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Book Part Citation - Scopus: 2Trace Element Containing Nano-HAp for Preventing Musculoskeletal Infections(Springer Science and Business Media B.V., 2021) Gizer,M.; Boyacıoğlu,Ö.; Korkusuz,P.; Korkusuz,F.Musculoskeletal infections are difficult to diagnose and rapidly reach the chronic phase that is difficult to treat. Osteomyelitis and septic arthritis are inflammatory musculoskeletal diseases and their recovery should contain bone or joint regeneration approaches. Nanometer-sized hydroxyapatite is the main inorganic component of the bone tissue that resembles its extracellular matrix. Nanometer-sized hydroxyapatite composite is also an efficient carrier for various regenerative molecules and medicine. Trace elements on the other hand enhance bone formation, mineralization and have antibacterial properties. Bioactivity, biocompatibility, and antibacterial properties of nanometer-sized hydroxyapatite can be gained and improved with trace elements such as zinc, boron, magnesium, strontium, and molybdenum. This chapter summarizes studies on the effects of zinc, boron, magnesium, strontium, and/or molybdenum-doped nanometer-sized hydroxyapatite that can be used to treat musculoskeletal infections. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.Article Citation - WoS: 45Citation - Scopus: 45An Ambipolar Low Band Gap Material Based on Bodipy and Edot(Elsevier Science Bv, 2009) Algi, Fatih; Cihaner, AtillaA novel donor-acceptor type conducting polymer based on BODIPY dye as acceptor and EDOT units as donor parts is synthesized electrochemically. The unique combination of BODIPY and EDOT units provides an ambipolar (n- and p-doping processes) low band gap material (4). This is the first example of p-n junction in an organic pi-conjugated material where BODIPY unit is incorporated directly in the main chain. Furthermore, the polymer film exhibits electrochromic behavior upon p-doping: a color change from light violet (neutral) to indigo (oxidized). (C) 2009 Elsevier B.V. All rights reserved.Book Part Citation - Scopus: 1Community Development, Frustration and Overtourism(Emerald Group Publishing Ltd., 2021) Koç,B.; Küçükergin,K.G.Tourism and community development are two complementary variables. There are many studies in the literature examining the effects of tourism on society. However, the number of studies focussing on the subject from the perspective of overtourism is still very limited. Although a shrinking in tourism demand is estimated for the next few years due to Covid-19, it is expected that the sector will face an even more intense tourist boom around the world after this health crisis. Therefore, the phenomenon of overtourism remains important. In this context, a conceptual examination was made in the current chapter regarding the observed and possible effects of tourism density on communities. The existing literature clearly shows that being successful in the long term is impossible with a tourism plan that uses natural resources, infrastructure facilities and traditional values of the region to create tourist demand but ignores the wishes and well-being of the community residents. © 2021 by Emerald Publishing Limited.Article Citation - WoS: 47Citation - Scopus: 67Deep Learning Based Fall Detection Using Smartwatches for Healthcare Applications(Elsevier Sci Ltd, 2022) Sengul, Gokhan; Karakaya, Murat; Misra, Sanjay; Abayomi-Alli, Olusola O.; Damasevicius, RobertasWe implement a smart watch-based system to predict fall detection. We differentiate fall detection from four common daily activities: sitting, squatting, running, and walking. Moreover, we separate falling into falling from a chair and falling from a standing position. We develop a mobile application that collects the acceleration and gyroscope sensor data and transfers them to the cloud. In the cloud, we implement a deep learning algorithm to classify the activity according to the given classes. To increase the number of data samples available for training, we use the Bica cubic Hermite interpolation, which allows us to improve the accuracy of the neural network. The 38 statistical data features were calculated using the rolling update approach and used as input to the classifier. For activity classification, we have adopted the bi-directional long short-term memory (BiLSTM) neural network. The results demonstrate that our system can detect falling with an accuracy of 99.59% (using leave-one-activityout cross-validation) and 97.35% (using leave-one-subject-out cross-validation) considering all activities. When considering only binary classification (falling vs. all other activities), perfect accuracy is achieved.Article Citation - WoS: 1Citation - Scopus: 2Parametric Sensitivity Analysis and Performance Evaluation of High-Temperature Macro-Encapsulated Packed-Bed Latent Heat Storage System Operating With Transient Inlet Boundary Conditions(Mdpi, 2022) Mehrtash, Mehdi; Tari, IlkerThis paper presents the results of comprehensive numerical analyses in the performance of a packed-bed latent heat storage (PBLHS) system in terms of key performance indicators, namely charging time, charging rate, charging capacity, and charging efficiency. Numerical simulations are performed for the packed bed region using a transient two-dimensional axisymmetric model based on the local thermal non-equilibrium (LTNE) approach. The model considers the variation in the inlet temperature of the system as these storage systems are typically integrated with solar collectors that operate with intermittent solar radiation intensity. The model results are validated using the experimental data for temperature distribution throughout the bed. The simulations are carried out while changing the operating parameters such as the capsule diameter, bed porosity, inlet velocity, and the height-to-diameter aspect ratio to investigate their impact on the performance indicators. Observations indicate that low porosity, large-sized capsules, low inlet velocity, and a low height-to-diameter aspect ratio increase the charging time. In terms of achieving a high charging rate, a bed with low porosity, small-sized capsules, a high inflow velocity, and a high height-to-diameter aspect ratio is deemed advantageous. It is shown that raising the flow velocity and the height-to-diameter aspect ratio can improve the charging efficiency. These findings provide recommendations for optimizing the design and operating conditions of the system within the practical constraints.Article Citation - Scopus: 2Symbolic polynomial interpolation using mathematica(Springer Verlag, 2004) Yazici,A.; Altas,I.; Ergenc,T.This paper discusses teaching polynomial interpolation with the help of Mathematica. The symbolic power of Mathematica is utilized to prove a theorem for the error term in Lagrange interpolating formula. Derivation of the Lagrange formula is provided symbolically and numerically. Runge phenomenon is also illustrated. A simple and efficient symbolic derivation of cubic splines is also provided. © Springer-Verlag Berlin Heidelberg 2004.Article Citation - WoS: 2Citation - Scopus: 1Comparison of the Performance of Structural Break Tests in Stationary and Nonstationary Series: a New Bootstrap Algorithm(Springer, 2024) Camalan, Ozge; Hasdemir, Esra; Omay, Tolga; Kucuker, Mustafa CanStructural breaks are considered as permanent changes in the series mainly because of shocks, policy changes, and global crises. Hence, making estimations by ignoring the presence of structural breaks may cause the biased parameter value. In this context, it is vital to identify the presence of the structural breaks and the break dates in the series to prevent misleading results. Accordingly, the first aim of this study is to compare the performance of unit root with structural break tests allowing a single break and multiple structural breaks. For this purpose, firstly, a Monte Carlo simulation study has been conducted through using a generated homoscedastic and stationary series in different sample sizes to evaluate the performances of these tests. As a result of the simulation study, Zivot and Andrews (J Bus Econ Stat 20(1):25-44, 1992) are the best-performing tests in capturing a single break. The most powerful tests for the multiple break setting are those developed by Kapetanios (J Time Ser Anal 26(1):123-133, 2005) and Perron (Palgrave Handb Econom 1:278-352, 2006). A new Bootstrap algorithm has been proposed along with the study's primary aim. This newly proposed Bootstrap algorithm calculates the optimal number of statistically significant structural breaks under more general assumptions. Therefore, it guarantees finding an accurate number of optimal breaks in real-world data. In the empirical part, structural breaks in the real interest rate data of the US and Australia resulting from policy changes have been examined. The results concluded that the bootstrap sequential break test is the best-performing approach due to the general assumption made to cover real-world data.Article Citation - WoS: 14Citation - Scopus: 25On Coupled Fixed Point Theorems on Partially Ordered g-metric Spaces(Springeropen, 2012) Karapinar, Erdal; Kaymakcalan, Billur; Tas, KenanIn this manuscript, we