarnio, Emma; Hafez, Gaye; Kamusheva, Maria; Leiva-Fernandez, Francisca; Mihajlovic, Jovan; Qvarnstrom, Miriam[No abstract available]Öğe DEVELOPMENT AND VERIFICATION OF A DIGITAL TWIN PATIENT MODEL TO PREDICT TREATMENT RESPONSE IN SEPSIS(Lippincott Williams & Wilkins, 2021) Lal, Amos; Li, Guangxi; Cubro, Edin; Chalmers, Sarah; Li, Heyi; Herasevich, Vitaly; Dong, Yue[No abstract available]Öğe PAN-EUROPEAN STUDY ON THE MANAGEMENT OF MEDICATION ADHERENCE: A STUDY PROTOCOL BY COST ACTION 'ENABLE' WORKING GROUP 1(Elsevier Science Inc, 2022) Mihajlovic, J.; Mucherino, S.; Aarnio, E. J.; Hafez, G.; Kamusheva, M.; Leiva-Fernandez, F.; Qvarnstrom, M.[No abstract available]
