Effect of non-genetic factors on replacement rate and its components in Murrah buffaloes of Tamil Nadu

The average value (in %) for abnormal birth, male birth, female birth, death of female calves, culling of female calves, replacement rate on basis of total pregnancies and total female calves born were 2.82, 51.4, 48.6, 38.8, 21.2, 19.4 and 40.0 respectively. On an average 4 to 5 pregnancies were required for one female calf to reach milking herd. Among the non-genetic factors, period of birth contributed for major variation in replacement rate and its components. The effects of different non-genetic factors (viz. season, periods and parity) affecting replacement rate and its components revealed that period of birth affected the replacement rate and its components highly significantly (P<0.01). Beyond fifth lactation the efficacy of cows to replace a heifer decreased gradually

Modeling Specifications for HiVision Millimeter Wave Radar for Multisensory Enhanced Vision Systems

A number of projects have been developed to increase flight safety and economy of aviation. The development and validation of systems for pilot assistance is also one field of interest. To improve the situational awareness of an aircrew during poor visibility, different approaches emerged during the past few years. Enhanced vision systems (EVS based on sensor images) are one of those. Typically, Enhanced vision systems consist of two main partssensor vision and Synthetic vision. Sensor vision uses weather penetrating forward looking image sensors such as Forward Looking Infrared Radar (FLIR) and HiVision Millimeter Wave Radar (HiVision MMWR). The main contribution of this paper is to set up the procedure based on literature survey to model the HiVision Millimeter Wave Radar for Enhanced Vision Systems functionalitie

Synthesis and Characterization of Bi&lt;sub&gt;2&lt;/sub&gt;S&lt;sub&gt;3&lt;/sub&gt; Nanorods Decorated on Carbon Sphere and Study its Electrochemical Application

Bismuth sulfide(Bi2S3) nanorods(NRs) decorated on uniform shape carbon sphere(CS)have been prepared by hydrothermal method, using single source precursorpolyvinyl pyrrolidone(PVP) as a capping agent. The nanoparticles were synthesized with different ratio of capping agent at different temperatures.The prepared nanoparticles were characterized by FTIR spectroscopy,thermo gravimetric and differential thermal analysis. The crystallinity, morphology and elemental composition of the synthesized nanocrystals have been confirmed through X-ray diffraction (XRD), HRSEMand EDX. The electrochemical catalytic activity on the reduction of catechol of the synthesized Bi2S3NRs has been investigated.The electrocatalytic oxidation of catechol done with Bi2S3NRs coated CS/GCE modified by using CV and the effect of the scan rate also studied. The modified nanocomposites Bi2S3NRs on CS in GCE are act as a good sensor by detection of catechol in ultra trace level by using DPV techniques.</jats:p

Bacteria and primary production

139-141Distribution of bacteria and bacterial activities in sediments in relation to primary production of overlying water at 10 stations in the backwaters and the adjoining mangrove forests (Pichavaram) were studied. Total nitrogen, total phosphorus and organic carbon of the sediments, and the nutrients and plant pigments of the water, were also estimated. Total bacterial population ranged from 1.48 x 106 to 13.10 x 106/g sediment. Phosphatase activity varied from 5.09 to 31.29 µ g phenol/g/hr. Phosphate solubilizing bacteria varied between 1.27 x 106 and 10.26 x 106/g sediment. Chlorophyll a, b and c varied from 3.68 to 31.88, 0 to 10.32 and 6.08 to 38.80 µu g/litre respectively, and carotenoids from 4.56 to 12.80 MSPU/m3. Gross production varied from 25. 21 to 336.12 mg C/m3/hr, and net production from 8.40 to 193.27 mg C/m3 /hr. Positive significant correlations were found between phosphatase producers and chl. a (r = 0.75), chl. a and net production r = 0.6) and phosphatase producers and phosphatase activity (r = 0.8). Similar relationships were also evident between the elements (nitrogen, phosphorus and carbon) and phosphatase producers, and the elements and phosphatase activity

Tool wear prediction in hard turning of EN8 steel using cutting force and surface roughness with artificial neural network

In this work, the flank wear of the cutting tool is predicted using artificial neural network based on the responses of cutting force and surface roughness. EN8 steel is chosen as a work piece material and turning test is conducted with various levels of speed, feed and depth of cut. Cutting force and surface roughness are measured for both the fresh and dull tool under dry cutting conditions. The tool insert used is CNMG 120408 grade, TiN coated cemented carbide tool. The experiments are conducted based on the response surface methodology face central composite design of experiments. The feed rate (14.52%), depth of cut (27.72%) and the interaction of feed rate and depth of cut (50.39%) influence the cutting force. The feed rate (21.33%) and the interaction of cutting speed and depth of cut (26.67%) influence the flank wear. The feed rate (61.63%) has the significant influence on surface roughness. The feed forward back propagation neural network of 5-n-1 architecture is trained using the algorithms like Levenberg Marquardt, BFGS quasi-Newton, and Gradient Descent with Momentum and Gradient descent with adaptive learning rate. The network performance has been assessed based on their mean square error and computation time. From this analysis, the BFGS quasi-Newton back propagation algorithm produced the least mean squared error value with minimum computation time. </jats:p