extend, generalize and enrich some recent coupled fixed point theorems in the framework of partially ordered G-metric spaces in a way that is essentially more natural.Article Citation - WoS: 5Citation - Scopus: 6A Novel Deep Learning-Based Framework With Particle Swarm Optimisation for Intrusion Detection in Computer Networks(Public Library Science, 2025) Yilmaz, Abdullah AsimIntrusion detection plays a significant role in the provision of information security. The most critical element is the ability to precisely identify different types of intrusions into the network. However, the detection of intrusions poses a important challenge, as many new types of intrusion are now generated by cyber-attackers every day. A robust system is still elusive, despite the various strategies that have been proposed in recent years. Hence, a novel deep-learning-based architecture for detecting intrusions into a computer network is proposed in this paper. The aim is to construct a hybrid system that enhances the efficiency and accuracy of intrusion detection. The main contribution of our work is a novel deep learning-based hybrid architecture in which PSO is used for hyperparameter optimisation and three well-known pre-trained network models are combined in an optimised way. The suggested method involves six key stages: data gathering, pre-processing, deep neural network (DNN) architecture design, optimisation of hyperparameters, training, and evaluation of the trained DNN. To verify the superiority of the suggested method over alternative state-of-the-art schemes, it was evaluated on the KDDCUP'99, NSL-KDD and UNSW-NB15 datasets. Our empirical findings show that the proposed model successfully and correctly classifies different types of attacks with 82.44%, 90.42% and 93.55% accuracy values obtained on UNSW-B15, NSL-KDD and KDDCUP'99 datasets, respectively, and outperforms alternative schemes in the literature.Article Citation - WoS: 4Citation - Scopus: 4The Effect of Cerium Oxide (ceo2) on Ischemia-Reperfusion Injury in Skeletal Muscle in Mice With Streptozocin-Induced Diabetes(Mdpi, 2024) Ozer, Abdullah; Sengel, Necmiye; Kucuk, Ayseguel; Yigman, Zeynep; Ozdemir, Cagri; Kilic, Yigit; Arslan, MustafaObjective: Lower extremity ischemia-reperfusion injury (IRI) may occur with trauma-related vascular injury and various vascular diseases, during the use of a tourniquet, in temporary clamping of the aorta in aortic surgery, or following acute or bilateral acute femoral artery occlusion. Mitochondrial dysfunction and increased basal oxidative stress in diabetes may cause an increase in the effects of increased reactive oxygen species (ROS) and mitochondrial dysfunction due to IRI. It is of great importance to examine therapeutic approaches that can minimize the effects of IRI, especially for patient groups under chronic oxidative stress such as DM. Cerium oxide (CeO2) nanoparticles mimic antioxidant enzymes and act as a catalyst that scavenges ROS. In this study, it was aimed to investigate whether CeO2 has protective effects on skeletal muscles in lower extremity IRI in mice with streptozocin-induced diabetes. Methods: A total of 38 Swiss albino mice were divided into six groups as follows: control group (group C, n = 6), diabetes group (group D, n = 8), diabetes-CeO2 (group DCO, n = 8), diabetes-ischemia/reperfusion (group DIR, n = 8), and diabetes-ischemia/reperfusion-CeO2 (group DIRCO, n = 8). The DCO and DIRCO groups were given doses of CeO2 of 0.5 mg/kg intraperitoneally 30 min before the IR procedure. A 120 min ischemia-120 min reperfusion period with 100% O-2 was performed. At the end of the reperfusion period, muscle tissues were removed for histopathological and biochemical examinations. Results: Total antioxidant status (TAS) levels were found to be significantly lower in group DIR compared with group D (p = 0.047 and p = 0.022, respectively). In group DIRCO, total oxidant status (TOS) levels were found to be significantly higher than in group DIR (p < 0.001). The oxidative stress index (OSI) was found to be significantly lower in group DIR compared with group DCO (p < 0.001). Paraoxanase (PON) enzyme activity was found to be significantly increased in group DIR compared with group DCO (p < 0.001). The disorganization and degeneration score for muscle cells, inflammatory cell infiltration score, and total injury score in group DIRCO were found to be significantly lower than in group DIR (p = 0.002, p = 0.034, and p = 0.001, respectively). Conclusions: Our results confirm that CeO2, with its antioxidative properties, reduces skeletal muscle damage in lower extremity IRI in diabetic mice.
