Browsing by Author "Gunal, Aysel Caglan"

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    Effect of Polynomial, Radial Basis, and Pearson VII Function Kernels in Support Vector Machine Algorithm for Classification of Crayfish
    (2022) Garabaghi, Farid Hassanbaki; Benzer, Recep; Benzer, Semra; Gunal, Aysel Caglan; 0000-0002-5339-0554; A-5050-2014
    Freshwater crayfish are one of the most important aquatic organisms that play a pivotal role in the aquatic food chain as well as serving as bioindicators for the aquatic ecosystem health assessment. Hemocytes, the blood cells of crustaceans, can be considered stress and health indicators in crayfish, and are used to evaluate the health response. Therefore, total hemocyte cell numbers (THCs) are useful parameters to show the health of crustaceans and serve as stress indicators to decide the quality of the habitat. Since, catching the fish and the other aquatic organisms, and collecting the data for further assessments are time-consuming and frustrating, today, scientists tend to use swift, more sophisticated, and more reliable methods for modeling the ecosystem stressors based on bioindicators. One tool which has attracted the attention of science communities in the last decades is machine learning algorithms that are reliable and accurate methods to solve classification and regression problems. In this study, a support vector machine is carried out as a machine learning algorithm to classify healthy and unhealthy crayfish based on physiological characteristics. To solve the non-linearity problem of the data by transporting data to high-dimensional space, different kernel functions including polynomial (PK), Pearson VII function-based universal (PUK), and radial basis function (RBF) kernels are used and their effect on the performance of the SVM model was evaluated. Both PK and PUK functions performed well in classifying the crayfish. RBF, however, had an adverse impact on the performance of the model. PUK kernel exhibited an outstanding performance (Accu-racy = 100%) for the classification of the healthy and unhealthy crayfish.
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    The Cerium Oxide Nanoparticles Toxicity Induced Physiological, Histological And Biochemical Alterations In Freshwater Mussels, Unio Crassus
    (JOURNAL OF TRACE ELEMENTS IN MEDICINE AND BIOLOGY, 2024-02-13) Turkmen, Ezgi Uluer; Arslan, Pinar; Erkoc, Figen; Gunal, Aysel Caglan; Duran, Hatice
    Introduction: Releasing of cerium oxide nanoparticles (nano-CeO2) to the nature has increased due to the widespread use in many fields ranging from cosmetics to the food industry. Therefore, nano-CeO2 has been included in the Organization for Economic Co-operation and Development's (OECD) priority list for engineering nanomaterials. In this study, the effects of nano-CeO2 on the freshwater mussels were investigated to reveal the impact on the freshwater systems on model organism. Methods: First, the chemical and structural properties of nano-CeO2 were characterized in details. Second, the freshwater mussels were exposed to environmentally relevant concentrations of nano-CeO2 as 10 mg, 25 mg and 50 mg/L during 48-h and 7-d. Third, after the exposure periods, hemolymph and tissue samples were taken to analyse the Total Hemocyte Counts (THCs) histology and oxidative stress parameters (total antioxidant status, glutathione, glutathione-S-transferase, and advanced oxidative protein products). Results: Significant decrease of the THCs was observed in the nano-CeO2 exposed mussels compared to the control group (P < 0.05). The histological results showed a positive association between nano-CeO2 exposure concentration in the water and level of tissue damage and histopathological alterations were detected in the gill and the digestive gland tissues. Oxidative stress parameters were slightly affected after exposure to nano-CeO2 (P > 0.05). In conclusion, this study showed that acute exposure of freshwater mussels to nano-CeO2 did not pose significant biological risk. However, it has been proven that mussels are able to accumulate nano-CeO2 significantly in their bodies. Conclusion: This suggests that nano-CeO2 may be a potential risk to other organisms in the ecosystem through trophic transfer in the food-web based on their habitat and niche in the ecosystem.