Impact of Qualification Framework in United Arab Emirates: A case study of Dubai Pharmacy College undergraduate curriculum

Purpose: To examine the impact of applying Qualifications Framework Emirates (QFE) on the undergraduate Bachelor of Pharmacy (BPharm) curriculum in the United Arab Emirates (UAE) context.Method: Curriculum developers (faculty and other stakeholders) have selected appropriate teaching, learning and assessment strategies for their course/s according to the level descriptors defined by the QFE. Such level descriptors serve as a common platform to support national and international accreditation requirements. In order to align the BPharm curriculum with QFE, an outcomes-based approach had been adopted.Results: The program benefited in many aspects, particularly, in providing a frame of reference, enabling the offered qualification to be described and compared with similar programs, providing a baseline to compare UAE qualifications with other national and/or international ones, recognising the achievement in learning with different complexity levels. Other benefits include enabling the recognition of prior learning, identifying the learning outcomes needed for new qualifications, facilitating alignment and integration of the quality of educational and experiential outcomes with economic and social development and improving transparency of the individual qualifications through learning outcomes mapping.Conclusion: Application of QFE to BPharm curriculum at Dubai Pharmacy College ensures asystematic approach in designing and implementing the curriculum, and awarding a principalqualification, which in turn are necessary for effective quality assurance.Keywords: Qualifications Framework Emirates (QFE), Pharmacy curriculum, Outcome-based education, Quality assurance, Competencie

The Power of a Sound Mind: Exploring Meditation and Sound Therapies for Treating the Emotional Impact of Tinnitus

Tinnitus is described as a sound perceived by an individual that has no external source. Some individuals with tinnitus can habituate to this phantom sound, while others become emotionally disturbed by it. There are several theories which attempt to rationalize the cause of tinnitus, and various treatments which aim to eliminate, mask, or facilitate habituation to one’s tinnitus. Current common treatments include sound therapies and cognitive-behavioral therapy (CBT), either in isolation or in combination with one another. However, not all these treatments aim to address the emotional impact of tinnitus. Novel treatments are emerging, with some attempting to reduce the emotional impact tinnitus may have on the individual by utilizing sound in a therapeutic manner and incorporating CBT or other mindfulness-based treatments. More research is required to confirm the efficacy of current and novel treatments. Based on the findings of this literature review, CBT and mindfulness-based treatments are most promising in their ability to reduce the emotional distress some individuals with tinnitus are facing

CYTOTOXIC EFFECT OF PEPTIDE FUNCTIONALIZED SILVER NANOPARTICLES SYNTHESIZED FROM ALOIN ON BREAST CANCER CELL LINE

Objective: The aim of the present study is to synthesize the silver (Ag) nanoparticle using Aloin with a focus on its antibacterial, antioxidant, and anticancer activity. Methods: The silver nanoparticles were synthesized using Aloin and were determined by UV-Visible spectrum. It was further characterized by scanning electron microscope (SEM), zeta potential, and dynamic light scattering (DLS). The Fourier transform infrared analysis was also carried out for the Aloin. Results: The UV-Visible absorption spectrum of the synthesized silver nanoparticles has shown the absorption peak at 439nm which proves the formation of silver nanoparticles in the solution. The SEM analysis revealed that the Ag nanoparticles were spherical in shape. The IR spectra showed that there are 6 functional groups are present in Aloin extract. The synthesized nanoparticles are found to be highly stable with an average particle size of 130.7nm which was confirmed by zeta potential and DLS analysis. The synthesized nanoparticles had a good antibacterial and antioxidant activity. It shows a very good cytotoxic effect against breast cancer cell line. Conclusion: The present study suggests that the synthesis route is free from the requirements such as high energy, extended preparation time, and special equipments and thus can be used for large-scale synthesis in food industries for food preservation and these Ag nanoparticles can be used for its therapeutic purposes for developing a new drug against cancer

Posttraumatic stress disorder and psychiatric comorbidity following the 2010 flood in Pakistan: Exposure characteristics, cognitive distortions, and emotional suppression

