Honey is a natural animal product. The elemental composition of honey varies greatly depending on the source of nectar, honeydew, pollen and environmental conditions. The aim of the present study was to determine the levels of chromium (Cr), copper (Cu), iron (Fe), magnesium (Mg), manganese (Mn), selenium (Se), zinc (Zn), cadmium (Cd), lead (Pb) and aluminium (Al) in a total of 65 honey samples procured from different regions of Turkey. Element levels were measured by using an inductively coupled plasma optical emission spectrophotometer (OCP-DES). Minimum and maximum levels of the elements, indicated as µg/g wet weight were as follows: Cr: 0.126-7.964, Cu: 0.Practical Application: Honey contains many elements necessary for life. Alongside its nutritional value, honey may also contain toxic elements.
Mammary carcinoma, breast cancer, is the most commonly diagnosed cancer type among women. Therefore, potential new technologies for the diagnosis and treatment of the disease are being investigated. One promising technique is microwave applications designed to exploit the inherent dielectric property discrepancy between the malignant and normal tissues. In theory, the anomalies can be characterized by simply measuring the dielectric properties. However, the current measurement technique is error-prone and a single measurement is not accurate enough to detect anomalies with high confidence. This work proposes to classify the rat mammary carcinoma, based on collected large-scale in vivo S$$_{11}$$
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measurements and corresponding tissue dielectric properties with a circular diffraction antenna. The tissues were classified with high accuracy in a reproducible way by leveraging a learning-based linear classifier. Moreover, the most discriminative S$$_{11}$$
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measurement was identified, and to our surprise, using the discriminative measurement along with a linear classifier an 86.92% accuracy was achieved. These findings suggest that a narrow band microwave circuitry can support the antenna enabling a low-cost automated microwave diagnostic system.
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