This study was aimed to investigate the load of bacterial contaminant in fresh meat with different types of bacteria.One handered and seven samples were collected from different regions of Baghdad . These samples included 37 of fresh beef 70 of fresh sheep meat. All samples were cultured on different selective media to identitfy of contaminated bacteria .The result revealed that The percentage of bacterial isolate from raw sheep meat were, % 23.8of StreptococcusgroupD,29.4 % of Staphylococcus aureus ,14.7 % of E.coli , %4.9of Salmonella spp, ,%3.5 of pseudomonas aeruginosa, %14.7.%14.7 of Proteus spp.% 2.1 of Listeria spp while the raw beef meat content %5.55 of Staphylococcus aureus, %8.14 of streptococcus group D , %5.18 %1.85 of E.coli,

ABSTRACT: Pathogenic bacteria responsible for the causation of many common diseases have been identified on currency notes. The present investigation was carried out on one hundred currency notes of all the denominations (50, 100, 250, 500 and 1000RY), obtained from different occupational mainly bus drivers, hawker street, vegetable vendor, restaurants and butchers and fish seller groups in Taiz city,Yemen. Identification and characterization revealed active participation of the following species of organisms in the ascending order of percentage as E. coli(50.28 %),Staphylococci aureus(14.04 %), Klebsiellaspp(4.39 %),proteus(4.39 %), salmonella(1.25 %), shigella(0.72 %), Coagulase negative staphylococcus(0.60 %), pseudomonas(0.50 %),

Background: The stethoscope is a tool that doctors use daily in the examination of patients and  it  can take part in the transmission of health care-associated infections. In a single day it may come in direct contact with multiple patients and the intra hospital environment  may be contaminated by various type of bacteria and possibly transmit to others.

Objective:- The study was to know the attitude and knowledge about   the stethoscope hygiene behavior among physicians  and to determine the types of  bacterial agents that can contaminate stethoscopes.

Type of the study: The study was a cross-sectional study

Metho

Al-Yusifia river was assessed at three sampling stations with study period from Autumn 2010 to the end of Summer 2011. The present investigation was carried out on diversity of fungi and bacteria from Al-Yusifia river, Baghdad city. During the study, a total of 12 fungal genus and 6 bacterial genus were isolated during the year seasons. The dominant fungus at the three stations were Penicillium sp., then Rhizopus and Trichophyton   megninii while the dominant bacteria was Escherichia coli and Klebsiella sp.

            The higher

Dust samples have been collected from three areas in Baghdad during dust storm occurred in 18th of June 2009 to characterize elemental particle size and composition by different techniques. The x-ray diffraction detected six minerals those are calcite, and quartz, present as a major components, dolomite, kaolinite, gypsum and plagioclase present as miner components .EDX detected some normal elements presented in local soil except traces of lead , nickel, and chromium. The particle size analysis by a set of sieves have revealed that the majority particle distribution was between (32 and 45)μm . To isolate the aerosol size, PM10 buoyancy method of powder in water showed a signifying amounts of particulate size .Scheerer’s method was app

Bis-anthraquinones with a unique molecular backbone, (+)-2,2’-epicytoskyrin A (epi) and (+)-1,1′-bislunatin (bis), was produced by endophytic fungi Diaporthe sp GNBP-10 associated with Gambir plant (Uncaria gambier). Epi and bis possess robust antimicrobial activity toward various pathogens. This study focus on knowing the optimum condition of epi and bis production from Diaporthe sp GNBP-10. A series of culture media with various nutrient compositions was investigated in epi and bis production. The content of epi and bis was determined by measuring the area under the curve from TLC-densitometric (scanner) experiment. The linear regression analysis was then applied to obtain the results. The optimi

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into