Bacterial strains were isolated from oil-contaminated soil, in 2018, these isolates were identified, and with the aim of finding out the ability of these isolates to degrede the oil compounds, the color change of medium which added to it isolates was read by the method of Pacto Bushnell Hans. Then the change in the petroleum compounds was read by gas chromatography, for the most effective isolates.

The nine isolated bacterial showed different degrees of color change, and the isolates (Pseudomonas, Bacillus, Micrococcus) outperformed the color change amount (78, 78, 77) %, respectively, compared to the control, and the three isolates together showed the best color change of 90.7. % Compared to the control, and the

The current study included the isolation, purification and cultivation of blue-green alga Oscillatoria pseudogeminata G.Schmidle from soil using the BG-11liquid culture medium for 60 days of cultivation. The growth constant (k) and generation time (G) were measured which (K=0.144) and (G=2.09 days).

Microcystins were purified and determined qualitatively and quantitatively from this alga by using the technique of enzyme linked immunosorbent assay (Elisa Kits). The alga showed the ability to produce microcystins in concentration reached 1.47 µg/L for each 50 mg DW. Tomato plants (Lycopersicon esculentum) aged two months were irrigated with three concentrations of purified microcystins 0.5 , 3.0 and 6.0

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

A nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na

The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.

Tuberculosis status as the second leading causes of significant morbidity and mortality from an infectious disease worldwide, after human immunodeficiency virus (HIV). Sample collection was conducted at the Institute of Chest and Respiratory Diseases/Baghdad Medical City in Baghdad. The collection interval was from August to October 2014, 629 suspected TB patients were examined during this period. The results revealed among total 629 specimens, 56 (8.9%) of the specimens were positive by direct examination and 573 (91.1%) negative specimens by smear microscopy. Fifty six DNA samples were extracted from positive ZN smears of sputum specimens and 40 samples from healthy persons (as control) were subjected to molecular diagnosis by real tim

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Background: The emergence and spread of multidrug-resistant Gram-negative bacilliin burn wound infections related to biofilm formation, which lend to challenge in treatment with conventional antibiotics andprompting to search for novel antimicrobial agents to control the infections.Silver nanoparticles (AgNPs) have wide spectrum biological properties with different mechanisms of action and less toxicity towards human cells.

Objective:The goal of this study was to evaluated the anti-bacterial and anti-biofilm activities of AgNPs alone and in combination with aminoglycoside (Amikacin) and β-lactam (Ampicillin) antibiotics against multidrug resistant Gram-negative bacilli (Pseudomonas aeruginos

This study is an investigation of the drugs effect on some pathogenic Acanthamoeba isolated from Iraqi waters, where the problem of environmental adaptation that characterizes this organism in addition to being a reservoir for many pathogenic microorganisms that take shelter in it to escape disinfectants and medicines is sometimes difficult to treat it with traditional treatments.  Twenty water samples were collected from different water regions in Iraq, namely the Dokan Lake, Tigris River, Euphrates River and Najaf Sea, 5 samples from each source.  Acanthamoeba was isolated from water samples on NNA and PYG media, using an inverted microscope with an electron microscope to determine their phenotypic features. PCR and