The objective of the study was to develop microneedle (MN) patch, with suitable properties to ensure the delivery of a therapeutic level of lornoxicam (LXM) in a period suitable to replace parenteral administration in patients, especially those who fear needles. The used polymers were cold water-soluble polyvinyl alcohol (PVA) and polyvinylpyrrolidone (PVP) of low molecular weight with PEG 400 as plasticizer and Tween 80 (to enhance the release) using micro molding technique. Patches were studied for needle morphology, drug content, axial fracture force measurement and drug release while the optimized formulas were further subjected to pH measurement, folding endurance, ex vivo permeation study, histopathology study, stability study and

This research aimed to evaluate the level of readiness to teach science in the light of the information, media, and technology skills among undergraduate students at the Faculty of Edu-cation, King Khalid University. To achieve this goal, a descriptive and analytical approach was used. A list of readiness to teach science was prepared in the light of Information, media, and technology skills, and in the light of this list, a cognitive test, observation sheet, and attitude scale were prepared to assess readiness to teach science in its three aspects, cognitive, behavioral, and emotional. The sample of the research consisted of (42) students enrolled in field training courses at the sixth, seventh and eighth levels. Research tools were app

     Facing industrial companies many pressures and challenges due to rapid changes in the business environment of contemporary, which requires them to do their performance look more inclusive rather than limiting performance evaluation on the financial perspective in spite of its importance, prompting companies to rethink their reality competitive through the adoption of methodologies and new philosophies to manage competitiveness of total quality management, and re-engineering of production processes, and knowledge management,... etc., as This study framework cognitive and practical "to evaluate the performance of a company Diyala General Electric Industries and how to rehabilitate

The research aimed to evaluate the financial performance of the Public Company for the manufacture of medicines and medical supplies / Samarra - Iraq to know the strengths and weaknesses that affect its performance, as well as to compare its performance in the years between (2017-2019), which are characterized by security stability with its performance in previous years (2014 -2016) which is characterized by security instability, to assess the extent of its ability to achieve growth in performance, by answering the main question, what is the evaluation of the performance of the Public Company for the manufacture of medicines and medical supplies / Samarra - Iraq in the light of financial indicators?

           The international field has witnessed economical and technological developments which made the world one market . this increased the competence among the international dealers .  the market, thus comprises states, governments, international organizations, and giant economic blocs which all seek to unify the behavior of the game by dealing and seizing the opportunities and facing the threats which concern deregulation in all its forms .This led to a number of developments including the increasing number of mergers and posts which are considered investment alternatives.                &nb

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor