A series of trials, including hydroponics and soil experiments, were conducted to document the phenotypic variation among rice genotypes and the response of selected genotypes to inorganic and/ or organic sources of K under standard rice management (SRM) and system of rice intensification (SRI). In a solution culture study, changes in growth attributes under both deficient and adequate K levels indicated differential adaptation of 26 rice genotypes. Three of 26 genotypes, namely, IR-6, Super basmati and 99509, were selected for subsequent studies on the basis of their differential responses for K use efficiency (KUE), shoot biomass, and K uptake at deficient and adequate K levels. The categorization of rice genotypes was made using the index scoring technique. Accordingly, 99509 was categorized as highly efficient-medium responsive, Super basmati as medium efficient-medium responsive, while IR-6 as low efficient-low responsive. Correlation among various growth parameters was calculated, and a strong correlation was found among shoot biomass, KUE, and total K uptake. The growth and yield responses of these selected genotypes were subsequently studied with exogenously applied K (K 2 SO 4 ) in pot trials. On overall basis, the KUE determined the responses of various growth and yield parameters against varying levels of K application. Again, the order of genotypes with respect to KUE was found to be the same as that observed in the hydroponic study, i.e., 99509 was found to be highly efficient, Super basmati was medium efficient, and IR-6 was non-efficient in term of growth and yield attribute formation. A dose of 60 kg K ha -1 was found optimum for increasing most of the growth and yield attributes of the three rice genotypes, which was very close to that calculated amounts obtained using the quadratic model. Keeping in view the cumulative effects, a dose of 60 kg K ha -1 was selected for subsequent field trials. Thereafter, the genotypes were tested under the conventional SRM (continuously flooded) and SRI (intermittently flooded) systems. The growth, yield and quality of the three genotypes were studied under single and integrated use of inorganic and organic K fertilizer. Most of the growth and yield attributes gave maximum response with integrated application of 30 kg K ha -1 as K 2 SO 4 + 30 kg K ha -1 as K-enriched compost under SRM, while 15 kg K ha -1 as K 2 SO 4 + 15 kg K ha -1 as K-enriched compost proved best under SRI. Super basmati gave the maximum grain yield under SRM, while under SRI 99509 was best, both with integrated application of 15 kg K ha -1 as K 2 SO 4 + 15 kg K ha -1 as K-enriched compost. However, maximum straw yield was produced by 99509 with integrated application 1of 15 kg K ha -1 as K 2 SO 4 + 15 kg K ha -1 as K-enriched compost under SRM, while integrated application of 30 kg K ha -1 as K 2 SO 4 + 30 kg K ha -1 as K-enriched compost resulted in maximum straw yield in Super basmati under SRI. IR-6 remained relatively poor in performance in most of the growth and yield parameters. It was note worthy that the genotype 99509, which was rated highly efficient in K use in hydroponic trial changed its response as medium efficient in K use in field trials (both in SRI and SRM), while exactly reverse trend with respect to KUE was observed in case of Super basmati. IR-6 remained relatively poor in growth, yield and KUE under both the systems of management. Total K uptake and KUE of the genotypes varied with K doses and sources under SRM and SRI, affecting the growth and yield parameters of the three rice genotypes tested. Most of the quality parameters under SRI and SRM gave almost similar values, implying that SRI had no negative effect on yield and quality of both coarse and fine varieties of rice. Moreover, SRI was seen to be a viable approach to save water without compromising the yield and quality of the produce, thus it may be adopted as a low-input technology system.
پروفیسر رشید احمد صدیقی افسوس ہے ابھی مولانا عبدالماجد دریابادی کے اشک ماتم خشک بھی نہیں ہوئے تھے کہ اردو ادب وانشا کے میدان کاایک اورشہسوار گرا یعنی پروفیسر رشید احمد صاحب صدیقی نے کم وبیش پچاسی برس کی عمر میں علی گڑھ میں وفات پائی اور وہیں سپردخاک ہوئے۔ مرحوم کا اصل وطن جونپور تھا لیکن طالب علمی کے زمانہ میں علی گڑھ آئے تو بس یہیں کے ہوکر رہ گئے، یہیں انھوں نے تعلیم حاصل کی۔ اُس زمانہ میں اردو میں ایم۔اے نہیں ہوتاتھا اس لیے فارسی میں ایم۔اے کیا، پھر یہیں اردوکے لیکچرر ہوئے اورایک عرصہ کے بعدریڈر بنے۔ڈاکٹر ذاکر حسین صاحب جن کومرحوم ہمیشہ مرشد کہتے اورلکھتے تھے اُن کی وائس چانسلری کے زمانہ میں پروفیسر ہوگئے لیکن اس عہدہ پرفائز ہوئے ابھی دو ہی برس ہوئے تھے کہ ملازمت سے سبکدوش کردیے گئے۔ یونیورسٹی کے قانون کے مطابق وہ ابھی توسیع کے مستحق تھے لیکن اس زمانہ میں یونیورسٹی میں جو سیاست چل رہی تھی وہ مانع ہوئی اور شیخ عبدالرشید(شعبۂ تاریخ)وغیرہ کے ساتھ یہ بھی ریٹائرڈ کرد یے گئے۔ مرحوم نہایت خوددار اورحساس تھے اس لیے انھوں نے شکوہ شکایت کسی سے نہیں کیا لیکن انھیں اس کااحساس عمر بھررہا چنانچہ وہ علی گڑھ میں ہی اپنے ذاتی طویل و عریض مکان میں ایسے گوشہ نشین ہوکربیٹھ گئے کہ نہ کبھی اردو ڈپارٹمنٹ میں قدم رکھا اورنہ یونیورسٹی کی کسی تقریب،کسی پارٹی اورفنکشن میں کہیں نظر آئے۔ مرحوم نے اگرچہ کوئی مستقل کتاب کبھی نہیں لکھی اورنہ کوئی علمی اورتحقیقی کام کیا لیکن وہ اردو زبان کے عظیم نکتہ دان اورادیب تھے، اس لیے مضامین کثرت سے لکھے جن کے دومجموعے ’ ’طنزیات ومضحکات‘‘ اور ’’مضامین رشید‘‘ کے نام سے طبع ہوکر ارباب ذوق میں مقبول اورمشہور ہوئے۔ علاوہ ازیں بعض خطبات بھی چھپے ہیں۔ ان کااردو، فارسی اور انگریزی ادب...
The study designed the impact of an interest rate change on the profitability of the banking sector in India. In this work comparative analysis of various profitability performance ratios like ROA, ROE, ROCE, Net Profit Margin Ratio, EPS, etc… and also find out the impact of interest rate on banks profitability with the help of correlation and regression analysis of selected nine nationalized banks in India. The data is collected through various annual reports of selected respective banks from 2011-12 to 2019-20. For the analysis, the data researchers have used various statistical tools like Mean, Ratio, Correlation Analysis, and Regression Analysis. This study concluded that out of all selected ratios, ROA, ROCE, Net Profit Margin Ratio, Net Interest Income/Total assets, Net Interest Margin Ratio and Capital adequacy Ratio indicated that null hypothesis is rejected which means there is a significant difference between these ratios of selected nationalized banks during the study period and also found that Bank Rate has significantly impacted on Net Profit Margin Ratio in all selected nationalized banks in India.
Medical image analysis is very popular research area these days in which digital images are analyzed for the diagnosis and screening of different medical problems. Diabetic retinopathy (DR) is an eye disease caused by the increase of insulin in blood and may cause blindness if not treated in time. Healthy retina contains blood vessels, optic disc and macula as main components but abnormal retina may contain other components and signs as well. An au- tomated system for early detection of DR can save patient’s vision and can also help the ophthalmologists in screening of DR. In this thesis, we develop algorithms for retinal image analysis based on image processing and pattern classification. Image processing techniques are used for retinal image enhancement and pattern recognition is used for classification of DR stages. The proposed system consists of different stages such as preprocessing, compo- nent extraction, candidate region detection, feature extraction and finally the classification. The first phase consists of input retinal image enhancement, noise removal, extraction of main retinal components and candidate lesions detection. We apply Gabor wavelets and Gabor filter banks for lesion detection. The system then extracts features from candidate lesions using four main properties, i.e. shape, color, gray level and statistical. Finally the classifier takes the feature vectors as inputs and grades the input retinal image into dif- ferent stages of DR. We present a hybrid classifier which combines the Gaussian Mixture Model (GMM), Support Vector Machine (SVM) and an extension of multimodel mediod based modeling approach in an ensemble to improve the accuracy of classification. The im- plemented algorithms are tested and evaluated on publicly available retinal image databases using performance parameters such as sensitivity, specificity, positive predictive value and accuracy. The performance improvement of our proposed system is demonstrated by com- paring them with recently proposed and published methods.