A domain adaptive stochastic collocation approach for analysis of MEMS under uncertainties

This work proposes a domain adaptive stochastic collocation approach for uncertainty quantification, suitable for effective handling of discontinuities or sharp variations in the random domain. The basic idea of the proposed methodology is to adaptively decompose the random domain into subdomains. Within each subdomain, a sparse grid interpolant is constructed using the classical Smolyak construction [S. Smolyak, Quadrature and interpo- lation formulas for tensor products of certain classes of functions, Soviet Math. Dokl. 4 (1963) 240–243], to approximate the stochastic solution locally. The adaptive strategy is governed by the hierarchical surpluses, which are computed as part of the interpolation procedure. These hierarchical surpluses then serve as an error indicator for each subdo- main, and lead to subdivision whenever it becomes greater than a threshold value. The hierarchical surpluses also provide information about the more important dimensions, and accordingly the random elements can be split along those dimensions. The proposed adaptive approach is employed to quantify the effect of uncertainty in input parameters on the performance of micro-electromechanical systems (MEMS). Specifically, we study the effect of uncertain material properties and geometrical parameters on the pull-in behavior and actuation properties of a MEMS switch. Using the adaptive approach, we resolve the pull-in instability in MEMS switches. The results from the proposed approach are verified using Monte Carlo simulations and it is demonstrated that it computes the required statistics effectively

Squarepants in a Tree: Sum of Subtree Clustering and Hyperbolic Pants Decomposition

We provide efficient constant factor approximation algorithms for the problems of finding a hierarchical clustering of a point set in any metric space, minimizing the sum of minimimum spanning tree lengths within each cluster, and in the hyperbolic or Euclidean planes, minimizing the sum of cluster perimeters. Our algorithms for the hyperbolic and Euclidean planes can also be used to provide a pants decomposition, that is, a set of disjoint simple closed curves partitioning the plane minus the input points into subsets with exactly three boundary components, with approximately minimum total length. In the Euclidean case, these curves are squares; in the hyperbolic case, they combine our Euclidean square pants decomposition with our tree clustering method for general metric spaces.Comment: 22 pages, 14 figures. This version replaces the proof of what is now Lemma 5.2, as the previous proof was erroneou

Image similarity in medical images

Recent experiments have indicated a strong influence of the substrate grain orientation on the self-ordering in anodic porous alumina. Anodic porous alumina with straight pore channels grown in a stable, self-ordered manner is formed on (001) oriented Al grain, while disordered porous pattern is formed on (101) oriented Al grain with tilted pore channels growing in an unstable manner. In this work, numerical simulation of the pore growth process is carried out to understand this phenomenon. The rate-determining step of the oxide growth is assumed to be the Cabrera-Mott barrier at the oxide/electrolyte (o/e) interface, while the substrate is assumed to determine the ratio β between the ionization and oxidation reactions at the metal/oxide (m/o) interface. By numerically solving the electric field inside a growing porous alumina during anodization, the migration rates of the ions and hence the evolution of the o/e and m/o interfaces are computed. The simulated results show that pore growth is more stable when β is higher. A higher β corresponds to more Al ionized and migrating away from the m/o interface rather than being oxidized, and hence a higher retained O:Al ratio in the oxide. Experimentally measured oxygen content in the self-ordered porous alumina on (001) Al is indeed found to be about 3% higher than that in the disordered alumina on (101) Al, in agreement with the theoretical prediction. The results, therefore, suggest that ionization on (001) Al substrate is relatively easier than on (101) Al, and this leads to the more stable growth of the pore channels on (001) Al

Novel Mannich bases bearing pyrazolone moiety. Synthesis, characterization and electrochemical studies

The present investigation describes a series of new {4-[3-Methyl-5-oxo-4-(4|-substituted phenyl hydrazono)-4,5-dihydro-pyrazol-1-yl]-phenoxy}-acetic acid (2-oxo-1-piperidine-1-ylmethyl-1,2-dihydro–indol-3-ylidene)-hydrazides synthesized by the Mannich reaction of {4-[3-Methyl-5-oxo-4-(4|-substituted phenyl hydrazono)-4,5-dihydro-pyrazol-1-yl]-phenoxy}-acetic acid (2-oxo-1,2-dihydro-indol-3-ylidene)-hydrazide with aqueous formaldehyde and a solution of piperidine in dimethylformamide. These novel Mannich bases were characterized by elemental analysis, IR, 1H NMR and mass spectral data. Electrochemical behavior of these compounds were studied by two techniques namely polarography and cyclic voltammetry. The results from both the techniques were compared and the reduction mechanism in acidic as well as basic medium was proposed

Quasiharmonic models for the calculation of thermodynamic properties of crystalline silicon under strain,

Quasiharmonic models with Tersoff ͓Phys. Rev. B 38, 9902 ͑1988͔͒ interatomic potential are used to study the thermodynamic properties of crystalline silicon. It is shown that, compared to the molecular dynamics simulation data, the reciprocal space quasiharmonic model accurately predicts the thermal properties for temperatures up to 800 K. For higher temperatures, anharmonic effects become significant. With a significantly higher computational cost, the results from the real space quasiharmonic model approach the results from the reciprocal space quasiharmonic model as the number of atoms increases. The local quasiharmonic model does not accurately describe the thermal properties as it neglects the vibrational coupling of the atoms. We also investigate the effect of the strain on the thermodynamic properties. The variation of the thermodynamic properties with temperature under a tension, compression, and a shear deformation state is computed

Two-Phase Analysis in Consensus Genetic Mapping

Numerous mapping projects conducted on different species have generated an abundance of mapping data. Consequently, many multilocus maps have been constructed using diverse mapping populations and marker sets for the same organism. The quality of maps varies broadly among populations, marker sets, and software used, necessitating efforts to integrate the mapping information and generate consensus maps. The problem of consensus genetic mapping (MCGM) is by far more challenging compared with genetic mapping based on a single dataset, which by itself is also cumbersome. The additional complications introduced by consensus analysis include inter-population differences in recombination rate and exchange distribution along chromosomes; variations in dominance of the employed markers; and use of different subsets of markers in different labs. Hence, it is necessary to handle arbitrary patterns of shared sets of markers and different level of mapping data quality. In this article, we introduce a two-phase approach for solving MCGM. In phase 1, for each dataset, multilocus ordering is performed combined with iterative jackknife resampling to evaluate the stability of marker orders. In this phase, the ordering problem is reduced to the well-known traveling salesperson problem (TSP). Namely, for each dataset, we look for order that gives minimum sum of recombination distances between adjacent markers. In phase 2, the optimal consensus order of shared markers is selected from the set of allowed orders and gives the minimal sum of total lengths of nonconflicting maps of the chromosome. This criterion may be used in different modifications to take into account the variation in quality of the original data (population size, marker quality, etc.). In the foregoing formulation, consensus mapping is considered as a specific version of TSP that can be referred to as “synchronized TSP.” The conflicts detected after phase 1 are resolved using either a heuristic algorithm over the entire chromosome or an exact/heuristic algorithm applied subsequently to the revealed small non-overlapping regions with conflicts separated by non-conflicting regions. The proposed approach was tested on a wide range of simulated data and real datasets from maize

Adrenocorticotropic Hormone Suppresses Gonadotropin-Stimulated Estradiol Release from Zebrafish Ovarian Follicles

While stress is known to impact reproductive performance, the pathways involved are not entirely understood. Corticosteroid effects on the functioning of the hypothalamus-pituitary-gonadal axis are thought to be a key aspect of stress-mediated reproductive dysfunction. A vital component of the stress response is the pituitary secretion of adrenocorticotropic hormone (ACTH), which binds to the melanocortin 2 receptor (MC2R) in the adrenal glands and activates cortisol biosynthesis. We recently reported MC2R mRNA abundance in fish gonads leading to the hypothesis that ACTH may be directly involved in gonadal steroid modulation. Using zebrafish (Danio rerio) ovarian follicles, we tested the hypothesis that acute ACTH stimulation modulates cortisol and estradiol (E2) secretion. ACTH neither affected cortisol nor unstimulated E2 release from ovarian follicles. However, ACTH suppressed human chorionic gonadotropin (hCG)-stimulated E2 secretion in a dose-related manner, with a maximum decrease of 62% observed at 1 I.U. ACTH mL−1. This effect of ACTH on E2 release was not observed in the presence of either 8-bromo-cAMP or forskolin, suggesting that the mechanism(s) involved in steroid attenuation was upstream of adenylyl cyclase activation. Overall, our results suggest that a stress-induced rise in plasma ACTH levels may initiate a rapid down-regulation of acute stimulated E2 biosynthesis in the zebrafish ovary, underscoring a novel physiological role for this pituitary peptide in modulating reproductive activity

Imaging the real space structure of the spin fluctuations in an iron-based superconductor

Spin fluctuations are a leading candidate for the pairing mechanism in high temperature superconductors, supported by the common appearance of a distinct resonance in the spin susceptibility across the cuprates, iron-based superconductors and many heavy fermion materials1. The information we have about the spin resonance comes almost exclusively from neutron scattering. Here we demonstrate that by using low-temperature scanning tunneling microscopy and spectroscopy we can characterize the spin resonance in real space. We establish that inelastic tunneling leads to the characteristic "dip-hump" feature seen in tunneling spectra in high temperature superconductors and that this feature arises from excitations of the spin fluctuations. Spatial mapping of this feature near defects allows us to probe non-local properties of the spin susceptibility and to image its real space structure.Publisher PDFPeer reviewe

Impact of Iron-site defects on Superconductivity in LiFeAs

PW acknowledges funding from the MPG-UBC center and financial support from EPSRC (EP/I031014/1).In conventional s-wave superconductors, only magnetic impurities exhibit impurity bound states, whereas for an s order parameter they can occur for both magnetic and non-magnetic impurities. Impurity bound states in superconductors can thus provide important insight into the order parameter. Here, we present a combined experimental and theoretical study of native and engineered iron-site defects in LiFeAs. Detailed comparison of tunneling spectra measured on impurities with spin fluctuation theory reveals a continuous evolution from negligible impurity bound state features for weaker scattering potential to clearly detectable states for somewhat stronger scattering potentials. All bound states for these intermediate strength potentials are pinned at or close to the gap edge of the smaller gap, a phenomenon that we explain and ascribe to multi-orbital physics.PostprintPeer reviewe

Discovery of a strain-stabilised smectic electronic order in LiFeAs

CT, CMY and PW acknowledge funding from EPSRC through EP/L505079/1 and EP/I031014/1. Research at UBC was supported by the Natural Sciences and Engineering Research Council of Canada, the Canadian Institute for Advanced Research, and the Stewart Blusson Quantum Matter Institute.In many high temperature superconductors, small orthorhombic distortions of the lattice structure result in surprisingly large symmetry breaking of the electronic states and macroscopic properties, an effect often referred to as nematicity. To directly study the impact of symmetry-breaking lattice distortions on the electronic states, using low-temperature scanning tunnelling microscopy we image at the atomic scale the influence of strain-tuned lattice distortions on the correlated electronic states in the iron-based superconductor LiFeAs, a material which in its ground state is tetragonal with four-fold (C4) symmetry. Our experiments uncover a new strain-stabilised modulated phase which exhibits a smectic order in LiFeAs, an electronic state which not only breaks rotational symmetry but also reduces translational symmetry. We follow the evolution of the superconducting gap from the unstrained material with C4 symmetry through the new smectic phase with two-fold (C2) symmetry and charge-density wave order to a state where superconductivity is completely suppressed.Publisher PDFPeer reviewe