1,075 research outputs found

    The Causal Relationship between Foreign Direct Investment and Current Account: An Empirical Investigation for Pakistan Economy

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    This paper investigates relationship between FDI and current account (CA) in Pakistan using the Johansen-Juselius cointegration technique and the Granger causality test. The study results indicate that FDI and CA are cointegrated and thus exhibit a reliable long run relationship. The Granger causality test findings indicate that the causality between FDI and CA is uni-directional. However, there is no short run causality from FDI to CA and vice versa. Therefore, as a policy implication that FDI inflows may cause to the deterioration of the balance of payments in the long run should be taken into account when policy makers decide to implement policies to attract foreign investors.Asia; Pakistan; Cointegration; Granger; causality; FDI; Current Assount; error correction

    Role of Effective Feed Back in Multiple Choice Questions (MCQs) Designing for Faculty Development

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    errors in multiple choice questions (MCQs) designing by the faculty members and to obtain need assessment feedback for faculty development for MCQ designing. Methods: In this study, all MCQs submitted by faculty members of Islamic International Medical College (IIMC) over a period of one year and three months from January 2009 to April 2010 were reviewed from time to time by the assessment committee. A total of 922 MCQs were reviewed. The reviews were compiled and analyzed to find out the frequency and types of errors made inadvertently in the structure and design of MCQs. Results: During the study period, the faculty members submitted a total of 922 MCQs. Spectrum of errors in MCQs ranged from spellings to complex questions to question cues. A total of 40% items qualified for being included in final assessment Conclusion: Review process is very important in improving the quality of items

    Personalized drug concentration predictions with machine learning: an exploratory study

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    Background: The dose individualization by therapeutic drug monitoring (TDM) can be improved if population-based reference ranges are available, as there is large inter- and intrapatient variability. If these ranges are not available, dose individualization may not be optimal. Machine learning can help achieve accurate drug dose settings and predict the resultant levels.Methods: Two random forest models, a multi-class classifier to predict dose and a regression model to predict blood drug level were trained on 320 patients’ data, consisting of their age, sex, dose and blood drug level. The classifier consisted of 1000 estimators (decision trees) and the regression model consisted of 1300 estimators. The model was evaluated on randomly split test set having 10% of the total dataset size. The regression model was compared against k-Nearest neighbor and linear regression models. The classifier was evaluated using accuracy, precision, and F1 Score; the regression model was evaluated using R2, Root mean squared error, and mean absolute error.Results: The classifier had an out-of-sample accuracy of 68.75%, average precision of 0.7567, and an average F1 score of 0.6907. The regression model had an out-of-sample R2 value of 0.2183, root mean squared value of 3.7359, and a mean absolute error of 2.5156. These values signify an average classification performance, and a below-average regression performance due to small dataset.Conclusions: It is possible for machine learning algorithms to be used in therapeutic drug monitoring. With a well-structured, rich, and large dataset, a very accurate model can be built

    The impact of information and communication technologies (ICTs) on academic performance of medical students: an exploratory study

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    Background: Information and Communication Technology (ICT) has a potential to improve teaching and learning process. There are conflicting reports on the effect of ICT on student`s outcome. Though there is an early indication of positive impact, but the technology has a potential to have a detrimental effect. The present study was taken up to explore the effects of ICT on medical student’s academic performance.Methods: All the second professional students were given the questionnaire. Only 75 students had filled up the questionnaires completely.Results: The study population consisted of 48.00% males and 52.00% females. 97.33% students had smart phones, 44.00% had a laptop too. 10.66% students got less than 50% marks in the second professional examination, 14.66% got 50-59% marks, 62.66% got 60-69% marks and 12.00% got 70% or more marks. A low negative correlation was found between academic performance and possession of a smart phone (r= -0.062), and between academic performance and possession of a laptop (r= -0.029). A moderate negative correlation was found between academic performance and the time spent on a smart phone or laptop (r = -0.309). The correlations between academic performance and gender, and academic performance and the time spent on mobile phones or laptops were found statistically significant (p=0.000 and 0.007 respectively).Conclusions: Though ICT has capabilities of improving student`s academic performance, but it has a potential to have a negative effect if not used rationally. There is a vital need to sensitize the students about the potential academic risks associated with improper use of ICT. Students should be assisted and guided on how to use it judiciously

