Galaxy Clusters: Substructure and Mass Systematics

Science.gov (United States)

Zhang, Yu-Ying

2010-07-01

We calibrate the X-ray measured hydrostatic equilibrium (H.E.) mass and assess the origin of the H.E. mass systematics using 2-D spectrally measured X-ray properties. We obtained that the average X-ray mass derived from H.E. using XMM-Newton data is lower compared to the weak lensing mass from Subaru data for relaxed clusters in a sample of 12 clusters at z~0.2. This is comparable to the expectation of numerical simulations because of the non-thermal pressure support due to turbulence and bulk motions. The gas mass to weak lensing mass ratio shows no dependence on the cluster morphology, which indicates that the gas mass may be a good mass proxy regardless of the cluster dynamical state. To understand the origin of the systematics of the H.E. mass, we investigated 4 nearby clusters, for which the substructure is quantified by the radial fluctuations in the spectrally measured 2-D maps by a cumulative/differential scatter profile relative to the mean profile within/at a given radius. The amplitude of and the discontinuity in the scatter complements 2-D substructure diagnostics, e.g. indicating the most disturbed radial range. There is a tantalizing link between the substructure identified using the scatter of the entropy and pressure fluctuations and the deviation of the H.E. mass relative to the expected mass based on the representative scaling relation, e.g., M-Mgas, particularly at r500-the radius within which the over-density, Δ, is 500 with respect to the critical density. This indicates that at larger radii, the systematic error of the H.E. mass may well be caused by substructure.

Natural draft cooling tower with shell disconnected from the substructure

International Nuclear Information System (INIS)

Diver, Marius

1982-01-01

The aim of this paper is the analysis of results of a research done by Electricite de France, concerning a new type of cooling tower. The traditional structure (i.e. a hyperbolic shell supported by X shaped or diagonal columns) is replaced by two independent structures: the shell, becoming a self-contained structure, the lower rim being stiffened by an annular beam; the substructure, resting on the soil. This new type of cooling tower has an improved thermal performance due to the increase of the area of air entrance. Bearing pads are provided between the lower ring beam of the shell and the substructure. Any differential settlement can be coped with by jacking. The water distribution structure can be laid out so as to benefit from advantages offered by the presence of the stiff ring and columns of the substructure [fr

Jet substructure with analytical methods

Energy Technology Data Exchange (ETDEWEB)

Dasgupta, Mrinal [University of Manchester, Consortium for Fundamental Physics, School of Physics and Astronomy, Manchester (United Kingdom); Fregoso, Alessandro; Powling, Alexander [University of Manchester, School of Physics and Astronomy, Manchester (United Kingdom); Marzani, Simone [Durham University, Institute for Particle Physics Phenomenology, Durham (United Kingdom)

2013-11-15

We consider the mass distribution of QCD jets after the application of jet-substructure methods, specifically the mass-drop tagger, pruning, trimming and their variants. In contrast to most current studies employing Monte Carlo methods, we carry out analytical calculations at the next-to-leading order level, which are sufficient to extract the dominant logarithmic behaviour for each technique, and compare our findings to exact fixed-order results. Our results should ultimately lead to a better understanding of these jet-substructure methods which in turn will influence the development of future substructure tools for LHC phenomenology. (orig.)

The gamma-ray-flux PDF from galactic halo substructure

International Nuclear Information System (INIS)

Lee, Samuel K.; Ando, Shin'ichiro; Kamionkowski, Marc

2009-01-01

One of the targets of the recently launched Fermi Gamma-ray Space Telescope is a diffuse gamma-ray background from dark-matter annihilation or decay in the Galactic halo. N-body simulations and theoretical arguments suggest that the dark matter in the Galactic halo may be clumped into substructure, rather than smoothly distributed. Here we propose the gamma-ray-flux probability distribution function (PDF) as a probe of substructure in the Galactic halo. We calculate this PDF for a phenomenological model of halo substructure and determine the regions of the substructure parameter space in which the PDF may be distinguished from the PDF for a smooth distribution of dark matter. In principle, the PDF allows a statistical detection of substructure, even if individual halos cannot be detected. It may also allow detection of substructure on the smallest microhalo mass scales, ∼ M ⊕ , for weakly-interacting massive particles (WIMPs). Furthermore, it may also provide a method to measure the substructure mass function. However, an analysis that assumes a typical halo substructure model and a conservative estimate of the diffuse background suggests that the substructure PDF may not be detectable in the lifespan of Fermi in the specific case that the WIMP is a neutralino. Nevertheless, for a large range of substructure, WIMP annihilation, and diffuse background models, PDF analysis may provide a clear signature of substructure

Urban structures and substructures

Directory of Open Access Journals (Sweden)

Mierzejewska Lidia

2017-06-01

Full Text Available In urban geography, a traditional but always important research problem has been the spatial-functional structure of towns and changes that occur in this field. Two approaches can be distinguished here: the sociological and the geographical. The former follows in the steps of the so-called Chicago school, i.e. Park, Burgess and Hoyt, and the other of Ullman and Harris. It seems, however, that those two approaches do not exhaust the range of spatial-structural studies which may be conducted in modern towns since there are areas within them endowed with specific properties that can be called their substructures. This paper will present the general characteristics of such substructures and identify factors responsible for their appearance and development. It will also propose an empirical research pattern. The term ‘substructures’ is taken to denote relatively autonomous, highly uniform wholes standing out in the spatial-functional structure of a town, distinguished on the basis of spatial relations generated by people. While structural elements of towns in the approach of the Chicago school or that of Harris and Ullman can be identified with structural regions, urban substructures show a similarity to functional regions in their organisation, structure and operation. Thus, towns with identified substructures have a polycentric spatial- functional structure, favourable in terms of both the level of service of their inhabitants and their sustainable development.

Full Vehicle Vibration and Noise Analysis Based on Substructure Power Flow

Directory of Open Access Journals (Sweden)

Zhien Liu

2017-01-01

Full Text Available Combining substructure and power flow theory, in this paper an external program is written to control MSC. Nastran solution process and the substructure frequency response are also formulated accordingly. Based on a simple vehicle model, characteristics of vibration, noise, and power flow are studied, respectively. After being compared with the result of conventional FEM (finite element method, the new method is confirmed to be feasible. When it comes to a vehicle with the problem of low-frequency noise, finite element models of substructures for vehicle body and chassis are established, respectively. In addition, substructure power flow method is also employed to examine the transfer characteristics of multidimensional vibration energy for the whole vehicle system. By virtue of the adjustment stiffness of drive shaft support and bushes at rear suspension lower arm, the vehicle interior noise is decreased by about 3 dB when the engine speed is near 1050 rpm and 1650 rpm in experiment. At the same time, this method can increase the computation efficiency by 78%, 38%, and 98% when it comes to the optimization of chassis structure, body structure, and vibration isolation components, respectively.

Indirect Inverse Substructuring Method for Multibody Product Transport System with Rigid and Flexible Coupling

Directory of Open Access Journals (Sweden)

Jun Wang

2015-01-01

Full Text Available The aim of this paper is to develop a new frequency response function- (FRF- based indirect inverse substructuring method without measuring system-level FRFs in the coupling DOFs for the analysis of the dynamic characteristics of a three-substructure coupled product transport system with rigid and flexible coupling. By enforcing the dynamic equilibrium conditions at the coupling coordinates and the displacement compatibility conditions, a closed-form analytical solution to inverse substructuring analysis of multisubstructure coupled product transport system is derived based on the relationship of easy-to-monitor component-level FRFs and the system-level FRFs at the coupling coordinates. The proposed method is validated by a lumped mass-spring-damper model, and the predicted coupling dynamic stiffness is compared with the direct computation, showing exact agreement. The method developed offers an approach to predict the unknown coupling dynamic stiffness from measured FRFs purely. The suggested method may help to obtain the main controlling factors and contributions from the various structure-borne paths for product transport system.

RAG-3D: a search tool for RNA 3D substructures

Science.gov (United States)

Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

2015-01-01

To address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding. PMID:26304547

Galactic densities, substructure and the initial power spectrum

International Nuclear Information System (INIS)

Bullock, J.S.; Zentner, A.R.

2003-01-01

Although the currently favored cold dark matter plus cosmological constant model for structure formation assumes an n = 1 scale-invariant initial power spectrum, most inflation models produce at least mild deviations from n = 1. Because the lever arm from the CMB normalization to galaxy scales is long, even a small 'tilt' can have important implications for galactic observations. Here we calculate the COBS-normalized power spectra for several well-motivated models of inflation and compute implications for the substructure content and central densities of galaxy halos. Using an analytic model, normalized against N-body simulations, we show that while halos in the standard (n = 1) model are overdense by a factor of ∼ 6 compared to observations, several of our example inflation+LCDM models predict halo densities well within the range of observations, which prefer models with n ∼ 0.85. We go on to use a semi-analytic model (also normalized against N-body simulations) to follow the merger histories of galaxy-sized halos and track the orbital decay, disruption, and evolution of the merging substructure. Models with n ∼ 0.85 predict a factor of ∼ 3 fewer subhalos at a fixed circular velocity than the standard n 1 case. Although this level of reduction does not resolve the 'dwarf satellite problem', it does imply that the level of feedback required to match the observed number of dwarfs is sensitive to the initial power spectrum. Finally, the fraction of galaxy-halo mass that is bound up in substructure is consistent with limits imposed by multiply imaged quasars for all models considered: f sat > 0.01 even for an effective tilt of n ∼ 0.8. We conclude that, at their current level, lensing constraints of this kind do not provide an interesting probe of the primordial power spectrum

Jet Substructure Measurements Sensitive to Soft QCD effects with the ATLAS Detector

CERN Document Server

Asquith, Lily; The ATLAS collaboration

2017-01-01

Calculations of jet substructure observables which are accurate beyond leading-logarithmic accuracy have recently become available. Such observables are significant not only for probing a new regime of QCD at a hadron collider, but also for improving the understanding of jet substructure properties that are used in many studies at the Large Hadron Collider. In this talk, we discuss first measurement of jet substructure quantities at a hadron collider, calculated at next-to-next-to-leading-logarithm accuracy. The soft drop mass is measured in dijet events with the ATLAS detector at 13 TeV, unfolded to particle-level and compared to Monte Carlo simulations. In addition, we present a measurement of the splitting scales in the kt jet-clustering algorithm for final states containing a Z-boson candidate at a centre-of-mass energy of 8 TeV.  The data are also corrected for detector effects and are compared to state-of-the-art Monte Carlo predictions.

