Neonicotinoid Analysis in Sunflower (Helianthus annuus) Honey Samples Collected around Tekirdag in Turkey

In recent years, the widespread use of neonicotinoids in agricultural areas has caused environmental pollution due to its lower toxicity to mammals. Honey bees, which are considered as biological indicators of environmental pollution, can carry these pollutants to the hives. Forager bees returning from sunflower crops that have been treated with neonicotinoids treated sunflower fields cause residue accumulation in the hives, which reason colony-level adverse effects. This study analyses neonicotinoid residues in sunflower (Helianthus annuus) honey sampled by beekeepers from Tekirdag province. Honey samples have been subjected to liquid-liquid extraction methods before liquid chromatography-mass spectrometry (LC-MS/MS). The method validation was carried out to fulfill all the necessary requirements of procedures SANCO/12571/2013. Accuracy was in the range of 93.63-108.56%, for recovery in the range of 63.04-103.19%, and for precision in the range 6.03-12.77%. Detection and quantification limits were determined according to the maximum residue limits of each analyte. No neonicotinoid residues were found above the maximum residue limit in the sunflower honey samples analysed.Scientific Research Project Coordination Unit of Tekirdag Namik Kemal University [NKUBAP.00.23, AR.14.05]AcknowledgmentsThis work was supported by the Scientific Research Project Coordination Unit of Tekirdag Namik Kemal University, Tekirdag (project number: NKUBAP.00.23.AR.14.05)

A Feed-Forward Neural Network Approach to Istanbul Stock Exchange

In this study the trend estimation of the participation indices (PARTI) in the Istanbul Stock Exchange (BIST) using artificial neural network (ANN) theory. PARTI can be regarded as the Participation 50 Index (KAT50) and the Participation 30 Index (KATLM). Since KAT50 has only been calculated since 9th July 2014, there are only a few studies on this index. On the other hand, PARTI indices are growing more and more important in global economies, especially in Turkey, England, etc. Therefore, in this study, firstly, we have used ANN method, using 1410 daily closing values of KATLM, between 1st August 2012 and 30th June 2016. For the KAT50 index, we used 720 daily closing values between 9th July 2014 and 29th July 2016. We created a feed-forward back-propagation neural network model in order to predict the trends of these indices and we applied the previously mentioned daily closing values of these participation indices to this model. The results obtained using the ANN method are compared in the figures and tables. It can be concluded that the results of this study are very helpful for individual and institutional investors’ investment decisions within global economies

YÜKSEK SICAKLIK YAKIT PİLLERİ İÇİN DÜŞÜK ASİT KAYIPLI PBI ÇAPRAZ BAĞLI MEMBRANLARIN HAZIRLANMASI VE KARAKTERİZASYONU

YÜKSEK SICAKLIK YAKIT PİLLERİ İÇİN DÜŞÜK ASİT KAYIPLI PBI ÇAPRAZ BAĞLI MEMBRANLARIN HAZIRLANMASI VE KARAKTERİZASYON

FEN BİLİMLERİ ENSTİTÜSÜ/LİSANSÜSTÜ TEZ PROJESİ

YÜKSEK SICAKLIK YAKIT PİLLERİ İÇİN DÜŞÜK ASİT KAYIPLI PBI KOMPOZİT MEMBRANLARIN HAZIRLANMASI VE KARAKTERİZASYON

On the Solutions of Fractional Cauchy Problem Featuring Conformable Derivative

In this study, we have obtained analytical solutions of fractional Cauchy problem by using q-Homotopy Analysis Method (q-HAM) featuring conformable derivative. We have considered different situations according to the homogeneity and linearity of the fractional Cauchy differential equation. A detailed analysis of the results obtained in the study has been reported. According to the results, we have found out that our obtained solutions approach very speedily to the exact solutions

New Fractional Cancer Mathematical Model via IL-10 Cytokine and Anti-PD-L1 Inhibitor

In this study, we explore a recent biological model created to analyze the behavior of cancer cells by administering a dose of a drug containing anti-PD-L1 and IL-10 with the Caputo and Atangana–Baleanu derivative in the Caputo sense (ABC). Using the Caputo derivative in order to examine the stability of the non-linear system, we are able to demonstrate that it is existent and unique, and to introduce several numeric data obtained for the fractional values in MATLAB by using the Adams–Bashforth–Moulton (ABM) method. Additionally, by using the predictor–corrector approach, the numerical results from the system with ABC derivative will be produced. As a result, it has been observed that immune system cells that are exposed to single-dose drug with fractional order effectively combat cancer cells. The tumor cells decrease by 70.44% and 80.16% for the system generalized by the Caputo and ABC derivative, respectively, for the order α=0.42

European Vanilla Option Pricing Model of Fractional Order without Singular Kernel

Recently, fractional differential equations (FDEs) have attracted much more attention in modeling real-life problems. Since most FDEs do not have exact solutions, numerical solution methods are used commonly. Therefore, in this study, we have demonstrated a novel approximate-analytical solution method, which is called the Laplace homotopy analysis method (LHAM) using the Caputo–Fabrizio (CF) fractional derivative operator. The recommended method is obtained by combining Laplace transform (LT) and the homotopy analysis method (HAM). We have used the fractional operator suggested by Caputo and Fabrizio in 2015 based on the exponential kernel. We have considered the LHAM with this derivative in order to obtain the solutions of the fractional Black–Scholes equations (FBSEs) with the initial conditions. In addition to this, the convergence and stability analysis of the model have been constructed. According to the results of this study, it can be concluded that the LHAM in the sense of the CF fractional derivative is an effective and accurate method, which is computable in the series easily in a short time

Mathematical modelling and optimization of engineering problems

This book presents recent developments in modelling and optimization of engineering systems and the use of advanced mathematical methods for solving complex real-world problems. It provides recent theoretical developments and new techniques based on control, optimization theory, mathematical modeling and fractional calculus that can be used to model and understand complex behavior in natural phenomena including latest technologies such as additive manufacturing. Specific topics covered in detail include combinatorial optimization, flow and heat transfer, mathematical modelling, energy storage and management policy, artificial intelligence, optimal control, modelling and optimization of manufacturing systems. Presents new approaches to design and optimize emerging manufacturing systems Examines the similarities between design and optimization processes Explains metaheuristics applied to complex engineering problems Features sections on optimization in the energy storage and generation and optimal control in economics and operational research