In this study, we set up and analyze a cancer growth model that integrates a chemotherapy drug with the impact of vitamins in boosting and strengthening the immune system. The aim of this study is to determine the minimal amount of treatment required to eliminate cancer, which will help to reduce harm to patients. It is assumed that vitamins come from organic foods and beverages. The chemotherapy drug is added to delay and eliminate tumor cell growth and division. To that end, we suggest the tumor-immune model, composed of the interaction of tumor and immune cells, which is composed of two ordinary differential equations. The model’s fundamental mathematical properties, such as positivity, boundedness, and equilibrium existence, are exami

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

This study was designed to compare the effect of two types of viral hepatitis A and E (HAV
and HEV) on liver functions in Iraqi individuals by the measurement of biochemical changes
associated with hepatitis.
The study performed on 58 HEV and 66 HAV infected patients compared with 28 healthy
subjects. The measured biochemical tests include total serum bilirubin, serum transminases (ALT
and AST) alkaline phosphatase (ALP) and gamma glutamyl transferase (GGT).
The study showed that adolescent and young adults (17-29) years, were mostly affected by
HEV while children (5-12) years were frequently affected by HAV. The severity of liver damage in
HEV patients was higher than HAV patients as a result of high serum transa

The pandemic SARS-CoV-2 is highly transmittable with its proliferation among nations. This study aims to design and exploring the efficacy of novel nirmatrelvir derivatives as SARS entry inhibitors by adapting a molecular modeling approach combined with theoretical design. The study focuses on the preparation of these derivatives and understanding their effectiveness, with a special focus on their binding affinity to the S protein, which is pivotal for the virus’s access to the host cell. Considering molecular docking aspects in the scope of a study on nirmatrelvir derivatives and S protein, dynamics simulations with 25 nanoseconds of their binding are explored. The study shows that these derivatives might work as effective antivi

One of the most significant challenges of medical care is the infection of postoperative wounds, and conventional visual examination often fails to detect it early. This research proposes the design of an innovative, passive wireless telemetry system for non-intrusive monitoring of the wound-healing process.  The system integrates a biocompatible resonance circuit (LC) with a high-sensitivity piezoresistive sensor based on MXene (Ti3C2Tx). It operates within the standard industrial and medical (ISM) band at 13.56 MHz.The detection mechanism in the system is based on the principle of "impedance modulation" (Impedance Modulation), which arises from changes in the sensor's resistance under physiological tissue pressure. The system was

In order to promote sustainable steel-concrete composite structures, special shear connectors that can facilitate deconstruction are needed. A lockbolt demountable shear connector (LB-DSC), including a grout-filled steel tube embedded in the concrete slab and fastened to a geometrically compatible partial-thread bolt, which is bolted on the steel section's top flange of a composite beam, was proposed. The main drawback of previous similar demountable bolts is the sudden slip of the bolt inside its hole. This bolt has a locked conical seat lug that is secured inside a predrilled compatible counter-sunk hole in the steel section's flange to provide a non-slip bolt-flange connection. Deconstruction is achieved by demounting the tube from the t