Sub-structure

CSIR Research Space (South Africa)

Van Wyk, Llewellyn V

2010-04-01

Full Text Available in Conventional Sub-structure Element Concrete Volume (m 3 ) kgCO2/m 3 (see footnote) Total CO2 (kg) Foundations 1 3.69 209 2 771 Foundation walls 3 1.79 174 4 311 Concrete slab 5 4.09 250 6 1022 Total 9.57 2104 Raft foundations...

DETECTION OF LENSING SUBSTRUCTURE USING ALMA OBSERVATIONS OF THE DUSTY GALAXY SDP.81

Energy Technology Data Exchange (ETDEWEB)

Hezaveh, Yashar D.; Mao, Yao-Yuan; Morningstar, Warren; Blandford, Roger D.; Levasseur, Laurence Perreault; Wechsler, Risa H. [Kavli Institute for Particle Astrophysics and Cosmology and Department of Physics, Stanford University, 452 Lomita Mall, Stanford, CA 94305-4085 (United States); Dalal, Neal; Wen, Di; Kemball, Athol; Vieira, Joaquin D. [Astronomy Department, University of Illinois at Urbana-Champaign, 1002 W. Green Street, Urbana IL 61801 (United States); Marrone, Daniel P. [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Carlstrom, John E. [Kavli Institute for Cosmological Physics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States); Fassnacht, Christopher D. [Department of Physics, University of California, One Shields Avenue, Davis, CA 95616 (United States); Holder, Gilbert P. [Department of Physics, McGill University, 3600 Rue University, Montreal, Quebec H3A 2T8 (Canada); Marshall, Philip J. [Kavli Institute for Particle Astrophysics and Cosmology and Department of Particle Physics and Astrophysics, SLAC National Accelerator Laboratory, Menlo Park, CA 94305 (United States); Murray, Norman [CITA, University of Toronto, 60 St. George St., Toronto ON M5S 3H8 (Canada)

2016-05-20

We study the abundance of substructure in the matter density near galaxies using ALMA Science Verification observations of the strong lensing system SDP.81. We present a method to measure the abundance of subhalos around galaxies using interferometric observations of gravitational lenses. Using simulated ALMA observations we explore the effects of various systematics, including antenna phase errors and source priors, and show how such errors may be measured or marginalized. We apply our formalism to ALMA observations of SDP.81. We find evidence for the presence of a M = 10{sup 8.96±0.12} M {sub ⊙} subhalo near one of the images, with a significance of 6.9 σ in a joint fit to data from bands 6 and 7; the effect of the subhalo is also detected in both bands individually. We also derive constraints on the abundance of dark matter (DM) subhalos down to M ∼ 2 × 10{sup 7} M {sub ⊙}, pushing down to the mass regime of the smallest detected satellites in the Local Group, where there are significant discrepancies between the observed population of luminous galaxies and predicted DM subhalos. We find hints of additional substructure, warranting further study using the full SDP.81 data set (including, for example, the spectroscopic imaging of the lensed carbon monoxide emission). We compare the results of this search to the predictions of ΛCDM halos, and find that given current uncertainties in the host halo properties of SDP.81, our measurements of substructure are consistent with theoretical expectations. Observations of larger samples of gravitational lenses with ALMA should be able to improve the constraints on the abundance of galactic substructure.

DETECTION OF LENSING SUBSTRUCTURE USING ALMA OBSERVATIONS OF THE DUSTY GALAXY SDP.81

International Nuclear Information System (INIS)

Hezaveh, Yashar D.; Mao, Yao-Yuan; Morningstar, Warren; Blandford, Roger D.; Levasseur, Laurence Perreault; Wechsler, Risa H.; Dalal, Neal; Wen, Di; Kemball, Athol; Vieira, Joaquin D.; Marrone, Daniel P.; Carlstrom, John E.; Fassnacht, Christopher D.; Holder, Gilbert P.; Marshall, Philip J.; Murray, Norman

2016-01-01

We study the abundance of substructure in the matter density near galaxies using ALMA Science Verification observations of the strong lensing system SDP.81. We present a method to measure the abundance of subhalos around galaxies using interferometric observations of gravitational lenses. Using simulated ALMA observations we explore the effects of various systematics, including antenna phase errors and source priors, and show how such errors may be measured or marginalized. We apply our formalism to ALMA observations of SDP.81. We find evidence for the presence of a M = 10 8.96±0.12 M ⊙ subhalo near one of the images, with a significance of 6.9 σ in a joint fit to data from bands 6 and 7; the effect of the subhalo is also detected in both bands individually. We also derive constraints on the abundance of dark matter (DM) subhalos down to M ∼ 2 × 10 7 M ⊙ , pushing down to the mass regime of the smallest detected satellites in the Local Group, where there are significant discrepancies between the observed population of luminous galaxies and predicted DM subhalos. We find hints of additional substructure, warranting further study using the full SDP.81 data set (including, for example, the spectroscopic imaging of the lensed carbon monoxide emission). We compare the results of this search to the predictions of ΛCDM halos, and find that given current uncertainties in the host halo properties of SDP.81, our measurements of substructure are consistent with theoretical expectations. Observations of larger samples of gravitational lenses with ALMA should be able to improve the constraints on the abundance of galactic substructure.

Jet substructure measurements at ATLAS and CMS

CERN Document Server

Dattagupta, Aparajita; The ATLAS collaboration

2017-01-01

A review is given of recent Run II measurements of jet substructure at CMS and ATLAS, as well of the most relevant measurements from Run I. Quark and gluon discrimination, jet mass and other substructure observable are discussed together with prospects for future measurements with new insight from theory.

Soil and gas and radon entry potentials for substructure surfaces

International Nuclear Information System (INIS)

Harrison, J.; Sextro, R.G.

1990-01-01

This paper reports on measurement techniques and parameters that describe the potential for areas of a building substructure to have high soil gas and radon entry rates which have been developed. Flows and pressures measured at test holes in substructure surfaces while the substructure was intentionally depressurized were used in a highly simplified electrical circuit to model the substructure/soil network. Data from four New Jersey houses indicate that the soil was a factor of two to six times more resistant to soil gas flow than substructure surfaces, concrete slab floors, including perimeter gaps, cracks, and other penetrations, were approximately five times more resistant to soil gas movement than hollow block walls, and radon entry potentials were highest for slab floors. These indices of entry potential may be useful for characterizing the relative leakiness of below-grade substructure surfaces and for determining the selection and placement of radon control systems

A Modal-Based Substructure Method Applied to Nonlinear Rotordynamic Systems

Directory of Open Access Journals (Sweden)

Helmut J. Holl

2009-01-01

Full Text Available The discretisation of rotordynamic systems usually results in a high number of coordinates, so the computation of the solution of the equations of motion is very time consuming. An efficient semianalytic time-integration method combined with a substructure technique is given, which accounts for nonsymmetric matrices and local nonlinearities. The partitioning of the equation of motion into two substructures is performed. Symmetric and linear background systems are defined for each substructure. The excitation of the substructure comes from the given excitation force, the nonlinear restoring force, the induced force due to the gyroscopic and circulatory effects of the substructure under consideration and the coupling force of the substructures. The high effort for the analysis with complex numbers, which is necessary for nonsymmetric systems, is omitted. The solution is computed by means of an integral formulation. A suitable approximation for the unknown coordinates, which are involved in the coupling forces, has to be introduced and the integration results in Green's functions of the considered substructures. Modal analysis is performed for each linear and symmetric background system of the substructure. Modal reduction can be easily incorporated and the solution is calculated iteratively. The numerical behaviour of the algorithm is discussed and compared to other approximate methods of nonlinear structural dynamics for a benchmark problem and a representative example.

Substructuring by Lagrange multipliers for solids and plates

Energy Technology Data Exchange (ETDEWEB)

Mandel, J.; Tezaur, R. [Univ. of Colorado, Denver, CO (United States); Farhat, C. [Univ. of Colorado, Boulder, CO (United States)

1996-12-31

We present principles and theoreretical foundation of a substructuring method for large structural problems. The algorithm is preconditioned conjugate gradients on a subspace for the dual problem. The preconditioning is proved asymptotically optimal and the method is shown to be parallel scalable, i.e., the condition number is bounded independently of the number of substructures. For plate problems, a special modification is needed that retains continuity of the displacement solution at substructure crosspoints, resulting in an asymptically optimal method. The results are confirmed by numerical experiments.

