THE EFFECTS OF PESTICIDES IN WATER RESOURCES

Environmental pollution is concerned problem all around world due to rapid increase of industrialization and urbanization. Especially, the intensive pesticide use has caused some environmental problems in many countries. The major problem occurred in water resources. Therefore, these resources need to be protected from the contamination of pesticides for future sustainable use

GENESIS AND CLASSIFICATION OF INCEPTISOLS FORMED ON THE SLATE PARENT MATERIAL UNDER FOREST VEGETATION

Inceptisols are most extensive soils in this region. These soils are under forest vegetation. Ten soil profiles were selected in this research. The some important physical, chemical and morphological properties were investigated and classified according to USDA Soil Taxonomy

SOME IMPORTANT PROPERTIES AND CLASSIFICATION OF MOLLISOLS IN NORTHWESTERN TURKEY

Mollisols have developed under xeric moisture and thermic temperature regimes in northwestern Turkey. Six soil profiles were studied in this research. The morphological, physical and chemical properties of the soils were investigated and classified according to USDA Soil Taxonomy. The examined soils were showed some variations in their morphological, physical and chemical properties as a result of differences in mean annual precipitation, parent material, topography and vegetation

CHARACTERIZATION OF SOME IMPORTANT AGRICULTURAL SOILS UNDER OLIVE TREES

Olive production is important and intensive agricultural activity in this region. Generally, olive trees occur coastal side of the region under brown forest soils. Ten olive tree plantations were selected in this research. The some important physical, chemical and morphological properties were investigated and classifi ed according to USDA Soil Taxonomy as Typic Xerochrepts

Measurement and Analysis of In Vivo Microwave Dielectric Properties Collected From Normal, Benign, and Malignant Rat Breast Tissues: Classification Using Supervised Machine Learning Algorithms

This work presents large-scale measurements of in vivo rat breast tissue dielectric properties (DPs) from 0.5 to 6 GHz and classifies the collected data using supervised machine learning (ML) algorithms. The main goals of this work are, first, to report in vivo animal tissue DPs for microwave medical device development and, second, to demonstrate that microwave devices can be utilized for diagnostics. To this end, we separated 18 Sprague-Dawley female rats into control and experimental groups. The experimental group was subjected to chemically induced breast cancer, and the DPs of normal tissues (NTs) and tumor tissues from the control and experimental groups were measured using the open-ended coaxial probe (OECP) technique. DPs of rat breast tissues are presented with Cole-Cole parameters. The OECP method is preferred since it can collect broadband measurements without sample preparation. Due to these advantages, the method was previously envisioned as a diagnostic tool to aid in biopsy procedures. However, high measurement error prevented the specialized device’s development and, consequently, the clinical deployment of OECP. We demonstrate that high error rates can be mitigated with the application of ML algorithms. Among seven different ML algorithms, the support vector machines (SVMs) algorithm classifies rat malignant tissues, benign tissues, and NTs with a median accuracy (ACC) of 94.4%, Matthews correlation coefficient (MCC) of 91.9%, recall of 94.4%, precision of 94.9%, and $F1$ score of 94.4%