Leishmania is one of the protozoan parasites that are transferred to human by infected sand flies and gives rise to a range of diseases entitled as Leishmaniasis. More than 20 known species of Leishmania can infect humans and cause various clinical symptoms. Three most known clinical manifestations are Cutaneous Leishmaniasis (CL), Mucocutaneous Leishmaniasis (MCL) and Visceral Leishmaniasis (VL) (kala-azar or black fever). The difference in the clinical form dependent on several factors: species of Leishmania, type of vector that transmits the Leishmania, and the immune status of an infected individual. The current drugs which are used as anti-leishaminial treatment are characterized by enormou

Genistein (GEN) is The major isoflavone found in soybeans, has a number of cardiovascular health benefits, Postmenopausal syndrome and osteoporosis. A direct flow injection analysis method for estimation of (GEN) in pure and supplements formulation . This system is based on diazotization coupling reactions between procaine penciline (PR) and genistein in basic medium, they formed yellow dyes have maximum absorption at 416 nm. Calibration curve were constructed over different GEN concentrations, linearity for GEN was 10-100 µg.mL-1 and detection limits of 1.51 ?g/mL. In the FIA technique, all analytical factors were analyzed and optimized. The established method was successfully used to determine GEN in the formulations of its supplement

     In this study, out of 50 isolates of some nosocomial infections from some Baghdad hospitals, only 13 (26%) were identified as Escherichia coli. Depending on selective media, morphological and biochemical tests the species was then confirmed by molecular methods. Later on  antimicrobial resistance test was performed by the Kirby-Bauer method. The molecular characterization of blaTEM and blaCTX-M genes in different clinical isolates of E. coli was done through polymerase chain reaction (PCR) by utilizing special primers. These genes were positive to only 4 (30.7%) isolates. The sequence of nucleotides of positive genes was carried out for four isolates. The results showed that there was no vari

A simple, low cost and rapid flow injection turbidimetric method was developed and validated for mebeverine hydrochloride (MBH) determination in pharmaceutical preparations. The developed method is based on forming of a white, turbid ion-pair product as a result of a reaction between the MBH and sodium persulfate in a closed flow injection system where the sodium persulfate is used as precipitation reagent. The turbidity of the formed complex was measured at the detection angle of 180° (attenuated detection) using NAG dual&Solo (0-180°) detector which contained dual detections zones (i.e., measuring cells 1 & 2). The increase in the turbidity of the complex was directly proportional to the increase of the MBH concentration

The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.

     Cadastral map environment is directed, more than ever before, towards Artificial Intelligence use to produce fast and accurate maps and keep up with the huge population growth. The traditional approach currently in production of maps is expensive and effort-intensive in addition to be considered as highly time-consuming process.  UAV-based cadastral mapping imagery that use automatic techniques are newly being exploited to accelerate the process of production or updating. The state-of-the-art intelligent algorithms are capable to extract land boundaries from images better than conventional techniques. This paper presents an automatic workflow of cadastral map production based on land boundary and automatic f

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener