A total of sixty raw milk samples were collected from (street vendors and shops) from Baghdad city, Iraq. The samples were inoculated into peptone water and, then, subcultured onto MacConkey agar and Blood agar. Identification of isolates was confirmed by microscopic examination, cultural characteristic, biochemical tests, Vitek (VITEK®2 system), and Biolog GN substrate reactions followed by 16S rRNA and specific genes sequencing. Of 60 raw cow’s milk samples, Providencia spp. were identified only in 4 samples (6.67%) and P. rettgeri was the most common, 2/4 (50%), followed by P. stuartii and P. vermicola, 1/4 (25%). Antimicrobial susceptibility tests were conducted against ten antibiotics by the disc diffusion method. All Provid

Microsporum canis is considered one of the filamentous fungi that cause surface fungal contagion in the humans and animals. The present study aimed to diagnose M. canis via the molecular method and differentiating its local Iraqi isolates from global isolates. Microscopic examination showed 55 specimens with M. canis from 130 specimens collected from children aged between 4-10 years suspected of dermatophytes who attended Medical City Laboratories and Baghdad Hospital in Baghdad city from 1/12/2022 to 1/3/2023. The results showed that the frequency of M. canis infections was 55/130 (42.31%). The results demonstrated significant differences in the animals' contact (p <0.0001), lesions (0.03) and habitation area (p =0.002). Whilst

Continuous escalation of the cost of generating energy is preceded by the fact of scary depletion of the energy reserve of the fossil fuels and pollution of the environment as developed and developing countries burn these fuels. To meet the challenge of the impending energy crisis, renewable energy has been growing rapidly in the last decade. Among the renewable energy sources, solar energy is the most extensively available energy, has the least effect on the environment, and is very efficient in terms of energy conversion. Thus, solar energy has become one of the preferred sources of renewable energy. Flat-plate solar collectors are one of the extensively-used and well-known types of solar collectors. However, the effectiveness of the coll

The varied applications of polystyrene in various fields of life led to examining the cause of radiation influence on some rheological behavior of commercial Polystyrene (PS) solution in the chloroform (CHCl3) solvent. Polystyrene grains shape samples were irradiated using the radioactive element Cesium- 137 with (9 µci) activity for 10, 20, and 30 minutes. The viscosity of the polymer solution depends on the concentration and size (i.e. molecular weight) of the dissolved polymer. Experimental data showed that the radiation dose affected the value of viscosity (shear, relative, specific, and reduced). The viscosity value significantly reduced at 10 min radiation dose and when increasing the dose, the viscosity value increased

Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

In the current study, three types of algae namely Tetradesmus nygaardi (MZ801740), Scenedesmus quadricauda (MZ801741) and Coelastrella sp (MZ801742) were extracted by 95% ethanol and hexane against two types of gram positive and two types of gram negative bacteria by wells diffusion methods. Eleven concentrations from the extract of algae (2, 5, 10, 15, 20, 25, 30, 35, 40, 45 and 50 mg/ml) were utilized. It was noticed that ethanolic extraction was more effective than hexane in Scenedesmus quadricauda than the two other mentioned algal species against all pathogenic bacteria, Acintobacter baumanii (ATCC: 19606), Klebsiella pneumonia (ATCC: 13883) Enterococcus faecalis (ATCC: 29212) and Staphylococc