The aims of this study are to explore the commercial artifacts in the following three kinds of vegetables oils, Nigella Sativa, Trigonella foenum-graecum Linn,and Zingiber officinale. These oils have been very popular medicinal plants which are commonly used in traditional medicine .These commercial oils have been compared with the extracts of these plants.
The physical properties of extracts and commercial oils of these plants have been stuied. We observed that the refractive index of the plants matches and non-significant, while specific gravity of Nigella Sativa has similar specific gravity in both extracts and commercial oil in contrast with Trigonella foenum Linn,and Zingiber officinale and we found significant difference (P&lt

The study was carried out to study the quality of 7 samples of imported frozen chicken that are available in locally markets. These samples were collected from Baghdad markets in June 2010. The results were showed that the all samples were not content the name of company and batch number one the labeling, while the microbial test refer to found contamination in all samples, but it in the limited of Iraqi standers specification for frozen chicken, also note Staphylococcus aureus in all samples, the samples C1 and C2 have Salmonella ohio, while not observe Coliform bacteria in all samples.

Background: Parvovirus B19 is a human pathogenic virus associated with a wide range of clinical conditions. During pregnancy congenital infection with parvovirus B19 can be associated with poor outcome, including miscarriage, fetal anemia and non-immune hydrops.  

Objective: The study aimed to determine the prevalenceof Parvovirus B19 DNA in pregnant women attending the Military hospital in Khartoum, demonstrating the association between the virus and poor pregnancy outcomes.

Subjects and methods: This study was a cross sectional study, testing pregnant Sudanese women whole blood samples (n= 97) for the presence of Parvovirus B1

     Today in the digital realm, where images constitute the massive resource of the social media base but unfortunately suffer from two issues of size and transmission, compression is the ideal solution. Pixel base techniques are one of the modern spatially optimized modeling techniques of deterministic and probabilistic bases that imply mean, index, and residual. This paper introduces adaptive pixel-based coding techniques for the probabilistic part of a lossy scheme by incorporating the MMSA of the C321 base along with the utilization of the deterministic part losslessly. The tested results achieved higher size reduction performance compared to the traditional pixel-based techniques and the standard JPEG by about 40% and 50%,

The current study was designed to investigate the presence of aflatoxin M1 in 25 samples of pasteurized canned milk which collected randomly from some Iraqi local markets using ELISA technique. Aflatoxin M1 was present in 21 samples, the concentration of aflatoxin M1 ranged from (0.25-50 ppb). UV radiation (365nm wave length) was used for detoxification of aflatoxin M1 (sample with highest concentration /50 ppb of aflatoxin M1 in two different volumes ((25 & 50 ml)) for two different time (15 & 30 min) and 30, 60, 90 cm distance between lamp and milk layer were used for this purpose). Results showed that distance between lamp and milk layer was the most effective parameter in reduction of aflatoxin M1, and whenever the distance increase the

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

The development of Web 2.0 has improved people's ability to share their opinions. These opinions serve as an important piece of knowledge for other reviewers. To figure out what the opinions is all about, an automatic system of analysis is needed. Aspect-based sentiment analysis is the most important research topic conducted to extract reviewers-opinions about certain attribute, for instance opinion-target (aspect). In aspect-based tasks, the identification of the implicit aspect such as aspects implicitly implied in a review, is the most challenging task to accomplish. However, this paper strives to identify the implicit aspects based on hierarchical algorithm incorporated with common-sense knowledge by means of dimensionality reduction.

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has