Star formation in giant extragalactic H II regions

Star formation properties in Giant Extragalactic H II Regions (GEHRs) are investigated using optical photometry and evolutionary population synthesis models. Photometric data in $BVR$ bands and in the emission line of H-alpha are obtained by CCD imaging at Vainu Bappu Observatory, Kavalur. Aperture photometry is performed for 180 GEHRs in galaxies NGC 1365, 1566, 2366, 2903, 2997, 3351, 4303, 4449, 4656 and 5253. Thirty six of these GEHRs having published spectroscopic data are studied for star formation properties. The population synthesis model is constructed based on Maeder's stellar evolutionary and Kurucz stellar atmosphere models, to synthesize observational quantities of embedded clusters in GEHRs. The observed H-alpha luminosity is a measure of the number of massive stars while the contribution to BVR bands is from intermediate mass (5-15 solar mass) stars when the cluster is young and from evolving supergiants when the cluster is old (age >/= 6~Myr). Differential reddening between gas and embedded stars is essential to constrain the dereddened cluster colors within the range of youngest clusters. Obscuring dust closely associated with gas, which is distributed in filaments and clumps, as in the case of 30 Doradus, is the most likely configuration giving rise to net reduction of extinction towards stars. The fraction of the stellar photons escaping the nebula unattenuated is estimated to be 50%. GEHRs are rarely found to be simple systems containing stars from single generation. In the present sample such regions in addition to being older than 3~Myr, have their Lyman continuum luminosity reduced by as much as 60%, compared to the observed $B$ band luminosity for a normal IMF. The missing ionizing photons may be escaping the nebula, leading to the ionization of extra-H II region ionized medium. Co-existence of young (age and old populations (~10~Myr; Red Supergiants) is found to be common in GEHRs. The emission and continuum knots are seen spatially separated (40-100 pc) on CCD images in NGC 2997, 4303 and 4449 and may be direct evidences for the co-existence of young and old populations in giant star forming complexes. Triggering of star formation from earlier bursts is the most likely cause of new generation of stars, and may be a common phenomenon in GEHRs. Spatial separation between the young and old stars (~30 pc) had been earlier reported in 30 Doradus. Thus GEHRs in nearby galaxies share many of the properties shown by 30 Dor, the nearest GEHR. (SECTION: Dissertation Summaries)

A Comparative Study of the Formulations for Topology Optimization of Compliant Mechanisms

The topology optimization problem for the synthesis of compliant mechanisms has been formulated in many different ways in the last 15 years, but there is not yet a definitive formulation that is universally accepted. Furthermore, there are two unresolved issues in this problem. In this paper, we present a comparative study of five distinctly different formulations that are reported in the literature. Three benchmark examples are solved with these formulations using the same input and output specifications and the same numerical optimization algorithm. A total of 35 different synthesis examples are implemented. The examples are limited to desired instantaneous output direction for prescribed input force direction. Hence, this study is limited to linear elastic modeling with small deformations. Two design parameterizations, namely, the frame element based ground structure and the density approach using continuum elements, are used. The obtained designs are evaluated with all other objective functions and are compared with each other. The checkerboard patterns, point flexures, the ability to converge from an unbiased uniform initial guess, and the computation time are analyzed. Some observations are noted based on the extensive implementation done in this study. Complete details of the benchmark problems and the results are included. The computer codes related to this study are made available on the internet for ready access.

Single Cavity Trapped Vortex Combustor Simulations

The present work describes steady and unsteady computation of reacting flow in a Trapped Vortex Combustor. The primary motivation of this study is to develop this concept into a working combustor in modern gas turbines. The present work is an effort towards development of an experimental model test rig for further understanding dynamics of a single cavity trapped vortex combustor. The steady computations with and without combustion have been done for L/D of 0.8, 1 and 1.2; also unsteady non-reacting flow simulation has been done for L/D of 1. Fuel used for the present study is methane and Eddy-Dissipation model has been used for combustion-turbulence interactions. For L/D of 0.8, combustion efficiency is maximum and pattern factor is minimum. Also, primary vortex in the cavity is more stable and symmetric for L/D of 0.8. From unsteady non-reacting flow simulations, it is found that there is no vortex shedding from the cavity but there are oscillations in the span-wise direction of the combustor.

