The study is designed to identify intestinal parasitic infections examined at Al-Aziziyah Hospital in Wasit Governorate in Iraq. In this study, a total of (460) internal and external patients were monitored for intestinal parasitic infections. All stool samples were analyzed by the direct method (microscopic exam.) to discover the trophozoite stages and cyst stages for intestinal protozoan parasites. The most incidence parasites in different sex, area residence and different age groups. Out of (460) patient sample were infected with 217 at a percentage of (47.17%), 101(46.5%) were for males and 116 (53.5%) were for females. It was found that the numbers and percentages of a single (one

The present study dealt with the morphological, anatomical,trichomespollen grains,and ecological characteristics of Caroxylon jordanicola (EigAkhani & Roalson (Amaranthaceae) in Al-Tar Caves, Karbala, Iraq which belongs to the Amaranthaceae family. The results of the present study demonstrated that There are distinctive characteristics of the studied species distinguish it from other species and facilitate its diagnosis. The sample was diagnosed using the taxonomic keys of the Iraqi flora and the flora of neighboring countriesIn addition to some available research. The results of the morphological and anatomical features investigation provide really significant taxonomical value to distinguish the species. The results that showe

Breast cancer is the most diagnosed form of malignant tumour in Iraqi women. Tamoxifen and trastuzumab are highly effective adjuvant therapy for breast cancer.

This study's objectives were to define the patient's belief in tamoxifen or trastuzumab when used as adjuvant therapy and to determine the variation in belief between the two medications in a sample of Iraqi breast cancer patients.

The cross-section survey was conducted using the BMQ-Specific questionnaire. Ninety-seven participants (sixty-seven tamoxifen, thirty trastuzumab) participated in this study.

The mean of specific-necessity scale for tamoxifen was (3.7) and for trastuzumab (4). The findings showed a high necessity for both medicines, and there wer

To enhance the structural performance of concrete-filled steel tube (CFST) columns, various strengthening techniques have been proposed, including the use of internal steel stiffeners, external wrapping with carbon fiber-reinforced polymer (CFRP) sheets, and embedded steel elements. However, the behavior of concrete-filled stainless-steel tube (CFSST) columns remains insufficiently explored. This study numerically investigates the axial performance of square CFSST columns internally strengthened with embedded I-section steel profiles under biaxial eccentric loading. Finite element (FE) simulations were conducted using ABAQUS v. 6.2, and the developed models were validated against experimental results from the literature. A comprehen

Dyes are extensively water-soluble and toxic chemicals. The disposing of wastewater rich with such chemicals has severely impacted surface water quality (rivers and lakes). In the current study, an anionic dye, methyl orange, were extracted from wastewater fluids using bulk liquid membranes supplemented with an anionic carrier (Aliquat 336 (QCI)). Parameters including solvent type (carbon tetrachloride and chloroform), membrane stirring speed (100-250 rpm), mixing speed of both phases (50-100 rpm), The feed pH (2-12) and implemented temperature (35-60 °C) were thoroughly analyzed to determine the effect of such variables on extraction effectiveness. Furthermore, the effect of methyl orange (10-50 ppm) in the feed stage and NaOH (0

Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health