Background: Reliable detection the etiological agent of amoebic dysentery and extra-intestinal amoebiasis have Public health importance specially in asymptomatic human and animals, Since the acquisition of pet dogs in the recent period has become widespread in our city. Aim: To give correct perception of infection rate in asymptomatic individuals (human and domestic dogs) for the first aspect and about detection and diagnosis of the pathogenic species of Entamoeba histolytica from another morphologically similar and commensal one using the molecular technique in stool samples of asymptomatic individuals the second aspect. Methods: During the study period from the beginning of September 2020 to the end of February 2021, a total of 95 stool sample was collected from asymptomatic 71 male and 24 female ages between 20-45 years old also 50 fecal samples of asymptomatic domestic dogs (male) belongs to some patients regardless of the breed were in counter. Results: Microscopic and molecular diagnosis for E.histolytica was done using traditional wet mount method and Real Time polymerase chain reaction (RT-PCR) employing phospholipase gene respectively. The result highlighted the microscopic diagnosis of cyst stage in 33 asymptomatic patient out of 95 (34.73%) with significant differences P<0.05 between males 22/71(66.66%) and females 11/24 (33.33%). For domestic dogs, 9 out of 50 samples (18%) were detected as positive. On the other hand the molecular diagnosis results showed presence of E.histolytica in 10 sample out of 33 (30.3%) with non significant differences P>0.05 between males 7/22 (31.81%) and females 3/11 (27.27%) while for domestic dogs no positive results were recorded. Conclusion: The presence of the pathogen E.histolytica in asymptomatic patients. The microscopic examination of stool sample show a possibility of error to differentiate pathogenic E. histolytica from those of morphologically similar non-pathogenic species lead to inaccurate results therefore, the molecular methods must be adopted for diagnosis. Domestic dogs do not pose a risk of transmitting E.histolytica infection but it can transmit other types of pathogens.
In a connected graph , the distance function between each pair of two vertices from a set vertex is the shortest distance between them and the vertex degree denoted by is the number of edges which are incident to the vertex The Schultz and modified Schultz polynomials of are have defined as:
respectively, where the summations are taken over all unordered pairs of distinct vertices in and is the distance between and in The general forms of Schultz and modified Schultz polynomials shall be found and indices of the edge – identification chain and ring – square graphs in the present work.
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Human identification is crucial in forensics for the investigation of large-scale disasters such as fires, epidemics, earthquakes, and tsunamis. Even though biometric identification using panoramic dental radiography (PDR) has been the subject of several studies in the literature, further study remains a necessary and challenging issue. In this research, a human identification system was developed based on a convolutional neural network (CNN) and contour transform (CT). The proposed system was implemented on a total of 1540 PDR from 302 individuals. The preprocessing applied to PDRs for enhancing and taking the Region of Interest (ROI). The features were extracted using CT transform. These features were fused with features extracted
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This study was conducted to know the effect of some phenotype characteristics of corn plant on infection by (CSB), using 13 genotypes of corn plant, planting during autumn season 1997 and 1998. The result revealed that the mean of plant height (with male flowering) was (183-219) cm, the mean of leaf No./ plant in all genotypes was (16-18) leaf but the leaf area of plant was (4350-6249) cm2, there were significant differences of phenotype characteristics between genotypes ,the percentage of infection by (CSB) was (5.9-35.9),% the result showed that the phenotype characteristics had non effect on the infection percentage by (CSB) and the correlation coefficient was not significant.
Background: COVID-19 is an ongoing disease that caused, and still causes, many challenges for humanity. In fact, COVID-19 death cases reached more than 4.5 million by the end of August 2021, although an improvement in the medical treatments and pharmaceutical protocols was obtained, and many vaccines were released. Objective: To, statistically, analyze the data of COVID-19 patients at Alshifaa Healthcare Center (Baghdad, Iraq). Methods: In this work, a statistical analysis was conducted on data included the total number, positive cases, and negative cases of people tested for COVID-19 at the Alshifaa Healthcare Center/Baghdad for the period 1 September – 31 December 2020. The number of people who got the test was 1080, where 424 w
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Background: Alternative natural therapy by plants extracts had opened wide door for the use of natural products as an alternative therapy instead of many antibiotics and drugs , which had many harmful side effects.Also, an increased interest has been centered on the industrial wastes, especially plant raw materials which contain phenols (e.g. Pomegranate peel and Bay leaves) which is a sources of natural antioxidants ,which are on the contrary of synthetic antioxidants that had restrict use due to their health risks , carcinogenesis and toxicity .
Objectives :This study was done to fi
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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
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Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T
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