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A Reduced Switch Count Single-Stage Three-Phase Bidirectional Rectifier With High-Frequency Isolation
No full textDual active bridge (DAB) based converters offer the benefit of smaller volume due to high-frequency isolation and controllability of active power flow, making them attractive for various applications, such as renewable energy generation, plug-in hybrid vehicles, and distribution systems. This paper presents a novel converter topology along with a modulation strategy for a DAB-based three-phase ac to dc converter. The major benefits are single-stage conversion, no unreliable intermediate dc-link capacitor, reduced number of switches, i.e., only two active switches on the ac side, simple control scheme, open-loop unity power factor operation, bidirectional power flow, and partial soft-switching. This paper presents the analysis of all the operating modes of the converter, resulting in the analytical estimation of power transfer and rms winding current and investigation of soft-switching conditions for the power devices. Simulation and experimental results have been presented to demonstrate the advantages of the proposed technique and accuracy of the analysis
Cost reduction of stochastic Galerkin method by adaptive identification of significant polynomial chaos bases for elliptic equations
No full textOne widely used and computationally efficient method for uncertainty quantification using spectral stochastic finite element is the stochastic Galerkin method. Here the solution is represented in polynomial chaos expansion, and the residual of the discretized governing equation is projected on the polynomial chaos bases. This results in a system of deterministic algebraic equations with the polynomials chaos coefficients as unknown. However, one impediment for its large scale applications is the curse of dimensionality, that is, the exponential growth of the number of polynomial chaos bases with the stochastic dimensionality and degree of expansion. Here, for a stochastic elliptic problem, an adaptive selection of polynomial chaos bases is proposed. Accordingly, during the first few iterations in the preconditioned conjugate gradient method for solving the system of linear algebraic equations, the chaos bases with maximal contribution -in an appropriately defined metric - to the solution are first identified. Subsequently, only these bases are retained for further iterations until convergence is achieved. Using numerical studies a three times cost saving over the existing method is observed. Furthermore, for enhancing the computational cost gain, the stochastic Galerkin method is reformulated as a generalized Sylvester equation. This step allowed efficient usage of the sparsity of moments of product of polynomial chaos bases. Through numerical studies on problems with large stochastic dimensionality, an additional cost saving of up to one order of magnitude -twenty times -is observed. This amounts to sixty times speedup over the existing method, when adaptive selection and generalized Sylvester equation formulation are used together. The proposed methodology can be easily incorporated in an existing standard stochastic Galerkin method solver for elliptic problems. (C) 2018 Elsevier B.V. All rights reserved
Coordination-driven self-assembly of discrete Ru-6-Pt-6 prismatic cages
No full textThe coordination-driven self-assembly of two new Ru-6-Pt-6 hexanuclear trigonal prismatic cages comprising arene-ruthenium(II) clips (1a(NO3)(2) and 1b(NO3)(2)) and a tritopic platinum(II) metalloligand 2 has been performed in methanol at room temperature. The 3 + 2] hexanuclear cages 3a and 3b were isolated in good yields and characterized by well-known spectroscopic techniques including multinuclear NMR, mass spectrometry, UV-vis and infrared studies. Geometry optimization revealed the shapes and sizes of these hexanuclear prismatic cages. The combination of ruthenium and platinum metal center in a one-pot self-assembly reaction showcases the construction of aesthetically elegant heterometallic structures in supramolecular chemistry leading to the formation of a single major product
A generalized family of anisotropic compact object in general relativity
No full textWe present model for anisotropic compact star under the general theory of relativity of Einstein. In the study a 4-dimensional spacetime has been considered which is embedded into the 5-dimensional flat metric so that the spherically symmetric metric has class 1. A set of solutions for the field equations are found depending on the index n involved in the physical parameters. The interior solutions have been matched smoothly at the boundary of the spherical distribution to the exterior Schwarzschild solution which necessarily provides values of the unknown constants. We have chosen the values of n as n = 2 and n=10 to 20000 for which interesting and physically viable results can be found out. The investigations on the physical features of the model include several astrophysical issues, like (i) regularity behaviour of stars at the centre, (ii) well behaved condition for velocity of sound, (iii) energy conditions, (iv) stability of the system via the following three techniques - adiabatic index, Herrera cracking concept and TOV equation, (v) total mass, effective mass and compactification factor and (vi) surface redshift. Specific numerical values of the compact star candidates LMC X-4 and SMC X-1 are calculated for central and surface densities as well as central pressure to compare the model value with actual observational data. (C) 2018 Published by Elsevier Inc
Spatially dispersed synapses yield sharply-tuned place cell responses through dendritic spike initiation
No full textA prominent hypothesis spanning several sensory-perceptual systems implicates spatially clustered synapses in the generation of dendritic spikes that mediate sharply-tuned neuronal responses to input features. In this conductance-based morphologically-precise computational study, we tested this hypothesis by systematically analysing the impact of distinct synaptic and channel localization profiles on sharpness of spatial tuning in hippocampal pyramidal neurons. We found that the generation of dendritic spikes, the emergence of an excitatory ramp in somatic voltage responses, the expression of several intrinsic somatodendritic functional maps and sharp tuning of place-cell responses were all attainable even when iso-feature synapses are randomly dispersed across the dendritic arbor of models with disparate channel combinations. Strikingly, the generation and propagation of dendritic spikes, reliant on dendritic sodium channels and N-methyl-d-asparate receptors, mediated the sharpness of spatial tuning achieved with dispersed synaptic localization. To ensure that our results were not artefacts of narrow parametric choices, we confirmed these conclusions with independent multiparametric stochastic search algorithms spanning thousands of unique models for each synaptic localization scenario.Next, employing virtual knockout models, we demonstrated a vital role for dendritically expressed voltage-gated ion channels, especially the transient potassium channels, in maintaining sharpness of place-cell tuning. Importantly, we established that synaptic potentiation targeted to afferents from one specific place field was sufficient to impart place field selectivity even when intrinsically disparate neurons received randomly dispersed afferents from multiple place field locations. Our results provide quantitative evidence for disparate combinations of channel and synaptic localization profiles to concomitantly yield similar tuning and similar intrinsic properties
Sparse Recovery From Multiple Measurement Vectors Using Exponentiated Gradient Updates
No full textIn this letter, we address the problem of reconstructing the common nonzero support of multiple joint sparse vectors from their noisy and underdetermined linear measurements. The support recovery problem is formulated as the selection of non-negative hyperparameters of a correlation-aware, joint sparsity inducing Gaussian prior. The hyperparameters are recovered as a non-negative sparse solution of covariance-matching constraints formulated in the observation space by solving a sequence of proximal regularized convex optimization problems. For proximal regularization based on Von Neumann Bregman matrix divergence, an exponentiated gradient (EG) update is proposed, which when applied iteratively, converges to hyperparameters with the correct sparse support. Compared to existing multiple measurement vector support recovery algorithms, the proposed multiplicative EG update has a significantly lower computational and storage complexity and takes fewer iterations to converge. We empirically demonstrate that the support-recovery algorithm based on the proposed EG update can solve million variable support recovery problems in tens of seconds. Additionally, by leveraging its correlation-awareness property, the proposed algorithm can recover supports of size as high as O(m(2)) from only m linear measurements per joint sparse vector
Woody plant diversity in relation to environmental factors in a seasonally dry tropical forest landscape
No full textQuestionsWater availability is known to be a first-order driver of plant diversity; yet water also affects fire regimes and soil fertility, which, in turn, affect plant diversity. We examined how precipitation, fire and soil properties jointly determine woody plant diversity. Specifically, we asked how woody plant diversity varies along a sharp precipitation gradient (about 600-1,800mm mean annual precipitation MAP]within a similar to 45-km distance) exhibiting considerable variation in long-term fire burn frequency and soil fertility, in a southern Indian seasonally dry tropical forest (SDTF) landscape. LocationMudumalai, Western Ghats, India. MethodsWoody plants 1-cm DBH were enumerated in 19 1-ha permanent plots spanning a range of tropical vegetation types from dry thorn forest, through dry and moist deciduous forest to semi-evergreen forest. Burn frequencies were derived from annual fire maps. Six measures of surface soil properties - total exchangeable bases (Ca+Mg+K), organic carbon (OC), total N, pH, plant available P and micronutrients (Fe+Cu+Zn+Mn) were used in the analyses. Five measures of diversity - species richness, Shannon diversity, the rarefied/extrapolated versions of these two measures, and Fisher's - were modelled as functions of MAP, annual fire burn frequency and the principal components of soil properties. ResultsMost soil nutrients and OC increased with MAP, except in the wettest sites. Woody productivity increased with MAP, while fire frequency was highest at intermediate values of MAP. Woody plant diversity increased with MAP but decreased with increasing fire frequency, resulting in two local diversity maxima along the MAP gradient - in the semi-evergreen and dry thorn forest - separated by a low-diversity central region in dry deciduous forest where fire frequency was highest. Soil variables were, on the whole, less strongly correlated with diversity than MAP. ConclusionsAlthough woody plant diversity in this landscape, representative of regional SDTFs, is primarily limited by water availability, our study emphasizes the role of fire as a potentially important second-order driver that acts to reduce diversity in this landscape
Petersson norms of not necessarily cuspidal Jacobi modular forms and applications
No full textWe extend the usual notion of Petersson inner product on the space of cuspidal Jacobi forms to include non-cuspidal forms as well. This is done by examining carefully the relation between certain ``growth-killing'' invariant differential operators on H-2 and those on H-1 x C (here H-n denotes the Siegel upper half space of degree n). As applications, we can understand better the growth of Petersson norms of Fourier Jacobi coefficients of Klingen Eisenstein series, which in turn has applications to finer issues about representation numbers of quadratic forms; and as a by-product we also show that any Siegel modular form of degree 2 is determined by its `fundamental' Fourier coefficients. (C) 2018 Elsevier Inc. All rights reserved
Extraction and bioactive profile of the compounds produced by Rhodococcus sp. VLD-10 (vol 6, 261, 2016)
No full textNanofiber-Directed Anisotropic Self-Assembly of CdSe-CdS Quantum Rods for Linearly Polarized Light Emission Evidenced by Quantum Rod Orientation Microscopy
No full textHybrid soft materials composed of CdSe-CdS nanorods or ``quantum rods'' (QRs) and the fluorescent 2,3-didecyloxyanthracene (DDOA) low molecular weight organogelator are obtained through self-assembly. Spectroscopy, microscopy, and rheology studies show that the QRs and DDOA coassemble, thereby stabilizing the organogels. Depending on the QR load and excitation wavelength, single nanofibers (NFs) of the hybrid gel display either sharp polarized red luminescence (under green excitation), or dual perpendicularly polarized blue and red emissions (under UV excitation). Transmission electron microscopy, microspectroscopy, and quantum rod orientation microscopy (QROM) reveal that QRs align along the organogel NFs with order parameters reaching 76% and 87%. This paves the way for obtaining surfaces of QR/NF assemblies yielding sharp red linearly polarized emission. In addition, this work demonstrates that QRs can be used more generally to probe nanostructured soft materials, even nonemissive ones. QROM allows to establish maps of the orientation of single QRs dispersed onto or within a gel network by measuring the polarization of the emission of the individual QRs. As occurs within this work in which QRs and NFs interact, the orientation of each QR reveals information on the underlying nanostructure (such as surface striation, bundle formation, and helicity)