Variability of Indian summer monsoon rainfall in daily data from gauge and satellite

It has long been thought that tropical rainfall retrievals from satellites have large errors. Here we show, using a new daily 1 degree gridded rainfall data set based on about 1800 gauges from the India Meteorology Department (IMD), that modern satellite estimates are reasonably close to observed rainfall over the Indian monsoon region. Daily satellite rainfalls from the Global Precipitation Climatology Project (GPCP 1DD) and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) are available since 1998. The high summer monsoon (June-September) rain over the Western Ghats and Himalayan foothills is captured in TMPA data. Away from hilly regions, the seasonal mean and intraseasonal variability of rainfall (averaged over regions of a few hundred kilometers linear dimension) from both satellite products are about 15% of observations. Satellite data generally underestimate both the mean and variability of rain, but the phase of intraseasonal variations is accurate. On synoptic timescales, TMPA gives reasonable depiction of the pattern and intensity of torrential rain from individual monsoon low-pressure systems and depressions. A pronounced biennial oscillation of seasonal total central India rain is seen in all three data sets, with GPCP 1DD being closest to IMD observations. The new satellite data are a promising resource for the study of tropical rainfall variability.

A conditional random field-based downscaling method for assessment of climate change impact on multisite daily precipitation in the Mahanadi basin

Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

Succinate and malate improve development of hamster eight-cell embryos in vitro: Confirmation of viability by embryo transfer

The in vitro development of hamster preimplantation embryos is supported by non-glucose energy substrates. To investigate the importance of embryonic metabolism, influence of succinate and malate on the development of hamster 8-cell embryos to blastocysts was examined using a chemically defined protein-free modified hamster embryo culture medium-2 (HECM-2m). There was a dose-dependent influence of succinate on blastocyst development; 0.5 mM succinate was optimal (85.1% ± 3.9 vs. 54.5% ± 3.5). In succinate-supplemented HECM-2m, blastocyst development was reduced by omission of lactate (68.5% ± 7.2), but not pyruvate (85.8% ± 6.2) or glutamine (84.1% ± 2.1). Succinate along with either glutamine or lactate or pyruvate poorly supported blastocyst development (28%-58%). Malate also stimulated blastocyst development; 0.01 mM malate was optimal (86.3% ± 2.8). Supplementation of both succinate and malate to HECM-2m supported maximal (100%) blastocyst development, which was inhibited 4-fold by the addition of glucose/phosphate. The mean cell numbers (MCN) of blastocysts cultured in succinate-supplemented HECM-2m was higher (28.3 ± 1.1) than it was for those cultured in the absence of glutamine or pyruvate (range 20-24). The MCN was the highest (33.4 ± 1.6) for blastocysts cultured in succinate-malate-supplemented HECM-2m followed by those in succinate (28.3 ± 1.1) or malate (24.7 ± 0.5) supplemented HECM-2m. Embryo transfer experiments showed that 29.8% (±4.5) of transferred blastocysts cultured in succinate-malate-supplemented HECM-2m produced live births, similar (P > 0.1) to the control transfers of freshly recovered 8-cells (33.5% ± 2.0) or blastocysts (28.9% ± 3.0). These data show that supplementation of succinate and malate to HECM-2m supports 100% development of hamster 8-cell embryos to high quality viable blastocysts and that non-glucose oxidizable energy substrates are the most preferred components in hamster embryo culture medium. Mol. Reprod. Dev. 47:440-447, 1997. © 1997 Wiley-Liss, Inc.

Pharmacological inhibition of gut-derived serotonin synthesis is a potential bone anabolic treatment for osteoporosis

Osteoporosis is a disease of low bone mass most often caused by an increase in bone resorption that is not sufficiently compensated for by a corresponding increase in bone formation(1). As gut-derived serotonin (GDS) inhibits bone formation(2), we asked whether hampering its biosynthesis could treat osteoporosis through an anabolic mechanism (that is, by increasing bone formation). We synthesized and used LP533401, a small molecule inhibitor of tryptophan hydroxylase-1 (Tph-1), the initial enzyme in GDS biosynthesis. Oral administration of this small molecule once daily for up to six weeks acts prophylactically or therapeutically, in a dose-dependent manner, to treat osteoporosis in ovariectomized rodents because of an isolated increase in bone formation. These results provide a proof of principle that inhibiting GDS biosynthesis could become a new anabolic treatment for osteoporosis.

Nonlinear ensemble prediction of chaotic daily rainfall

The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. Many of these approaches aim at only analyzing the chaotic nature and not its prediction. In the present study, an attempt is made to identify chaos using various techniques and prediction is also done by generating ensembles in order to quantify the uncertainty involved. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha, Mahanadi and All-India for the period 1955-2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series. Correlation dimension method is done on th phase randomized and first derivative of the data series to check whether the saturation of the dimension is due to the inherent linear correlation structure or due to low dimensional dynamics. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996-2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are done from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. (C) 2010 Elsevier Ltd. All rights reserved.

Hepatotoxicity of pulegone in rats: Its effects on microsomal enzymes, in vivo

Oral administration of pulegone (400 mg/kg) to rats once daily for five days caused significant decreases in the levels of liver microsomal cytochrome P-450 and heme. Cytochrome b5 and NAD(P)H-cytochrome c-reductase activities were not affected. Massive hepatotoxicy accompanied by an increase in serum glutamate pyruvate transaminase (SGPT) and a decrease in glucose-6-phosphatase were observed upon treatment with pulegone. A significant decrease in aminopyrine N-demethylase was also noticed after pulegone administration. Menthone or carvone (600 mg/kg), compounds related to pulegone, when administered orally did not cause any decrease in cytochrome P-450 levels. The hepatotoxic effects of pulegone were both dose and time dependent. Pretreatment of rats with phenobarbital (PB) or diethylmaleate (DEM) potentiated the hepatotoxicity caused by pulegone, whereas, pretreatment with 3-methylcholanthrene (3-MC) or piperonyl butoxide protected from it. It appears that a PB induced cytochrome P-450 catalysed reactive metabolite(s) may be responsible for the hepatotoxicity caused by pulegone.

Simultaneous effect of lead and cadmium on granulosa cells: A cellular model for ovarian toxicity

Lead (Pb) and cadmium (Cd) are known reproductive toxicants, which accumulate in granulosa cells of the ovary. Female Charles foster rats were treated with sodium acetate (control), lead acetate and cadmium acetate either alone or in combination at a dose 0.05 mg/kg body weight intra-peritoneally for 15 days daily. Animals were killed at proestrous stage and granulosa cells were isolated from the ovaries. Binding of I-125-luteinizing hormone (I-125-LH), I-125-follicle stimulating hormone (I-125-FSH) and 17 beta-hydroxysteroid dehydrogenase activity were measured. As these receptors are localized on the surface of the cell membrane, we also estimated the membrane parameters of these cells. Our results demonstrated that both lead and cadmium caused a significant reduction in gonadotropin binding, which altered steroidogenic enzyme activity of granulosa cells. These changes exhibited a positive correlation with membrane changes of the granulosa cells.

Supramolecular insulin assembly II for a sustained treatment of type 1 diabetes mellitus

Diabetes is a chronic disease requiring continuous medical supervision and patient education to prevent acute secondary complications. In this study, we have harnessed the inherent property of insulin to aggregate into an oligomeric intermediate on the pathway to amyloid formation, to generate a form that exhibits controlled and sustained release for extended periods. Administration of a single dose of the insulin oligomer, defined here as the supramolecular insulin assembly II (SIA-II), to experimental animals rendered diabetic by streptozotocin or alloxan, released the hormone capable of maintaining physiologic glucose levels for > 120 days for bovine and > 140 days for recombinant human insulin without fasting hypoglycemia. Moreover, the novel SIA-II described here not only improved the glycemic control, but also reduced the extent of secondary diabetic complications.

Active and break spells of the Indian summer monsoon

In this paper, we suggest criteria for the identification of active and break events of the Indian summer monsoon on the basis of recently derived high resolution daily gridded rainfall dataset over India (1951-2007). Active and break events are defined as periods during the peak monsoon months of July and August, in which the normalized anomaly of the rainfall over a critical area, called the monsoon core zone exceeds 1 or is less than -1.0 respectively, provided the criterion is satisfied for at least three consecutive days. We elucidate the major features of these events. We consider very briefly the relationship of the intraseasonal fluctuations between these events and the interannual variation of the summer monsoon rainfall. We find that breaks tend to have a longer life-span than active spells.While, almost 80% of the active spells lasted 3-4 days, only 40% of the break spells were of such short duration. A small fraction (9%) of active spells and 32% of break spells lasted for a week or longer. While active events occurred almost every year, not a single break occurred in 26% of the years considered. On an average, there are 7 days of active and break events from July through August. There are no significant trends in either the days of active or break events. We have shown that there is a major difference between weak spells and long intense breaks. While weak spells are characterized by weak moist convective regimes, long intense break events have a heat trough type circulation which is similar to the circulation over the Indian subcontinent before the onset of the monsoon. The space-time evolution of the rainfall composite patterns suggests that the revival from breaks occurs primarily from northward propagations of the convective cloud zone. There are important differences between the spatial patterns of the active/break spells and those characteristic of interannual variation, particularly those associated with the link to ENSO. Hence, the interannual variation of the Indian monsoon cannot be considered as primarily arising from the interannual variation of intraseasonal variation. However, the signature over the eastern equatorial Indian Ocean on intraseasonal time scales is similar to that on the interannual time scales.

Sliding Modes for the Simulation of Mechanical and Electrical Systems Defined by Differential-Algebraic Equations

We offer a technique, motivated by feedback control and specifically sliding mode control, for the simulation of differential-algebraic equations (DAEs) that describe common engineering systems such as constrained multibody mechanical structures and electric networks. Our algorithm exploits the basic results from sliding mode control theory to establish a simulation environment that then requires only the most primitive of numerical solvers. We circumvent the most important requisite for the conventionalsimulation of DAEs: the calculation of a set of consistent initial conditions. Our algorithm, which relies on the enforcement and occurrence of sliding mode, will ensure that the algebraic equation is satisfied by the dynamic system even for inconsistent initial conditions and for all time thereafter. [DOI:10.1115/1.4001904]

Chaperone expression profiles correlate with distinct physiological states of Plasmodium falciparum in malaria patients

Background: Molecular chaperones have been shown to be important in the growth of the malaria parasite Plasmodium falciparum and inhibition of chaperone function by pharmacological agents has been shown to abrogate parasite growth. A recent study has demonstrated that clinical isolates of the parasite have distinct physiological states, one of which resembles environmental stress response showing up-regulation of specific molecular chaperones. Methods: Chaperone networks operational in the distinct physiological clusters in clinical malaria parasites were constructed using cytoscape by utilizing their clinical expression profiles. Results: Molecular chaperones show distinct profiles in the previously defined physiologically distinct states. Further, expression profiles of the chaperones from different cellular compartments correlate with specific patient clusters. While cluster 1 parasites, representing a starvation response, show up-regulation of organellar chaperones, cluster 2 parasites, which resemble active growth based on glycolysis, show up-regulation of cytoplasmic chaperones. Interestingly, cytoplasmic Hsp90 and its co-chaperones, previously implicated as drug targets in malaria, cluster in the same group. Detailed analysis of chaperone expression in the patient cluster 2 reveals up-regulation of the entire Hsp90-dependent pro-survival circuitries. In addition, cluster 2 also shows up-regulation of Plasmodium export element (PEXEL)-containing Hsp40s thought to have regulatory and host remodeling roles in the infected erythrocyte. Conclusion: In all, this study demonstrates an intimate involvement of parasite-encoded chaperones, PfHsp90 in particular, in defining pathogenesis of malaria.

Effects of menthofuran, a monoterpene furan on rat liver microsomal enzymes, in vivo

Oral administration (250 mg/kg) of menthofuran, a monoterpene furan, to rats once daily for 3 days caused hepatotoxicity as judged by a significant increase in serum glutamate pyruvate transaminase (SGPT) and decreases in glucose-6-phosphatase and aminopyrine N-demethylase activities. Administration of menthofuran also resulted in a decrease in the levels of liver microsomal cytochrome P-450, whereas cytochrome b(5) and NAD(P)H-cytochrome c reductase activities were not affected. These effects of menthofuran were both dose- and time-dependent. Pretreatment of rats with phenobarbital (PB) prior to menthofuran treatment potentiated hepatotoxicity suggesting that a PB-induced cytochrome P-450 catalyzed the formation of reactive metabolite(s) responsible for the hepatotoxicity.

Predictive uncertainty of chaotic daily streamflow using ensemble wavelet networks approach

Perfect or even mediocre weather predictions over a long period are almost impossible because of the ultimate growth of a small initial error into a significant one. Even though the sensitivity of initial conditions limits the predictability in chaotic systems, an ensemble of prediction from different possible initial conditions and also a prediction algorithm capable of resolving the fine structure of the chaotic attractor can reduce the prediction uncertainty to some extent. All of the traditional chaotic prediction methods in hydrology are based on single optimum initial condition local models which can model the sudden divergence of the trajectories with different local functions. Conceptually, global models are ineffective in modeling the highly unstable structure of the chaotic attractor. This paper focuses on an ensemble prediction approach by reconstructing the phase space using different combinations of chaotic parameters, i.e., embedding dimension and delay time to quantify the uncertainty in initial conditions. The ensemble approach is implemented through a local learning wavelet network model with a global feed-forward neural network structure for the phase space prediction of chaotic streamflow series. Quantification of uncertainties in future predictions are done by creating an ensemble of predictions with wavelet network using a range of plausible embedding dimensions and delay times. The ensemble approach is proved to be 50% more efficient than the single prediction for both local approximation and wavelet network approaches. The wavelet network approach has proved to be 30%-50% more superior to the local approximation approach. Compared to the traditional local approximation approach with single initial condition, the total predictive uncertainty in the streamflow is reduced when modeled with ensemble wavelet networks for different lead times. Localization property of wavelets, utilizing different dilation and translation parameters, helps in capturing most of the statistical properties of the observed data. The need for taking into account all plausible initial conditions and also bringing together the characteristics of both local and global approaches to model the unstable yet ordered chaotic attractor of a hydrologic series is clearly demonstrated.

Multivariate nonlinear ensemble prediction of daily chaotic rainfall with climate inputs

The basic characteristic of a chaotic system is its sensitivity to the infinitesimal changes in its initial conditions. A limit to predictability in chaotic system arises mainly due to this sensitivity and also due to the ineffectiveness of the model to reveal the underlying dynamics of the system. In the present study, an attempt is made to quantify these uncertainties involved and thereby improve the predictability by adopting a multivariate nonlinear ensemble prediction. Daily rainfall data of Malaprabha basin, India for the period 1955-2000 is used for the study. It is found to exhibit a low dimensional chaotic nature with the dimension varying from 5 to 7. A multivariate phase space is generated, considering a climate data set of 16 variables. The chaotic nature of each of these variables is confirmed using false nearest neighbor method. The redundancy, if any, of this atmospheric data set is further removed by employing principal component analysis (PCA) method and thereby reducing it to eight principal components (PCs). This multivariate series (rainfall along with eight PCs) is found to exhibit a low dimensional chaotic nature with dimension 10. Nonlinear prediction employing local approximation method is done using univariate series (rainfall alone) and multivariate series for different combinations of embedding dimensions and delay times. The uncertainty in initial conditions is thus addressed by reconstructing the phase space using different combinations of parameters. The ensembles generated from multivariate predictions are found to be better than those from univariate predictions. The uncertainty in predictions is decreased or in other words predictability is increased by adopting multivariate nonlinear ensemble prediction. The restriction on predictability of a chaotic series can thus be altered by quantifying the uncertainty in the initial conditions and also by including other possible variables, which may influence the system. (C) 2011 Elsevier B.V. All rights reserved.

Photo-Defined Electrically Assisted Etching Method for Metal Stencil Fabrication

Metal stencils are well known in electronics printing application such as for dispensing solder paste for surface mounting, printing embedded passive elements in multilayer structures, etc. For microprinting applications using stencils, the print quality depends on the smoothness of the stencil aperture and its dimensional accuracy, which in turn are invariably related to the method used to manufacture the stencils. In this paper, fabrication of metal stencils using a photo-defined electrically assisted etching method is described. Apertures in the stencil were made in neutral electrolyte using three different types of impressed current, namely, dc, pulsed dc, and periodic pulse reverse (PPR). Dimensional accuracy and wall smoothness of the etched apertures in each of the current waveforms were compared. Finally, paste transfer efficiency of the stencil obtained using PPR was calculated and compared with those of a laser-cut electropolished stencil. It is observed that the stencil fabricated using current in PPR waveform has better dimensional accuracy and aperture wall smoothness than those obtained with dc and pulsed dc. From the paste transfer efficiency experiment, it is concluded that photo-defined electrically assisted etching method can provide an alternate route for fabrication of metal stencils for future microelectronics printing applications.