Molecular characterization of Hymenolepis nana based on nuclear rDNA ITS2 gene marker

Introduction: Hymenolepis nana is a zoonotic tapeworm with widespread distribution. The goal of the present study was to identify the parasite in the specimens collected from NorthWestern regions of Iran using PCR-sequencing method. Methods: A total of 1521 stool samples were collected from the study individuals. Initially, the identification of hymenolepis nana was confirmed by parasitological method including direct wet-mount and formalin-ethyl acetate concentration methods. Afterward, PCR-sequencing analysis of ribosomal ITS2 fragment was targeted to investigate the molecular identification of the parasite. Results: Overall, 0.65% (10/1521) of the isolates were contaminated with H. nana in formalin-ethyl acetate concentration. All ten isolates were succefully amplified by PCR and further sequenced. The determined sequences were deposited in GenBank under the accession numbers MH337810 -MH337819. Conclusion: Our results clarified the presence of H. nana among the patients in the study areas. In addition, the molecular technique could be accessible when the human eggs are the only sources available to identify and diagnose the parasite. DOI: https://dx.doi.org/10.4314/ahs.v19i1.6 Cite as: Shahnazi M, Mehrizi MZ, Alizadeh SA, Heydarian P, Saraei M, Alipour M, Hajialilo E. Molecular characterization of Hymenolepis nana (Cestoda: Cyclophyllidea: Hymenolepididae) based on nuclear rDNA ITS2 gene marker. Afri Health Sci. 2019;19(1): 1346- 1352. https://dx.doi.org/10.4314/ahs.v19i1.

A Parametric Study on the Effect of FSW Parameters and the Tool Geometry on the Tensile Strength of AA2024–AA7075 Joints: Microstructure and Fracture

Friction stir welding (FSW) is a process by which a joint can be made in a solid state. The complexity of the process due to metallurgical phenomena necessitates the use of models with the ability to accurately correlate the process parameters with the joint properties. In the present study, a multilayer perceptron (MLP) artificial neural network (ANN) was used to model and predict the ultimate tensile strength (UTS) of the joint between the AA2024 and AA7075 aluminum alloys. Three pin geometries, pyramidal, conical, and cylindrical, were used for welding. The rotation speed varied between 800 and 1200 rpm and the welding speed varied between 10 and 50 mm/min. The obtained ANN model was used in a simulated annealing algorithm (SA algorithm) to optimize the process to attain the maximum UTS. The SA algorithm yielded the cylindrical pin and rotational speed of 1110 rpm to achieve the maximum UTS (395 MPa), which agreed well with the experiment. Tensile testing and scanning electron microscopy (SEM) were used to assess the joint strength and the microstructure of the joints, respectively. Various defects were detected in the joints, such as a root kissing bond and unconsolidated banding structures, whose formations were dependent on the tool geometry and the rotation speed

A Parametric Study on the Effect of FSW Parameters and the Tool Geometry on the Tensile Strength of AA2024–AA7075 Joints: Microstructure and Fracture

Friction stir welding (FSW) is a process by which a joint can be made in a solid state. The complexity of the process due to metallurgical phenomena necessitates the use of models with the ability to accurately correlate the process parameters with the joint properties. In the present study, a multilayer perceptron (MLP) artificial neural network (ANN) was used to model and predict the ultimate tensile strength (UTS) of the joint between the AA2024 and AA7075 aluminum alloys. Three pin geometries, pyramidal, conical, and cylindrical, were used for welding. The rotation speed varied between 800 and 1200 rpm and the welding speed varied between 10 and 50 mm/min. The obtained ANN model was used in a simulated annealing algorithm (SA algorithm) to optimize the process to attain the maximum UTS. The SA algorithm yielded the cylindrical pin and rotational speed of 1110 rpm to achieve the maximum UTS (395 MPa), which agreed well with the experiment. Tensile testing and scanning electron microscopy (SEM) were used to assess the joint strength and the microstructure of the joints, respectively. Various defects were detected in the joints, such as a root kissing bond and unconsolidated banding structures, whose formations were dependent on the tool geometry and the rotation speed