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Studies on the effect of imaging parameters on dynamic mode decomposition of time-resolved schlieren flow images
No full textDynamic modal analysis enables new insights into the spatio-temporal dynamics of complex flow scenarios. Time resolved schlieren imaging provides significant information in compressible flow scenarios on flow structures and their evolution. We conduct a systematic study using synthetic images and experimental schlieren images on the effect of image acquisition parameters on the modal analysis by dynamic mode decomposition (DMD). We consider the effect of two important capture parameters � the capture rate (f s ) and the exposure time (t exp ). Analysis is carried out on two sets of synthetic images, SI-I, an unsteady wavy interface created using a linear combination of sinusoids, and SI-II � hypothetical shock oscillations. Finally, a flapping supersonic jet is observed using high-speed schlieren with a nano-pulsed laser light source with three different imaging parameters. We find that among the two parameters the effect of exposure time on modal analysis and its interpretation is more pronounced than capture rate. An exposure time of 5 of maximum exposure produces 8 reduction in mode amplitude, and in case of long exposure the dynamic significance of modes undergoes complete change. If the flow images are instantaneous, then the spatial mode shapes of dominant modes remain the same irrespective of the capture rate. Aliasing has to be considered in sub-Nyquist capture rates, however, the actual frequencies can be suitably resolved. © 2019 Elsevier Masson SA
Use of sentinel-2 time-series images for classification and uncertainty analysis of inherent biophysical property: Case of soil texture mapping
No full textThe Sentinel-2 mission of the European Space Agency (ESA) Copernicus program provides multispectral remote sensing data at decametric spatial resolution and high temporal resolution. The objective of this work is to evaluate the ability of Sentinel-2 time-series data to enable classification of an inherent biophysical property, in terms of accuracy and uncertainty estimation. The tested inherent biophysical property was the soil texture. Soil texture classification was performed on each individual Sentinel-2 image with a linear support vector machine. Two sources of uncertainty were studied: uncertainties due to the Sentinel-2 acquisition date and uncertainties due to the soil sample selection in the training dataset. The first uncertainty analysis was achieved by analyzing the diversity of classification results obtained from the time series of soil texture classifications, considering that the temporal resolution is akin to a repetition of spectral measurements. The second uncertainty analysis was achieved from each individual Sentinel-2 image, based on a bootstrapping procedure corresponding to 100 independent classifications obtained with different training data. The Simpson index was used to compute this diversity in the classification results. This work was carried out in an Indian cultivated region (84 km 2 , part of Berambadi catchment, in the Karnataka state). It used a time-series of six Sentinel-2 images acquired from February to April 2017 and 130 soil surface samples, collected over the study area and characterized in terms of texture. The classification analysis showed the following: (i) each single-date image analysis resulted in moderate performances for soil texture classification, and (ii) high confusion was obtained between neighboring textural classes, and low confusion was obtained between remote textural classes. The uncertainty analysis showed that (i) the classification of remote textural classes (clay and sandy loam) was more certain than classifications of intermediate classes (sandy clay and sandy clay loam), (ii) a final soil textural map can be produced depending on the allowed uncertainty, and iii) a higher level of allowed uncertainty leads to increased bare soil coverage. These results illustrate the potential of Sentinel-2 for providing input for modeling environmental processes and crop management
DNN Based Speech Enhancement for Unseen Noises Using Monte Carlo Dropout
No full textIn this work, we propose the use of dropout as a Bayesian estimator for increasing the generalizability of a deep neural network (DNN) for speech enhancement. By using Monte Carlo (MC) dropout, we explore whether the DNN can accomplish better enhancement in unseen noisy conditions. Two DNNs are trained on speech corrupted with five different noises at three SNRs, one using conventional dropout and other with MC dropout and tested on speech with unseen noises. Speech samples are obtained from the TIMIT database and noises from NOISEX-92. In another experiment, we train five DNN models separately on speech corrupted with five different noises, at three SNRs. The model precision estimated using MC dropout is used as a proxy for squared error to dynamically select the best of the DNN models based on their performance on each frame of test data. The first set of experiments aims at improving the performance of an existing DNN with conventional dropout for unseen noises, by replacing the conventional dropout with MC dropout. The second set of experiments aims at finding an optimal way of choosing the best DNN model for de-noising when multiple noise-specific DNN models are available, for unseen noisy conditions. © 2018 IEEE
