Background: Diabetes mellitus (DM) could be regarded as a set of chronic metabolic disorders which have a common aspect of hyperglycemia. The resistance in the peripheral actions of insulin or impaired insulin secretion could be the reason  hepcidin which is a peptide hormone derived from liver, in systemic iron homeostasis is an essential regulator, and its lopsided production participates in the pathogenesis of iron disorders in spectrum. Osteoporosis often accompanies many diseases like ß-thalassemia, hemochromatosis, sickle liver diseases, cell disease and hemosiderosis featured by iron overload, evidences suggest that Iron overload and iron deficiency are suggested by evidences that they affect bone in a negative way, acting

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

The differential protection of power transformers appears to be more difficult than any type of protection for any other part or element in a power system. Such difficulties arise from the existence of the magnetizing inrush phenomenon. Therefore, it is necessary to recognize between inrush current and the current arise from internal faults. In this paper, two approaches based on wavelet packet transform (WPT) and S-transform (ST) are applied to recognize different types of currents following in the transformer. In WPT approach, the selection of optimal mother wavelet and the optimal number of resolution is carried out using minimum description length (MDL) criteria before taking the decision for the extraction features from the WPT tree

Chronic Hepatitis B(CHB) is a serious sequel after Hepatitis B Virus infection, although the rate of chronicity is inverse with age but it may be associated with a significant proportion of deaths related to cirrhosis and liver cancer. HBV serology and measurement of hepatocytic enzymes with viral load can predict disease prognosis and response to treatment. HBeAg refers to a high viral replication and associated with more infectivity to others. This study aimed to determine the impact of HBeAg status in chronically infected patients on various baseline tests. A total of 90 patients with CHB infection who were included in this study. Several standardized measures used for liver function tests, viral load and hepatitis B serological

 Polyaniline organic Semiconductor polymer was prepared by oxidation polymerization by adding hydrochloric acid concentration of 0.1M and potassium per sulfate concentration of 0.2M to 0.1M of aniline at room temperature, the polymer was deposited at glass substrate, the structural and optical properties were studies through UV-VIS, IR, XRD measurements, films have been operated as a sensor of vapor  H₂SO₄ and HCl  acids.

Chronic kidney Failure, a progressive disease, includes both medical and biochemical features that damage kidneys and decrease their abilities to work effectively, this disease is characterized by a chronic disorders to both the innate and adaptive immune systems, generate a complex and not fully understood immune dysfunction. In the present study, (30) men suffering from chronic kidney failure with age in range (40-55) year and (30) healthy men within the same range of age were enrolled in this study. The aim of this study is to highlight the role of immunological aspect (IL-35), hormonal aspects (PTH), some functional proteins and immunological electrolytes in sera of chronic kidney failure (CKF) patients. Biochemical parameters were dete

The impact of decorating Fe, Ru, Rh, and Ir metals upon the sensing capability of a gallium nitride nanotube (GaNNT) in detecting chlorine trifluoride (CT) was scrutinized using the density functionals B3LYP and B97D. The interaction of the pristine GaNNT with CT was a physical adsorption with the sensing response (SR) of approximately 6.9. After decorating the above-mentioned metals on the GaNNT, adsorption energy of CT changed from −5.8 to −18.6, −18.9, −19.4, and −20.1 kcal/mol by decorating the Fe, Ru, Rh, and Ir metals into the GaNNT surface, respectively. Also, the corresponding SR dramatically increased to 39.6, 52.3, 63.8, and 106.6. This shows that the sensitivity of the metal-decorated GaNNT (metal@GaNNT) increased by in

The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model