Investigation of aflatoxin and metal concentrations in animal feeds and feed ingredients from Turkey

The contents of aflatoxin B-1 (AFB(1)), aflatoxin B-2 (AFB(2)), aflatoxin G(1) (AFG(1)) aflatoxin G(2) (AFG(2)), aluminium (Al), arsenic (As), barium (Ba), calcium (Ca), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), potassium (K), magnesium (Mg), manganese (Mn), sodium (Na), nickel (Ni), phosphorus (P), lead (Pb), selenium (Se), tin (Sn) and zinc (Zn) in animal feed samples in Turkey were screened. Eighty animal feeds and feed ingredients were collected from different cities in Turkey. Aflatoxins were determined using the HPLC instrument after pre-separation using immuno affinity column, and also the instrument of ICP-MS was used for metal determinations. All types of animal feed samples have led concentrations lower than the maximum EU and Turkey regulation limit, while 1.25% and 11.8 of mixed and feed additive samples had AFB(1) and Hg concentrations higher than the maximum limits, respectively. A single correlation analysis was used to determine the relationship between AFB(1) and total AFs and metal contents in mixed animal feed samples (p<0.05). A strong positive correlation was found between As and AFB(1) and total AFs contents; whereas Cr was correlated negatively to AFB(1) and total AFs, using single correlation analyses

Artificial Neural Networks Based Inverse Kinematics Solution and Simulation of a Six Degree of Freedom Lighting Manipulator

Inverse kinematics problem of a robot manipulator is calculation of joint variables of the manipulator. Inverse kinematic is a challenging problem of robots. The inverse kinematics in robotic is the determination of joint angles for a desired position of the end effector. This paper proposes an Artificial Neural Network (ANN) model to find Inverse kinematic solution of a 6- DOF manipulator, which is designed instead of a manually lighting system that is used in surgery rooms. After obtaining forward kinematic equations, these equations were used to derive training data of ANN. The manipulator was designed in a computer aided design (CAD) program and this CAD model transferred to Simulink environment for a realistic and visual simulation purpose. To evaluate the trained ANN performance visually, this Simulink model were used. A test input set is introduced to the trained ANN. Results are discussed and demonstrated graphically. It was observed that obtained results are satisfactory, and the error of ANN for a reference position is acceptable

Experimentally flight performances comparison of octocopter, decacopter and dodecacopter using universal UAV

This study presents a comparative analysis of different unmanned aerial vehicle (UAV) configurations using a proposed universal UAV. The octocopter, decacopter, and dodecacopter were experimentally evaluated through point tracking flight performances and vibration level analyses. To the best of our knowledge, this is the first study to conduct a comparative analysis of these configurations on the same platform. Our findings indicate that the dodecacopter exhibited the best overall performance, whereas the decacopter showed the lowest roll angle error. Notably, the implemented decacopter exhibited the highest pitch angle error and north position error due to its asymmetric rotor placement in the pitch axis. We observed that the octocopter demonstrated the best vibrationless flight performance, while increasing vibration magnitude was observed with an increase in the number of rotors