Blooming Trees: Substructures and Surrounding Groups of Galaxy Clusters

Science.gov (United States)

Yu, Heng; Diaferio, Antonaldo; Serra, Ana Laura; Baldi, Marco

2018-06-01

We develop the Blooming Tree Algorithm, a new technique that uses spectroscopic redshift data alone to identify the substructures and the surrounding groups of galaxy clusters, along with their member galaxies. Based on the estimated binding energy of galaxy pairs, the algorithm builds a binary tree that hierarchically arranges all of the galaxies in the field of view. The algorithm searches for buds, corresponding to gravitational potential minima on the binary tree branches; for each bud, the algorithm combines the number of galaxies, their velocity dispersion, and their average pairwise distance into a parameter that discriminates between the buds that do not correspond to any substructure or group, and thus eventually die, and the buds that correspond to substructures and groups, and thus bloom into the identified structures. We test our new algorithm with a sample of 300 mock redshift surveys of clusters in different dynamical states; the clusters are extracted from a large cosmological N-body simulation of a ΛCDM model. We limit our analysis to substructures and surrounding groups identified in the simulation with mass larger than 1013 h ‑1 M ⊙. With mock redshift surveys with 200 galaxies within 6 h ‑1 Mpc from the cluster center, the technique recovers 80% of the real substructures and 60% of the surrounding groups; in 57% of the identified structures, at least 60% of the member galaxies of the substructures and groups belong to the same real structure. These results improve by roughly a factor of two the performance of the best substructure identification algorithm currently available, the σ plateau algorithm, and suggest that our Blooming Tree Algorithm can be an invaluable tool for detecting substructures of galaxy clusters and investigating their complex dynamics.

Substructure evolution of Zircaloy-4 during creep and implications for the Modified Jogged-Screw model

Energy Technology Data Exchange (ETDEWEB)

Morrow, B.M., E-mail: morrow@lanl.gov [The Ohio State University, 2041 College Rd., 477 Watts Hall, Columbus, OH 43210 (United States); Los Alamos National Laboratory, P.O. Box 1663, MS G755, Los Alamos, NM 87545 (United States); Kozar, R.W.; Anderson, K.R. [Bettis Laboratory, Bechtel Marine Propulsion Corp., West Mifflin, PA 15122 (United States); Mills, M.J., E-mail: millsmj@mse.osu.edu [The Ohio State University, 2041 College Rd., 477 Watts Hall, Columbus, OH 43210 (United States)

2016-05-17

Several specimens of Zircaloy-4 were creep tested at a single stress-temperature condition, and interrupted at different accumulated strain levels. Substructural observations were performed using bright field scanning transmission electron microscopy (BF STEM). The dislocation substructure was characterized to ascertain how creep strain evolution impacts the Modified Jogged-Screw (MJS) model, which has previously been utilized to predict steady-state strain rates in Zircaloy-4. Special attention was paid to the evolution of individual model parameters with increasing strain. Results of model parameter measurements are reported and discussed, along with possible extensions to the MJS model.

Small but mighty: Dark matter substructures

Science.gov (United States)

Cyr-Racine, Francis-Yan; Keeton, Charles; Moustakas, Leonidas

2018-01-01

The fundamental properties of dark matter, such as its mass, self-interaction, and coupling to other particles, can have a major impact on the evolution of cosmological density fluctuations on small length scales. Strong gravitational lenses have long been recognized as powerful tools to study the dark matter distribution on these small subgalactic scales. In this talk, we discuss how gravitationally lensed quasars and extended lensed arcs could be used to probe non minimal dark matter models. We comment on the possibilities enabled by precise astrometry, deep imaging, and time delays to extract information about mass substructures inside lens galaxies. To this end, we introduce a new lensing statistics that allows for a robust diagnostic of the presence of perturbations caused by substructures. We determine which properties of mass substructures are most readily constrained by lensing data and forecast the constraining power of current and future observations.

DISCOVERY OF SUBSTRUCTURE IN THE SCATTER-BROADENED IMAGE OF SGR A*

Energy Technology Data Exchange (ETDEWEB)

Gwinn, C. R. [Physics Department, Broida Hall, University of California, Santa Barbara, CA 93117 (United States); Kovalev, Y. Y.; Soglasnov, V. A. [Astro Space Center, Lebedev Physical Institute, Russian Academy of Sciences, Profsoyuznaya Str. 84/32, Moscow 117997 (Russian Federation); Johnson, M. D., E-mail: cgwinn@physics.ucsb.edu [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States)

2014-10-10

We have detected substructure within the smooth scattering disk of the celebrated Galactic center radio source Sagittarius A* (Sgr A*). We observed this structure at 1.3 cm wavelength with the Very Long Baseline Array together with the Green Bank Telescope, on baselines of up to 3000 km, long enough to completely resolve the average scattering disk. Such structure is predicted theoretically as a consequence of refraction by large-scale plasma fluctuations in the interstellar medium. Along with the much-studied θ{sub d}∝λ{sup 2} scaling of angular broadening θ{sub d} with observing wavelength λ, our observations indicate that the spectrum of interstellar turbulence is shallow with an inner scale larger than 300 km. The substructure is consistent with an intrinsic size of about 1 mas at 1.3 cm wavelength, as inferred from deconvolution of the average scattering. Further observations of the substructure can set stronger constraints on the properties of scattering material and on the intrinsic size of Sgr A*. These constraints will guide our understanding of the effects of scatter broadening and the emission physics near the black hole in images with the Event Horizon Telescope at millimeter wavelengths.

Fracture behaviour of zirconia FPDs substructures.

Science.gov (United States)

Kou, W; Sjögren, G

2010-04-01

The purpose of this study was to evaluate the occurrence of superficial flaws after machining and to identify fracture initiation and propagation in three-unit heat-treated machined fixed partial dentures (FPDs) substructures made of hot isostatic pressed (HIPed) yttria-stabilized tetragonal zirconia polycrystal (Y-TZP) after loaded to fracture. Four three-unit HIPed Y-TZP-based FPDs substructures were examined. To evaluate the occurrence of superficial flaws after machining, the surfaces were studied utilizing a fluorescent penetrant method. After static loading to fracture, characteristic fracture features on both mating halves of the fractured specimens were studied using a stereomicroscope and a scanning electron microscope. Grinding grooves were clearly visible on the surfaces of the machined FPDs substructures, but no other flaws could be seen with the fluorescent penetrant method. After loading to fracture, the characteristic fracture features of arrest lines, compression curl, fracture mirror, fracture origin, hackle and twist hackle were detected. These findings indicated that the decisive fracture was initiated at the gingival embrasure of the pontic in association with a grinding groove. Thus, in three-unit heat-treated machined HIPed Y-TZP FPDs substructures, with the shape studied in this study, the gingival embrasure of the pontic seems to be a weak area providing a location for tensile stresses when they are occlusally loaded. In this area, fracture initiation may be located to a grinding groove.

An Impulse Based Substructuring approach for impact analysis and load case simulations

Science.gov (United States)

Rixen, Daniel J.; van der Valk, Paul L. C.

2013-12-01

In the present paper we outline the basic theory of assembling substructures for which the dynamics are described as Impulse Response Functions. The assembly procedure computes the time response of a system by evaluating per substructure the convolution product between the Impulse Response Functions and the applied forces, including the interface forces that are computed to satisfy the interface compatibility. We call this approach the Impulse Based Substructuring method since it transposes to the time domain the Frequency Based Substructuring approach. In the Impulse Based Substructuring technique the Impulse Response Functions of the substructures can be gathered either from experimental tests using a hammer impact or from time-integration of numerical submodels. In this paper the implementation of the method is outlined for the case when the impulse responses of the substructures are computed numerically. A simple bar example is shown in order to illustrate the concept. The Impulse Based Substructuring allows fast evaluation of impact response of a structure when the impulse response of its components is known. It can thus be used to efficiently optimize designs of consumer products by including impact behavior at the early stage of the design, but also for performing substructured simulations of complex structures such as offshore wind turbines.

A sub-structure method for multidimensional integral transport calculations

International Nuclear Information System (INIS)

Kavenoky, A.; Stankovski, Z.

1983-03-01

A new method has been developed for fine structure burn-up calculations of very heterogeneous large size media. It is a generalization of the well-known surface-source method, allowing coupling actual two-dimensional heterogeneous assemblies, called sub-structures. The method has been applied to a rectangular medium, divided into sub-structures, containing rectangular and/or cylindrical fuel, moderator and structure elements. The sub-structures are divided into homogeneous zones. A zone-wise flux expansion is used to formulate a direct collision probability problem within it (linear or flat flux expansion in the rectangular zones, flat flux in the others). The coupling of the sub-structures is performed by making extra assumptions on the currents entering and leaving the interfaces. The accuracies and computing times achieved are illustrated by numerical results on two benchmark problems

THE SEGUE K GIANT SURVEY. III. QUANTIFYING GALACTIC HALO SUBSTRUCTURE

Energy Technology Data Exchange (ETDEWEB)

Janesh, William; Morrison, Heather L.; Ma, Zhibo; Harding, Paul [Department of Astronomy, Case Western Reserve University, Cleveland, OH 44106 (United States); Rockosi, Constance [UCO/Lick Observatory, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA 95064 (United States); Starkenburg, Else [Department of Physics and Astronomy, University of Victoria, P.O. Box 1700, STN CSC, Victoria BC V8W 3P6 (Canada); Xue, Xiang Xiang; Rix, Hans-Walter [Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany); Beers, Timothy C. [Department of Physics and JINA Center for the Evolution of the Elements, University of Notre Dame, Notre Dame, IN 46556 (United States); Johnson, Jennifer [Department of Astronomy, Ohio State University, 140 West 18th Avenue, Columbus, OH 43210 (United States); Lee, Young Sun [Department of Astronomy and Space Science, Chungnam National University, Daejeon 34134 (Korea, Republic of); Schneider, Donald P. [Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802 (United States)

2016-01-10

We statistically quantify the amount of substructure in the Milky Way stellar halo using a sample of 4568 halo K giant stars at Galactocentric distances ranging over 5–125 kpc. These stars have been selected photometrically and confirmed spectroscopically as K giants from the Sloan Digital Sky Survey’s Sloan Extension for Galactic Understanding and Exploration project. Using a position–velocity clustering estimator (the 4distance) and a model of a smooth stellar halo, we quantify the amount of substructure in the halo, divided by distance and metallicity. Overall, we find that the halo as a whole is highly structured. We also confirm earlier work using blue horizontal branch (BHB) stars which showed that there is an increasing amount of substructure with increasing Galactocentric radius, and additionally find that the amount of substructure in the halo increases with increasing metallicity. Comparing to resampled BHB stars, we find that K giants and BHBs have similar amounts of substructure over equivalent ranges of Galactocentric radius. Using a friends-of-friends algorithm to identify members of individual groups, we find that a large fraction (∼33%) of grouped stars are associated with Sgr, and identify stars belonging to other halo star streams: the Orphan Stream, the Cetus Polar Stream, and others, including previously unknown substructures. A large fraction of sample K giants (more than 50%) are not grouped into any substructure. We find also that the Sgr stream strongly dominates groups in the outer halo for all except the most metal-poor stars, and suggest that this is the source of the increase of substructure with Galactocentric radius and metallicity.

Substructural Regularization With Data-Sensitive Granularity for Sequence Transfer Learning.

Science.gov (United States)

Sun, Shichang; Liu, Hongbo; Meng, Jiana; Chen, C L Philip; Yang, Yu

2018-06-01

Sequence transfer learning is of interest in both academia and industry with the emergence of numerous new text domains from Twitter and other social media tools. In this paper, we put forward the data-sensitive granularity for transfer learning, and then, a novel substructural regularization transfer learning model (STLM) is proposed to preserve target domain features at substructural granularity in the light of the condition of labeled data set size. Our model is underpinned by hidden Markov model and regularization theory, where the substructural representation can be integrated as a penalty after measuring the dissimilarity of substructures between target domain and STLM with relative entropy. STLM can achieve the competing goals of preserving the target domain substructure and utilizing the observations from both the target and source domains simultaneously. The estimation of STLM is very efficient since an analytical solution can be derived as a necessary and sufficient condition. The relative usability of substructures to act as regularization parameters and the time complexity of STLM are also analyzed and discussed. Comprehensive experiments of part-of-speech tagging with both Brown and Twitter corpora fully justify that our model can make improvements on all the combinations of source and target domains.

An algebraic sub-structuring method for large-scale eigenvalue calculation

International Nuclear Information System (INIS)

Yang, C.; Gao, W.; Bai, Z.; Li, X.; Lee, L.; Husbands, P.; Ng, E.

2004-01-01

We examine sub-structuring methods for solving large-scale generalized eigenvalue problems from a purely algebraic point of view. We use the term 'algebraic sub-structuring' to refer to the process of applying matrix reordering and partitioning algorithms to divide a large sparse matrix into smaller submatrices from which a subset of spectral components are extracted and combined to provide approximate solutions to the original problem. We are interested in the question of which spectral components one should extract from each sub-structure in order to produce an approximate solution to the original problem with a desired level of accuracy. Error estimate for the approximation to the smallest eigenpair is developed. The estimate leads to a simple heuristic for choosing spectral components (modes) from each sub-structure. The effectiveness of such a heuristic is demonstrated with numerical examples. We show that algebraic sub-structuring can be effectively used to solve a generalized eigenvalue problem arising from the simulation of an accelerator structure. One interesting characteristic of this application is that the stiffness matrix produced by a hierarchical vector finite elements scheme contains a null space of large dimension. We present an efficient scheme to deflate this null space in the algebraic sub-structuring process

Substructure boosts to dark matter annihilation from Sommerfeld enhancement

International Nuclear Information System (INIS)

Bovy, Jo

2009-01-01

The recently introduced Sommerfeld enhancement of the dark matter annihilation cross section has important implications for the detection of dark matter annihilation in subhalos in the Galactic halo. In addition to the boost to the dark matter annihilation cross section from the high densities of these subhalos with respect to the main halo, an additional boost caused by the Sommerfeld enhancement results from the fact that they are kinematically colder than the Galactic halo. If we further believe the generic prediction of the cold dark matter paradigm that in each subhalo there is an abundance of substructure which is approximately self-similar to that of the Galactic halo, then I show that additional boosts coming from the density enhancements of these small substructures and their small velocity dispersions enhance the dark matter annihilation cross section even further. I find that very large boost factors (10 5 to 10 9 ) are obtained in a large class of models. The implications of these boost factors for the detection of dark matter annihilation from dwarf spheroidal galaxies in the Galactic halo are such that, generically, they outshine the background gamma-ray flux and are detectable by the Fermi Gamma-ray Space Telescope.

The nonlinear response of the complex structural system in nuclear reactors using dynamic substructure method

International Nuclear Information System (INIS)

Zheng, Z.C.; Xie, G.; Du, Q.H.

1987-01-01

Because of the existence of nonlinear characteristics in practical engineering structures, such as large steam turbine-foundation system and offshore platform, it is necessary to predict nonlinear dynamic responses for these very large and complex structural systems subjected extreme load. Due to the limited storage and high executing cost of computers, there are still some difficulties in the analysis for such systems although the traditional finite element methods provide basic available methods to the problems. The dynamic substructure methods, which were developed as a branch of general structural dynamics in the past more than 20 years and have been widely used from aircraft, space vehicles to other mechanical and civil engineering structures, present a powerful method to the analysis of very large structural systems. The key to success is due to the considerable reduction in the number of degrees of freedom while not changing the physical essence of the problems investigated. The dynamic substructure method has been extended to nonlinear system and applicated to the analysis of nonlinear dynamic response of an offshore platform by Z.C. Zheng, et al. (1983, 1985a, b, c). In this paper, the method is presented to analyze dynamic responses of the systems contained intrinsic nonlinearities and with nonlinear attachments and nonlinear supports of nuclear structural systems. The efficiency of the method becomes more clear for nonlinear dynamic problems due to the adoption of iterating processes. For simplicity, the analysis procedure is demonstrated briefly. The generalized substructure method of nonlinear systems is similar to linear systems, only the nonlinear terms are treated as pseudo-forces. Interface coordinates are classified into two categories, the connecting interface coordinates which connect with each other directly in the global system and the linking interface coordinates which link to each other through attachments. (orig./GL)

Substructure and electrical resistivity analyses of pure tungsten sheet

International Nuclear Information System (INIS)

Trybus, C.L.; Sellers, C.H.; Anderl, R.A.

1991-01-01

The substructure of pure tungsten sheet (0.025 mm thick) is examined and quantified by transmission electron microscopy (TEM). Dislocation populations and arrangements are evaluated for as-worked and various annealed conditions of the tungsten sheet. The worked (rolled) tungsten substructure was nonhomogeneous, consisting of areas of very high and low dislocation densities. These results are correlated to resistivity measurements of the tungsten sheet following thermal cycling to 1200 degrees C to determine the substructural changes as a function of temperature. The comparison between the two characterization techniques is used to examine the relationship between structural and electronic properties in tungsten. 15 refs., 6 figs., 2 tabs

Analysis and application of European genetic substructure using 300 K SNP information.

Directory of Open Access Journals (Sweden)

Chao Tian

2008-01-01

Full Text Available European population genetic substructure was examined in a diverse set of >1,000 individuals of European descent, each genotyped with >300 K SNPs. Both STRUCTURE and principal component analyses (PCA showed the largest division/principal component (PC differentiated northern from southern European ancestry. A second PC further separated Italian, Spanish, and Greek individuals from those of Ashkenazi Jewish ancestry as well as distinguishing among northern European populations. In separate analyses of northern European participants other substructure relationships were discerned showing a west to east gradient. Application of this substructure information was critical in examining a real dataset in whole genome association (WGA analyses for rheumatoid arthritis in European Americans to reduce false positive signals. In addition, two sets of European substructure ancestry informative markers (ESAIMs were identified that provide substantial substructure information. The results provide further insight into European population genetic substructure and show that this information can be used for improving error rates in association testing of candidate genes and in replication studies of WGA scans.

Social-group identity and population substructure in admixed populations in New Mexico and Latin America.

Directory of Open Access Journals (Sweden)

Meghan E Healy

Full Text Available We examined the relationship between continental-level genetic ancestry and racial and ethnic identity in an admixed population in New Mexico with the goal of increasing our understanding of how racial and ethnic identity influence genetic substructure in admixed populations. Our sample consists of 98 New Mexicans who self-identified as Hispanic or Latino (NM-HL and who further categorized themselves by race and ethnic subgroup membership. The genetic data consist of 270 newly-published autosomal microsatellites from the NM-HL sample and previously published data from 57 globally distributed populations, including 13 admixed samples from Central and South America. For these data, we 1 summarized the major axes of genetic variation using principal component analyses, 2 performed tests of Hardy Weinberg equilibrium, 3 compared empirical genetic ancestry distributions to those predicted under a model of admixture that lacked substructure, 4 tested the hypotheses that individuals in each sample had 100%, 0%, and the sample-mean percentage of African, European, and Native American ancestry. We found that most NM-HL identify themselves and their parents as belonging to one of two groups, conforming to a region-specific narrative that distinguishes recent immigrants from Mexico from individuals whose families have resided in New Mexico for generations and who emphasize their Spanish heritage. The "Spanish" group had significantly lower Native American ancestry and higher European ancestry than the "Mexican" group. Positive FIS values, PCA plots, and heterogeneous ancestry distributions suggest that most Central and South America admixed samples also contain substructure, and that this substructure may be related to variation in social identity. Genetic substructure appears to be common in admixed populations in the Americas and may confound attempts to identify disease-causing genes and to understand the social causes of variation in health outcomes

Facile approach to the fabrication of a micropattern possessing nanoscale substructure.

Science.gov (United States)

Ji, Qiang; Jiang, Xuesong; Yin, Jie

2007-12-04

On the basis of the combined technologies of photolithography and reaction-induced phase separation (RIPS), a facile approach has been successfully developed for the fabrication of a micropattern possessing nanoscale substructure on the thin film surface. This approach involves three steps. In the first step, a thin film was prepared by spin coating from a solution of a commercial random copolymer, polystyrene-r-poly(methyl methacrylate) (PS-r-PMMA) and a commercial crosslinker, trimethylolpropane triacrylate (TMPTA). In the second step, photolithograph was performed with the thin film using a 250 W high-pressure mercury lamp to produce the micropattern. Finally, the resulting micropattern was annealed at 200 degrees C for a certain time, and reaction-induced phase separation occurred. After soaking in chloroform for 4 h, nanoscale substructure was obtained. The whole processes were traced by atomic force microscopy (AFM), X-ray photoelectron spectrometry (XPS), and Fourier transform infrared (FTIR) spectroscopy, and the results supported the proposed structure.

Evolution of the degree of substructures in simulated galaxy clusters

Science.gov (United States)

De Boni, Cristiano; Böhringer, Hans; Chon, Gayoung; Dolag, Klaus

2018-05-01

We study the evolution of substructure in the mass distribution with mass, redshift and radius in a sample of simulated galaxy clusters. The sample, containing 1226 objects, spans the mass range M200 = 1014 - 1.74 × 1015 M⊙ h-1 in six redshift bins from z = 0 to z = 1.179. We consider three different diagnostics: 1) subhalos identified with SUBFIND; 2) overdense regions localized by dividing the cluster into octants; 3) offset between the potential minimum and the center of mass. The octant analysis is a new method that we introduce in this work. We find that none of the diagnostics indicate a correlation between the mass of the cluster and the fraction of substructures. On the other hand, all the diagnostics suggest an evolution of substructures with redshift. For SUBFIND halos, the mass fraction is constant with redshift at Rvir, but shows a mild evolution at R200 and R500. Also, the fraction of clusters with at least a subhalo more massive than one thirtieth of the total mass is less than 20%. Our new method based on the octants returns a mass fraction in substructures which has a strong evolution with redshift at all radii. The offsets also evolve strongly with redshift. We also find a strong correlation for individual clusters between the offset and the fraction of substructures identified with the octant analysis. Our work puts strong constraints on the amount of substructures we expect to find in galaxy clusters and on their evolution with redshift.

Identifying a new particle with jet substructures

CERN Document Server

Lim, Sung Hak; Kim, Doojin; Kim, Minho; Kong, Kyoungchul; Park, Myeonghun

2017-01-01

We investigate a potential of measuring properties of a heavy resonance X, exploiting jet substructure techniques. Motivated by heavy higgs boson searches, we focus on the decays of X into a pair of (massive) electroweak gauge bosons. More specifically, we consider a hadronic Z boson, which makes it possible to determine properties of X at an earlier stage. For $m_X$ of O(1) TeV, two quarks from a Z boson would be captured as a "merged jet" in a significant fraction of events. The use of the merged jet enables us to consider a Z-induced jet as a reconstructed object without any combinatorial ambiguity. We apply a conventional jet substructure method to extract four-momenta of subjets from a merged jet. We find that jet substructure procedures may enhance features in some kinematic observables formed with subjets. Subjet momenta are fed into the matrix element associated with a given hypothesis on the nature of X, which is further processed to construct a matrix element method (MEM)-based observable. For both ...

Efficient heuristics for maximum common substructure search.

Science.gov (United States)

Englert, Péter; Kovács, Péter

2015-05-26

Maximum common substructure search is a computationally hard optimization problem with diverse applications in the field of cheminformatics, including similarity search, lead optimization, molecule alignment, and clustering. Most of these applications have strict constraints on running time, so heuristic methods are often preferred. However, the development of an algorithm that is both fast enough and accurate enough for most practical purposes is still a challenge. Moreover, in some applications, the quality of a common substructure depends not only on its size but also on various topological features of the one-to-one atom correspondence it defines. Two state-of-the-art heuristic algorithms for finding maximum common substructures have been implemented at ChemAxon Ltd., and effective heuristics have been developed to improve both their efficiency and the relevance of the atom mappings they provide. The implementations have been thoroughly evaluated and compared with existing solutions (KCOMBU and Indigo). The heuristics have been found to greatly improve the performance and applicability of the algorithms. The purpose of this paper is to introduce the applied methods and present the experimental results.

Substructure method of soil-structure interaction analysis for earthquake loadings

Energy Technology Data Exchange (ETDEWEB)

Park, H. G.; Joe, Y. H. [Industrial Development Research Center, Univ. of Incheon, Incheon (Korea, Republic of)

1997-07-15

Substructure method has been preferably adopted for soil-structure interaction analysis because of its simplicity and economy in practical application. However, substructure method has some limitation in application and does not always give reliable results especially for embedded structures or layered soil conditions. The objective of this study to validate the reliability of the soil-structure interaction analysis results by the proposed substructure method using lumped-parameter model and suggest a method of seismic design of nuclear power plant structures with specific design conditions. In this study, theoretic background and modeling technique of soil-structure interaction phenomenon have been reviewed and an analysis technique based on substructure method using lumped-parameter model has been suggested. The practicality and reliability of the proposed method have been validated through the application of the method to the seismic analysis of the large-scale seismic test models. A technical guide for practical application and evaluation of the proposed method have been also provided through the various type parametric.

Factorization for groomed jet substructure beyond the next-to-leading logarithm

Energy Technology Data Exchange (ETDEWEB)

Frye, Christopher; Larkoski, Andrew J.; Schwartz, Matthew D.; Yan, Kai [Center for the Fundamental Laws of Nature, Harvard University,17 Oxford Street, Cambridge, MA 02138 (United States)

2016-07-12

Jet grooming algorithms are widely used in experimental analyses at hadron colliders to remove contaminating radiation from within jets. While the algorithms perform a great service to the experiments, their intricate algorithmic structure and multiple parameters has frustrated precision theoretic understanding. In this paper, we demonstrate that one particular groomer called soft drop actually makes precision jet substructure easier. In particular, we derive a factorization formula for a large class of soft drop jet substructure observables, including jet mass. The essential observation that allows for this factorization is that, without the soft wide-angle radiation groomed by soft drop, all singular contributions are collinear. The simplicity and universality of the collinear limit in QCD allows us to show that to all orders, the normalized differential cross section has no contributions from non-global logarithms. It is also independent of process, up to the relative fraction of quark and gluon jets. In fact, soft drop allows us to define this fraction precisely. The factorization theorem also explains why soft drop observables are less sensitive to hadronization than their ungroomed counterparts. Using the factorization theorem, we resum the soft drop jet mass to next-to-next-to-leading logarithmic accuracy. This requires calculating some clustering effects that are closely related to corresponding effects found in jet veto calculations. We match our resummed calculation to fixed order results for both e{sup +}e{sup −}→ dijets and pp→Z+j events, producing the first jet substructure predictions (groomed or ungroomed) to this accuracy for the LHC.

Factorization for groomed jet substructure beyond the next-to-leading logarithm

International Nuclear Information System (INIS)

Frye, Christopher; Larkoski, Andrew J.; Schwartz, Matthew D.; Yan, Kai

2016-01-01

Jet grooming algorithms are widely used in experimental analyses at hadron colliders to remove contaminating radiation from within jets. While the algorithms perform a great service to the experiments, their intricate algorithmic structure and multiple parameters has frustrated precision theoretic understanding. In this paper, we demonstrate that one particular groomer called soft drop actually makes precision jet substructure easier. In particular, we derive a factorization formula for a large class of soft drop jet substructure observables, including jet mass. The essential observation that allows for this factorization is that, without the soft wide-angle radiation groomed by soft drop, all singular contributions are collinear. The simplicity and universality of the collinear limit in QCD allows us to show that to all orders, the normalized differential cross section has no contributions from non-global logarithms. It is also independent of process, up to the relative fraction of quark and gluon jets. In fact, soft drop allows us to define this fraction precisely. The factorization theorem also explains why soft drop observables are less sensitive to hadronization than their ungroomed counterparts. Using the factorization theorem, we resum the soft drop jet mass to next-to-next-to-leading logarithmic accuracy. This requires calculating some clustering effects that are closely related to corresponding effects found in jet veto calculations. We match our resummed calculation to fixed order results for both e + e − → dijets and pp→Z+j events, producing the first jet substructure predictions (groomed or ungroomed) to this accuracy for the LHC.

Gas expulsion in highly substructured embedded star clusters

Science.gov (United States)

Farias, J. P.; Fellhauer, M.; Smith, R.; Domínguez, R.; Dabringhausen, J.

