Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

In the early 90s military operations and United Nations Special Commission “UNSCOM” teams have been destroyed the past Iraqi chemical program. Both operations led an extensive number of scattered remnants of contaminated areas. The quantities of hazardous materials, incomplete destructed materials, and toxic chemicals were sealed in two bunkers. Deficiency of appropriate destruction technology led to spreading the contamination around the storage site. This paper aims to introduce the environmental detection of the contamination in the storage site area using geospatial analysis technique. The environmental contamination level of nutrients and major ions such as sulphate (SO₄), potassium (K), sodium (Na), magnesi

A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as

This work aims to investigate the inhibition of vitality of Streptococcus mutans, which is the causative agent of caries. A 632.8 nm He-Ne laser with the output power of 4.5mW was used in combination with toluidine blue O (TBO) at the concentration of 50μg/ml as a photosensitizer. Streptococcus mutans was isolated from 35 patients if carious teeth. Three isolates were chosen and exposed to different energy densities of He – Ne laser light 3.8, 11.7, 34.5 and 104.1 J/cm². After irradiation, substantial reduction was observed in the number of colony forming units (CFU)/ ml. The reduction in the number of CFU was increasing as the dose increased.

N, N′- bis[4-hydroxy phenyl] pyromillitdiimide [II] was prepared from the corresponding diamic acid , which was transfered to its new ester by the reaction with chloroethyl acetate [III ], [III] was used to prepare the novel hydrazide derivative [IV] , which was allowed to react with several aldehydes to yield the hydrazones [V – IX]. All the new compounds were synthesized , and characterized by their melting points .HNMR for some of them1FTIR,C,H,N analysis and ,

In this work, a functional nanocomposite consisting of multi walled carbon nanotubes combined with nanoparticles of silver and Pomegranate peel extract (MWCNTs- SNPs -NPGPE) was successfully synthesized using ultra sonic technique. The nanocomposite has been characterized using Transmission electron microscope (TEM), XRD, Energy dispersive X-ray spectroscopy (EDS) UV-Vis and FTIR. The obtained results reveal that the MWCNTs-SNPs-NPGPE nanocomposite exhibits form of nanotubes with rough surfaces and containing black spots, which are the silver nanoparticles. The dimensions of this tube are 161 nm in length and 60 nm in width with nanoparticles of silver not exceeding 20 nm. The XRD pattern of the prepared MWCNTs-SNPs-NPGPE nanocomposite s