Given that the Crimean and Congo hemorrhagic fever is one of the deadly viral diseases that occur seasonally due to the activity of the carrier “tick,” studying and developing a mathematical model simulating this illness are crucial. Due to the delay in the disease’s incubation time in the sick individual, the paper involved the development of a mathematical model modeling the transmission of the disease from the carrier to humans and its spread among them. The major objective is to comprehend the dynamics of illness transmission so that it may be controlled, as well as how time delay affects this. The discussion of every one of the solution’s qualitative attributes is included. According to the established basic reproductio

As many expensive and invasive procedures are used for the diagnosis or follow-up of clinical conditions, the measurement of cell-free DNA is a promising, noninvasive method, which considers using blood, follicular fluid, or seminal fluid. This method is used to determine chromosomal abnormalities, genetic disorders, and indicators of some diseases such as polycystic ovary syndrome, pre-eclampsia, and some malignancies. Cell-free DNA, which are DNA fragments outside the nucleus, originates from an apoptotic process. However, to be used as a marker for the previously mentioned diseases is still under investigation. We discuss some aspects of using cell-free DNA measurements as an indicator or marker for pathological conditions.

This work suggests a system of ordinary differential equations (ODEs) containing a three-species food chain model incorporating wind and fear effects. The properties of the solution, like positivity and bound-ness, were investigated. All equilibrium points (biologically feasible) have been obtained, and the local stability of these equilibriums has been carried out. The global stability outcomes on the equilibrium points under specific restrictions have been established. Also, the persistence restrictions have been investigated. By utilizing Sotomayor’s theorem, the local bifurcation of the suggested model has been inspected. Furthermore, numerical analysis was carried out to ensure the theoretical results obtained by utilizing MA

Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

This study aims to measure and analyze the direct and indirect effects of the financial variables, namely (public spending, public revenues, internal debt, and external debt), on the non-oil productive sectors with and without bank credit as an intermediate variable, using quarterly data for the period (2004Q1–2021Q4), converted using Eviews 12. To measure the objective of the study, the path analysis method was used using IBM SPSS-AMOS. The study concluded that the direct and indirect effects of financial variables have a weak role in directing bank credit towards the productive sectors in Iraq, which amounted to (0.18), as a result of market risks or unstable expectations in the economy. In addition to the weak credit ratings of borr