Border basis detection is NP-complete

Border basis detection (BBD) is described as follows: given a set of generators of an ideal, decide whether that set of generators is a border basis of the ideal with respect to some order ideal. The motivation for this problem comes from a similar problem related to Grobner bases termed as Grobner basis detection (GBD) which was proposed by Gritzmann and Sturmfels (1993). GBD was shown to be NP-hard by Sturmfels and Wiegelmann (1996). In this paper, we investigate the computational complexity of BBD and show that it is NP-complete.

Active Dendrites Regulate Spectral Selectivity in Location-Dependent Spike Initiation Dynamics of Hippocampal Model Neurons

How does the presence of plastic active dendrites in a pyramidal neuron alter its spike initiation dynamics? To answer this question, we measured the spike-triggered average (STA) from experimentally constrained, conductance-based hippocampal neuronal models of various morphological complexities. We transformed the STA computed from these models to the spectral and the spectrotemporal domains and found that the spike initiation dynamics exhibited temporally localized selectivity to a characteristic frequency. In the presence of the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, the STA characteristic frequency strongly correlated with the subthreshold resonance frequency in the theta frequency range. Increases in HCN channel density or in input variance increased the STA characteristic frequency and its selectivity strength. In the absence of HCN channels, the STA exhibited weak delta frequency selectivity and the characteristic frequency was related to the repolarization dynamics of the action potentials and the recovery kinetics of sodium channels from inactivation. Comparison of STA obtained with inputs at various dendritic locations revealed that nonspiking and spiking dendrites increased and reduced the spectrotemporal integration window of the STA with increasing distance from the soma as direct consequences of passive filtering and dendritic spike initiation, respectively. Finally, the presence of HCN channels set the STA characteristic frequency in the theta range across the somatodendritic arbor and specific STA measurements were strongly related to equivalent transfer-impedance-related measurements. Our results identify explicit roles for plastic active dendrites in neural coding and strongly recommend a dynamically reconfigurable multi-STA model to characterize location-dependent input feature selectivity in pyramidal neurons.

Homeostasis of functional maps in active dendrites emerges in the absence of individual channelostasis

The maintenance of ion channel homeostasis, or channelostasis, is a complex puzzle in neurons with extensive dendritic arborization, encompassing a combinatorial diversity of proteins that encode these channels and their auxiliary subunits, their localization profiles, and associated signaling machinery. Despite this, neurons exhibit amazingly stereotypic, topographically continuous maps of several functional properties along their active dendritic arbor. Here, we asked whether the membrane composition of neurons, at the level of individual ion channels, is constrained by this structural requirement of sustaining several functional maps along the same topograph. We performed global sensitivity analysis on morphologically realistic conductance-based models of hippocampal pyramidal neurons that coexpressed six well-characterized functional maps along their trunk. We generated randomized models by varying 32 underlying parameters and constrained these models with quantitative experimental measurements from the soma and dendrites of hippocampal pyramidal neurons. Analyzing valid models that satisfied experimental constraints on all six functional maps, we found topographically analogous functional maps to emerge from disparate model parameters with weak pairwise correlations between parameters. Finally, we derived a methodology to assess the contribution of individual channel conductances to the various functional measurements, using virtual knockout simulations on the valid model population. We found that the virtual knockout of individual channels resulted in variable, measurement and location-specific impacts across the population. Our results suggest collective channelostasis as a mechanism behind the robust emergence of analogous functional maps and have significant ramifications for the localization and targeting of ion channels and enzymes that regulate neural coding and homeostasis.

