Development of an LH receptor assay capable of measuring serum LH/CG in a wide variety of species

The development of a radioreceptor assay (RRA) that can measure serum LH in a variety of species and CG in sera and urine of pregnant women and monkeys is reported. Using sheep luteal membrane as the receptor source and I-125-labelled hLH/hCG as the tracer, dose-response (displacement) curves were obtained using hLH or hCG as standard. The addition of LH-free serum (200 mul per tube) had no affect on the standard displacement curve. The assay is simple, requires less than 90 min to complete and provides reproducible results. The sensitivity of the assay was 0.6 ng hLH per tube and the intra- and interassay variations were 9.6 and 9.8, respectively. Sera obtained from male and female bonnet monkeys (Macaca radiata) and monkey pituitary extract showed parallelism to the standard curve. The concentrations of LH measured correlated with the physiological status of the animals. Sera of rats, rabbits, hamsters, guinea-pigs, sheep and humans showed parallelism to the hLH standard curve indicating the viability of the RRA to measure serum LH of different species. Since the receptors recognize LH and CG, detection of pregnancy in monkeys and women was possible using this assay. The sensitivity of the assay for hCG was 8.7 miu per tube. This RRA could be a convenient alternative to the Leydig cell bioassay for obtaining the LH bioactivity profile of sera and biological fluids.

Fatigue life prediction of adhesively bonded single lap joints

Better fatigue performance of adhesively bonded joints makes them suitable for most structural applications. However, predicting the service life of bonded joints accurately remains a challenge. In this present study, nonlinear computational simulations have been performed on adhesively bonded single lap ASTM-D1002 shear joint considering both geometrical and material nonlinearities to predict the fatigue life by judiciously applying the modified Coffin-Manson equation for adhesive joints. Elasto-plastic material models have been employed for both the adhesive and the adherends. The predicted life has close agreement in the high cycle fatigue (HCF) regime with empirical observations reported in the literature. (C) 2010 Elsevier Ltd. All rights reserved.

NDDO-based CI methods for the prediction of electronic spectra and sum-over-states molecular hyperpolarization

NDDO-based (AM1) configuration interaction (CI) calculations have been used to calculate the wavelength and oscillator strengths of electronic absorptions in organic molecules and the results used in a sum-over-states treatment to calculate second-order-hyperpolarizabilities. The results for both spectra and hyperpolarizabilities are of acceptable quality as long as a suitable CI-expansion is used. We have found that using an active space of eight electrons in eight orbitals and including all single and pair-double excitations in the CI leads to results that agree well with experiment and that do not change significantly with increasing active space for most organic molecules. Calculated second-order hyperpolarizabilities using this type of CI within a sum-over-states calculation appear to be of useful accuracy.

Prediction of load-deflection behaviour using fracture energy GF: A comparative study of two fracture models for concrete

Load-deflection curves for a notched beam under three-point load are determined using the Fictitious Crack Model (FCM) and Blunt Crack Model (BCM). Two values of fracture energy GF are used in this analysis: (i) GF obtained from the size effect law and (ii) GF obtained independently of the size effect. The predicted load-deflection diagrams are compared with the experimental ones obtained for the beams tested by Jenq and Shah. In addition, the values of maximum load (Pmax) obtained by the analyses are compared with the experimental ones for beams tested by Jenq and Shah and by Bažant and Pfeiffer. The results indicate that the descending portion of the load-deflection curve is very sensitive to the GF value used.

Area Optimized H.264 Intra Prediction Architecture for 1080p HD Resolution

High performance video standards use prediction techniques to achieve high picture quality at low bit rates. The type of prediction decides the bit rates and the image quality. Intra Prediction achieves high video quality with significant reduction in bit rate. This paper present an area optimized architecture for Intra prediction, for H.264 decoding at HDTV resolution with a target of achieving 60 fps. The architecture was validated on Virtex-5 FPGA based platform. The architecture achieves a frame rate of 64 fps. The architecture is based on multi-level memory hierarchy to reduce latency and ensure optimum resources utilization. It removes redundancy by reusing same functional blocks across different modes. The proposed architecture uses only 13% of the total LUTs available on the Xilinx FPGA XC5VLX50T.

