This paper introduces an innovative method for image encryption called "Two-Fold Cryptography," which leverages the Henon map in a dual-layer encryption framework. By applying two distinct encryption processes, this approach offers enhanced security for images. Key parameters generated by the Henon map dynamically shape both stages of encryption, creating a sophisticated and robust security system. The findings reveal that Two-Fold Cryptography provides a notable improvement in image protection, outperforming traditional single-layer encryption techniques.

Introduction: Rheumatoid arthritis (RA) is one of the most prevalent systemic inflammatory diseases worldwide. Cardiac complications present the most common mortality cause among RA patients. One of the most important comorbid conditions with RA is diabetic hyperglycemia mainly type 2 diabetes mellitus (T2DM). Aim of the study: The present study was conducted to assess prevalence of T2DM among patients diagnosed with RA from Iraq. Methodology: We included a randomly selected 100 rheumatoid arthritis. All included patients were subjected to anthropometric measurements, diabetic profile assessment and ESR, CRP and rheumatoid factor measurement. Results: Among the included RA patients, 28 patients were diagnosed with new-onset DM. Our

Background: Because of many factors play a role in the developing of late lower arch crowding, therefore the objective of the current study is to do vertical analysis for subjects with late lower dental arch crowding. The conducted study is the first attempt to do vertical analysis for Iraqi subjects with late lower arch crowding to see if there is a vertical discrepancy in such patients. Subjects and methods: Eighty subjects were selected according to certain inclusion criteria from patients attending the Orthodontic Department in the College of Dentistry, Baghdad University, patients ranged between 18-25 years old. The 80 patients were divided into two groups (crowding and normal), 40 patients each (20 males and 20 females). A study cast

This study investigates the influence of five nanomaterials nano-alumina (NA), nano-silica (NS), nano-titanium (NT), nano-zinc oxide (NZ), and carbon nanotubes (CNT)on enhancing the fatigue resistance of asphalt binders. NA, NS, and NT were incorporated at dosages of 2%, 4%, 6%, 8%, and 10%, while NZ and CNT were added at 1%, 2%, 3%, 4%, and 5%. A series of physical, rheological, and performance-based tests were conducted, including penetration, softening point, ductility, and rotational viscosity. Based on the outcomes of the overall desirability evaluation, the first three dosages of each nanomaterial were selected for further testing due to their superior workability and binder flexibility. Subsequent investigations included the high-tem

Let be a ring. Given two positive integers and , an module is said to be -presented, if there is an exact sequence of -modules with is -generated. A submodule of a right -module is said to be -pure in , if for every -Presented left -module the canonical map is a monomorphism. An -module has the -pure intersection property if the intersection of any two -pure submodules is again -pure. In this paper we give some characterizations, theorems and properties of modules with the -pure intersection property.

Visceral leishmaniasis (VL) is a parasitic infection caused by an intracellular growth of Leishmania spp. in macrophage cells. The autoimmune disorder is a condition takes place when the immune system produces antibodies which incorrectly attacked its own body tissues. VL has been involved as an effect or on the autoimmune aspect. This study was conducted to identify the auto antibodies profile in patients infected with VL. The presences of auto antibodies in 21 Iraqi children infected with VL were tested for laboratory autoimmune aspect. The highest percentage of seropositive in Leishmania patients was observed for anti-ds DNA, anti-Mi-2, anti-Ku and anti-PCNA antibodies (90.5%, 90.5%, 90.5% and 61.9%) respectively, while the lowest percen

Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty