Cryptosporidiosis is an intestinal protozoan parasitic disease that infects human and animals, caused by apicomplexan parasite belong to the genusof Cryptosporidium. The current study was done to record the infection rate of cryptosporidiosis in human and cattle, and genotype the clinical isolates of Cryptosporidium in Baghdad Province. A total of 265 stool sample were collected (150 from human and 115 from cattle) during the period from December 2016 to the May 2017. Cryptosporidial infection was detected using modified acid fast stain. DNA of the parasite was extracted from oocysts of positive fecal samples and nested PCR method was used for partial 60 kDa glycoprotein (gp60) gene amplification then sequence analysis for selected samples.The total infection rates of Cryptosporidium in human and cattle were 47.33% (71/150), 35.63% (41/115) respectively. The results of this study record that Cryptosporidium parvum was found in all positive samples of human and cattle except two human samples which were Cryptosporidium hominis, and all were belonging to the common allele family IIa.The prevalent zoonotic subtype of C. parvum species (IIa) in this study highlights the significance of zoonotic transmission of cryptosporidiosis in the country.
In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho
... Show MoreThis study included the isolation and identification of Aspergillus flavus isolates associated with imported American rice grains and local corn grains which collected from local markets, using UV light with 365 nm wave length and different media (PDA, YEA, COA, and CDA ). One hundred and seven fungal isolates were identified in rice and 147 isolates in corn.4 genera and 7 species were associated with grains, the genera were Aspergillus ,Fusarium ,Neurospora ,Penicillium . Aspergillus was dominant with occurrence of 0.47% and frequency of 11.75% in rice grains whereas in corn grains the genus Neurospora was dominant with occurrence of 1.09% and frequency 27.25% ,results revealed that 20 isolates out of 50 A. flavus isolates were able
... Show MoreMinister Yacoub Ben Keles distinguished himself with leadership and administrative talents, as well as his abilities in the field of jurisprudence, which made him the top political, administrative and cultural scene of the Fatimid state and left its mark on it by influencing its fateful decisions.
He was the son of Kels of the Jews of Baghdad, where he learned writing and arithmetic, and moved with his father to Syria and then carried him to Egypt.
Egypt embraced the son of Kels, living in a transitional period from the Achaishid era to the Fatimid period. Both these two covenants reconciled this man to his career until he became minister in the Fatimids in 368 A.H. / 978 A.D.
His character was overshadowed by most of the state'
Nonsteroidal anti-inflammatory drugs (NSAIDs) are drugs that help reduce inflammation, which often helps to relieve pain. In this research new ibuprofen oxothiazolidnone derivatives were synthesized from the reaction of Schiff base derivatives of Ibuprofen with mercapto acetic acid VI a-c, to improve the potency and to decrease the drug's potential side effects, a new series of 4-thiazolidinone derivatives of ibuprofen was synthesized VI a-c . The characterizations of the compounds were identified by using FTIR, 1HNMR technique and by measuring the physical properties.
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
... Show MoreIn this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.