Seasonal prediction of the Indian monsoon

Under the project `Seasonal Prediction of the Indian Monsoon' (SPIM), the prediction of Indian summer monsoon rainfall by five atmospheric general circulation models (AGCMs) during 1985-2004 was assessed. The project was a collaborative effort of the coordinators and scientists from the different modelling groups across the country. All the runs were made at the Centre for Development of Advanced Computing (CDAC) at Bangalore on the PARAM Padma supercomputing system. Two sets of simulations were made for this purpose. In the first set, the AGCMs were forced by the observed sea surface temperature (SST) for May-September during 1985-2004. In the second set, runs were made for 1987, 1988, 1994, 1997 and 2002 forced by SST which was obtained by assuming that the April anomalies persist during May-September. The results of the first set of runs show, as expected from earlier studies, that none of the models were able to simulate the correct sign of the anomaly of the Indian summer monsoon rainfall for all the years. However, among the five models, one simulated the correct sign in the largest number of years and the second model showed maximum skill in the simulation of the extremes (i.e. droughts or excess rainfall years). The first set of runs showed some common bias which could arise either from an excessive sensitivity of the models to El Nino Southern Oscillation (ENSO) or an inability of the models to simulate the link of the Indian monsoon rainfall to Equatorial Indian Ocean Oscillation (EQUINOO), or both. Analysis of the second set of runs showed that with a weaker ENSO forcing, some models could simulate the link with EQUINOO, suggesting that the errors in the monsoon simulations with observed SST by these models could be attributed to unrealistically high sensitivity to ENSO.

Prediction of the Indian summer monsoon rainfall using a state-of-the-art coupled ocean-atmosphere model

A state-of-the-art model of the coupled ocean-atmosphere system, the climate forecast system (CFS), from the National Centres for Environmental Prediction (NCEP), USA, has been ported onto the PARAM Padma parallel computing system at the Centre for Development of Advanced Computing (CDAC), Bangalore and retrospective predictions for the summer monsoon (June-September) season of 2009 have been generated, using five initial conditions for the atmosphere and one initial condition for the ocean for May 2009. Whereas a large deficit in the Indian summer monsoon rainfall (ISMR; June-September) was experienced over the Indian region (with the all-India rainfall deficit by 22% of the average), the ensemble average prediction was for above-average rainfall during the summer monsoon. The retrospective predictions of ISMR with CFS from NCEP for 1981-2008 have been analysed. The retrospective predictions from NCEP for the summer monsoon of 1994 and that from CDAC for 2009 have been compared with the simulations for each of the seasons with the stand-alone atmospheric component of the model, the global forecast system (GFS), and observations. It has been shown that the simulation with GFS for 2009 showed deficit rainfall as observed. The large error in the prediction for the monsoon of 2009 can be attributed to a positive Indian Ocean Dipole event seen in the prediction from July onwards, which was not present in the observations. This suggests that the error could be reduced with improvement of the ocean model over the equatorial Indian Ocean.

A quasi-steady performance prediction model for dynamic characteristics of a volute pump

A performance prediction model generally applicable for volute-type centrifugal pumps has been extended to predict the dynamic characteristics of a pump during its normal starting and stopping periods. Experiments have been conducted on a volute pump with different valve openings to study the dynamic behaviour of the pump during normal start-up and stopping, when a small length of discharge pipeline is connected to the discharge flange of the pump. Such experiments have also been conducted when the test pump was part of a hydraulic system, an experimental rig, where it is pumping against three similar pumps, known as supply pumps, connected in series, with the supply pumps kept idle or running. Instantaneous rotational speed, flowrate, and delivery and suction pressures of the pump were recorded and it was observed in all the tested cases that the change of pump behaviour during the transient period was quasi-steady, which validates the quasi-steady approach presented in this paper. The nature of variation of parameters during the transients has been discussed. The model-predicted dynamic head-capacity curves agree well with the experimental data for almost all the tested cases.

Data compression by linear prediction for storage and transmission of EEG signals

The EEG time series has been subjected to various formalisms of analysis to extract meaningful information regarding the underlying neural events. In this paper the linear prediction (LP) method has been used for analysis and presentation of spectral array data for the better visualisation of background EEG activity. It has also been used for signal generation, efficient data storage and transmission of EEG. The LP method is compared with the standard Fourier method of compressed spectral array (CSA) of the multichannel EEG data. The autocorrelation autoregressive (AR) technique is used for obtaining the LP coefficients with a model order of 15. While the Fourier method reduces the data only by half, the LP method just requires the storage of signal variance and LP coefficients. The signal generated using white Gaussian noise as the input to the LP filter has a high correlation coefficient of 0.97 with that of original signal, thus making LP as a useful tool for storage and transmission of EEG. The biological significance of Fourier method and the LP method in respect to the microstructure of neuronal events in the generation of EEG is discussed.

Anomalous viscous loss in emulsions

We propose a model for concentrated emulsions based on the speculation that a macroscopic shear strain does not produce an affine deformation in the randomly close-packed droplet structure. The model yields an anomalous contribution to the complex dynamic shear modulus that varies as the square root of frequency. We test this prediction using a novel light scattering technique to measure the dynamic shear modulus, and directly observe the predicted behavior over six decades of frequency and a wide range of volume fractions.

A novel neural network design for long range prediction of rainfall pattern

The importance of long-range prediction of rainfall pattern for devising and planning agricultural strategies cannot be overemphasized. However, the prediction of rainfall pattern remains a difficult problem and the desired level of accuracy has not been reached. The conventional methods for prediction of rainfall use either dynamical or statistical modelling. In this article we report the results of a new modelling technique using artificial neural networks. Artificial neural networks are especially useful where the dynamical processes and their interrelations for a given phenomenon are not known with sufficient accuracy. Since conventional neural networks were found to be unsuitable for simulating and predicting rainfall patterns, a generalized structure of a neural network was then explored and found to provide consistent prediction (hindcast) of all-India annual mean rainfall with good accuracy. Performance and consistency of this network are evaluated and compared with those of other (conventional) neural networks. It is shown that the generalized network can make consistently good prediction of annual mean rainfall. Immediate application and potential of such a prediction system are discussed.

Quantum and non-Markovian effects in the electron transfer reaction dynamics in the Marcus inverted region

Electron transfer reactions in large molecules may often be coupled to both the polar solvent modes and the intramolecular vibrational modes of the molecule. This can give rise to a complex dynamics which may in some systems, like betaine, be controlled more by vibrational rather than by solvent effects. Additionally, a significant contribution from an ultrafast relaxation component in the solvation dynamics may enhance the complexity. To explain the wide range of behavior that has been observed experimentally, Barbara et al. recently proposed that a model of an electron transfer reaction should minimally consist of a low-frequency classical solvent mode (X), a low-frequency vibrational mode (Q), and a high-frequency quantum mode (q) (J. Phys. Chem. 1991, 96, 3728). In the present work, a theoretical study of this model is described. This study generalizes earlier work by including the biphasic solvent response and the dynamics of the low-frequency vibrational mode in the presence of a delocalized, extended reaction zone. A novel Green's function technique has been developed which allowed us to study the non-Markovian dynamics on a multidimensional surface. The contributions from the high-frequency vibrational mode and the ultrafast component in the non-Markovian solvent dynamics are found to be primarily responsible for the dramatic increase in charge transfer rate over the prediction of the classical theories that neglect both these factors. These, along with a large coupling between the reactant and the product states, may combine to render the electron transfer rate both very large and constant over a wide range of solvent relaxation rates. A study on the free energy gap dependence of the electron transfer rate reveals that the rates are sensitive to changes in the quantum frequency particularly when the free energy gap is very large.

Prediction of nonlocal scaling parameter for armchair and zigzag single-walled carbon nanotubes based on molecular structural mechanics, nonlocal elasticity and wave propagation

Atomic vibration in the Carbon Nanotubes (CNTs) gives rise to non-local interactions. In this paper, an expression for the non-local scaling parameter is derived as a function of the geometric and electronic properties of the rolled graphene sheet in single-walled CNTs. A self-consistent method is developed for the linearization of the problem of ultrasonic wave propagation in CNTs. We show that (i) the general three-dimensional elastic problem leads to a single non-local scaling parameter (e(0)), (ii) e(0) is almost constant irrespective of chirality of CNT in the case of longitudinal wave propagation, (iii) e(0) is a linear function of diameter of CNT for the case of torsional mode of wave propagation, (iv) e(0) in the case of coupled longitudinal-torsional modes of wave propagation, is a function which exponentially converges to that of axial mode at large diameters and to torsional mode at smaller diameters. These results are valid in the long-wavelength limit. (C) 2011 Elsevier Ltd. All rights reserved.