Choosing antimicrobials is a common dilemma when the expected rate of bacterial resistance is high. The observed resistance values in unequal groups of isolates tested for different antimicrobials can be misleading. This can affect the decision to recommend one antibiotic over the other. We analyzed recalled data with the statistical consideration of unequal sample groups. Data was collected concerning children suspected to have typhoid fever at Al Alwyia Pediatric Teaching Hospital in Baghdad, Iraq. The study period extended from September 2021 to September 2022. A novel algorithm was developed to compare the drug sensitivity among unequal numbers of Salmonella typhi (S. Typhi) isolates tested with different antibacterials.

It is generally accepted that there are two spectrophotometric techniques for quantifying ceftazidime (CFT) in bulk medications and pharmaceutical formulations.  The methods  are described as simple, sensitive, selective, accurate and efficient techniques. The first method used an alkaline medium to convert ceftazidime to its diazonium salt, which is then combined with the 1-Naphthol (1-NPT) and 2-Naphthol (2-NPT) reagents. The azo dye that was produced brown  and red in color with absorption intensities of ƛmax 585 and 545nm respectively. Beer's law was followed in terms of concentration ranging from  (3-40) µg .ml^-1 For (CFT-1-NPT) and (CFT-2-NPT), the detection limits were 1.0096 and 0.8017 µg.ml^-1, respec

Keys to four genera and twelve species of the subfamily Phlaeothripinae (Phlaeothripidae) were constructed, these are: Haplothrips; Karnyothrips; Phlaeothrips; and Dolicholepta ,and the species are: Haplothrips cerealis Priesner; Haplothrips tritici kurdjumov, Haplothrips hukkineni Priesner; Haplothrips subtilissimus (Haliday) ؛ Haplothrips reuteri Karny; Haplothrips jasonis Priesner; Haplothrips sallloumensis Priesner ; Haplothrips pharao Priesner ; Phlaeothrips sycomri Priesner ; Karnyothrips flavipus (Jones); Karnyothrips melaleucus (Bagnall) ; Dolicholepta micrurus (Bagnall). These were collected from Baghdad

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

the study including isolation and identification of candida spp causing UTIs from patintes coming to al-yarmouk hospital

Ag nanoparticles were prepared using Nd:YAG laser from Ag matel in distilled water using different energies laser (100 and 600) mJ using 200 pulses, and study the effect of the preparation conditions on the structural characteristics of and then study the effect of nanoparticles on the rate of killing the two types of bacteria particles (Staph and E.coli). The goal is to prepare the nanoparticle effectively used to kill bacteria.

The haplotype association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease.Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls.It starts with inferring haplotypes from genotypes followed by a haplotype co-classification and marginal screening for disease-associated haplotypes.Unfortunately,phasing uncertainty may have a strong effects on the haplotype co-classification and therefore on the accuracy of predicting risk haplotypes.Here,to address the issue,we propose an alternative approach:In Stage 1,we select potential risk genotypes inste