© 2014 Washington School of Psychiatry. This study investigated the extent of posttraumatic stress disorder (PTSD) and psychiatric comorbidity among the 2010 flood victims in Pakistan and its relationship with disaster exposure characteristics, cognitive distortions, and emotional suppression. One hundred and thirty-one (F = 89, iM = 42) flood victims were assessed using the Posttraumatic Diagnostic Scale, the General Health Questionnaire-28, the Cognitive Distortion Scales, and the Courtauld Emotional Control Scale. The results showed that all victims met the diagnostic criteria for PTSD and scored above the cut-off for psychiatric caseness. Partial least squares modelling showed that disaster exposure characteristics were significantly correlated with PTSD and psychiatric comorbidity. Disaster exposure characteristics were also significantly associated with cognitive distortions which in turn were also significantly associated with PTSD and psychiatric comorbidity. Cognitive distortions were also correlated with emotional suppression which, however, was not associated with PTSD or psychiatric comorbidity. To conclude, the flood victims reported PTSD and psychiatric comorbid symptoms which were related to their subjective exposure to the flood. Such exposure led to the development of dysfunctional thinking patterns which in turn influenced distress symptoms

Intussusception among Infants Given an Oral Rotavirus Vaccine

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Diagnosis of enteric fever in the emergency department: a retrospective study from Pakistan

Background:Enteric fever is one of the top differential diagnoses of fever in many parts of the world. Generally, the diagnosis is suspected and treatment is initiated based on clinical and basic laboratory parameters.Aims: The present study identifies the clinical and laboratory parameters predicting enteric fever in Patients visiting the emergency department of a tertiary care hospital in Pakistan.Methods:This is a retrospective chart review of all adult Patients with clinically suspected enteric fever admitted to the hospital through the emergency department during a 5-year period (2000-2005).Results:A total of 421 emergency department Patients were admitted to the hospital with suspected enteric fever. There were 53 cases of blood culture-positive enteric fever and 296 disease-negative cases on culture. The mean age in the blood culture-positive group was 27 years (SD: 10) and in the group with negative blood culture for enteric fever, 35 years (SD: 15) with a male to female ratio of 1:0.6 in both groups. Less than half (48%) of all Patients admitted with suspected enteric fever had the discharge diagnosis of enteric fever, of which only 13% of the Patients had blood culture/serologically confirmed enteric fever. None of the common clinical and laboratory parameters differed between enteric fever-positive Patients and those without it.Conclusion:Commonly cited clinical and laboratory parameters were not able to predict enteric fever

Online prediction of DGA results for intelligent condition monitoring of power transformers

Transformers form a major part of a power system in transmission as well as distribution of power. Considering the criticality, finance, and time involved in repair, periodic condition monitoring and maintenance of transformers are the key to ensure electrical safety as well as stable operation of the large interconnected power system. Dissolved Gas Analysis (DGA) is an established tool used to determine the incipient faults within the transformer by analyzing the concentration of different gases in the transformer oil and giving early warnings and diagnoses. Currently, transformers worldwide utilise online sensors to monitor dissolved gases and moisture content in oil. The online DGA sensor uses a small amount of oil from transformer to perform real-time DGA analysis and gives the ppm content of dissolved gases for further course of action. Considering the large quantity of assets and the huge amount of data produced, it is imperative to develop a tool to aid the operators in assimilating the available data for diagnosis and proactive decision making. The present study improvises AI techniques to predict future dissolved gas concentrations using real time DGA data collected from the transmission utility of the country. The prediction helps to forecast the trend of development of incipient faults in the transformer. The complete project scope is to develop a highly reliable diagnostic tool to emulate the decision-making ability of a human expert in transformer DGA analysis to enhance transformer life. In the present paper, models based on Auto-regressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Vector Auto Regression (VAR) are implemented to predict DGA data of three in-service transformers. DGA data is forecasted for up to 8 monthly samples in the future, and the accuracy of results is compared with each other. The LSTM-VAR combined model is seen to provide the best results among them