Decreased [ 3 H] YM-09151-2 binding to dopamine D2 receptors in the hypothalamus, brainstem and pancreatic islets of streptozotocin -induced diabetic rats

In the present study dopamine was measured in the hypothalamus, brainstem, pancreatic islets and plasma, using HPLC. Dopamine D2 receptor changes in the hypothalamus, brainstem and pancreatic islets were studied using [3H] YM-09151-2 in streptozotocin-induced diabetic and insulintreated diabetic rats. There was a significant decrease in dopatnine content in the hypothalamus (P<0.001), brainstem (P<0.001), pancreatic islets (P<0.001) and plasma (P<0.00I) in diabetic rats when compared to control. Scatchard analysis of [3H] YM-09151-2 in the hypothalamus of diabetic rats showed a significant decrease in Bax (P<0.001) and Kd, showing an increased affinity of D2 receptors when compared to control. Insulin treatment did not completely reverse the changes that occurred during diabetes. There was a significant decrease in B,nax (P<0.01) with decreased affinity in the brainstem of diabetic rats. The islet membrane preparation of diabetic rats showed a significant decrease (P<0.001) in the binding of [3H] YM-09 151-2 with decreased Kd (P<0.001) compared to control. The increase in affinity of D2 receptors in hypothalamus and pancreatic islets and the decreased affinity in brainstem were confirmed by competition analysis. Thus our results suggest that the decreased dopamine D, receptor function in the hypothalamus, brainstem and pancreas affects insulin secretion in diabetic rats, which has immense clinical relevance to the management of diabetes.

Drastic variation in the surface boundary layer parameters over Cochin during the annular solar eclipse: Analysis using sonic anemometer data

Atmospheric surface boundary layer parameters vary anomalously in response to the occurrence of annular solar eclipse on 15th January 2010 over Cochin. It was the longest annular solar eclipse occurred over South India with high intensity. As it occurred during the noon hours, it is considered to be much more significant because of its effects in all the regions of atmosphere including ionosphere. Since the insolation is the main driving factor responsible for the anomalous changes occurred in the surface layer due to annular solar eclipse, occurred on 15th January 2010, that played very important role in understanding dynamics of the atmosphere during the eclipse period because of its coincidence with the noon time. The Sonic anemometer is able to give data of zonal, meridional and vertical wind as well as the air temperature at a temporal resolution of 1 s. Different surface boundary layer parameters and turbulent fluxes were computed by the application of eddy correlation technique using the high resolution station data. The surface boundary layer parameters that are computed using the sonic anemometer data during the period are momentum flux, sensible heat flux, turbulent kinetic energy, frictional velocity (u*), variance of temperature, variances of u, v and w wind. In order to compare the results, a control run has been done using the data of previous day as well as next day. It is noted that over the specified time period of annular solar eclipse, all the above stated surface boundary layer parameters vary anomalously when compared with the control run. From the observations we could note that momentum flux was 0.1 Nm 2 instead of the mean value 0.2 Nm-2 when there was eclipse. Sensible heat flux anomalously decreases to 50 Nm 2 instead of the mean value 200 Nm 2 at the time of solar eclipse. The turbulent kinetic energy decreases to 0.2 m2s 2 from the mean value 1 m2s 2. The frictional velocity value decreases to 0.05 ms 1 instead of the mean value 0.2 ms 1. The present study aimed at understanding the dynamics of surface layer in response to the annular solar eclipse over a tropical coastal station, occurred during the noon hours. Key words: annular solar eclipse, surface boundary layer, sonic anemometer

Quadratic Predictor based Differential Encoding and Decoding of Speech Signals

Modeling nonlinear systems using Volterra series is a century old method but practical realizations were hampered by inadequate hardware to handle the increased computational complexity stemming from its use. But interest is renewed recently, in designing and implementing filters which can model much of the polynomial nonlinearities inherent in practical systems. The key advantage in resorting to Volterra power series for this purpose is that nonlinear filters so designed can be made to work in parallel with the existing LTI systems, yielding improved performance. This paper describes the inclusion of a quadratic predictor (with nonlinearity order 2) with a linear predictor in an analog source coding system. Analog coding schemes generally ignore the source generation mechanisms but focuses on high fidelity reconstruction at the receiver. The widely used method of differential pnlse code modulation (DPCM) for speech transmission uses a linear predictor to estimate the next possible value of the input speech signal. But this linear system do not account for the inherent nonlinearities in speech signals arising out of multiple reflections in the vocal tract. So a quadratic predictor is designed and implemented in parallel with the linear predictor to yield improved mean square error performance. The augmented speech coder is tested on speech signals transmitted over an additive white gaussian noise (AWGN) channel.