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Development of Biodegradable Thin Films for Efficient, Specific and Controlled Delivery of Anticancer Drugs

Thesis Info

Author

Irum Gul

Supervisor

Uzma Yunus

Institute

Allama Iqbal Open University

Institute Type

Public

City

Islamabad

Country

Pakistan

Thesis Completing Year

2019

Thesis Completion Status

Completed

Page

iv, 60.

Subject

Chemistry

Language

English

Other

Call No: 547.2 IRD; Publisher: Aiou

Added

2021-02-17 19:49:13

Modified

2023-01-06 19:20:37

ARI ID

1676709901638

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دکھاں دی پنڈ چائی جاواں

دکھاں دی پنڈ چائی جاواں

دکھی سجن بنائی جاواں
دکھ سمیٹاں جگ دے سارے

سکھاں نال وٹائی جاواں
دکھیاں نوں میں سینے لاکے

سکھاں سیر کرائی جاواں
ہر پاسے ای کیرے کر کے

پھلاں باغ لگائی جاواں
جنہاں روگ اولے لگے

اوہناں روگ ونڈائی جاواں
ونڈاں خوشیاں تے ودھ جاون

ونڈاں دکھ گھٹائی جاواں

تاریخ کبیر میں امام بخاری کا رواۃ پر تنقید کے اسلوب کاجائزہ

Muḥadithīn have played a dynamic role in the preservation and compilation of Ḥadīth of the Prophet (SAW). Among them the contribution of Imam Bukhārī is unavoidable and remarkable in the field of Ḥadīth and its sciences. Since, he is known “Hafiz and Compiler” and considered as “Imam” and “authority” in the field of both higher and lower criticism. His book "Al-Tārīkh al Kabīr" (08 volumes) is considered as one of the ancient books in field of Ḥadīth and its sciences. This paper aims to describe the methodology of Imam Bukhārī in Al-Tārīkh al Kabīr. He described the biography of thirteen thousand seven hundred and seventy nine only (13779) in alphabetic order. Although his methodology was to mention names of the narrators alphabetically, but in respect with the Prophet (SAW), he gave place to eleven narrators among the companion whom names were started with the names of “Muhammad”. In the Methodology of Imam Bukhārī (RA), it is found that either the narrators are rejected or given authenticity, on the basis of not only his own examinations but he relied on the sayings of other Muḥadithīn as well. It is also pertinent to mention that he awarded degree to a little number of the narrators while left over most of the narrators undecided, because the main objective of the book was to portray the biographies of the narrators rather to make analysis of all the narrators.

Assessing Independence and Causality in Time Series

Assessing independence of two series was, is and will be the most fundamental goal of econometric/economic practitioners. Most of the economic (especially macroeconomic) data are time dependent and economists are interested to validate different economic theories using sophisticated data analysis tools. At the end of 19th century Karl Pearson developed coefficient of correlation to assess correlation between two series, however Yule (1926) criticized the use of this coefficient for time series because of its autocorrelated behavior. Haugh (1976) was considered the first to propose a measure of correlation for time series. His idea of pre-whitening the series’ first and then apply correlation coefficient became very famous. Since then different versions of Haugh test were developed. The latest version was developed by Rehman and Malik (2014) that is also based on the same idea, however, the pre-whitening process became more refined and modified. For the last four decades, several tests of independence for time series are developed. Every test was developed on a particular property of underlying assumptions, and it works in its own domain and fails to work in other situations/domains. Researchers working in this area, presented few results to compare proposed test and one or two previously developed tests and concluded superiority of his/her proposed test. These studies include Hong (1996b), Duchesne and Roy (2003a) and so on. These comparisons are ad hoc in nature and no comprehensive study available in the literature to unfold the strengths and weaknesses of these tests. We organized a comprehensive Monte Carlo simulation study to compare tests of independence and selected a broad data generating process in a common framework. For this purpose, standard stringency criteria of Zaman (1996) has been used. In presented study, we have selected eleven available tests of independence for time series. To use stringency criteria, tests of independence should maintain a stable size and then based on its powers we can decide about the appropriateness of the test. For checking the size stability of the tests, we have used twenty-one different specifications of stochastic part in our data generating process, similarly two specifications of deterministic part have been used for each stochastic part case. So, we have tested size stability at total forty-two different combinations of data generating process. Simulated critical values were used, as past studies suggested that asymptotic critical values are not appropriate. All eleven tests of independence have their sizes around nominal size of 5%. Following the stable size, power analysis has been carried out for the same combinations of the data generating process and results suggests that Atiq test performs well in small sample size in almost all cases. PhamRoy test remains on second position in small samples but in many situations, it supersedes Atiq test in medium and large sample sizes. Haugh test remains at third place in almost all cases of the simulation study however the difference between the shortcomings of Haugh and PhamRoy test are very large. The remaining tests have not shown any considerable performance. Kim Lee, LiHui and Bouhaddioui tests considered worst in all sample sizes and with and without deterministic part cases. Another important contribution of this study is to compare three important techniques used to check the dependence of two or more-time series, these include cointegration, Granger causality and Tests of independence for time series. Using renowned Keynesian function of income and consumption, we applied these tests on real economic data of income and consumption of 100 countries from 1970 to 2014. The results depict that three selected tests of independence, i.e. Atiq, PhamRoy and Haugh tests have appreciable power gains and lower size distortions. Again, it is observed that Atiq test shows better empirical power gain with least size distortion. PhamRoy and Haugh tests also shows good performance, have good power gains and small size distortions. However, five cointegration tests which are considered relatively better by Khan (2017) and famous Granger causality test have shown very poor performance both in terms of real empirical size and power.