Structural studies on M-tuberculosis argininosuccinate lyase and its liganded complex: Insights into catalytic mechanism
No full textArgininosuccinate lyase catalyses the reversible breakdown of argininosuccinate into arginine and fumarate and is known to form tetramers in its quaternary association. The absence of structures involving competent enzymes bound to substrate/products came in the way of the precise elucidation of the catalytic mechanism of this family of proteins. Crystal structures of the enzyme from Mycobacterium tuberculosis in an unliganded form and its complex with the substrate/products have now been determined at 2.2 and 2.7 angstrom, respectively. The refinement of the structure of the complex was bedevilled by the presence of a lattice translocation defect. The two tetramers in the apo-crystals and the one in the crystals of the liganded protein, have the same structure except for the movements associated with enzyme action. Each molecule consists of an N-domain, an M-domain, and a C-domain. The molecule consists of four binding sites, each made up of peptide stretches from three subunits. Three binding sites appear to be occupied by the ligand in the transition state, while the products occupy the fourth site. The structure exhibits the movement of a loop in the M-domain and parts of the C-domain. This is the first instance when the appropriate movements are observed in a complex with bound substrate/product. The detailed picture of the binding site, active site residues and the movements associated with catalysis thus obtained, enabled a revisit of the mechanism of action of the enzyme. (c) 2019 IUBMB Life, 71(5):643-652, 201
Effect of equal channel angular pressing (ECAP) on the evolution of texture, microstructure and mechanical properties in the Al-Cu-Li alloy AA2195
No full textIn this study, one of the severe plastic deformation (SPD) techniques, Equal Channel Angular Pressing (ECAP) has been successfully applied to the Al-Cu-Li alloy AA2195 at 250 degrees C and the development of microstructure, texture and mechanical properties has been studied. A systematic analysis has been carried out by using EBSD and TEM to understand the microstructural features, and the nature of different precipitates presence in the alloy AA2195. Microstructural features indicate considerable grain refinement leading to an average grain size of 2.8 +/- 0.7 mu m after 4 ECAP passes. Continuous dynamic recrystallization (CDRX) has been identified as the mechanism that leads to the formation of fine grain structure in the alloy AA2195 during the warm ECAP process. TEM results confirm the distribution of strengthening precipitates delta'(Al3Li),beta(Al3Zr) and T-1(Al2CuLi) in the alloy. The overall texture has become weak after ECAP processing and has been simulated using Visco-plastic self-consistent simulation (VPSC). The evaluation of mechanical properties indicates a substantial increment in hardness, strength properties with a minor reduction of ductility after 4 passes. Low mechanical property anisotropy is expected in the processed AA2195 alloy due to its weak texture. (C) 2019 Elsevier B.V. All rights reserved
Stores, Channels, Glue, and Trees: Active Glial and Active Dendritic Physiology
No full textGlial cells and neuronal dendrites were historically assumed to be passive structures that play only supportive physiological roles, with no active contribution to information processing in the central nervous system. Research spanning the past few decades has clearly established this assumption to be far from physiological realities. Whereas the discovery of active channel conductances and their localized plasticity was the turning point for dendritic structures, the demonstration that glial cells release transmitter molecules and communicate across the neuroglia syncytium through calcium wave propagation constituted path-breaking discoveries for glial cell physiology. An additional commonality between these two structures is the ability of calcium stores within their endoplasmic reticulum (ER) to support active propagation of calcium waves, which play crucial roles in the spatiotemporal integration of information within and across cells. Although there have been several demonstrations of regulatory roles of glial cells and dendritic structures in achieving common physiological goals such as information propagation and adaptability through plasticity, studies assessing physiological interactions between these two active structures have been few and far. This lacuna is especially striking given the strong connectivity that is known to exist between these two structures through several complex and tightly intercoupled mechanisms that also recruit their respective ER structures. In this review, we present brief overviews of the parallel literatures on active dendrites and active glial physiology and make a strong case for future studies to directly assess the strong interactions between these two structures in regulating physiology and pathophysiology of the brain
Intricate modulation of interlayer coupling at the graphene oxide/MoSe2 interface: Application in time-dependent optics and device transport
No full textIn the GO/MoSe2 semiconductor heterostructure, we have demonstrated a subtle control on the doping dynamics by modulating interlayer coupling through the combination of strain-reducing relative rotation of the constituting layers and variation of ligand type and concentration. By first-principles calculations incorporating spin-orbit coupling, we have investigated the impact of variable interlayer coupling in introducing noncollinear magnetic behavior in the heterostructure. The outcome of varying carrier type and their respective concentrations are investigated by static as well as time-dependent density functional calculations, which indicate the presence of optical anisotropy and time-dependent optical phenomena such as exciton quenching and band-gap renormalization. The performance of such heterostructures as channel material in devices with top and edge metal contacts is analyzed. Our self-consistent quantum transport calculations have evinced that the interface-induced variation in doping pattern is extrapolated only for devices with top contacts. The edge contact, although it exhibits a better transmission, is inefficient in sensing the ligand-induced doping modulation introduced via vertical interlayer charge transfer
Stochastic time domain spectral element analysis of beam structures
No full textIn this work, a stochastic time domain spectral element method (STSEM) is proposed for stochastic modeling and uncertainty quantification of engineering structures. To perform the analysis, both an isotropic Timoshenko beam (TB) and a sandwich beam are considered. The sandwich beam is modeled considering higher-order sandwich panel theory which is capable of addressing the core flexibility. The material properties are considered as 1D non-Gaussian random fields, and optimal linear estimation (OLE) is used for the discretization of the random fields. The OLE-based discretization of a random field allows simulating the random fields numerically, resulting in realizations of the stiffness, mass matrix, and dynamic stiffness matrix. In the current work, the computationally efficient time domain spectral element method (TSEM) is used to develop the STSEM formulation. The STSEM reduces the CPU time significantly as the number of degrees of freedom (dof) is much smaller than in FEM. TSEM also provides a consistent diagonal mass matrix which reduces the computation cost in case of dynamic problems. The deflection statistics of the beam for static, free vibration and dynamic cases are investigated for both TB and sandwich beam. The computational efficiency of the proposed method and the effect of material variability on the response statistics are also discussed. Moreover, the effect of different correlation lengths on the response statistics is studied
Wannier pairs in superconducting twisted bilayer graphene and related systems
No full textUnconventional superconductivity often arises from Cooper pairing between neighboring atomic sites, stipulating a characteristic pairing symmetry in the reciprocal space. The twisted bilayer graphene (TBG) presents a new setting where superconductivity emerges on the flatbands whose Wannier wave functions spread over many graphene unit cells, forming the so-called moire pattern. To unravel how Wannier states form Cooper pairs, we study the interplay between electronic, structural, and pairing instabilities in TBG. For comparisons, we also study graphene on boron-nitride (GBN) possessing a different moire pattern, and single-layer graphene (SLG) without a moire pattern. For all cases, we compute the pairing eigenvalues and eigenfunctions by solving a linearized superconducting gap equation, where the spin-fluctuation mediated pairing potential is evaluated from materials-specific tight-binding band structures. We find an extended s wave as the leading pairing symmetry in TBG, in which the nearest-neighbor Wannier sites form Cooper pairs with same phase. In contrast, GBN assumes a p + ip-wave pairing between nearest-neighbor Wannier states with odd-parity phase, while SLG has the d + id-wave symmetry for intersublattice pairing with even-parity phase. Moreover, p + ip and d + id pairings are chiral, and nodeless, but the extended s-wave channel possesses accidental nodes. The nodal pairing symmetry makes it easily distinguishable via power-law dependencies in thermodynamical entities, in addition to their direct visualization via spectroscopies