Background: Breast cancer is the most common cancer in Iraq and the United Kingdom. While the disease is frequently diagnosed among middleaged Iraqi women at advanced stages accounting for the second cause of cancer-related deaths, breast cancer often affects elderly British women yielding the highest survival of all registered malignancies in the UK. Objective: To compare the clinical and pathological profiles of breast cancer among Iraqi and British women; correlating age at diagnosis with the tumor characteristics, receptor-defined biomarkers and phenotype patterns. Methods: This comparative retrospective study included the clinical and pathological characteristics of (1,940) consecutive female patients who were diagnosed with invasive b

  Anthropogenic activities cause soil pollution with different serious pollutants, such as polycyclic aromatic hydrocarbon (PAHs) compounds. This study assessed the contamination of PAHs in soil samples collected from 30 sites divided into eight groups (residential areas, oil areas, agricultural areas, roads, petrol stations, power plants, public parks and electrical generators) in Basrah city-Iraq during 2019-2020. The soil characteristics including (moisture, pH, EC and TOC) were measured. Results showed the following ranges (soil moisture (0.03-0.18%),pH (6.90-8.16), EC (2.48-104.80) mS/cm and TOC (9.90-20.50%)). Gas Chromatography (GC) was used to measure PAHs in extracted soil samples. The total PAH range (499.96 - 5864.86) ng/g dr

Foreign direct investment (FDI) is one of the most practical types of foreign investment. FDI contributes to job creation, foreign exchange earnings and national income escalation, improving semi-skill and skilled labor. Based on our knowledge, this paper is the first study attempting to investigate the effect of political stability on the FDI in Turkey using an econometric approach. Achieving this objective, a co-integration analysis was conducted between the FDI and its determinants in the short-run and long-run including “macroeconomic indicators” and “Political Stability (PS)” in Turkey. Using annual data from 1974 to 2017 via Auto-Regressive Distributed Lag (ARDL) model. The results confirm the positive correlation betwe

This paper compares between the direct and indirect georeferencing techniques in Photogrammetry bases on a simulation model. A flight plan is designed which consists of three strips with nine overlapped images for each strip by a (Canon 500D) digital camera with a resolution of 15 Mega Pixels.

The triangulation computations are carried out by using (ERDAS LPS) software, and the direct measurements are taken directly on the simulated model to substitute using GPS/INS in real case. Two computational tests have been implemented to evaluate the positional accuracy for the whole model and the Root Mean Square Error (RMSE) relating to (30) check points show that th

Background: Contact between implant material and bones must be strong and fast creation, to fulfill these properties appropriate surface modifications must apply on used implants. In this contribution; double surface modifications are applied on Ti-6Al-4V alloy to accelerate osseointegration. Materials and methods: Anodic process is utilized to create titania nanotubes (TNTs) on the screws made from Ti-6Al-4V alloy. These implants were coated with nano ZrO2 particles. Second modification was annealing anodized screws at 8000C, and implanted in tibiae of nine adult New Zealand white rabbits. Results: Physical and histological consequences of two surface modifications on Ti-6Al-4V alloy screws were studied. Scanning electron microscope (SEM)

This study investigates the influence of fear, refuge, and migration in a predator–prey model, where the interactions between the species follow an asymmetric function response. In contrast to some other findings, we propose that prey develop an anti-predator response in response to a concentration of predators, which in turn increases the fear factor of the predators. The conditions under which all ecologically meaningful equilibrium points exist are discussed in detail. The local and global dynamics of the model are determined at all equilibrium points. The model admits several interesting results by changing the rate of fear of predators and predator aggregate sensitivity. Numerical simulations have been performed to verify our theoret

A many risk challenge in (settings hospital) are multi- bacteria are antibiotic-resistant. Some type strains that ability adhesion surface-attached bio-film census. Fifteen MRSA isolates were considered as high biofilm producers Moreover all MRSA isolates; M3, M5, M7 and M11 produced biofilms but the thickest biofilm seen M7strain. The MIC values of N. sativa oil against clinical isolates of MRSA were between (0.25, 0.5, 0.75, 1.0) μg/ml While MRSAcin (50, 75, 100, 125) µg\ ml. All biofilms treated with MRSAcin and Nigella sativa developed a presence of live cells after cultured on plate agar with inhibition zone between MIC (18 – 15) and (14- 11)mm respectively.Yet, results showed that MRSA supernatant developed a inhibitory ef

Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi