Girsanov Transformation-Based Reliability Modeling and Testing of Actively Controlled Structures

The problem of estimation of the time-variant reliability of actively controlled structural dynamical systems under stochastic excitations is considered. Monte Carlo simulations, reinforced with Girsanov transformation-based sampling variance reduction, are used to tackle the problem. In this approach, the external excitations are biased by an additional artificial control force. The conflicting objectives of the two control forces-one designed to reduce structural responses and the other to promote limit-state violations (but to reduce sampling variance)-are noted. The control for variance reduction is fashioned after design-point oscillations based on a first-order reliability method. It is shown that for structures that are amenable to laboratory testing, the reliability can be estimated experimentally with reduced testing times by devising a procedure based on the ideas of the Girsanov transformation. Illustrative examples include studies on a building frame with a magnetorheologic damper-based isolation system subject to nonstationary random earthquake excitations. (C) 2014 American Society of Civil Engineers.

Risk-Sensitive Ergodic Control of Continuous Time Markov Processes With Denumerable State Space

In this article, we study risk-sensitive control problem with controlled continuous time Markov chain state dynamics. Using multiplicative dynamic programming principle along with the atomic structure of the state dynamics, we prove the existence and a characterization of optimal risk-sensitive control under geometric ergodicity of the state dynamics along with a smallness condition on the running cost.

Ag+-induced reverse vesicle to helical fiber transformation in a self-assembly by adjusting the keto-enol equilibrium of a chiral salicylideneaniline

A new chiral amphiphilic salicylideneaniline bearing a terminal pyridine was synthesized. It formed reverse vesicles in toluene. The addition of Ag+, however, reversibly transforms these reverse vesicles into left-handed nanohelices accompanied by spontaneous gel formation at room temperature.

Dependence of shear yield strain and shear transformation zone on the glass transition temperature in thin film metallic glasses

The dependence of shear yield strain, the activation energy and volume of shear transformation zone on the glass transition temperature was investigated through the analysis of statistical distributions of the first pop-in events during spherical indentation of four different thin film metallic glasses. Only the Cu-Zr metallic glass exhibits a bimodal distribution of the first pop-in loads, whereas W-Ru-B, Zr-Cu-Ni-Al and La-Co-Al metallic glasses show an unimodal distribution. Results show that shear yield strain and activation energy of shear transformation zone decrease whereas the volume of shear transformation zone increases with increasing homologous temperature, indicating that it is the activation energy rather than the volume of shear transformation zone that controls shear yield strain. (C) 2015 Elsevier B.V. All rights reserved.

Partial rotation of the isopropyl group in the solid state: single-crystal-to-single-crystal phase transformation in a carvacrol derivative

A hitherto unseen rotation of the isopropyl group in the solid state, predicted to be forbidden based on theoretical investigations, is reported. This C-C rotation observed during the temperature dependent single-crystal-to-single-crystal transformation is attributed to the concomitant changes in molecular structure and intermolecular packing.

On the detection of human influence in extreme precipitation over India

Climate change is expected to influence extreme precipitation which in turn might affect risks of pluvial flooding. Recent studies on extreme rainfall over India vary in their definition of extremes, scales of analyses and conclusions about nature of changes in such extremes. Fingerprint-based detection and attribution (D&A) offer a formal way of investigating the presence of anthropogenic signals in hydroclimatic observations. There have been recent efforts to quantify human effects in the components of the hydrologic cycle at large scales, including precipitation extremes. This study conducts a D&A analysis on precipitation extremes over India, considering both univariate and multivariate fingerprints, using a standardized probability-based index (SPI) from annual maximum one-day (RX1D) and five-day accumulated (RX5D) rainfall. The pattern-correlation based fingerprint method is used for the D&A analysis. Transformation of annual extreme values to SPI and subsequent interpolation to coarser grids are carried out to facilitate comparison between observations and model simulations. Our results show that in spite of employing these methods to address scale and physical processes mismatch between observed and model simulated extremes, attributing changes in regional extreme precipitation to anthropogenic climate change is difficult. At very high (95%) confidence, no signals are detected for RX1D, while for the RX5D and multivariate cases only the anthropogenic (ANT) signal is detected, though the fingerprints are in general found to be noisy. The findings indicate that model simulations may underestimate regional climate system responses to increasing human forcings for extremes, and though anthropogenic factors may have a role to play in causing changes in extreme precipitation, their detection is difficult at regional scales and not statistically significant. (C) 2015 Elsevier B.V. All rights reserved.

