Background: The longevity of any prosthesis depends on the materials from which it was fabricated, that is why, defects in the material properties may reduce the service life of prosthesis and necessitate its replacement. The aim of this study was to evaluate the effect of adding different concentrations of Polyamide-6 (Nylon-6) on the tear and tensile strength of A-2186 RTV silicone elastomer. Materials and Methods: 80 samples were fabricated by the addition of 0%, 1%, 3% and 5% by weight PA-6 micro-particles powder to A-2186 platinum RTV silicone elastomer. The study samples were divided into four (4) groups, each group containing 20 samples. One control group was prepared without PA-6 micro particles and three experimental groups were pr

Objective: Assessment the psychological problems in patients with colorectal cancer, and to find out the
relationship between socio-demographic characteristics such as (age, sex, marital status, educational level,
and occupation) and psychological problems for those patients.
Methodology: A descriptive design is employed through the present study from 1
st July 2011 to 25
th December
2011 in order to study the quality of life in colorectal cancer patients with psychological problems.
A purposive (non probability) sample is selected for the study which includes (60) patients diagnosed with
colorectal cancer were treated in Mosul Oncology and Nuclear Medicine hospital or the patients who visited
the outpatient cl

Background: The transcriptional control of various cell types, especially in the development or functioning of immune system cells involved in either promoting or inhibiting the immune response against cancer, is significantly influenced by DNA or RNA methylation. Multifaceted interconnections exist between immunological or cancer cell populations in the tumor's microenvironment (TME). TME alters the fluctuating DNA (as well as RNA) methylation sequences in these immunological cells to change their development into pro- or anti-cancer cell categories (such as T cells, which are regulatory, for instance). Objective: This review highlights the impact of DNA and RNA methylation on myeloid and lymphoid cells, unraveling their intricate

Amygdalin (d-Mandelonitrile 6-O-β-d-glucosido-β-d-glucoside) and its semi synthetic product is Laetrile ( also called vitamin B17): a natural cyanogenic glycoside occurring in the seeds of some edible plants, such as bitter almonds and peaches. Early in the 19th century, Amygdalin was first isolated in 1830 by two French chemists, Robiquet and Boutron-Charlard, as active components in various fruit pits and raw nuts. However, the systematized study of vitamin B17 started when chemist Bohn (1802) discovered that a hydrocyanic acid is released during distillation of the water from bitter almonds. The various pharmacological effects of Laetrile include antiatherogenic, activity in renal fibrosis, pulmonary fibrosis, immune regulation, ant

Thin films Tin sulfide SnS pure and doped with different ratios of Cu (X=0, 0.01, 0.03 and 0.05) were prepared using thermal evaporation with a vacuum of 4*10^-6mbar on two types of substrates n-type Si and glass with (500) nm thickness for solar cell application. X-ray diffraction and AFM analysis were carried out to explain the influence of Cu ratio dopant on structural and morphological properties respectively. SnS phase appeared forming orthorhombic structure with preferred orientation (111), increase the crystallinity degree and surface roughness with increase Cu ratio. UV/Visible measurement revealed the decrease in energy gap from 1.9eV for pure SnS to 1.5 for SnS: Cu (0.05) making these samples suitable f

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

The Jeribe reservoir in the Jambour Oil Field is a complex and heterogeneous carbonate reservoir characterized by a wide range of permeability variations. Due to limited availability of core plugs in most wells, it becomes crucial to establish correlations between cored wells and apply them to uncored wells for predicting permeability. In recent years, the Flow Zone Indicator (FZI) approach has gained significant applicability for predicting hydraulic flow units (HFUs) and identifying rock types within the reservoir units.

   This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized por