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Article Citation - WoS: 1Citation - Scopus: 1Identifying Risk Factors for Blood Culture Negative Infective Endocarditis: an International Id-Iri Study(Elsevier Sci Ltd, 2024) Filiz, Mine; Erdem, Hakan; Ankarali, Handan; Puca, Edmond; Ruch, Yvon; Santos, Lurdes; Agalar, CananBackground: Blood culture-negative endocarditis (BCNE) is a diagnostic challenge, therefore our objective was to pinpoint high-risk cohorts for BCNE. Methods: The study included adult patients with definite endocarditis. Data were collected via the Infectious Diseases International Research Initiative (ID-IRI). The study analysing one of the largest case series ever reported was conducted across 41 centers in 13 countries. We analysed the database to determine the predictors of BCNE using univariate and logistic regression analyses. Results: Blood cultures were negative in 101 (11.65 %) of 867 patients. We disclosed that as patients age, the likelihood of a negative blood culture significantly decreases (OR 0.975, 95 % CI 0.963-0.987, p < 0.001). Additionally, factors such as rheumatic heart disease (OR 2.036, 95 % CI 0.970-4.276, p = 0.049), aortic stenosis (OR 3.066, 95 % CI 1.564-6.010, p = 0.001), mitral regurgitation (OR 1.693, 95 % CI 1.012-2.833, p = 0.045), and prosthetic valves (OR 2.539, 95 % CI 1.599-4.031, p < 0.001) are associated with higher likelihoods of negative blood cultures. Our model can predict whether a patient falls into the culture-negative or culture-positive groups with a threshold of 0.104 (AUC +/- SE = 0.707 +/- 0.027). The final model demonstrates a sensitivity of 70.3 % and a specificity of 57.0 %. Conclusion: Caution should be exercised when diagnosing endocarditis in patients with concurrent cardiac disorders, particularly in younger cases.Article Citation - WoS: 46Citation - Scopus: 56Marginal and Joint Reliability Importance Based on Survival Signature(Elsevier Sci Ltd, 2018) Eryilmaz, Serkan; Coolen, Frank P. A.; Coolen-Maturi, TahaniMarginal and joint reliability importance measures have been found to be useful in optimal system design. Various importance measures have been defined and studied for a variety of system models. The results in the literature are mostly based on the assumption that the components within the system are independent or identical. The present paper is concerned with computation of marginal and joint reliability importance for a coherent system that consists of multiple types of dependent components. In particular, by utilizing the concept of survival signature, expressions for marginal and joint reliability importance measures are presented. We also introduce reliability importance for a system of which only the survival signature is known, which therefore can be regarded to be a black box system. (C) 2017 Elsevier Ltd. All rights reserved.Article Citation - WoS: 3Citation - Scopus: 4A Simple Method To Set the Spray Properties for Flame Spray Pyrolysis Production of Nanoparticles(Elsevier Sci Ltd, 2020) Alhaleeb, Mustafi A.; Machin, Nesrin E.The most critical part of the flame spray pyrolysis (FSP) process is the nozzle, since it plays a key role in setting the spray properties. In this study, we developed an approach to adjust the nozzle throat gap size for a desired dispersion gas flow rate and upstream pressure, based on the external size and shape of a two phase external mixing nozzle. An equation was derived and validated by comparing the predicted gas flow rates with the data provided in a commercial nozzle supplier chart. Experiments were also conducted in our lab-scale FSP reactor to test the validity of the predictions. The approach developed here was found to closely predict the gap size necessary to pass the required dispersion gas flow at a desired pressure drop. Error in predictions was found to be less than 3% at an upstream pressure range of 3-10 bars. The isentropic flow assumption for perfect gases across the convergent-divergent nozzle was found to fail below 2 bars, consistent with the theory applied. By using the method here, the nozzle setting for a desired operation in an FSP process can be easily done, minimizing the time-consuming trial and error steps needed otherwise.Review Citation - WoS: 45Citation - Scopus: 44Profiling Infectious Diseases in Turkey After the Influx of 3.5 Million Syrian Refugees(Elsevier Sci Ltd, 2020) Ergonul, O.; Tulek, N.; Kayi, I; Irmak, H.; Erdem, O.; Dara, M.Background: Since 2011, the conflict in Syria has led to over five million refugees. Turkey hosts the highest number of Syrian refugees in the world. By February 2019 over 3.6 million people had fled to Turkey to seek safety. Only 6.1% of Syrian refugees live in temporary shelters. Owing to the disrupted healthcare services, many children coming from the conflict zones are less likely to have received vaccination. In temporary shelters immunization coverage is >95% and the refugee population is receptive to vaccination. Aims: The objective of this study was to review the infectious diseases situation among Syrian refugees in Turkey. Sources: We have reviewed the reports and studies provided by the governmental and non-governmental organizations and obtained more detailed data from the Ministry of Health in Turkey. Content: Between 2012 and 2016, 1 299 209 cases of respiratory tract infection and 158 058 episodes of diarrhoea with 59 bloody diarrhoeas were reported; 1354 hepatitis A cases and 108 active tuberculosis cases were detected and treated in the temporary shelters for Syrian refugees. Overall in Turkey, 7794 cutaneous leishmaniasis have been reported. Implications: Since the influx of Syrian refugees, there has been an increase in cases of leishmaniasis and measles. No significant increase was detected for tuberculosis, other vector-borne infections, and healthcare associated or sexually transmitted infections. The Syrian refugees can be considered as a vulnerable group in Turkey due to their living and working conditions. Based on available data and our detailed analysis, the numbers show a stable situation regarding infectious diseases. (C) 2019 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.Correction Characterization of Lead Glazed Potteries From Smyrna (izmir/Turkey) Using Multiple Analytical Techniques; Part I: Glaze and Engobe (vol 40, Pg 2143, 2014)(Elsevier Sci Ltd, 2014) Ozcatal, M.; Yaygingol, M.; Issi, A.; Kara, A.; Turan, S.; Okyar, F.; Minceva-Sukarova, B.[No Abstract Available]Review Citation - WoS: 193Citation - Scopus: 205Stimulus-Responsive Sequential Release Systems for Drug and Gene Delivery(Elsevier Sci Ltd, 2020) Ahmadi, Sepideh; Rabiee, Navid; Bagherzadeh, Mojtaba; Elmi, Faranak; Fatahi, Yousef; Farjadian, Fatemeh; Hamblin, Michael R.In recent years, a range of studies have been conducted with the aim to design and characterize delivery systems that are able to release multiple therapeutic agents in controlled and programmed temporal sequences, or with spatial resolution inside the body. This sequential release occurs in response to different stimuli, including changes in pH, redox potential, enzyme activity, temperature gradients, light irradiation, and by applying external magnetic and electrical fields. Sequential release (SR)-based delivery systems, are often based on a range of different micro- or nanocarriers and may offer a silver bullet in the battle against various diseases, such as cancer. Their distinctive characteristic is the ability to release one or more drugs (or release drugs along with genes) in a controlled sequence at different times or at different sites. This approach can lengthen gene expression periods, reduce the side effects of drugs, enhance the efficacy of drugs, and induce an anti-proliferative effect on cancer cells due to the synergistic effects of genes and drugs. The key objective of this review is to summarize recent progress in SR-based drug/gene delivery systems for cancer and other diseases. (C) 2020 Elsevier Ltd. All rights reserved.Article Citation - WoS: 13Citation - Scopus: 13A Comprehensive Characterization of the Effect of Spatter Powder on In939 Parts Fabricated by Laser Powder Bed Fusion(Elsevier Sci Ltd, 2023) Dogu, Merve Nur; Mussatto, Andre; Yalcin, Mustafa Alp; Ozer, Seren; Davut, Kemal; Obeidi, Muhannad Ahmed; Brabazon, DermotThis study is focused on a comprehensive characterization of virgin and spatter IN939 powders and the effects of a certain amount of spatter powder on the part quality of IN939 fabricated by the L-PBF process. A brown tint coloration formed Al2O3 oxide, pores, a 124.4% increase in the average particle size, a 10.2% decrease in the powder circularity, and a 7.5% decrease in the powder aspect ratio were observed in the spatter powder. Additionally, higher average grain size and lower nanohardness were obtained for the spatter powder. In order to understand the effect of a certain amount of spatter powder on the part quality, 10 wt% spatter powder was mixed with the virgin powder. This addition was found to decrease the flowability of the powder. Moreover, this addition decreased relative density by around 0.3% and increased surface roughness by around 80.8% in the fabricated samples (termed as V and SV). On the other hand, there was no considerable microstructural, texture, microhardness, and nanohardness difference between V and SV samples, although the spatter powder addition caused a 30.2% increase in the average grain size of SV. The overall texture for both V and SV samples exhibit (00 1)//BD.Article Citation - WoS: 2Citation - Scopus: 4Precision Forecasting for Hybrid Energy Systems Using Five Deep Learning Algorithms for Meteorological Parameter Prediction(Elsevier Sci Ltd, 2025) Ceylan, Ceren; Yumurtaci, ZehraThe intermittent nature of renewable energy sources necessitates accurate power production forecasting to ensure system sustainability and balance between energy supply and demand. Although the deep learning-based meteorological forecasting is significantly studied in literature, most of the current literature applies single-algorithm based on each individual energy source and less multi-algorithm based on comparative studies on multiple architectures as applied to integrated hybrid systems. In addition, most of the research uses the same algorithmic solution to all the meteorological parameters without identifying parameter-specific optimization potential, and recent research is verified on actual future time steps instead of historical train-test split. This study presents a comprehensive comparative analysis of five deep learning algorithms, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and CNN-LSTM hybrid, for forecasting critical meteorological parameters (wind speed, ambient temperature, and solar radiation) that determine energy output in a wind and solar-based hybrid energy system (HES). Using five years of Istanbul meteorological data (2018-2022), optimal algorithms were systematically identified for each parameter through rigorous hyperparameter optimization and cross-validation. Key results demonstrate that GRU achieves superior performance in wind speed prediction (RMSE: 0.049 m/s, R2: 0.8634) and solar radiation forecasting (RMSE: 0.146 W/m2, R2: 0.6643), while CNN-LSTM excels in ambient temperature prediction (RMSE: 0.011 degrees C, R2: 0.9976). The integrated approach predicted annual hybrid system energy production with 89 % accuracy, demonstrating 0.48 % deviation from observed values. Most significantly, our framework successfully forecasted sixth year (2023) energy production with 1.55 % error, validating its real-world applicability. This research contributes to the methodological advancement of renewable energy forecasting by systematically identifying optimal algorithmic approaches for different meteorological parameters in hybrid systems, thereby supporting the integration of intermittent renewable sources into sustainable energy infrastructures.Article Citation - WoS: 7Citation - Scopus: 8Elastostatics of star-polygon tile-based architectured planar lattices(Elsevier Sci Ltd, 2023) Soyarslan, Celal; Gleadall, Andrew; Yan, Jiongyi; Argeso, Hakan; Sozumert, EmrahA panoptic view of architectured planar lattices based on star-polygon tilings was developed. Four starpolygon-based lattice sub-families, formed of systematically arranged triangles, squares, or hexagons, were investigated numerically and experimentally. Finite-element-based homogenization allowed computation of Poisson's ratio, elastic modulus, shear modulus, and planar bulk modulus. A comprehensive understanding of the range of properties and micromechanical deformation mechanisms was developed. Adjusting the star-polygon angle achieved an over 250-fold range in elastic modulus, over a 10-fold range in density, and a range of -0.919 to +0.988 for Poisson's ratio. Additively manufactured lattices, achieved by novel printing strategies, showed good agreement in properties. Parametric additive manufacturing procedures for all lattices are available on www.fullcontrol.xyz/#/models/1d3528. Three of the four sub-families exhibited in-plane elastic isotropy. One showed high stiffness with auxeticity at low density and a primarily axial deformation mode as opposed to bending deformation for the other three lattices. The range of achievable properties, demonstrated with property maps, proves the extension of the conventional material-property space. Lattice metamaterials with Triangle-Triangle, Kagome, Hexagonal, Square, Truncated Archimedean, Triangular, and Truncated Hexagonal topologies have been studied in the literature individually. Here, it is shown that these structures belong to the presented overarching lattice family. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Article Evaluation of Clinical Characteristics, Risk Factors and Prognosis of Herpes Zoster (Shingles) Infection in Turkiye: Varicomp-Adult Study(Elsevier Sci Ltd, 2025) Ozgen-Top, Ozge; Karacaer, Zehra; Ozkan, Ece Firuze; Ozger, Hasan Selcuk; Saltoglu, Nese; Oztoprak-Cuvalci, Nefise; Senol, EsinObjective: The study aimed to determine the estimated prevalence of herpes zoster (HZ) infection in the adult population in Turkiye and the rates of HZ-associated complications and risk factors. Methods: This retrospective, multicenter ( n = 11), cross-sectional study was conducted between January 2016 and January 2022 and included all patients aged >= 18 years diagnosed with shingles following screening based on ICD-10 codes. The prevalence of HZ infection was calculated; rates of HZ-related complications (recurrence, hospitalization, postherpetic neuralgia [PHN]) and associated risk factors were determined. Results: A total of 6114 HZ patients were included; the estimated 5-year HZ prevalence in Turkiye was 908.7 per 10 0,0 0 0 population. Of the patients, 851 (14.2%) were immunocompromised, 366 (6%) were hospitalized due to HZ, 284 (8.9%) experienced PHN, 97 (3.2%) experienced recurrence of the patients. Risk factors for PHN were older age ( >= 50 years [OR = 3.19; P < 0.001)], and trigeminal dermatome involvement (OR = 2.45; P = 0.006). Antiviral use was associated with reduced PHN risk (OR = 0.16; P < 0.001). Conclusions: Our multicenter cross-sectional study revealed the high burden of HZ in Turkiye and high-lighted the potential for increasing prevalence due to risk factors including aging and comorbidities. (c) 2025 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
