G. tuberculosa is a newly recorded species from the Caryophyllaceae family for Iraqi flora, collected from the Arbil district from May to August. Morphological descriptions with macro and micro features illustrated with plates and dimensions, the species is related to G. pallida and distinguished from calyx properties, especially the presence of large prominent druses crystals. Keywords: Caryophyllaceae, Gypsophila, Iraq, New record, pallida.

Five species of Trogoderma Berthold are reported from Iraq. These are: I inclus,n LeCont. T.
granarium Everts, T. variable Ballion. I. bactrianum Zantiev and T. irroraturn Reitter. A key
to the species is presented, with redeseriptions and illustrations of all species.

  Acinetobacter baumannii (A. baumannii ) is considered a critical healthcare problem for patients in intensive care units due to its high ability to be multidrug-resistant to most commercially available antibiotics. The aim of this study is to develop a colorimetric assay to quantitatively detect the target DNA of A. baumannii based on unmodified gold nanoparticles (AuNPs) from different clinical samples (burns, surgical wounds, sputum, blood and urine). A total of thirty-six A. baumannii clinical isolates were collected from five Iraqi hospitals in Erbil and Mosul provinces within the period from September 2020 to January 2021. Bacterial isolation and biochemical identification of isolates

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

The Tulostoma genus, known as stalkballs or stalked puffballs, belongs to the Agaricaceae family. This study was designed to identify an unknown fungal species collected from the Al‐Dujail district in Iraq based on morphological examination and molecular analysis of the internal transcribed spacer (ITS) region. Between April and July 2019, samples were collected from garden soil in the Al‐Dujail district, Salah Al‐Din Governorate, Iraq. Morphological characteristics were documented using light microscopy. Genomic DNA was extracted and purified, and the ITS region was amplified using conventional PCR with specific primers. The amplified products were sequenced, and phylogenetic analysis was conducted using MEGA11 software. Morp

Five serological methods for detection of Brucella were compaired in this study, Four of the methods are commonely used in the detections:- 1-Rose-Bengal: as primary screening test which depends on detecting antibodies in the blood serum. 2-IFAT: which detects IgG and IgM antibodies in the serum. 3-ELISA test: which detects IgG antibodies in the serum. 4-2ME test: which detects IgG antibodies The fifth methods. It was developed by a reasercher in one of the health centers in Baghdad. It was given the name of spot Immune Assay (SIA). Results declares that among (100) samples of patients blood, 76, 49, 49, 37, and 28. samples were positive to Rose Bengal, ELISA, SIA, 2ME and IFAT tests, respectively. When efficiency, sensitivity and specific

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS,