سر چارلس لایل
ماہ گزشتہ میں انگلستان کے ایک مشہور متشرق سر چارلس لایل کی وفات ہوئی موصوف مدت تک ہندوستان میں ممتاز ملکی مناصب پر مامور رہے تھے، ۱۸۹۸ء میں چیف کمشنر صوبہ متوسط کے مرتبہ سے پنشن پائی اور اس کے بعد بارہ برس تک انڈیا آفس میں کام کرتے رہے، مسلمانوں کے علوم و السنہ، خصوصاً فارسی، عربی اور اردو کے وہ ایک مستند عالم خیال کئے جاتے تھے اور شعراء عرب کے متعدد دواوین ان کے تحشیہ و مقدمہ کے ساتھ شائع ہوئے، وہ برٹش اکاڈیمی کے فیلو تھے اور ایڈنبرا، آکسفورڈ، اسٹراسبرگ، مختلف یونیورسٹیوں سے ال۔ال۔ڈی، پی۔ایچ۔ ڈی، ڈی۔لٹ وغیرہ کی اعزازی ڈگریاں رکھتے تھے، انسائیکلوپیڈیا برٹانیکا کے آخری ایڈیشن میں ہندوستانی (اردو) لٹریچر پر مضمون انہی کے قلم سے تھا، ان کی عمر ۷۵ سال کی تھی۔ (اکتوبر ۱۹۲۰ء)
Tuberculosis (TB) is a lethal disease and developing countries are struggling to overcome this health hazard especially in rural areas and faced globally. Therefore, serious measures are required to reduce this global health hazard. Millary and pulmonary are the most common types of tuberculosis occurring globally. X-ray is the preliminary method to detect tuberculosis; however, the diagnosis is quite often subject to human error. In contrast, the chances of curing Tuberculosis depend on its timely and accurate diagnosis. Therefore, an intelligent machine learning algorithm is developed in this study to assist the clinician in an accurate TB identification in x-ray images. The proposed method pre-processes the X-ray image, enhances its quality and extracts the features of each class which are further passed on to a Deep Convolutional Neural Network-based design for the X-ray image classification, followed by the identification of the tuberculosis type i.e. Millary, Cavitary, Healthy. The classification accuracy for the developed method resulted in 88% and 89% for millary and cavitary TB diseases in x ray images.
The thesis is a systematic study of the causes of emigration, particularly of human capital flows and human capital flight (i.e., brain drain) from Pakistan to 27 destination countries over the past 36 years. The study reviews relevant Pakistani migration history, summarizes and compares models of migration, review empirical studies from multiple disciplines, develops a bi-polar specification of gravity model based on push and pull factors and augmented by a neo-classical utilitarian approach of migration, locates relevant data from Pakistan and 27 major destination countries, construct indices from drivers of human capital mobility using principal component and principal factor analysis, presents dynamic analyses of the drivers of human capital mobility from Pakistan with panel unit root tests, pairwise panel Granger causality test and dynamic ordinary least squares co-integration regressions, and interprets the results with particular attention to differences by regional destinations and to policy implications. Over all the empirical findings support the underlying theories of migration, and helps to conclude that in an over-populated country like Pakistan, unplanned brain-drain need to be re-oriented: first, to take the form of planned brain-export to improve the national balance sheet through foreign earnings in form of foreign direct investment and remittances from overseas Pakistanis and secondly, through the return of experienced Pakistani diaspora and through the realization of professional and technical education in case of brain circulation