Cause and Effect of Feedback: Multiphase Gas in Cluster Cores Heated by AGN Jets

Multiwavelength data indicate that the X-ray-emitting plasma in the cores of galaxy clusters is not cooling catastrophically. To a large extent, cooling is offset by heating due to active galactic nuclei (AGNs) via jets. The cool-core clusters, with cooler/denser plasmas, show multiphase gas and signs of some cooling in their cores. These observations suggest that the cool core is locally thermally unstable while maintaining global thermal equilibrium. Using high-resolution, three-dimensional simulations we study the formation of multiphase gas in cluster cores heated by collimated bipolar AGN jets. Our key conclusion is that spatially extended multiphase filaments form only when the instantaneous ratio of the thermal instability and free-fall timescales (t(TI)/t(ff)) falls below a critical threshold of approximate to 10. When this happens, dense cold gas decouples from the hot intracluster medium (ICM) phase and generates inhomogeneous and spatially extended Ha filaments. These cold gas clumps and filaments ``rain'' down onto the central regions of the core, forming a cold rotating torus and in part feeding the supermassive black hole. Consequently, the self-regulated feedback enhances AGN heating and the core returns to a higher entropy level with t(TI)/t(ff) > 10. Eventually, the core reaches quasi-stable global thermal equilibrium, and cold filaments condense out of the hot ICM whenever t(TI)/t(ff) less than or similar to 10. This occurs despite the fact that the energy from AGN jets is supplied to the core in a highly anisotropic fashion. The effective spatial redistribution of heat is enabled in part by the turbulent motions in the wake of freely falling cold filaments. Increased AGN activity can locally reverse the cold gas flow, launching cold filamentary gas away from the cluster center. Our criterion for the condensation of spatially extended cold gas is in agreement with observations and previous idealized simulations.

Influence fields: a quantitative framework for representation and analysis of active dendrites

Rathour RK, Narayanan R. Influence fields: a quantitative framework for representation and analysis of active dendrites. J Neurophysiol 107: 2313-2334, 2012. First published January 18, 2012; doi:10.1152/jn.00846.2011.-Neuronal dendrites express numerous voltage-gated ion channels (VGICs), typically with spatial gradients in their densities and properties. Dendritic VGICs, their gradients, and their plasticity endow neurons with information processing capabilities that are higher than those of neurons with passive dendrites. Despite this, frameworks that incorporate dendritic VGICs and their plasticity into neurophysiological and learning theory models have been far and few. Here, we develop a generalized quantitative framework to analyze the extent of influence of a spatially localized VGIC conductance on different physiological properties along the entire stretch of a neuron. Employing this framework, we show that the extent of influence of a VGIC conductance is largely independent of the conductance magnitude but is heavily dependent on the specific physiological property and background conductances. Morphologically, our analyses demonstrate that the influences of different VGIC conductances located on an oblique dendrite are confined within that oblique dendrite, thus providing further credence to the postulate that dendritic branches act as independent computational units. Furthermore, distinguishing between active and passive propagation of signals within a neuron, we demonstrate that the influence of a VGIC conductance is spatially confined only when propagation is active. Finally, we reconstruct functional gradients from VGIC conductance gradients using influence fields and demonstrate that the cumulative contribution of VGIC conductances in adjacent compartments plays a critical role in determining physiological properties at a given location. We suggest that our framework provides a quantitative basis for unraveling the roles of dendritic VGICs and their plasticity in neural coding, learning, and homeostasis.

Extent of Structural Asymmetry in Homodimeric Proteins: Prevalence and Relevance

Most homodimeric proteins have symmetric structure. Although symmetry is known to confer structural and functional advantage, asymmetric organization is also observed. Using a non-redundant dataset of 223 high-resolution crystal structures of biologically relevant homodimers, we address questions on the prevalence and significance of asymmetry. We used two measures to quantify global and interface asymmetry, and assess the correlation of several molecular and structural parameters with asymmetry. We have identified rare cases (11/223) of biologically relevant homodimers with pronounced global asymmetry. Asymmetry serves as a means to bring about 2:1 binding between the homodimer and another molecule; it also enables cellular signalling arising from asymmetric macromolecular ligands such as DNA. Analysis of these cases reveals two possible mechanisms by which possible infinite array formation is prevented. In case of homodimers associating via non-topologically equivalent surfaces in their tertiary structures, ligand-dependent mechanisms are used. For stable dimers binding via large surfaces, ligand-dependent structural change regulates polymerisation/depolymerisation; for unstable dimers binding via smaller surfaces that are not evolutionarily well conserved, dimerisation occurs only in the presence of the ligand. In case of homodimers associating via interaction surfaces with parts of the surfaces topologically equivalent in the tertiary structures, steric hindrance serves as the preventive mechanism of infinite array. We also find that homodimers exhibiting grossly symmetric organization rarely exhibit either perfect local symmetry or high local asymmetry. Binding of small ligands at the interface does not cause any significant variation in interface asymmetry. However, identification of biologically relevant interface asymmetry in grossly symmetric homodimers is confounded by the presence of similar small magnitude changes caused due to artefacts of crystallisation. Our study provides new insights regarding accommodation of asymmetry in homodimers.

