Reverse shoulder arthroplasty is an increasingly common surgical intervention. However there are concerns and known limitations in relation to such joint replacement, while novel designs of reverse shoulder prostheses continue to appear on the market. Many claim to offer improvements over older designs but such assertions are difficult to validate when there is no consensus as to how such implants should be tested in vitro or even if such testing is necessary. In order to permit appropriate in vitro testing of reverse shoulder prostheses a unique, multi-station test rig was designed which was capable of applying motion in three axes to test prostheses. The shoulder simulator can apply up to 110° of motion in the flexion–extension and abd

In this paper, the system of the power plant has been investigated as a special type of industrial systems, which has a significant role in improving societies since the electrical energy has entered all kinds of industries, and it is considered as the artery of modern life.

   The aim of this research is to construct a programming system, which could be used to identify the most important failure modes that are occur in a steam type of power plants. Also the effects and reasons of each failure mode could be analyzed through the usage of this programming system reaching to the basic events (main reasons) that causing each failure mode. The construction of this system for FMEA is dependi

Orthogonal Frequency Division Multiplexing (OFDM) is an efficient multi-carrier technique.The core operation in the OFDM systems is the FFT/IFFT unit that requires a large amount of hardware resources and processing delay. The developments in implementation techniques likes Field Programmable Gate Array (FPGA) technologies have made OFDM a feasible option. The goal of this paper is to design and implement an OFDM transmitter based on Altera FPGA using Quartus software. The proposed transmitter is carried out to simplify the Fourier transform calculation by using decoder instead of multipliers. After programming ALTERA DE2 FPGA kit with implemented project, several practical tests have been done starting from monitoring all the results of

The accumulation of toxic elements in vegetables and melons grown in agriculture, Brassica rapa - turnip, Solanum lycopersicum - tomato, Citrullus lanatus - watermelon, Capsicum annuum - bell pepper, Daucus carota - carrots, Cucurbita pepo - pumpkin, Cucumis melo - melon, and also Prunus armeniaca - apricot from fruit trees were analyzed. The excess of maximum allowable concentrations in agricultural crops of the element As by 1.65-1.75, Cd - 1.6-2.3, Cr -1.2-2.35, Cu -1.6-3.3, Ni - 1.16-3.53, Pb - 1.54-3.08, Al - 1.36-3.5, Sb - 2.0-33, Se - 1.1-3.3 times was established. The maximum allowable concentration of mercury in vegetables and melons was equal to 0.02 mg/kg,

ZnO organic hybrid junction (electroluminescence EL device) was fabricated using phase segregation method. ZnO-nanoparticle (NPs) was prepared as a colloidal by self–assembly method of Zinc acetate solution with KOH solution. Nanoparticle is employed to form organic-inorganic hybrid film and generate white light emission, while N,N’–diphenyl-N,N’ –bis(3-methylphenyl)-1,1’-biphenyl 4,4’-diamine (TPD) and polymethyl methacrylate (PMMA) are adopted as the organic matrices. ZnO NPs was used to fabricate TPD: PMMA: ZnO NPs hybrid junction device. The photoluminescence (PL) and electroluminescence (EL) spectra of the TPD: PMMA: ZnO NPs hybrid device provided a broad emission band covering entirely the visible spectrum (∼350-∼700

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121