Planform structure of turbulent free convection on horizontal surfaces

The planform structure of turbulent free convection over a heated horizontal surface has been visualized and analyzed for different boundary conditions at the top and for different aspect ratios, for flux Rayleigh numbers ranging from 10 exp 8 - 10 exp 10. The different boundary conditions correspond to Rayleigh-Benard convection, open convection with evaporation at the top and with an imposed external flow on the heated boundary. Without the external flow the planform is one randomly oriented line plume. At large Ra, these line plumes seem to align along the diagonal, persumably due to a large-scale flow along as visualized in the side view. When the external flow is imposed, the line plumes clearly align in the direction of external flow. Flow visualization reveals that at these Ra, the shear tends to break the plumes which otherwise would reach the opposite boundary. (Author)

Learning polyhedral classifiers using logistic function

In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimization problem, our method solves an unconstrained optimization problem. Our method is based on a logistic function based model for the posterior probability function. We propose an alternating optimization algorithm, namely, SPLA1 (Single Polyhedral Learning Algorithm1) which maximizes the loglikelihood of the training data to learn the parameters. We also extend our method to make it independent of any user specified parameter (e.g., number of hyperplanes required to form a polyhedral set) in SPLA2. We show the effectiveness of our approach with experiments on various synthetic and real world datasets and compare our approach with a standard decision tree method (OC1) and a constrained optimization based method for learning polyhedral sets.

A Revisit to Capture the Entire Behavior of Ultrasonic Wave Dispersion Characteristics of Single Walled Carbon Nanotubes Based on Nonlocal Elasticity Theory and Flugge Shell Model

In this paper, an ultrasonic wave propagation analysis in single-walled carbon nanotube (SWCNT) is re-studied using nonlocal elasticity theory, to capture the whole behaviour. The SWCNT is modeled using Flugge's shell theory, with the wall having axial, circumferential and radial degrees of freedom and also including small scale effects. Nonlocal governing equations for this system are derived and wave propagation analysis is also carried out. The revisited nonlocal elasticity calculation shows that the wavenumber tends to infinite at certain frequencies and the corresponding wave velocity tends to zero at those frequencies indicating localization and stationary behavior. This frequency is termed as escape frequency. This behavior is observed only for axial and radial waves in SWCNT. It has been shown that the circumferential waves will propagate dispersively at higher frequencies in nonlocality. The magnitudes of wave velocities of circumferential waves are smaller in nonlocal elasticity as compared to local elasticity. We also show that the explicit expressions of cut-off frequency depend on the nonlocal scaling parameter and the axial wavenumber. The effect of axial wavenumber on the ultrasonic wave behavior in SWCNTs is also discussed. The present results are compared with the corresponding results (for first mode) obtained from ab initio and 3-D elastodynamic continuum models. The acoustic phonon dispersion relation predicted by the present model is in good agreement with that obtained from literature. The results are new and can provide useful guidance for the study and design of the next generation of nanodevices that make use of the wave propagation properties of single-walled carbon nanotubes.

Small-Angle Neutron-Scattering Studies of Mixed Micellar Structures Made of Dimeric Surfactants Having Imidazolium and Ammonium Headgroups

Planar imidazolium cation based gemini surfactants 16-Im-n-Im-16], 2Br(-) (where n = 2, 3, 4, 5, 6, 8, 10, and 12), exhibit different morphologies and internal packing arrangements by adopting different supramolecular assemblies in aqueous media depending on their number of spacer methylene units (CH2)(n). Detailed measurements of the small-angle neutron-scattering (SANS) cross sections from different imidazolium-based surfactant micelles in aqueous media (D2O) are reported. The SANS data, containing the information of aggregation behavior of such surfactants in the molecular level, have been analyzed on the basis of the Hayter and Penfold model for the macro ion solution to compute the interparticle structure factor S(Q) taking into account the screened Coulomb interactions between the dimeric surfactant micelles. The characteristic changes in the SANS spectra of the dimeric surfactant with n = 4 due to variation of temperature have also been investigated. These data are then compared with the SANS characterization data of the corresponding gemini micelles containing tetrahedral ammonium ion based polar headgroups. The critical micellar concentration of each surfactant micelle (cmc) has been determined using pyrene as an extrinsic fluorescence probe. The variation of cmc as a function of spacer chain length has been explained in terms of conformational variation and progressive looping of the spacer into the micellar interior upon increasing the n values. Small-angle neutron-scattering (SANS) cross sections from different mixed micelles composed of surfactants with ammonium headgroups, 16-A(0), 16-Am-n-Am-16], 2Br(-) (where n = 4), 16-I-0, and 16-Im-n-Im-16], 2Br(-) (where n = 4), in aqueous media (D2O) have also been analyzed. The aggregate composition matches with that predicted from the ideal mixing model.

Automatic road extraction using high resolution satellite images based on Level Set and Mean Shift methods

Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

Synthesis, Characterization, and Properties of Few-Layer MoO3

Nanosheets of MoO3 that consist of only a few layers have been prepared by using four methods, including the oxidation of MoS2 nanosheets, intercalation with LiBr, and ultrasonication. These nanosheets have been characterized by atomic force microscopy and other techniques. Besides showing a blue-shift of the optical absorption band compared to the bulk sample, few-layer MoO3 exhibits enhanced photocatalytic activity. In combination with a borocarbonitride, few-layer MoO3 shows good performance characteristics as a supercapacitor electrode.

On piercing (pseudo)lines and boxes

We say a family of geometric objects C has (l;k)-property if every subfamily C0C of cardinality at most lisk- piercable. In this paper we investigate the existence of g(k;d)such that if any family of objects C in Rd has the (g(k;d);k)-property, then C is k-piercable. Danzer and Gr̈ unbaum showed that g(k;d)is infinite for fami-lies of boxes and translates of centrally symmetric convex hexagons. In this paper we show that any family of pseudo-lines(lines) with (k2+k+ 1;k)-property is k-piercable and extend this result to certain families of objects with discrete intersections. This is the first positive result for arbitrary k for a general family of objects. We also pose a relaxed ver-sion of the above question and show that any family of boxes in Rd with (k2d;k)-property is 2dk- piercable.

Hardness results for computing optimal locally Gabriel graphs

Delaunay and Gabriel graphs are widely studied geo-metric proximity structures. Motivated by applications in wireless routing, relaxed versions of these graphs known as Locally Delaunay Graphs (LDGs) and Lo-cally Gabriel Graphs (LGGs) have been proposed. We propose another generalization of LGGs called Gener-alized Locally Gabriel Graphs (GLGGs) in the context when certain edges are forbidden in the graph. Unlike a Gabriel Graph, there is no unique LGG or GLGG for a given point set because no edge is necessarily in-cluded or excluded. This property allows us to choose an LGG/GLGG that optimizes a parameter of interest in the graph. We show that computing an edge max-imum GLGG for a given problem instance is NP-hard and also APX-hard. We also show that computing an LGG on a given point set with dilation ≤k is NP-hard. Finally, we give an algorithm to verify whether a given geometric graph G= (V, E) is a valid LGG.

Synconset Waves and Chains: Spiking Onsets in Synchronous Populations Predict and Are Predicted by Network Structure

Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define `synconset wave' as a cascade of first spikes within a synchronisation event. Synconset waves would occur in `synconset chains', which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony.

Long-Term Environmental Correlates of Invasion by Lantana camara (Verbenaceae) in a Seasonally Dry Tropical Forest

Invasive species, local plant communities and invaded ecosystems change over space and time. Quantifying this change may lead to a better understanding of the ecology and the effective management of invasive species. We used data on density of the highly invasive shrub Lantana camara (lantana) for the period 1990-2008 from a 50 ha permanent plot in a seasonally dry tropical forest of Mudumalai in southern India. We used a cumulative link mixed-effects regression approach to model the transition of lantana from one qualitative density state to another as a function of biotic factors such as indicators of competition from local species (lantana itself, perennial grasses, invasive Chromolaena odorata, the native shrub Helicteres isora and basal area of native trees) and abiotic factors such as fire frequency, inter-annual variability of rainfall and relative soil moisture. The density of lantana increased substantially during the study period. Lantana density was negatively associated with the density of H. isora, positively associated with basal area of native trees, but not affected by the presence of grasses or other invasive species. In the absence of fire, lantana density increased with increasing rainfall. When fires occurred, transitions to higher densities occurred at low rainfall values. In drier regions, lantana changed from low to high density as rainfall increased while in wetter regions of the plot, lantana persisted in the dense category irrespective of rainfall. Lantana seems to effectively utilize resources distributed in space and time to its advantage, thus outcompeting local species and maintaining a population that is not yet self-limiting. High-risk areas and years could potentially be identified based on inferences from this study for facilitating management of lantana in tropical dry forests.

Density Functional Theoretical Modeling, Electrostatic Surface Potential and Surface Enhanced Raman Spectroscopic Studies on Biosynthesized Silver Nanoparticles: Observation of 400 pM Sensitivity to Explosives

Interaction of adsorbate on charged surfaces, orientation of the analyte on the surface, and surface enhancement aspects have been studied. These aspects have been explored in details to explain the surface-enhanced Raman spectroscopic (SERS) spectra of 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (HNIW or CL-20), a well-known explosive, and 2,4,6-trinitrotoluene (TNT) using one-pot synthesis of silver nanoparticles via biosynthetic route using natural precursor extracts of clove and pepper. The biosynthesized silver nanoparticles (bio Ag Nps) have been characterized using UV-vis spectroscopy, scanning electron microscopy and atomic force microscopy. SERS studies conducted using bio Ag Nps on different water insoluble analytes, such as CL-20 and TNT, lead to SERS signals at concentration levels of 400 pM. The experimental findings have been corroborated with density functional computational results, electrostatic surface potential calculations, Fukui functions and potential measurements.

An Improved Dead-Time Compensation Scheme for Voltage Source Inverters Considering the Device Switching Transition Times

Inverter dead-time, which is meant to prevent shoot-through fault, causes harmonic distortion and change in the fundamental voltage in the inverter output. Typical dead-time compensation schemes ensure that the amplitude of the fundamental output current is as desired, and also improve the current waveform quality significantly. However, even with compensation, the motor line current waveform is observed to be distorted close to the current zero-crossings. The IGBT switching transition times being significantly longer at low currents than at high currents is an important reason for this zero-crossover distortion. Hence, this paper proposes an improved dead-time compensation scheme, which makes use of the measured IGBT switching transition times at low currents. Measured line current waveforms in a 2.2 kW induction motor drive with the proposed compensation scheme are compared against those with the conventional dead-time compensation scheme and without dead-time compensation. The experimental results on the motor drive clearly demonstrate the improvement in the line current waveform quality with the proposed method.

Coupling geomorphology parameters with lithology for micro-level groundwater resource assessment: a case study from semi-arid hard rock terrain in Tamil Nadu, India

The standard procedure of groundwater resource estimation in India till date is based on the specific yield parameters of each rock type (lithology) derived through pumping test analysis. Using the change in groundwater level, specific yield, and area of influence, groundwater storage change could be estimated. However, terrain conditions in the form of geomorphological variations have an important bearing on the net groundwater recharge. In this study, an attempt was made to use both lithology and geomorphology as input variables to estimate the recharge from different sources in each lithology unit influenced by the geomorphic conditions (lith-geom), season wise separately. The study provided a methodological approach for an evaluation of groundwater in a semi-arid hard rock terrain in Tirunelveli, Tamil Nadu, India. While characterizing the gneissic rock, it was found that the geomorphologic variations in the gneissic rock due to weathering and deposition behaved differently with respect to aquifer recharge. The three different geomorphic units identified in gneissic rock (pediplain shallow weathered (PPS), pediplain moderate weathered (PPM), and buried pediplain moderate (BPM)) showed a significant variation in recharge conditions among themselves. It was found from the study that Peninsular gneiss gives a net recharge value of 0.13 m/year/unit area when considered as a single unit w.r.t. lithology, whereas the same area considered with lith-geom classes gives recharge values between 0.1 and 0.41 m/year presenting a different assessment. It is also found from this study that the stage of development (SOD) for each lith-geom unit in Peninsular gneiss varies from 168 to 230 %, whereas the SOD is 223 % for the lithology as a single unit.