Background: Diabetes and diabetic complications are becoming major "health problems" in India. Diabetes affects all tissues, causing neuropathy, vasculopathy, myopathy, etc. Retina is both vascular and sensory neural tissue, and perhaps the damage is also two-fold. Aims and Objectives: To study incidence of diabetic retinopathy (DR) in a cohort of diabetic patients with nerve conduction velocity (NCV) proven neuropathy. Materials and Methods: a total of 50 diabetic patients aged more than 30 years, with NCV -proven diabetic neuropathy were selected for the study from a Tertiary Care Hospital in semi-rural Maharashtra. Fundoscopy after midriasis and fluorescein angiography, where indicated were performed in all patients. Data were tabulated and analyzed by multivariate analysis and then subjected to regression analysis and anova. Results: Of cohort of 50, 38 patients had retinopathy (76%), mean age of patients with retinopathy was 55.3, a male preponderance was seen 72.7%. Conclusions: higher incidence of retinopathy was seen in diabetic patients with neuropathy more so in patients with sensory neuropathy. Thus making us reflect on the possibility: of DR also being a neuropathy, to begin with and whether neuroprotective agents will have a role in preventing and postponing DR.

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Water resources projects are very complex in nature, requires huge financial investment and requires to consider socioeconomic, political, environmental aspects apart from technical aspects. There are many techniques evolved over the years to solve complex water resource problems. Pimpalgaon Dhale medium irrigation project system is considered in this project is located in Barshi taluka of Solapur district. It is planned to irrigate an ICA of 2400 ha of 6 villages namely Pimpalgaon, Pangaon, Yawali, Sakat, Undegaon and Irle. Dam is completed in 2008 however distribution system is still incomplete. The system is optimized to calculate maximize net benefit from the crops subjected to various constraints (viz. water availability, land availability, male and female labour availability, capital availability etc,). Single objective linear programming model is formulated and constraints are written and solver program of MS excel is used to derive maximum net benefit from the irrigation system under consideration. Benefit Cost ratio is calculated and compared it with that calculated adopting conventional methodology. The data required for model formulation is adopted from various sources such as Government reports/ documents, reports available on websites, research papers etc. The constraints such as capital availability within irrigation system during kharif and rabi season, female labour hours availability during kharif and rabi season limits the area under crops as well as net benefits however there is substantial increase in area under irrigation and net benefits from the irrigation system. The Solver program of MS Excel is very useful and convenient to use for solving linear programming. Keywords: Water Resource Projects, Maximize net benefit, Benefit Cost Ratio, Linear programming.,

A transmission or gearbox provides speed and torque conversions from a rotating power source to another device using gear ratios. The most common use is in motor vehicles, where the transmission adapts the output of the internal combustion engine to the drive wheels. Such engines need to operate at a relatively high rotational speed, which is inappropriate for starting, stopping, and slower travel. The transmission reduces the higher engine speed to the slower wheel speed, increasing torque in the process. We have designed a differential gearbox and tried to create the frictional contact between two mating gears. And we have performed the structural analysis on gear box by providing the torque to the assembly of crown gear and pinion gear, assembly of inner gears- spider gears and side gears and crown gear with the cage to attach spider gears. We have selected two kinds of alloy steel and have compared the factor of safety and structural analysis of the both.

Pronunciation lexicons and prediction models are a key component in several speech synthesis and recognition systems. We know that morphologically related words typically follow a fixed pattern of pronunciation which can be described by language-specific paradigms. In this work we explore how deep recurrent neural networks can be used to automatically learn and exploit this pattern to improve the pronunciation prediction quality of words related by morphological inflection. We propose two novel approaches for supplying morphological information, using the word's morphological class and its lemma, which are typically annotated in standard lexicons. We report improvements across a number of European languages with varying degrees of phonological and morphological complexity, and two language families, with greater improvements for languages where the pronunciation prediction task is inherently more challenging. We also observe that combining bidirectional LSTM networks with attention mechanisms is an effective neural approach for the computational problem considered, across languages. Our approach seems particularly beneficial in the low resource setting, both by itself and in conjunction with transfer learning.