    Nutrition and Indirect Calorimetry

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    Nutrition support is important in the care of patients with both acute and chronic illness. Optimizing nutritional support for the critically ill and patients with acute and chronic respiratory disorders has been shown to shorten length of stay, shorten duration of mechanical ventilation, lower health-care costs and reduce morbidity and mortality while improving functional quality of life. Nutritional requirements are difficult to predict in patients diagnosed with cancer due to their disease processes, altered inflammatory responses and metabolic rates among many other variables. Often predictive equations are used to estimate energy requirements and the average dietary energy intake needed to maintain energy balance. Energy requirements can be estimated through the use of over 200 predictive equations. Utilization of indirect calorimetry as the ‘gold standard’ for measuring resting metabolic rate (RMR) and resting energy expenditure (REE) can provide support in all states of health and disease. This chapter will identify and discuss the role of indirect calorimetry, examine the reasons why indirect calorimetry is more reliable than predictive equations in determining a patient’s calorie requirement, and when it is most applicable to incorporate indirect calorimetry measurements in the care of cancer patients

    Islamic (Sukuk) vs. Conventional Financing: Analysis of Profitability

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    Over the last decade, Islamic Financials (Sukuk) emerged as a pioneering capital market instrument. One of the fundamental reasons for the emerging demand of Islamic Financing (Sukuk) includes its adherence to the finance in accordance to the Islamic values, avoiding Riba, which is the generation of money from money such as usury or interest. Sukuk issues have notably proliferated, which fuels the debate regarding the between the conventional and the Islamic finance. To investigate the impact of Islamic and Conventional Financials on shareholders’ wealth, this study takes the profitability ratios (including ROA, ROE, ROCE, and NPM) of 11 companies issuing Islamic Financials and 11 companies issuing Conventional Financials from the period between 2010 and 2015 and compares the profitability of both financials. The findings reveal the Islamic Financials (Sukuk) to be a significantly high source of profitability for a company along with the other clients’ catchy determinants such as religious principles, sharia-compliant instruments, and interest (Riba) free financing

    Design of PVT System for Typical Indian Village and its Analysis for the Reduction of Co2 Emission

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    This dissertation work outline is that by using Solar Photovoltaic (SPV) System in typical Indian villages, how we can remove the CO2 emissions. Requirement of PVT system is calculated according to the actual energy demand of a village population and its impact on CO2 reduction is assessed. It is, therefore, important to consider the possibility of utilizing the renewable energy resources, which do not degrade the environment. It is a well-known fact that the average living standard of rural population is lower than that of urban population. One way of improving the living standards is to provide better energy facilities. This will also check the migration of population from rural to urban area. This migration causes social and economic imbalances and is, there on, not desirable

    catena-Poly[(diaqua­strontium)-bis­(μ-2-methyl-3,5-dinitro­benzoato)]

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    The title compound, [Sr(C8H5N2O6)2(H2O)2]n, essentially consists of a one-dimensional polymeric network with Sr2O2 rings extending along the [100] direction. The range of Sr—O bond lengths is 2.4822 (13)–2.8113 (13) Å. C—H⋯O and O—H⋯O hydrogen-bonding inter­actions stabilize the mol­ecules in the form of a two-dimensional polymeric network parallel to (001). One of the nitro groups is disordered over three sets of sites with the occupancy ratio of 0.46:0.32:0.22

    catena-Poly[bis­(μ3-2-methyl­benzoato)disilver(I)]

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    The crystal structure of the title compound, [Ag2(C8H7O2)2]n, features polymeric chains extending along the a axis, with the two Ag+ cations in a distorted trigonal coordination. The range of Ag—O bond lengths is 2.169 (2)–2.433 (2) Å, whereas the Ag⋯Ag separations are in the range 2.8674 (4)–3.6256 (5) Å. The 2-methyl­benzoate groups are oriented at a dihedral angle of 60.7 (1)° with respect to each other

    Comparative assessment of antibiotic self-medication practices among under-graduate medical students and general population

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    Background: Self-medication with antibiotics is a global problem and increases the risk of antibiotic resistance which impacts morbidity and mortality.Methods: A total of 180 Medical students and the same number of people from general population were given a pre-validated questionnaire. The total respondents were 168 among general population and 173 among medical students. Results: 21.42% respondents from general population and 82.08% medical students practiced antibiotic self-medication. 66.66% respondents from general population practiced antibiotic self- medication to save time and money. 57.04% medical students had previous experience of treating similar symptoms.83.33% respondents from general population and 89.43% medical students used antibiotics to treat fever, cough, cold, sore throat and similar symptoms. 50.00% respondents from general population consulted the chemist/pharmacist before using the antibiotics.38.02% students consulted their textbooks for drug information. Only 16.66% respondents from general population and 24.64% students continued the antibiotics till full recovery.Conclusions: Antibiotic self- medication is more prevalent among medical students as compared to general population. Medical students need to be targeted repeatedly during their education and be taught the value of using antibiotics with caution. Public awareness and strict enforcement of law to control the sale of antibiotics without a valid prescription are needed to minimize antibiotic self- medication and associated risks
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