Assessment of luteal rescue and desensitization of macaque corpus luteum brought about by human chorionic gonadotrophin and deglycosylated human chorionic gonadotrophin treatment

The objective of the current study was to investigate the mechanism by which the corpus luteum (CL) of the monkey undergoes desensitization to luteinizing hormone following exposure to increasing concentration of human chorionic gonadotrophin (hCG) as it occurs in pregnancy. Female bonnet monkeys were injected (im) increasing doses of hCG or dghCG beginning from day 6 or 12 of the luteal phase for either 10 or 4 or 2 days. The day of oestrogen surge was considered as day '0' of luteal phase. Luteal cells obtained from CL of these animals were incubated with hCG (2 and 200 pg/ml) or dbcAMP (2.5, 25 and 100 mu M) for 3 h at 37 degrees C and progesterone secreted was estimated. Corpora lutea of normal cycling monkeys on day 10/16/22 of the luteal phase were used as controls, In addition the in vivo response to CG and deglycosylated hCG (dghCG) was assessed by determining serum steroid profiles following their administration. hCG (from 15-90 IU) but not dghCG (15-90 IU) treatment in vivo significantly (P < 0.05) elevated serum progesterone and oestradiol levels. Serum progesterone, however, could not be maintained at a elevated level by continuous treatment with hCG (from day 6-15), the progesterone level declining beyond day 13 of luteal phase. Administering low doses of hCG (15-90 IU/day) from day 6-9 or high doses (600 IU/day) on days 8 and 9 of the luteal phase resulted in significant increase (about 10-fold over corresponding control P < 0.005) in the ability of luteal cells to synthesize progesterone (incubated controls) in vitro. The luteal cells of the treated animals responded to dbcAMP (P < 0.05) but not to hCG added in vitro, The in vitro response of luteal cells to added hCG was inhibited by 0, 50 and 100% if the animals were injected with low (15-90 IU) or medium (100 IU) between day 6-9 of luteal phase and high (600 IU on day 8 and 9 of luteal phase) doses of dghCG respectively; such treatment had no effect on responsivity of the cells to dbcAMP, The luteal cell responsiveness to dbcAMP in vitro was also blocked if hCG was administered for 10 days beginning day 6 of the luteal phase. Though short term hCG treatment during late luteal phase (from days 12-15) had no effect on luteal function, 10 day treatment beginning day 12 of luteal phase resulted in regain of in vitro responsiveness to both hCG (P < 0.05) and dbcAMP (P < 0.05) suggesting that luteal rescue can occur even at this late stage. In conclusion, desensitization of the CL to hCG appears to be governed by the dose/period for which it is exposed to hCG/dghCG. That desensitization is due to receptor occupancy is brought out by the fact that (i) this can be achieved by giving a larger dose of hCG over a 2 day period instead of a lower dose of the hormone for a longer (4 to 10 days) period and (ii) the effect can largely be reproduced by using dghCG instead of hCG to block the receptor sites. It appears that to achieve desensitization to dbcAMP also it is necessary to expose the luteal cell to relatively high dose of hCG for more than 4 days.

Correction for Bias in Downscaling GCM Simulations for Hydrologic Impact Assessment

In a statistical downscaling model, it is important to remove the bias of General Circulations Model (GCM) outputs resulting from various assumptions about the geophysical processes. One conventional method for correcting such bias is standardisation, which is used prior to statistical downscaling to reduce systematic bias in the mean and variances of GCM predictors relative to the observations or National Centre for Environmental Prediction/ National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data. A major drawback of standardisation is that it may reduce the bias in the mean and variance of the predictor variable but it is much harder to accommodate the bias in large-scale patterns of atmospheric circulation in GCMs (e.g. shifts in the dominant storm track relative to observed data) or unrealistic inter-variable relationships. While predicting hydrologic scenarios, such uncorrected bias should be taken care of; otherwise it will propagate in the computations for subsequent years. A statistical method based on equi-probability transformation is applied in this study after downscaling, to remove the bias from the predicted hydrologic variable relative to the observed hydrologic variable for a baseline period. The model is applied in prediction of monsoon stream flow of Mahanadi River in India, from GCM generated large scale climatological data.

Seismic reliability assessment of internal stability of reinforced soil walls using the pseudo-dynamic method

The study focuses on probabilistic assessment of the internal seismic stability of reinforced soil structures (RSS) subjected to earthquake loading in the framework of the pseudo-dynamic method. In the literature, the pseudo-static approach has been used to compute reliability indices against the tension and pullout failure modes, and the real dynamic nature of earthquake accelerations cannot be considered. The work presented in this paper makes use of the horizontal and vertical sinusoidal accelerations, amplification of vibrations, shear wave and primary wave velocities and time period. This approach is applied to quantify the influence of the backfill properties, geosynthetic reinforcement and characteristics of earthquake ground motions on reliability indices in relation to the tension and pullout failure modes. Seismic reliability indices at different levels of geosynthetic layers are determined for different magnitudes of seismic acceleration, soil amplification, shear wave and primary wave velocities. The results are compared with the pseudo-static method, and the significance of the present methodology for designing reinforced soil structures is discussed.

Assessment of seismic hazard and liquefaction potential of Gujarat based on probabilistic approaches

Gujarat is one of the fastest-growing states of India with high industrial activities coming up in major cities of the state. It is indispensable to analyse seismic hazard as the region is considered to be most seismically active in stable continental region of India. The Bhuj earthquake of 2001 has caused extensive damage in terms of causality and economic loss. In the present study, the seismic hazard of Gujarat evaluated using a probabilistic approach with the use of logic tree framework that minimizes the uncertainties in hazard assessment. The peak horizontal acceleration (PHA) and spectral acceleration (Sa) values were evaluated for 10 and 2 % probability of exceedance in 50 years. Two important geotechnical effects of earthquakes, site amplification and liquefaction, are also evaluated, considering site characterization based on site classes. The liquefaction return period for the entire state of Gujarat is evaluated using a performance-based approach. The maps of PHA and PGA values prepared in this study are very useful for seismic hazard mitigation of the region in future.

Large scale features and assessment of spatial scale correspondence between TMPA and IMD rainfall datasets over Indian landmass

Daily rainfall datasets of 10 years (1998-2007) of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) version 6 and India Meteorological Department (IMD) gridded rain gauge have been compared over the Indian landmass, both in large and small spatial scales. On the larger spatial scale, the pattern correlation between the two datasets on daily scales during individual years of the study period is ranging from 0.4 to 0.7. The correlation improved significantly (similar to 0.9) when the study was confined to specific wet and dry spells each of about 5-8 days. Wavelet analysis of intraseasonal oscillations (ISO) of the southwest monsoon rainfall show the percentage contribution of the major two modes (30-50 days and 10-20 days), to be ranging respectively between similar to 30-40% and 5-10% for the various years. Analysis of inter-annual variability shows the satellite data to be underestimating seasonal rainfall by similar to 110 mm during southwest monsoon and overestimating by similar to 150 mm during northeast monsoon season. At high spatio-temporal scales, viz., 1 degrees x1 degrees grid, TMPA data do not correspond to ground truth. We have proposed here a new analysis procedure to assess the minimum spatial scale at which the two datasets are compatible with each other. This has been done by studying the contribution to total seasonal rainfall from different rainfall rate windows (at 1 mm intervals) on different spatial scales (at daily time scale). The compatibility spatial scale is seen to be beyond 5 degrees x5 degrees average spatial scale over the Indian landmass. This will help to decide the usability of TMPA products, if averaged at appropriate spatial scales, for specific process studies, e.g., cloud scale, meso scale or synoptic scale.

An insight into real-time performance assessment of a building integrated photovoltaic (BIPV) installation in Bangalore (India)

Building integrated photovoltaic (BIPV) applications are gaining widespread popularity. The performance of any given BIPV system is dependent on prevalent meteorological factors, site conditions and system characteristics. Investigations pertaining to the performance assessment of photovoltaic (PV) systems are generally confined to either controlled environment-chambers or computer-based simulation studies. Such investigations fall short of providing a realistic insight into how a PV system actually performs real-time. Solar radiation and the PV cell temperature are amongst the most crucial parameters affecting PV output. The current paper deals with the real-time performance assessment of a recently commissioned 5.25 kW, BIPV system installed at the Center for Sustainable Technologies, Indian Institute of Science, Bangalore. The overall average system efficiency was found to be 6% for the period May 2011-April 2012. This paper provides a critical appraisal of PV system performance based on ground realities, particularly characteristic to tropical (moderate) regions such as Bangalore, India. (C) 2013 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

Comprehensive seismic hazard assessment of Tripura and Mizoram states

Northeast India is one of the most highly seismically active regions in the world with more than seven earthquakes on an average per year of magnitude 5.0 and above. Reliable seismic hazard assessment could provide the necessary design inputs for earthquake resistant design of structures in this' region. In this study, deterministic as well as probabilistic methods have been attempted for seismic hazard assessment of Tripura and Mizoram states at bedrock level condition. An updated earthquake catalogue was collected from various national and international seismological agencies for the period from 1731 to 2011. The homogenization, declustering and data completeness analysis of events have been carried out before hazard evaluation. Seismicity parameters have been estimated using G R relationship for each source zone. Based on the seismicity, tectonic features and fault rupture mechanism, this region was divided into six major subzones. Region specific correlations were used for magnitude conversion for homogenization of earthquake size. Ground motion equations (Atkinson and Boore 2003; Gupta 2010) were validated with the observed PGA (peak ground acceleration) values before use in the hazard evaluation. In this study, the hazard is estimated using linear sources, identified in and around the study area. Results are presented in the form of PGA using both DSHA (deterministic seismic hazard analysis) and PSHA (probabilistic seismic hazard analysis) with 2 and 10% probability of exceedance in 50 years, and spectral acceleration (T = 0. 2 s, 1.0 s) for both the states (2% probability of exceedance in 50 years). The results are important to provide inputs for planning risk reduction strategies, for developing risk acceptance criteria and financial analysis for possible damages in the study area with a comprehensive analysis and higher resolution hazard mapping.

An assessment of terrestrial water storage, rainfall and river discharge over Northern India from satellite data

Terrestrial water storage (TWS) plays a key role in the global water cycle and is highly influenced by climate variability and human activities. In this study, monthly TWS, rainfall and Ganga-Brahmaputra river discharge (GBRD) are analysed over India for the period of 2003-12 using remote sensing satellite data. The spatial pattern of mean TWS shows a decrease over a large and populous region of Northern India comprising the foothills of the Himalayas, the Indo-Gangetic Plains and North East India. Over this region, the mean monthly TWS exhibits a pronounced seasonal cycle and a large interannual variability, highly correlated with rainfall and GBRD variations (r > 0.8) with a lag time of 2 months and 1 month respectively. The time series of monthly TWS shows a consistent and statistically significant decrease of about 1 cm year(-1) over Northern India, which is not associated with changes in rainfall and GBRD. This recent change in TWS suggests a possible impact of rapid industrialization, urbanization and increase in population on land water resources. Our analysis highlights the potential of the Earth-observation satellite data for hydrological applications.

Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data

Surface energy processes has an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. The research was undertaken to analyze the potential of Landsat and MODIS data in retrieving biophysical parameters in estimating land surface temperature & heat fluxes diurnally in summer and winter seasons of years 2000 and 2010 and understanding its effect on anthropogenic heat disturbance over Delhi and surrounding region. Results show that during years 2000-2010, settlement and industrial area increased from 5.66 to 11.74% and 4.92 to 11.87% respectively which in turn has direct effect on land surface temperature (LST) and heat fluxes including anthropogenic heat flux. Based on the energy balance model for land surface, a method to estimate the increase in anthropogenic heat flux (Has) has been proposed. The settlement and industrial areas has higher amounts of energy consumed and has high values of Has in all seasons. The comparison of satellite derived LST with that of field measured values show that Landsat estimated values are in close agreement within error of 2 degrees C than MODIS with an error of 3 degrees C. It was observed that, during 2000 and 2010, the average change in surface temperature using Landsat over settlement & industrial areas of both seasons is 1.4 degrees C & for MODIS data is 3.7 degrees C. The seasonal average change in anthropogenic heat flux (Has) estimated using Landsat & MODIS is up by around 38 W/m(2) and 62 W/m(2) respectively while higher change is observed over settlement and concrete structures. The study reveals that the dynamic range of Has values has increased in the 10 year period due to the strong anthropogenic influence over the area. The study showed that anthropogenic heat flux is an indicator of the strength of urban heat island effect, and can be used to quantify the magnitude of the urban heat island effect. (C) 2013 Elsevier Ltd. All rights reserved.