Cams are considered as one of the most important mechanical components that depends the contact action to do its job and suffer a lot of with drawbacks to be predicted and overcame in the design process. this work aims to investigate the induced cam contact and the maximum shear stress energy or (von misses) stresses during the course of action analytically using Hertz contact stress equation and the principal stress formulations to find the maximum stress value and its position beneath the contacting surfaces. The experimental investigation adopted two dimensions photoelastic technique to analyze cam stresses under a plane polarized light. The problem has been numerically simulated using Ansys software version 15 as FE

Hsieh-Wildenthal (HW) and G-matrix PF1, (GXPF1) interactions for 40Ca and 48Ca, respectively. The 40Ca was considered to be consisted of 32S as a core and 1d3/21f7/2 subshells as a model space. The 48Ca was considered to be consisted of 40Ca as a core and 1f7/22p3/21f5/2 2p1/2 subshells as a model space. The obtained one body-density matrix elements (OBDME) for both interactions for the studied Coulomb transitions:  For 40Ca, the three non-normal parity transitions (C3): ,  and  and one C5 transitions,  .  For 48Ca, the two C2 transitions:  and  and one C4 transitions  were used in parallel with the transformed harmonic-oscillator basis to compute charge density, elastic electron scattering differential cross-section and ela

Diabetic kidney disease (DKD) is caused by a variety of processes. As a result, one biomarker is insufficient to represent the complete process. This study Evaluate the diagnostic value of serum kidney injury molecule-1(KIM-1) and cystatin C (CysC) as early biochemical markers of DKD and predictive their sensitivities and specificities as biomarkers of nephropathy in Iraqi type 2 diabetic (T2DM) patients. This cross-sectional study include 161 T2DM patients from Diabetes and Endocrinology Center at Merjan medical city in Babylon. Patients divided according to urinary albumin creatinine ratio(ACR) (Group1:ACR≤30mg/g,Group2:ACR>30mg/g). Random spot urine and fasting blood samples were taken from each patient and urinary ACR, bloo

The present study aims to evaluate the biosorption of reactive orange dye by using garden grass. Experiments were carried out in a batch reactor to obtain equilibrium and thermodynamic data. Experimental parameters affecting the biosorption process such as pH, shaking time, initial dye concentrations, and temperature were thoroughly examined. The optimum pH for removal was found to be 4. Fourier transform infrared spectroscopy analysis indicated that the electronegative groups on the surface of garden grass were the major groups responsible for the biosorption process. Four sorption isotherm models were employed to analyze the experimental data of which Temkin and Pyzhey model was found to be most suitable one. The maxim

Contracting cancer typically induces a state of terror among the individuals who are affected. Exploring how glucose excess, estrogen excess, and anxiety work together to affect the speed at which breast cancer cells multiply and the immune system’s response model is necessary to conceive of ways to stop the spread of cancer. This paper proposes a mathematical model to investigate the impact of psychological panic, glucose excess, and estrogen excess on the interaction of cancer and immunity. The proposed model is precisely described. The focus of the model’s dynamic analysis is to identify the potential equilibrium locations. According to the analysis, it is possible to establish four equilibrium positions. The stability analys

Mass transfer was examined at a stationary rectangular copper electrode (cathode) by using the reduction of cupric ions as the electrochemical reaction. The influence of electrolyte temperature (25, 45, and 65 ^oC), and cupric ions concentration (4, 8, and 12 mM) on mass transfer coefficient were investigated by using limiting current technique. The mass transfer coefficient and hence the Sherwood number was correlated as Sh =

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv