13 research outputs found
Mummification in a Bitch: A case report
Get PDFA pug aged 5 years was admitted in the Lyka pet clinic with difficulty in parturition. Breeding history of the dog was collected from the owner. X-ray was conducted which confirmed the presence of foetus. The bitch was manually handled to relieve the Dystocia following intravenous drip of N.S.S. and oxytocin. In the vent of unsuccessful attempt the bitch was surgically operated for C.S. and six fetuses of which four normal and two mummified were relieved. Routine post operative care were undertaken and the bitch recovered normally with out any complication. Photographic recording was also made during the recovery of mummified foetus
Influence of the SiC Reinforcement on the Abrasive Wear Response of an Al-Cu Alloy Under the Conditions of Varying Abrasive Size and Applied Load.
No full text
Dry Sliding Wear Behaviour of a Zinc-Based Alloy: A Comparative Study with a Leaded-Tin Bronze.
No full textSliding Wear Behaviour of Some Al-Si Alloys: Role of Shape and Size of Si Particles and Test Conditions.
No full textNowcasting of Yes/No rain situations at a station using soft computing technique to the radar imagery
No full text92-102A soft computing
model for nowcasting of Yes/No rain situations, with a lead time of 2 h, is
developed over DWR station at Satish Dhawan Space Centre (SDSD), Shriharikota
(13.66°N, 80.23°E) using Doppler weather radar (DWR) reflectivity imageries. Primarily,
precipitating systems of mesoscale, i.e. meso-gamma (2-20 km), meso-beta
(20-200 km) and meso-alpha
(200-2000 km) are considered for the present study. The main components of soft computing approach are:
analysis of two-dimensional reflectivity imageries from DWR and utilization of
artificial neural network (ANN) for training of input/output data. About 15
input and one output parameters are extracted from radar imageries. The image analysis
and training of ANN are carried out on MATLAB platform. After training of ANN,
91 and 77% results are matched with the observed values for No rain and Yes
rain situations, respectively. The probability of detection (POD) for the
nowcasting of Yes/No rain situations is found to be 0.84. The significant
improvement in the nowcasting of Yes/No rain situations is observed by the
developed methodology as compared to linear multivariable regression method.
The POD of Yes/No rain for other two locations, namely Chennai (12.99°N, 80.18°E)
and Tiruvallur (13.09°N, 79.57°E) are found to be 0.81 and 0.77, respectively.
Overall, reasonably good results are obtained by the newly developed soft
computing model
Effects of Primary Silicon Particles on the Sliding Wear Behaviour of Aluminium-Silicon Alloys.
No full text
