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اسمِ اعظم کے وہ اسرار کو پالیتے ہیں

اسمِ اعظم کے وہ اسرار کو پا لیتے ہیں
’’عشقِ سرکاؐر جو سینے میں بسا لیتے ہیں‘‘

نعمتِ عُظمیٰ کا فیضان انہیں ملتا ہے
جو درِ قدس پہ دامن کو بچھا لیتے ہیں

اُن کو آتے ہیں نظر نورِ ہدیٰ کے جلوے
خاک طیبہ کی جو آنکھوں میں لگا لیتے ہیں

ہر صحابیؓ کا یہ مسلک ہے کہ رودادِ الم
جنؐ کی سُنتا ہے خدا اُنؐ کو سُنا لیتے ہیں

روزنِ چشمِ تصوّر سے اُنہیںؐ دیکھتے ہیں
دوریوں میں یوں حضوری کا مزا لیتے ہیں

شوقِ طیبہ کا شجر سوکھنے کب دیتے ہیں
اشکِ ہجراں کا اِسے پانی لگا لیتے ہیں

اُن کی سانسوں میں بسی خلدِ بریں کی خوشبو
شہرِ طیبہ کی جو عرفانؔ ہوا لیتے ہیں

Frequency of Osteopenia and its association with Socio Economic Status among general female population aged 18-60 years Osteopenia and Socio Economic Status

Osteopenia is regarded as the Bone Mineral Density (BMD) which is lower than that of the average value but not as low as Osteoporosis. In Pakistan, Osteoporosis and Osteopenia among women have become one of the most common problems of recent times. Objectives: To find the frequency of osteopenia among females in Faisalabad and its association with SES (Socio Economic Status). Methodology: It was an analytical and cross-sectional study which was conducted at Niaz Medicare Clinic in Faisalabad. The study was completed in 9 months from 18 October 2019 to 18 July 2020. Non probability purposive sampling was done and 323 females were taken for the study. Results: The results demonstrated that 56.3% of the population had Osteopenia. Socio Economic Status had as statistically significant association with Osteopenia (p= 0.041). The results also revealed that the females belonging to middle class and lower class had a higher prevalence of Osteopenia than the females of upper Socio Economic Status. Conclusion: the frequency of Osteopenia was fairly high among females specifically the age group 18-29 years. There was an association found between Osteopenia and Socio Economic status (p =0.041).

Bayesian Analysis of Some Randomly Censored Lifetime Distributions

The thesis presents the Bayesian analysis of some two-parameter lifetime distributions in presence of random censoring. It is well known that for the distributions having shape parameter(s), the conjugate joint prior distributions of shape and scale parameters do not exist while computing the Bayes estimates. In this thesis it is assumed that the shape and scale parameters have independent gamma priors. In case of no prior information about the parameters, the commonly used noninformative priors on the shape and scale parameters are considered. It is observed that the closedform expressions for the Bayes estimators cannot be obtained; four different methods of Bayesian computation are proposed in the crucial places to obtain the approximate Bayes estimates. Among these two are based on analytical approximation, namely, the Lindley’s approximation and the Tierney-Kadane’s approximation; and two are based on Monte Carlo sampling that are importance sampling and Gibbs sampling. For each model, we use three different methods of estimation: maximum likelihood, analytical approximation and Monte Carlo sampling. Simulation studies are carried out to observe the behavior of the Bayes estimators and to compare with the maximum likelihood estimators of the unknown parameters, the hazard function and the reliability function for different sample sizes, different priors, different loss functions, different loss function parameter values and for different censoring rates. The analysis of real data examples is performed in a noble way to illustrate the proposed 10 methodology. Several model fitness measures are taken into consideration to check the goodness-of-fit of the proposed models
Asian Research Index Whatsapp Chanel
Asian Research Index Whatsapp Chanel

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