Spatial Filter Based Bessel-Like Beam for Improved Penetration Depth Imaging in Fluorescence Microscopy

Monitoring and visualizing specimens at a large penetration depth is a challenge. At depths of hundreds of microns, several physical effects (such as, scattering, PSF distortion and noise) deteriorate the image quality and prohibit a detailed study of key biological phenomena. In this study, we use a Bessel-like beam in-conjugation with an orthogonal detection system to achieve depth imaging. A Bessel-like penetrating diffractionless beam is generated by engineering the back-aperture of the excitation objective. The proposed excitation scheme allows continuous scanning by simply translating the detection PSF. This type of imaging system is beneficial for obtaining depth information from any desired specimen layer, including nano-particle tracking in thick tissue. As demonstrated by imaging the fluorescent polymer-tagged-CaCO3 particles and yeast cells in a tissue-like gel-matrix, the system offers a penetration depth that extends up to 650 mu m. This achievement will advance the field of fluorescence imaging and deep nano-particle tracking.

Spatial Modulation and Space Shift Keying in Single Carrier Communication

Spatial modulation (SM) and space shift keying (SSK) are relatively new modulation techniques which are attractive in multi-antenna communications. Single carrier (SC) systems can avoid the peak-to-average power ratio (PAPR) problem encountered in multicarrier systems. In this paper, we study SM and SSK signaling in cyclic-prefixed SC (CPSC) systems on MIMO-ISI channels. We present a diversity analysis of MIMO-CPSC systems under SSK and SM signaling. Our analysis shows that the diversity order achieved by (n(t), n(r)) SSK scheme and (n(t), n(r), Theta(M)) SM scheme in MIMO-CPSC systems under maximum-likelihood (ML) detection is n(r), where n(t), n(r) denote the number of transmit and receive antennas and Theta(M) denotes the modulation alphabet of size M. Bit error rate (BER) simulation results validate this predicted diversity order. Simulation results also show that MIMO-CPSC with SM and SSK achieves much better performance than MIMO-OFDM with SM and SSK.

Spatial SINR Games of Base Station Placement and Mobile Association

We study the question of determining locations of base stations (BSs) that may belong to the same or to competing service providers. We take into account the impact of these decisions on the behavior of intelligent mobile terminals that can connect to the base station that offers the best utility. The signal-to-interference-plus-noise ratio (SINR) is used as the quantity that determines the association. We first study the SINR association-game: We determine the cells corresponding to each base stations, i.e., the locations at which mobile terminals prefer to connect to a given base station than to others. We make some surprising observations: 1) displacing a base station a little in one direction may result in a displacement of the boundary of the corresponding cell to the opposite direction; 2) a cell corresponding to a BS may be the union of disconnected subcells. We then study the hierarchical equilibrium in the combined BS location and mobile association problem: We determine where to locate the BSs so as to maximize the revenues obtained at the induced SINR mobile association game. We consider the cases of single frequency band and two frequency bands of operation. Finally, we also consider hierarchical equilibria in two frequency systems with successive interference cancellation.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Modulation Diversity for Spatial Modulation Using Complex Interleaved Orthogonal Design

In this paper, we propose modulation diversity techniques for Spatial Modulation (SM) system using Complex Interleaved Orthogonal Design (CIOD). Specifically, we show that the standard SM scheme can achieve a transmit diversity order of two by using the CIOD meant for two transmit antenna system without incurring any additional system complexity or bandwidth requirement. Furthermore, we propose a low-complexity maximum likelihood detector for our CIOD based SM schemes by exploiting the structure of the CIOD. We show with our simulation results that the proposed schemes offer transmit diversity order of two and give a better symbol error rate performance than the conventional SM scheme.

Effect of leachate recirculation and extent of degradation on the stability of bioreactor landfill slopes

The stability of a bioreactor landfill slope is influenced by the quantity and method of leachate recirculation as well as on the degree of decomposition. Other factors include properties variation of waste material and geometrical configurations, i.e., height and slope of landfills. Conventionally, the stability of slopes is evaluated using factor of safety approach, in which the variability in the engineering properties of MSW is not considered directly and stability issues are resolved from past experiences and good engineering judgments. On the other hand, probabilistic approach considers variability in mathematical framework and provides stability in a rational manner that helps in decision making. The objective of the present study is to perform a parametric study on the stability of a bioreactor landfill slope in probabilistic framework considering important influencing factors, such as, variation in MSW properties, amount of leachate recirculation, and age of degradation, in a systematic manner. The results are discussed in the light of existing relevant regulations, design and operation issues.

Antenna selection in spatial modulation systems

Novel transmit antenna selection techniques are conceived for Spatial Modulation (SM) systems and their symbol error rate (SER) performance is investigated. Specifically, low-complexity Euclidean Distance optimized Antenna Selection (EDAS) and Capacity Optimized Antenna Selection (COAS) are studied. It is observed that the COAS scheme gives a better SER performance than the EDAS scheme. We show that the proposed antenna selection based SM systems are capable of attaining a significant gain in signal-to-noise ratio (SNR) compared to conventional SM systems, and also outperform the conventional MIMO systems employing antenna selection at both low and medium SNRs.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Multispecies coexistence of trees in tropical forests: spatial signals of topographic niche differentiation increase with environmental heterogeneity

Neutral and niche theories give contrasting explanations for the maintenance of tropical tree species diversity. Both have some empirical support, but methods to disentangle their effects have not yet been developed. We applied a statistical measure of spatial structure to data from 14 large tropical forest plots to test a prediction of niche theory that is incompatible with neutral theory: that species in heterogeneous environments should separate out in space according to their niche preferences. We chose plots across a range of topographic heterogeneity, and tested whether pairwise spatial associations among species were more variable in more heterogeneous sites. We found strong support for this prediction, based on a strong positive relationship between variance in the spatial structure of species pairs and topographic heterogeneity across sites. We interpret this pattern as evidence of pervasive niche differentiation, which increases in importance with increasing environmental heterogeneity.

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.

Spatial memory deficits in maternal iron deficiency paradigms are associated with altered glucocorticoid levels

``The goal of this study was to examine the effect of maternal iron deficiency on the developing hippocampus in order to define a developmental window for this effect, and to see whether iron deficiency causes changes in glucocorticoid levels. The study was carried out using pre-natal, post-natal, and pre + post-natal iron deficiency paradigm. Iron deficient pregnant dams and their pups displayed elevated corticosterone which, in turn, differentially affected glucocorticoid receptor (GR) expression in the CA1 and the dentate gyrus. Brain Derived Neurotrophic Factor (BDNF) was reduced in the hippocampi of pups following elevated corticosterone levels. Reduced neurogenesis at P7 was seen in pups born to iron deficient mothers, and these pups had reduced numbers of hippocampal pyramidal and granule cells as adults. Hippocampal subdivision volumes also were altered. The structural and molecular defects in the pups were correlated with radial arm maze performance; reference memory function was especially affected. Pups from dams that were iron deficient throughout pregnancy and lactation displayed the complete spectrum of defects, while pups from dams that were iron deficient only during pregnancy or during lactation displayed subsets of defects. These findings show that maternal iron deficiency is associated with altered levels of corticosterone and GR expression, and with spatial memory deficits in their pups.'' (C) 2013 Elsevier Inc. All rights reserved.

Influence of Spatial Variation of Hydraulic Conductivity of Municipal Solid Waste on Performance of Bioreactor Landfill

The current study analyzes the leachate distribution in the Orchard Hills Landfill, Davis Junction, Illinois, using a two-phase flow model to assess the influence of variability in hydraulic conductivity on the effectiveness of the existing leachate recirculation system and its operations through reliability analysis. Numerical modeling, using finite-difference code, is performed with due consideration to the spatial variation of hydraulic conductivity of the municipal solid waste (MSW). The inhomogeneous and anisotropic waste condition is assumed because it is a more realistic representation of the MSW. For the reliability analysis, the landfill is divided into 10 MSW layers with different mean values of vertical and horizontal hydraulic conductivities (decreasing from top to bottom), and the parametric study is performed by taking the coefficients of variation (COVs) as 50, 100, 150, and 200%. Monte Carlo simulations are performed to obtain statistical information (mean and COV) of output parameters of the (1) wetted area of the MSW, (2) maximum induced pore pressure, and (3) leachate outflow. The results of the reliability analysis are used to determine the influence of hydraulic conductivity on the effectiveness of the leachate recirculation and are discussed in the light of a deterministic approach. The study is useful in understanding the efficiency of the leachate recirculation system. (C) 2013 American Society of Civil Engineers.