Multi-Temporal Satellite Image Analysis Using Gene Expression Programming

This paper discusses an approach for river mapping and flood evaluation to aid multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation to extract water covered region. Analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images is applied in two stages: before flood and during flood. For these images the extraction of water region utilizes spectral information for image classification and spatial information for image segmentation. Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as artificial neural networks and gene expression programming to separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water region. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification and region-based segmentation is an accurate and reliable for the extraction of water-covered region.

Basin Scale Water Resources Systems Modeling Under Cascading Uncertainties

Global change in climate and consequent large impacts on regional hydrologic systems have, in recent years, motivated significant research efforts in water resources modeling under climate change. In an integrated future hydrologic scenario, it is likely that water availability and demands will change significantly due to modifications in hydro-climatic variables such as rainfall, reservoir inflows, temperature, net radiation, wind speed and humidity. An integrated regional water resources management model should capture the likely impacts of climate change on water demands and water availability along with uncertainties associated with climate change impacts and with management goals and objectives under non-stationary conditions. Uncertainties in an integrated regional water resources management model, accumulating from various stages of decision making include climate model and scenario uncertainty in the hydro-climatic impact assessment, uncertainty due to conflicting interests of the water users and uncertainty due to inherent variability of the reservoir inflows. This paper presents an integrated regional water resources management modeling approach considering uncertainties at various stages of decision making by an integration of a hydro-climatic variable projection model, a water demand quantification model, a water quantity management model and a water quality control model. Modeling tools of canonical correlation analysis, stochastic dynamic programming and fuzzy optimization are used in an integrated framework, in the approach presented here. The proposed modeling approach is demonstrated with the case study of the Bhadra Reservoir system in Karnataka, India.

Activation of InsP(3) receptors is sufficient for inducing graded intrinsic plasticity in rat hippocampal pyramidal neurons

The synaptic plasticity literature has focused on establishing necessity and sufficiency as two essential and distinct features in causally relating a signaling molecule to plasticity induction, an approach that has been surprisingly lacking in the intrinsic plasticity literature. In this study, we complemented the recently established necessity of inositol trisphosphate (InsP(3)) receptors (InsP(3)R) in a form of intrinsic plasticity by asking if InsP(3)R activation was sufficient to induce intrinsic plasticity in hippocampal neurons. Specifically, incorporation of D-myo-InsP(3) in the recording pipette reduced input resistance, maximal impedance amplitude, and temporal summation but increased resonance frequency, resonance strength, sag ratio, and impedance phase lead. Strikingly, the magnitude of plasticity in all these measurements was dependent on InsP 3 concentration, emphasizing the graded dependence of such plasticity on InsP(3)R activation. Mechanistically, we found that this InsP(3)-induced plasticity depended on hyperpolarization-activated cyclic nucleotide-gated channels. Moreover, this calcium-dependent form of plasticity was critically reliant on the release of calcium through InsP(3)Rs, the influx of calcium through N-methyl-D-aspartate receptors and voltage-gated calcium channels, and on the protein kinase A pathway. Our results delineate a causal role for InsP(3)Rs in graded adaptation of neuronal response dynamics, revealing novel regulatory roles for the endoplasmic reticulum in neural coding and homeostasis.

Global response sensitivity analysis of uncertain structures

The problem of characterizing global sensitivity indices of structural response when system uncertainties are represented using probabilistic and (or) non-probabilistic modeling frameworks (which include intervals, convex functions, and fuzzy variables) is considered. These indices are characterized in terms of distance measures between a fiducial model in which uncertainties in all the pertinent variables are taken into account and a family of hypothetical models in which uncertainty in one or more selected variables are suppressed. The distance measures considered include various probability distance measures (Hellinger,l(2), and the Kantorovich metrics, and the Kullback-Leibler divergence) and Hausdorff distance measure as applied to intervals and fuzzy variables. Illustrations include studies on an uncertainly parametered building frame carrying uncertain loads. (C) 2015 Elsevier Ltd. All rights reserved.