Microstructure and mechanical properties of continuous drive friction welded Ti_(2)AlNb alloy under different rotational rates

Ti_(2)AlNb-based alloy was joined in a continuous drive friction welding machine under different rotational rates(500,1000 and 1500 r/min).The microstructure and mechanical properties of the joints were investigated.It is shown that the weld zone(WZ) is fully composed of recrystallized B2 phase,and the grain size decreases with increasing rotational rate.The thermo-mechanically affected zone(TMAZ) suffers severe deformation during welding,due to which most of original precipitation phase is dissolved and streamlines are present.In the heat affected zone(HAZ),only the fine O phase is dissolved.The as-welded joint produced using 1000 r/min has the best mechanical properties,whose strength and elongation are both close to those of the base metal,while the as-welded joint obtained using 500 r/min exhibits the worst mechanical properties.Post-weld annealing treatment annihilates the deformation microstructure and fine O phase precipitates in the joints,consequently improving the mechanical properties significantly.Decomposed α_(2) phase is a weakness for the mechanical performance of the joint since microcracks are apt to form in it in the tensile test.

Determination of Gamma point source efficiency based on a backpropagation neural network

Efficiency is an important factor in quantitative and qualitative analysis of radionuclides, and the gamma point source efficiency is related to the radial angle,detection distance, and gamma-ray energy. In this work, on the basis of a back-propagation(BP) neural network model,a method to determine the gamma point source efficiency is developed and validated. The efficiency of the point sources ^(137)Cs and ^(60)Co at discrete radial angles, detection distances, and gamma-ray energies is measured, and the BP neural network prediction model is constructed using MATLAB. The gamma point source efficiencies at different radial angles, detection distances, and gamma-ray energies are predicted quickly and accurately using this nonlinear prediction model. The results show that the maximum error between the predicted and experimental values is 3.732% at 661.661 keV, 11π/24, and 35 cm, and those under other conditions are less than 3%. The gamma point source efficiencies obtained using the BP neural network model are in good agreement with experimental data.

Pilomatricoma With Bullous Appearance:A Case Report

Introduction:Pilomatricoma is usually a solitary,deep dermal firm nodule with an overlying normal epidermis.Bullous pilomatricoma is rarely reported;thus,its pathogenesis has not been elucidated.We report a case presenting the pilomatricoma with bullous change.Case presentation:A 19-year-old female presented a firm nodule covered by a bulla on her right upper arm.Histopathological examination showed the tumor was composed of basophilic basal-like cells and shadow cells.No cellular atypia or abnormal mitotic figures were observed.All these clinical characteristics and pathological results point to the diagnosis of bullous pilomatricoma.The tumor was surgically removed by enlargement.Discussion:We hypothesize that a history of trauma and rapid growth may contribute to the diagnosis of the bullous pilomatricoma.The appearance of the bullous can be explained by the dilated lymphatic vessels seen in histopathologic examination.We give a case report help clinicians to better diagnose this entity and decrease the rate of misdiagnosis.Conclusion:We observed a rare bullous variant of pilomatricoma.Hence,when identifying a patient of bullous pilomatricoma,a detailed medical history and physical examination are essential.