The electronic, chemical and electrocatalytic processes and intermediates on iron oxide surfaces during photoelectrochemical water splitting

We re-assess experimental soft X-ray absorption spectra of the oxygen K-shell which we recorded operando from iron oxide during photoelectrochemical water splitting in KOH electrolyte. In particular, we refer to recently reported transitional electron hole states which originate within the charge carrier depletion layer of the iron oxide and on the iron oxide surface. For the latter we find that an intermediate oxy-peroxo species is formed on the iron oxide with increasing bias potential, which disappears upon further polarization of the electrode, concomitantly with the evolution and disappearance of the aforementioned surface state. The oxygen spectra contain also the spectroscopic signatures of the electrolyte water, the position of which changes with increasing bias potential towards lower X-ray energies, revealing the breaking and formation of hydrogen bonds in the water during the experiment. Combined with potential dependent impedance spectroscopy data we are able to sketch the molecular structure of chemical intermediates and their charge carrier dynamics. (C) 2015 Elsevier B.V. All rights reserved.

Use of Sr isotopes as a tool to decipher the soil weathering processes in a tropical river catchment, southwestern India

River water composition (major ion and Sr-87/Sr-86 ratio) was monitored on a monthly basis over a period of three years from a mountainous river (Nethravati River) of southwestern India. The total dissolved solid (TDS) concentration is relatively low (46 mg L-1) with silica being the dominant contributor. The basin is characterised by lower dissolved Sr concentration (avg. 150 nmol L-1), with radiogenic Sr-87/Sr-86 isotopic ratios (avg. 0.72041 at outlet). The composition of Sr and Sr-87/Sr-86 and their correlation with silicate derived cations in the river basin reveal that their dominant source is from the radiogenic silicate rock minerals. Their composition in the stream is controlled by a combination of physical and chemical weathering occurring in the basin. The molar ratio of SiO2/Ca and Sr-87/Sr-86 isotopic ratio show strong seasonal variation in the river water, i.e., low SiO2/Ca ratio with radiogenic isotopes during non-monsoon and higher SiO2/Ca with less radiogenic isotopes during monsoon season. Whereas, the seasonal variation of Rb/Sr ratio in the stream water is not significant suggesting that change in the mineral phase being involved in the weathering reaction could be unlikely for the observed molar SiO2/Ca and Sr-87/Sr-86 isotope variation in river water. Therefore, the shift in the stream water chemical composition could be attributed to contribution of ground water which is in contact with the bedrock (weathering front) during non-monsoon and weathering of secondary soil minerals in the regolith layer during monsoon. The secondary soil mineral weathering leads to limited silicate cation and enhanced silica fluxes in the Nethravati river basin. (C) 2015 Elsevier Ltd. All rights reserved.

Relaxor ferroelectricity and electric-field-driven structural transformation in the giant lead-free piezoelectric (Ba,Ca)(Ti, Zr)O-3

There is great interest in lead-free (Ba0.85Ca0.15)(Ti0.90Zr0.10)O-3 (15/10BCTZ) because of its exceptionally large piezoelectric response Liu and Ren, Phys. Rev. Lett. 103, 257602 (2009)]. In this paper, we have analyzed the nature of: (i) crystallographic phase coexistence at room temperature, (ii) temperature-and field-induced phase transformation to throw light on the atomistic mechanisms associated with the large piezoelectric response of this system. A detailed temperature-dependent dielectric and lattice thermal expansion study proved that the system exhibits a weak dielectric relaxation, characteristic of a relaxor ferroelectric material on the verge of exhibiting a normal ferroelectric-paraelectric transformation. Careful structural analysis revealed that a ferroelectric state at room temperature is composed of three phase coexistences, tetragonal (P4mm)+ orthorhombic (Amm2) + rhombohedral (R3m). We also demonstrate that the giant piezoresponse is associated with a significant fraction of the tetragonal phase transforming to rhombohedral. It is argued that the polar nanoregions associated with relaxor ferroelectricity amplify the piezoresponse by providing an additional degree of intrinsic structural inhomogeneity to the system.