2018-06-01

We investigate the response of initially substructured, young, embedded star clusters to instantaneous gas expulsion of their natal gas. We introduce primordial substructure to the stars and the gas by simplistically modelling the star formation process so as to obtain a variety of substructure distributed within our modelled star-forming regions. We show that, by measuring the virial ratio of the stars alone (disregarding the gas completely), we can estimate how much mass a star cluster will retain after gas expulsion to within 10 per cent accuracy, no matter how complex the background structure of the gas is, and we present a simple analytical recipe describing this behaviour. We show that the evolution of the star cluster while still embedded in the natal gas, and the behaviour of the gas before being expelled, is crucial process that affect the time-scale on which the cluster can evolve into a virialized spherical system. Embedded star clusters that have high levels of substructure are subvirial for longer times, enabling them to survive gas expulsion better than a virialized and spherical system. By using a more realistic treatment for the background gas than our previous studies, we find it very difficult to destroy the young clusters with instantaneous gas expulsion. We conclude that gas removal may not be the main culprit for the dissolution of young star clusters.

Towards an understanding of jet substructure

CERN Document Server

Dasgupta, Mrinal; Marzani, Simone; Salam, Gavin P

2013-01-01

We present first analytic, resummed calculations of the rates at which widespread jet substructure tools tag QCD jets. As well as considering trimming, pruning and the mass-drop tagger, we introduce modified tools with improved analytical and phenomenological behaviours. Most taggers have double logarithmic resummed structures. The modified mass-drop tagger is special in that it involves only single logarithms, and is free from a complex class of terms known as non-global logarithms. The modification of pruning brings an improved ability to discriminate between the different colour structures that characterise signal and background. As we outline in an extensive phenomenological discussion, these results provide valuable insight into the performance of existing tools and help lay robust foundations for future substructure studies.

AN EXAMINATION OF THE OPTICAL SUBSTRUCTURE OF GALAXY CLUSTERS HOSTING RADIO SOURCES

International Nuclear Information System (INIS)

Wing, Joshua D.; Blanton, Elizabeth L.

2013-01-01

Using radio sources from the Faint Images of the Radio Sky at Twenty-cm survey, and optical counterparts in the Sloan Digital Sky Survey, we have identified a large number of galaxy clusters. The radio sources within these clusters are driven by active galactic nuclei, and our cluster samples include clusters with bent, and straight, double-lobed radio sources. We also included a single-radio-component comparison sample. We examine these galaxy clusters for evidence of optical substructure, testing the possibility that bent double-lobed radio sources are formed as a result of large-scale cluster mergers. We use a suite of substructure analysis tools to determine the location and extent of substructure visible in the optical distribution of cluster galaxies, and compare the rates of substructure in clusters with different types of radio sources. We found no preference for significant substructure in clusters hosting bent double-lobed radio sources compared to those with other types of radio sources.

A NEW METHOD TO QUANTIFY X-RAY SUBSTRUCTURES IN CLUSTERS OF GALAXIES

Energy Technology Data Exchange (ETDEWEB)

Andrade-Santos, Felipe; Lima Neto, Gastao B.; Lagana, Tatiana F. [Departamento de Astronomia, Instituto de Astronomia, Geofisica e Ciencias Atmosfericas, Universidade de Sao Paulo, Geofisica e Ciencias Atmosfericas, Rua do Matao 1226, Cidade Universitaria, 05508-090 Sao Paulo, SP (Brazil)

2012-02-20

We present a new method to quantify substructures in clusters of galaxies, based on the analysis of the intensity of structures. This analysis is done in a residual image that is the result of the subtraction of a surface brightness model, obtained by fitting a two-dimensional analytical model ({beta}-model or Sersic profile) with elliptical symmetry, from the X-ray image. Our method is applied to 34 clusters observed by the Chandra Space Telescope that are in the redshift range z in [0.02, 0.2] and have a signal-to-noise ratio (S/N) greater than 100. We present the calibration of the method and the relations between the substructure level with physical quantities, such as the mass, X-ray luminosity, temperature, and cluster redshift. We use our method to separate the clusters in two sub-samples of high- and low-substructure levels. We conclude, using Monte Carlo simulations, that the method recuperates very well the true amount of substructure for small angular core radii clusters (with respect to the whole image size) and good S/N observations. We find no evidence of correlation between the substructure level and physical properties of the clusters such as gas temperature, X-ray luminosity, and redshift; however, analysis suggest a trend between the substructure level and cluster mass. The scaling relations for the two sub-samples (high- and low-substructure level clusters) are different (they present an offset, i.e., given a fixed mass or temperature, low-substructure clusters tend to be more X-ray luminous), which is an important result for cosmological tests using the mass-luminosity relation to obtain the cluster mass function, since they rely on the assumption that clusters do not present different scaling relations according to their dynamical state.

Discovery of New Retrograde Substructures: The Shards of ω Centauri?

Science.gov (United States)

Myeong, G. C.; Evans, N. W.; Belokurov, V.; Sanders, J. L.; Koposov, S. E.

2018-06-01

We use the SDSS-Gaia catalogue to search for substructure in the stellar halo. The sample comprises 62 133 halo stars with full phase space coordinates and extends out to heliocentric distances of ˜10 kpc. As actions are conserved under slow changes of the potential, they permit identification of groups of stars with a common accretion history. We devise a method to identify halo substructures based on their clustering in action space, using metallicity as a secondary check. This is validated against smooth models and numerical constructed stellar halos from the Aquarius simulations. We identify 21 substructures in the SDSS-Gaia catalogue, including 7 high significance, high energy and retrograde ones. We investigate whether the retrograde substructures may be material stripped off the atypical globular cluster ω Centauri. Using a simple model of the accretion of the progenitor of the ω Centauri, we tentatively argue for the possible association of up to 5 of our new substructures (labelled Rg1, Rg3, Rg4, Rg6 and Rg7) with this event. This sets a minimum mass of 5× 108M⊙ for the progenitor, so as to bring ω Centauri to its current location in action - energy space. Our proposal can be tested by high resolution spectroscopy of the candidates to look for the unusual abundance patterns possessed by ω Centauri stars.

Star formation and substructure in galaxy clusters

International Nuclear Information System (INIS)

Cohen, Seth A.; Hickox, Ryan C.; Wegner, Gary A.; Einasto, Maret; Vennik, Jaan

2014-01-01

We investigate the relationship between star formation (SF) and substructure in a sample of 107 nearby galaxy clusters using data from the Sloan Digital Sky Survey. Several past studies of individual galaxy clusters have suggested that cluster mergers enhance cluster SF, while others find no such relationship. The SF fraction in multi-component clusters (0.228 ± 0.007) is higher than that in single-component clusters (0.175 ± 0.016) for galaxies with M r 0.1 <−20.5. In both single- and multi-component clusters, the fraction of star-forming galaxies increases with clustercentric distance and decreases with local galaxy number density, and multi-component clusters show a higher SF fraction than single-component clusters at almost all clustercentric distances and local densities. Comparing the SF fraction in individual clusters to several statistical measures of substructure, we find weak, but in most cases significant at greater than 2σ, correlations between substructure and SF fraction. These results could indicate that cluster mergers may cause weak but significant SF enhancement in clusters, or unrelaxed clusters exhibit slightly stronger SF due to their less evolved states relative to relaxed clusters.

Improving substructure identification accuracy of shear structures using virtual control system

Science.gov (United States)

Zhang, Dongyu; Yang, Yang; Wang, Tingqiang; Li, Hui

2018-02-01

Substructure identification is a powerful tool to identify the parameters of a complex structure. Previously, the authors developed an inductive substructure identification method for shear structures. The identification error analysis showed that the identification accuracy of this method is significantly influenced by the magnitudes of two key structural responses near a certain frequency; if these responses are unfavorable, the method cannot provide accurate estimation results. In this paper, a novel method is proposed to improve the substructure identification accuracy by introducing a virtual control system (VCS) into the structure. A virtual control system is a self-balanced system, which consists of some control devices and a set of self-balanced forces. The self-balanced forces counterbalance the forces that the control devices apply on the structure. The control devices are combined with the structure to form a controlled structure used to replace the original structure in the substructure identification; and the self-balance forces are treated as known external excitations to the controlled structure. By optimally tuning the VCS’s parameters, the dynamic characteristics of the controlled structure can be changed such that the original structural responses become more favorable for the substructure identification and, thus, the identification accuracy is improved. A numerical example of 6-story shear structure is utilized to verify the effectiveness of the VCS based controlled substructure identification method. Finally, shake table tests are conducted on a 3-story structural model to verify the efficacy of the VCS to enhance the identification accuracy of the structural parameters.

Substructuring in the implicit simulation of single point incremental sheet forming

NARCIS (Netherlands)

Hadoush, A.; van den Boogaard, Antonius H.

2009-01-01

This paper presents a direct substructuring method to reduce the computing time of implicit simulations of single point incremental forming (SPIF). Substructuring is used to divide the finite element (FE) mesh into several non-overlapping parts. Based on the hypothesis that plastic deformation is

Dislocation Substructures Formed After Fracture of Deformed Polycrystalline Cu-Al Alloys

Science.gov (United States)

Koneva, N. A.; Trishkina, L. I.; Cherkasova, T. V.

2017-08-01

The paper deals with the dislocation substructure of polycrystalline FCC alloys modified by plastic deformation at a distance from the area of the specimen fracture. Observations are performed using the transmission electron microscopy. Cu-Al alloys with grain size ranging from 10 to 240 μm are studied in this paper. The parameters of the dislocation substructure are measured and their variation is determined by the increasing distance from the fracture area. It is shown how the grain size influences these processes. The different dislocation substructures which determine the specimen fracture at a mesocscale level are found herein.

Mass-stiffness substructuring of an elastic metasurface for full transmission beam steering

Science.gov (United States)

Lee, Hyuk; Lee, Jun Kyu; Seung, Hong Min; Kim, Yoon Young

2018-03-01

The metasurface concept has a significant potential due to its novel wavefront-shaping functionalities that can be critically useful for ultrasonic and solid wave-based applications. To achieve the desired functionalities, elastic metasurfaces should cover full 2π phase shift and also acquire full transmission within subwavelength scale. However, they have not been explored much with respect to the elastic regime, because the intrinsic proportionality of mass-stiffness within the continuum elastic media causes an inevitable trade-off between abrupt phase shift and sufficient transmission. Our goal is to engineer an elastic metasurface that can realize an inverse relation between (amplified) effective mass and (weakened) stiffness in order to satisfy full 2π phase shift as well as full transmission. To achieve this goal, we propose a continuum elastic metasurface unit cell that is decomposed into two substructures, namely a mass-tuning substructure with a local dipolar resonator and a stiffness-tuning substructure composed of non-resonant multiply-perforated slits. We demonstrate analytically, numerically, and experimentally that this unique substructured unit cell can satisfy the required phase shift with high transmission. The substructuring enables independent tuning of the elastic properties over a wide range of values. We use a mass-spring model of the proposed continuum unit cell to investigate the working mechanism of the proposed metasurface. With the designed metasurface consisting of substructured unit cells embedded in an aluminum plate, we demonstrate that our metasurface can successfully realize anomalous steering and focusing of in-plane longitudinal ultrasonic beams. The proposed substructuring concept is expected to provide a new principle for the design of general elastic metasurfaces that can be used to efficiently engineer arbitrary wave profiles.

Dislocation-Disclination Substructures Formed in FCC Polycrystals Under Large Plastic Deformations: Evolution and Association with Flow Stress

Science.gov (United States)

Kozlov, É. V.; Koneva, N. A.; Trishkina, L. I.

2014-06-01

The evolution of dislocation substructures formed in polycrystalline Cu-Al and Cu-Mn alloys undergoing large plastic deformations is studied, using transmission electron microscopy. Microband and fragmented substructures are examined. The Al and Mn alloying element concentrations for which the substructures are formed have been found. The mechanisms involved in the formation of the substructures during the substructural evolution in the alloys subjected to deformation have been revealed. Parameters describing the substructures under study have been measured. The dependence of the parameters on the flow stress has been established.

Substructure of Highly Boosted Massive Jets

Energy Technology Data Exchange (ETDEWEB)

Alon, Raz [Weizmann Inst. of Science, Rehovot (Israel)

2012-10-01

Modern particle accelerators enable researchers to study new high energy frontiers which have never been explored before. This realm opens possibilities to further examine known fields such as Quantum Chromodynamics. In addition, it allows searching for new physics and setting new limits on the existence of such. This study examined the substructure of highly boosted massive jets measured by the CDF II detector. Events from 1.96 TeV proton-antiproton collisions at the Fermilab Tevatron Collider were collected out of a total integrated luminosity of 5.95 fb$^{-1}$. They were selected to have at least one jet with transverse momentum above 400 GeV/c. The jet mass, angularity, and planar flow were measured and compared with predictions of perturbative Quantum Chromodynamics, and were found to be consistent with the theory. A search for boosted top quarks was conducted and resulted in an upper limit on the production cross section of such top quarks.

Identifying a new particle with jet substructures

International Nuclear Information System (INIS)

Han, Chengcheng; Kim, Doojin; Kim, Minho; Postech, Pohang

2017-01-01

Here, we investigate a potential of determining properties of a new heavy resonance of mass O(1)TeV which decays to collimated jets via heavy Standard Model intermediary states, exploiting jet substructure techniques. Employing the Z gauge boson as a concrete example for the intermediary state, we utilize a "merged jet" defined by a large jet size to capture the two quarks from its decay. The use of the merged jet bene ts the identification of a Z-induced jet as a single, reconstructed object without any combinatorial ambiguity. We also find that jet substructure procedures may enhance features in some kinematic observables formed with subjet four-momenta extracted from a merged jet. This observation motivates us to feed subjet momenta into the matrix elements associated with plausible hypotheses on the nature of the heavy resonance, which are further processed to construct a matrix element method (MEM)-based observable. For both moderately and highly boosted Z bosons, we demonstrate that the MEM in combination with jet substructure techniques can be a very powerful tool for identifying its physical properties. Finally, we discuss effects from choosing different jet sizes for merged jets and jet-grooming parameters upon the MEM analyses.

Measurement of jet substructure observables in $\\mathrm{t \\bar t}$ events from pp collisions at $\\sqrt{s}=13~\\mathrm{TeV}$

CERN Document Server

CMS Collaboration

2018-01-01

A measurement of differential jet substructure observables is presented using $\\mathrm{t \\bar t}$ lepton+jets events from proton-proton collisions at $\\sqrt{s}=13~\\mathrm{TeV}$ recorded by the CMS experiment at the LHC in 2016 corresponding to an integrated luminosity of $35.9~\\mathrm{fb^{-1}}$. Multiple jet substructure variables, such as the particle multiplicity, width, eccentricity, $p_\\mathrm{T}$ dispersion, N-subjettiness ratios, generalized angularities, and energy correlation functions, are measured for inclusive jets, as well as for identified bottom, light-quark, and gluon jets from the $\\mathrm{t \\bar t}$ final state. The results are unfolded to the stable-particle level and compared to predictions from POWHEG interfaced with PYTHIA 8 and HERWIG 7.1, as well as from SHERPA 2 and DIRE. A reasonable agreement between the data and the Monte Carlo predictions is found. From a comparison of the jet width distribution to the prediction, it is shown that a lower value of the effective strong coupling in t...

QUANTIFYING KINEMATIC SUBSTRUCTURE IN THE MILKY WAY'S STELLAR HALO

International Nuclear Information System (INIS)

Xue Xiangxiang; Zhao Gang; Luo Ali; Rix, Hans-Walter; Bell, Eric F.; Koposov, Sergey E.; Kang, Xi; Liu, Chao; Yanny, Brian; Beers, Timothy C.; Lee, Young Sun; Bullock, James S.; Johnston, Kathryn V.; Morrison, Heather; Rockosi, Constance; Weaver, Benjamin A.

2011-01-01

We present and analyze the positions, distances, and radial velocities for over 4000 blue horizontal-branch (BHB) stars in the Milky Way's halo, drawn from SDSS DR8. We search for position-velocity substructure in these data, a signature of the hierarchical assembly of the stellar halo. Using a cumulative 'close pair distribution' as a statistic in the four-dimensional space of sky position, distance, and velocity, we quantify the presence of position-velocity substructure at high statistical significance among the BHB stars: pairs of BHB stars that are close in position on the sky tend to have more similar distances and radial velocities compared to a random sampling of these overall distributions. We make analogous mock observations of 11 numerical halo formation simulations, in which the stellar halo is entirely composed of disrupted satellite debris, and find a level of substructure comparable to that seen in the actually observed BHB star sample. This result quantitatively confirms the hierarchical build-up of the stellar halo through a signature in phase (position-velocity) space. In detail, the structure present in the BHB stars is somewhat less prominent than that seen in most simulated halos, quite possibly because BHB stars represent an older sub-population. BHB stars located beyond 20 kpc from the Galactic center exhibit stronger substructure than at r gc < 20 kpc.

Inspection of Asian Lacquer Substructures by Terahertz Time-Domain Imaging (THz-TDI)

DEFF Research Database (Denmark)

Dandolo, Corinna Ludovica Koch; Fukunaga, Kaori; Kohzuma, Yoshei

2017-01-01

Lacquering is considered one of the most representative Asian artistic techniques. While the decorative part of lacquerwares is the lacquer itself, their substructures serve as the backbone of the object itself. Very little is known about these hidden substructures. Since lacquerwares are mostly...... by inspecting the substructures of Asian lacquerwares by means of THz time-domain imaging (THz-TDI). Three different kinds of Asian lacquerwares were examined by THz-TDI, and the outcomes have been compared with those obtained by standard X-radiography. THz-TDI provides unique information on lacquerwares...

Analysis of random response of structure with uncertain parameters. Combination of substructure synthesis method and hierarchy method

International Nuclear Information System (INIS)

Iwatsubo, Takuzo; Kawamura, Shozo; Mori, Hiroyuki.

1995-01-01

In this paper, the method to obtain the random response of a structure with uncertain parameters is proposed. The proposed method is a combination of the substructure synthesis method and the hierarchy method. The concept of the proposed method is that the hierarchy equation of each substructure is obtained using the hierarchy method, and the hierarchy equation of the overall structure is obtained using the substructure synthesis method. Using the proposed method, the reduced order hierarchy equation can be obtained without analyzing the original whole structure. After the calculation of the mean square value of response, the reliability analysis can be carried out based on the first passage problem and Poisson's excursion rate. As a numerical example of structure, a simple piping system is considered. The damping constant of the support is considered as the uncertainty parameter. Then the random response is calculated using the proposed method. As a result, the proposed method is useful to analyze the random response in terms of the accuracy, computer storage and calculation time. (author)

Tagging partially reconstructed objects with jet substructure

Energy Technology Data Exchange (ETDEWEB)

Freytsis, Marat, E-mail: freytsis@uoregon.edu [Department of Physics, Harvard University, Cambridge, MA, 02138 (United States); Volansky, Tomer [Raymond and Beverly Sackler School of Physics and Astronomy, Tel-Aviv University, Tel-Aviv 69978 (Israel); Walsh, Jonathan R. [Ernest Orlando Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720 (United States); Berkeley Center for Theoretical Physics, University of California, Berkeley, CA 94720 (United States)

2017-06-10

We present a new tagger which aims at identifying partially reconstructed objects, in which only some of the constituents are collected in a single jet. As an example, we focus on top decays in which either part of the hadronically decaying W or the b jet is soft or falls outside of the top jet cone. We construct an observable to identify remnant substructure from the decay and employ aggressive jet grooming to reject QCD backgrounds. The tagger is complementary to existing ones and works well in the intermediate boost regime where jet substructure techniques usually fail. It is anticipated that a similar tagger can be used to identify non-QCD hadronic jets, such as those expected from hidden valleys.

Tagging partially reconstructed objects with jet substructure

International Nuclear Information System (INIS)

Freytsis, Marat; Volansky, Tomer; Walsh, Jonathan R.

2017-01-01

We present a new tagger which aims at identifying partially reconstructed objects, in which only some of the constituents are collected in a single jet. As an example, we focus on top decays in which either part of the hadronically decaying W or the b jet is soft or falls outside of the top jet cone. We construct an observable to identify remnant substructure from the decay and employ aggressive jet grooming to reject QCD backgrounds. The tagger is complementary to existing ones and works well in the intermediate boost regime where jet substructure techniques usually fail. It is anticipated that a similar tagger can be used to identify non-QCD hadronic jets, such as those expected from hidden valleys.

Tagging partially reconstructed objects with jet substructure

Science.gov (United States)

Freytsis, Marat; Volansky, Tomer; Walsh, Jonathan R.

2017-06-01

We present a new tagger which aims at identifying partially reconstructed objects, in which only some of the constituents are collected in a single jet. As an example, we focus on top decays in which either part of the hadronically decaying W or the b jet is soft or falls outside of the top jet cone. We construct an observable to identify remnant substructure from the decay and employ aggressive jet grooming to reject QCD backgrounds. The tagger is complementary to existing ones and works well in the intermediate boost regime where jet substructure techniques usually fail. It is anticipated that a similar tagger can be used to identify non-QCD hadronic jets, such as those expected from hidden valleys.

Inspection of Asian Lacquer Substructures by Terahertz Time-Domain Imaging (THz-TDI)

Science.gov (United States)

Dandolo, Corinna Ludovica Koch; Fukunaga, Kaori; Kohzuma, Yoshei; Kiriyama, Kyoko; Matsuda, Kazutaka; Jepsen, Peter Uhd

2017-04-01

Lacquering is considered one of the most representative Asian artistic techniques. While the decorative part of lacquerwares is the lacquer itself, their substructures serve as the backbone of the object itself. Very little is known about these hidden substructures. Since lacquerwares are mostly composed of organic materials, such as urushi, wood, carbon black, and fabrics which are very X-ray transparent, standard X-ray radiography has some problems in achieving clear X-ray radiographic images. Therefore, we wanted to contribute to the understanding of the lacquer manufacturing technique by inspecting the substructures of Asian lacquerwares by means of THz time-domain imaging (THz-TDI). Three different kinds of Asian lacquerwares were examined by THz-TDI, and the outcomes have been compared with those obtained by standard X-radiography. THz-TDI provides unique information on lacquerwares substructures, aiding in the comprehension of the manufacturing technology yielding to these precious artefacts.

Knowledge-based Fragment Binding Prediction

Science.gov (United States)

Tang, Grace W.; Altman, Russ B.

2014-01-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

Misoriented dislocation substructures and the fracture of polycrystalline Cu-Al alloys

Science.gov (United States)

Koneva, N. A.; Trishkina, L. I.; Cherkasova, T. V.; Kozlov, E. V.

2016-10-01

The evolution of the dislocation substructure in polycrystalline Cu-Al alloys with various grain sizes is studied during deformation to failure. A relation between the fracture of the alloys and the forming misorientation dislocation substructures is revealed. Microcracks in the alloy are found to form along grain boundaries and the boundaries of misoriented dislocation cells and microtwins.

Dynamic Analysis of Jacket Substructure for Offshore Wind Turbine Generators under Extreme Environmental Conditions

Directory of Open Access Journals (Sweden)

Wen-Jeng Lai

2016-10-01

Full Text Available In order to develop dynamic analysis technologies regarding the design of offshore wind turbine generators (OWTGs, a special project called Offshore Code Comparison Collaboration Continuation (OC4 was conducted by IEA (International Energy Agency in 2010. A similar project named INER-OC4 has been performed by the Institute of Nuclear Energy Research (INER to develop the OWTG technologies of Taiwan. Since the jacket substructure will be applied to Taiwan OWTGs before 2020, the INER-OC4 project has been devoted to the design and analysis of jacket support structure. In this work, the preliminary result of INER-OC4 is presented. A simplified analysis procedure for jacket support structure has been proposed. Both of the NREL (National Renewable Energy Laboratory 5 MW OWTG FAST model and OC4 jacket substructure model have been built and analyzed under severe design load cases (DLCs of IEC (International Electrotechnical commission 61400-3. Simulation results of six severe DLCs are performed in this work and the results are in agreement with the requirements of API (American Petroleum Institute and NORSOK (Norwegian Petroleum Industry standards.

MAPPING THE GALACTIC HALO. VIII. QUANTIFYING SUBSTRUCTURE

International Nuclear Information System (INIS)

Starkenburg, Else; Helmi, Amina; Van Woerden, Hugo; Morrison, Heather L.; Harding, Paul; Frey, Lucy; Oravetz, Dan; Mateo, Mario; Dohm-Palmer, R. C.; Olszewski, Edward W.; Sivarani, Thirupathi; Norris, John E.; Freeman, Kenneth C.; Shectman, Stephen A.

2009-01-01

We have measured the amount of kinematic substructure in the Galactic halo using the final data set from the Spaghetti project, a pencil-beam high-latitude sky survey. Our sample contains 101 photometrically selected and spectroscopically confirmed giants with accurate distance, radial velocity, and metallicity information. We have developed a new clustering estimator: the '4distance' measure, which when applied to our data set leads to the identification of one group and seven pairs of clumped stars. The group, with six members, can confidently be matched to tidal debris of the Sagittarius dwarf galaxy. Two pairs match the properties of known Virgo structures. Using models of the disruption of Sagittarius in Galactic potentials with different degrees of dark halo flattening, we show that this favors a spherical or prolate halo shape, as demonstrated by Newberg et al. using the Sloan Digital Sky Survey data. One additional pair can be linked to older Sagittarius debris. We find that 20% of the stars in the Spaghetti data set are in substructures. From comparison with random data sets, we derive a very conservative lower limit of 10% to the amount of substructure in the halo. However, comparison to numerical simulations shows that our results are also consistent with a halo entirely built up from disrupted satellites, provided that the dominating features are relatively broad due to early merging or relatively heavy progenitor satellites.

Stick-slip substructure in rapid tape peeling

KAUST Repository

Thoroddsen, Sigurdur T.

2010-10-15

The peeling of adhesive tape is known to proceed with a stick-slip mechanism and produces a characteristic ripping sound. The peeling also produces light and when peeled in a vacuum, even X-rays have been observed, whose emissions are correlated with the slip events. Here we present direct imaging of the detachment zone when Scotch tape is peeled off at high speed from a solid surface, revealing a highly regular substructure, during the slip phase. The typical 4-mm-long slip region has a regular substructure of transverse 220 μm wide slip bands, which fracture sideways at speeds over 300 m/s. The fracture tip emits waves into the detached section of the tape at ∼100 m/s, which promotes the sound, so characteristic of this phenomenon.

Stick-slip substructure in rapid tape peeling

KAUST Repository

Thoroddsen, Sigurdur T; Nguyen, H. D.; Takehara, K.; Etoh, T. G.

2010-01-01

The peeling of adhesive tape is known to proceed with a stick-slip mechanism and produces a characteristic ripping sound. The peeling also produces light and when peeled in a vacuum, even X-rays have been observed, whose emissions are correlated with the slip events. Here we present direct imaging of the detachment zone when Scotch tape is peeled off at high speed from a solid surface, revealing a highly regular substructure, during the slip phase. The typical 4-mm-long slip region has a regular substructure of transverse 220 μm wide slip bands, which fracture sideways at speeds over 300 m/s. The fracture tip emits waves into the detached section of the tape at ∼100 m/s, which promotes the sound, so characteristic of this phenomenon.

Earthquake analysis of structures including structure-soil interaction by a substructure method

International Nuclear Information System (INIS)

Chopra, A.K.; Guttierrez, J.A.

1977-01-01

A general substructure method for analysis of response of nuclear power plant structures to earthquake ground motion, including the effects of structure-soil interaction, is summarized. The method is applicable to complex structures idealized as finite element systems and the soil region treated as either a continuum, for example as a viscoelastic halfspace, or idealized as a finite element system. The halfspace idealization permits reliable analysis for sites where essentially similar soils extend to large depths and there is no rigid boundary such as soil-rock interface. For sites where layers of soft soil are underlain by rock at shallow depth, finite element idealization of the soil region is appropriate; in this case, the direct and substructure methods would lead to equivalent results but the latter provides the better alternative. Treating the free field motion directly as the earthquake input in the substructure method eliminates the deconvolution calculations and the related assumption -regarding type and direction of earthquake waves- required in the direct method. The substructure method is computationally efficient because the two substructures-the structure and the soil region- are analyzed separately; and, more important, it permits taking advantage of the important feature that response to earthquake ground motion is essentially contained in the lower few natural modes of vibration of the structure on fixed base. For sites where essentially similar soils extend to large depths and there is no obvious rigid boundary such as a soil-rock interface, numerical results for earthquake response of a nuclear reactor structure are presented to demonstrate that the commonly used finite element method may lead to unacceptable errors; but the substructure method leads to reliable results

THE UNORTHODOX ORBITS OF SUBSTRUCTURE HALOS

NARCIS (Netherlands)

Ludlow, Aaron D.; Navarro, