Examination of the role of follicle stimulating hormone in estrogen biosynthesis Image Image and Image Image in the ovary of cyclic hamster

The effect of neutralizing endogenous follicle stimulating hormone (FSH) or luteinizing hormone (LH) with specific antisera on the Image Image and Image Image synthesis of estrogen in the ovary of cycling hamster was studied. Neutralization of FSH or LH on proestrus resulted in a reduction in the estradiol concentration of the ovary on diestrus-2 and next proestrus, suggesting an impairment in follicular development.Injection of FSH antiserum at 0900 h of diestrus-2 significantly reduced the ovarian estradiol concentration within 6–7 h. Further, these ovaries on incubation with testosterone(T) Image Image at 1600 h of the same day or the next day synthesized significantly lower amounts of estradiol, compared to corresponding control ovaries. Although testosterone itself, in the absence of endogenous FSH, could stimulate estrogen synthesis to some extent, FSH had to be supplemented with T to restore estrogen synthesis to the level seen in control ovaries incubated with T. Lack of FSH thus appeared to affect the aromatization step in the estrogen biosynthetic pathway in the ovary of hamster on diestrus-2. In contrast to this, FSH antiserum given on the morning of proestrus had no effect on the Image Image and Image Image synthesis of estrogen, when examined 6–7 h later. The results suggest that there could be a difference in the need for FSH at different times of the cycle.Neutralization of LH either on diestrus-2 or proestrus resulted in a drastic reduction in estradiol concentration of the ovary. This block was at the level of androgen synthesis, since supplementing testosterone alone Image Image could stimulate estrogen synthesis to a more or less similar extent as in the ovaries of control hamsters.

Modeling server-unreliability in closed queuing-networks

A method is presented to model server unreliability in closed queuing networks. Breakdowns and repairs of servers, assumed to be time-dependent, are modeled using virtual customers and virtual servers in the system. The problem is thus converted into a closed queue with all reliable servers and preemptive resume priority centers. Several recent preemptive priority approximations and an approximation of the one proposed are used in the analysis. This method has approximately the same computational requirements as that of mean-value analysis for a network of identical dimensions and is therefore very efficient

Multiple contour extraction from graylevel images using an artificial neural network

For active contour modeling (ACM), we propose a novel self-organizing map (SOM)-based approach, called the batch-SOM (BSOM), that attempts to integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contours from images. We employ feature points, in the form of ail edge-map (as obtained from a standard edge-detection operation), to guide the contour (as in the case of SOM-based ACMs) along with the gradient and intensity variations in a local region to ensure that the contour does not "leak" into the object boundary in case of faulty feature points (weak or broken edges). In contrast with the snake-based ACMs, however, we do not use an explicit energy functional (based on gradient or intensity) for controlling the contour movement. We extend the BSOM to handle extraction of contours of multiple objects, by splitting a single contour into as many subcontours as the objects in the image. The BSOM and its extended version are tested on synthetic binary and gray-level images with both single and multiple objects. We also demonstrate the efficacy of the BSOM on images of objects having both convex and nonconvex boundaries. The results demonstrate the superiority of the BSOM over others. Finally, we analyze the limitations of the BSOM.

The fluctuations in slag foam under dynamic conditions

In the present article, slag foaming phenomenon under dynamic conditions is critically analyzed on the basis of the results of high-temperature X-ray image analysis experiments. The results indicate that the mismatch between the gas generation rate and gas escape rate has a serious impact on the foam height. This mismatch is attributed to the chemical reaction rate, which has to be considered in modeling slag foaming under dynamic conditions. The results further imply that a critical ratio of bubble size/crucible size exists, where wall effects are likely to become prominent.

New a posteriori error estimator and adaptive mesh refinement strategy for 2-D crack problems

A posteriori error estimation and adaptive refinement technique for fracture analysis of 2-D/3-D crack problems is the state-of-the-art. The objective of the present paper is to propose a new a posteriori error estimator based on strain energy release rate (SERR) or stress intensity factor (SIF) at the crack tip region and to use this along with the stress based error estimator available in the literature for the region away from the crack tip. The proposed a posteriori error estimator is called the K-S error estimator. Further, an adaptive mesh refinement (h-) strategy which can be used with K-S error estimator has been proposed for fracture analysis of 2-D crack problems. The performance of the proposed a posteriori error estimator and the h-adaptive refinement strategy have been demonstrated by employing the 4-noded, 8-noded and 9-noded plane stress finite elements. The proposed error estimator together with the h-adaptive refinement strategy will facilitate automation of fracture analysis process to provide reliable solutions.

Modeling of the sea surface for daylight imagery studies

Plastic-coated paper is shown to possess reflectivity characteristics quite similar to those of the surface of water. This correspondence has been used with a conversion factor to model a sea surface by means of plastic-coated paper. Such a paper model is then suitably illuminated and photographed, yielding physically simulated daylight imagery of the sea surface under controlled conditions. A simple example of sinusoidal surface simulation is described.

Simultaneous display of image and spectrum in the same plane: a generalized analysis

A generalized analysis, using the Vander Lugt operational notation, of the building block optical system comprising a single holographic optical element (HOE) for achieving simultaneous display of the spectrum and the image of an object in a single plane, has been carried out. The salient features of this analysis are: (1) it allows comprehensive characterization of the HOE, (2) it provides insights into the many possible configurations for the system, and (3) it explains the existing results in a consistent manner.

Experimental studies and phase field modeling of microstructure evolution during solidification with electromagnetic stirring

Thixocasting requires manufacturing of billets with non-dendritic microstructure. Aluminum alloy A356 billets were produced by rheocasting in a mould placed inside a linear electromagnetic stirrer. Subsequent heat treatment was used to produce a transition from rosette to globular microstructure. The current and the duration of stirring were explored as control parameters. Simultaneous induction heating of the billet during stirring was quantified using experimentally determined thermal profiles. The effect of processing parameters on the dendrite fragmentation was discussed. Corresponding computational modeling of the process was performed using phase-field modeling of alloy solidification in order to gain insight into the process of morphological changes of a solid during this process. A non-isothermal alloy solidification model was used for simulations. The morphological evolution under such imposed thermal cycles was simulated and compared with experimentally determined one. Suitable scaling using the thermosolutal diffusion distances was used to overcome computational difficulties in quantitative comparison at system scale. The results were interpreted in the light of existing theories of microstructure refinement and globularisation.

Complexation of siRNA with Dendrimer: A Molecular Modeling Approach

This paper reports the structural behavior and thermodynamics of the complexation of siRNA with poly(amidoamine) (PAMAM) dendrimers of generation 3 (G3) and 4 (G4) through fully atomistic molecular dynamics (MD) simulations accompanied by free energy calculations and inherent structure determination. We have also done simulation with one siRNA and two dendrimers (2 x G3 or 2xG4) to get the microscopic picture of various binding modes. Our simulation results reveal the formation of stable siRNA-dendrimer complex over nanosecond time scale. With the increase in dendrimcr generation, the charge ratio increases and hence the binding energy between siRNA and dendrimer also increases in accordance with available experimental measurements. Calculated radial distribution functions of amines groups of various subgenerations in a given generation of dendrimer and phosphate in backbone of siRNA reveals that one dendrimer of generation 4 shows better binding with siRNA almost wrapping the dendrimer when compared to the binding with lower generation dendrimer like G3. In contrast, two dendrimers of generation 4 show binding without siRNA wrapping the den-rimer because of repulsion between two dendrimers. The counterion distribution around the complex and the water molecules in the hydration shell of siRNA give microscopic picture of the binding dynamics. We see a clear correlation between water. counterions motions and the complexation i.e. the water molecules and counterions which condensed around siRNA are moved away from the siRNA backbone when dendrimer start binding to the siRNA back hone. As siRNA wraps/bind to the dendrimer counterions originally condensed onto siRNA (Na-1) and dendrimer (Cl-) get released. We give a quantitative estimate of the entropy of counterions and show that there is gain in entropy due to counterions release during the complexation. Furthermore, the free energy of complexation of IG3 and IG4 at two different salt concentrations shows that increase in salt concentration leads to the weakening of the binding affinity of siRNA and dendrimer.

Performance study of high operating temperature HgCdTe mid wave infrared detector through numerical modeling

The design of present generation uncooled Hg1-xCdxTe infrared photon detectors relies on complex heterostructures with a basic unit cell of type (n) under bar (+)/pi/(p) under bar (+). We present an analysis of double barrier (n) under bar (+)/pi/(p) under bar (+) mid wave infrared (x = 0.3) HgCdTe detector for near room temperature operation using numerical computations. The present work proposes an accurate and generalized methodology in terms of the device design, material properties, and operation temperature to study the effects of position dependence of carrier concentration, electrostatic potential, and generation-recombination (g-r) rates on detector performance. Position dependent profiles of electrostatic potential, carrier concentration, and g-r rates were simulated numerically. Performance of detector was studied as function of doping concentration of absorber and contact layers, width of both layers and minority carrier lifetime. Responsivity similar to 0.38 A W-1, noise current similar to 6 x 10(-14) A/Hz(1/2) and D* similar to 3.1 x 10(10)cm Hz(1/2) W-1 at 0.1 V reverse bias have been calculated using optimized values of doping concentration, absorber width and carrier lifetime. The suitability of the method has been illustrated by demonstrating the feasibility of achieving the optimum device performance by carefully selecting the device design and other parameters. (C) 2010 American Institute of Physics. doi:10.1063/1.3463379]

Analytical modeling of quantum threshold voltage for triple gate MOSFET

In this work a physically based analytical quantum threshold voltage model for the triple gate long channel metal oxide semiconductor field effect transistor is developed The proposed model is based on the analytical solution of two-dimensional Poisson and two-dimensional Schrodinger equation Proposed model is extended for short channel devices by including semi-empirical correction The impact of effective mass variation with film thicknesses is also discussed using the proposed model All models are fully validated against the professional numerical device simulator for a wide range of device geometries (C) 2010 Elsevier Ltd All rights reserved

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

Homomorphic Analysis and Modeling of ECG Signals

Homomorphic analysis and pole-zero modeling of electrocardiogram (ECG) signals are presented in this paper. Four typical ECG signals are considered and deconvolved into their minimum and maximum phase components through cepstral filtering, with a view to study the possibility of more efficient feature selection from the component signals for diagnostic purposes. The complex cepstra of the signals are linearly filtered to extract the basic wavelet and the excitation function. The ECG signals are, in general, mixed phase and hence, exponential weighting is done to aid deconvolution of the signals. The basic wavelet for normal ECG approximates the action potential of the muscle fiber of the heart and the excitation function corresponds to the excitation pattern of the heart muscles during a cardiac cycle. The ECG signals and their components are pole-zero modeled and the pole-zero pattern of the models can give a clue to classify the normal and abnormal signals. Besides, storing only the parameters of the model can result in a data reduction of more than 3:1 for normal signals sampled at a moderate 128 samples/s