Monoclinic to cubic phase transformation in combustion synthesized gadolinium oxide

Gadolinium oxide, cerium oxide, and 10 mol% gadolinia doped ceria ceramic powders have been synthesized using combustion technique. Though the cubic gadolinia phase is stable at room temperature, single phase monoclinic gadolinia was obtained as a result of combustion synthesis using fuel lean and stoichiometric precursor compositions. This powder was subjected to calcination treatment and ceria doping to study the stability of phases and the rate of phase transformation from monoclinic to cubic gadolinia. It was found that monoclinic gadolinia transforms to cubic gadolinia upon calcination at temperatures less than 1200 degrees C. It was also found that rate of phase transformation is more for powder produced using fuel lean compositions; and the rate is enhanced upon ceria doping. (C) 2015 Elsevier Ltd. All rights reserved.

Determinantal point processes in the plane from products of random matrices

We show that the density of eigenvalues for three classes of random matrix ensembles is determinantal. First we derive the density of eigenvalues of product of k independent n x n matrices with i.i.d. complex Gaussian entries with a few of matrices being inverted. In second example we calculate the same for (compatible) product of rectangular matrices with i.i.d. Gaussian entries and in last example we calculate for product of independent truncated unitary random matrices. We derive exact expressions for limiting expected empirical spectral distributions of above mentioned ensembles.

Outstanding dielectric constant and piezoelectric coefficient in electrospun nanofiber mats of PVDF containing silver decorated multiwall carbon nanotubes: assessing through piezoresponse force microscopy

In order to enhance the piezoelectric b-phase, PVDF was electrospun from DMF solution. The enhanced b-phase was discerned by comparing the electrospun fibers against the melt mixed samples. While both the processes resulted in phase transformation of a-to electroactive b-polymorph in PVDF, the fraction of b-phase was strongly dependent on the adopted process. Two different nanoscopic particles: carboxyl functionalized multiwall carbon nanotubes (CNTs) and silver (Ag) decorated CNTs were used to further enhance the piezoelectric coefficient in the electrospun fibers. Fourier transform infrared spectroscopy (FTIR) and wide-angle X-ray diffraction (XRD) supports the development of piezoelectric b-phase in PVDF. It was concluded that electrospinning was the best technique for inducing the b-polymorph in PVDF. This was attributed to the high voltage electrostatic field that generates extensional forces on the polymer chains that aligns the dipoles in one direction. The ferroelectric and piezoelectric measurement on electrospun fibers were studied using piezo-response force microscope (PFM). The Ag-CNTs filled PVDF electrospun fibers showed the highest piezoelectric coefficient (d(33) = 54 pm V-1) in contrast to PVDF/CNT fibers (35 pm V-1) and neat PVDF (30 pm V-1). This study demonstrates that the piezoelectric coefficient can be enhanced significantly by electrospinning PVDF containing Ag decorated nanoparticles.

Case studies on the formation of chalcogenide self-assembled monolayers on surfaces and dissociative processes

This report examines the assembly of chalcogenide organic molecules on various surfaces, focusing on cases when chemisorption is accompanied by carbon-chalcogen atom-bond scission. In the case of alkane and benzyl chalcogenides, this induces formation of a chalcogenized interface layer. This process can occur during the initial stages of adsorption and then, after passivation of the surface, molecular adsorption can proceed. The characteristics of the chalcogenized interface layer can be significantly different from the metal layer and can affect various properties such as electron conduction. For chalcogenophenes, the carbon-chalcogen atombond breaking can lead to opening of the ring and adsorption of an alkene chalcogenide. Such a disruption of the pi-electron system affects charge transport along the chains. Awareness about these effects is of importance from the point of view of molecular electronics. We discuss some recent studies based on X-ray photoelectron spectroscopy that shed light on these aspects for a series of such organic molecules.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.