A collection of 118 specimens of Iraqi phasianid birds belong to four species was examined
for haematozoa. Results show that 21.2% of them were infected with one or more of four
species of blood parasites; Haemoproteus danilewskyi, H. santosdiasi, Plasmodium sp. and
microfilaria. Haemoproteus danilewskyi is reported here for the first time in Iraq.

A new design of manifold flow injection (FI) coupling with a merging zone technique was studied for sulfamethoxazole determination spectrophotometrically. The semiautomated FI method has many advantages such as being fast, simple, highly accurate, economical with high throughput . The suggested method based on the production of the orange- colored compound of SMZ with (NQS)1,2-Naphthoquinone-4-Sulphonic acid Sodium salt in alkaline media NaOH at λ_max 496nm.The linearity range of sulfamethoxazole was  3-100  μg. mL^-1, with (LOD) was 0.593 μg. mL^-1 and the RSD% is about 1.25 and the recovery is 100.73%. All various physical and chemical parameters that have an effect on the stability and development of

Cryptosporidium is a protozoan parasite of medical and veterinary significance that causes gastroenteritis in a number of vertebrate hosts. Several studies have recorded different degrees of pathogenicity and virulence among Cryptosporidium species and isolates of the same species as well as evidence of variation in host susceptibility to infection. Nevertheless, important progress has been made in determining Cryptosporidium's putative virulence factors. Since the publication of C parvum and C. Hominis this development has been accelerated genomes, identified by a range of immunological and molecular techniques with the characterization of over 25 putative virulence factors, which are proposed to be involved in aspects of host-pat

Here we report for the first time the presence of Apoleptomastix bicoloricornis (Girault, 1915) (Hymenoptera, Encyrtidae), as parasitoid of the rice mealybug, Brevennia rehi (Lindinger, 1943) (Hemiptera, Psedococcidae) in Iraq. Brief notes are provided in distinguishing the parasitoid from other closely allied species.

This research deals with the aesthetics of describing nature and the joys of urban life in the environment of Fatimid Egypt, among a group of poets, who were deceived by its enchanting beauty and breathtaking scenery, through it they depicted the reality of the life they live, and the things that involved them, as well as showing their personal culture, and the joys of life that experience, articulating this with a descriptive and analytical study, focusing on how the poet portrayed the visual scene, in an important stage of Arabic literature in Egypt.

The ascaroid nematode Contracaecum rudolphii was recovered in large numbers from the
digestive tract of Phalacrocorax carbo collected in Baghdad area, Central Iraq. The infection
rates of the two sexes of the bird and some meristic and morphometric characters of the
parasite that allowed species determination of the nematode Contracaecum rudolphii were
discussed. This finding represents a new host record for this nematode in Iraq.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The study included general survey of some districts of Iraq in order to determinate new distribution areas for 33 species of the genus salvia L. ,new collections obtained , new locations for many species recorded. Observed specimens in most Iraqi herbaria were studies and identified. ,the flowering period were also studied

The study included general survey of some districts of Iraq in order to determinate new distribution areas for 33 species of the genus salvia L. ,new collections obtained , new locations for many species recorded. Observed specimens in most Iraqi herbaria were studies and identified. ,the flowering period were also studied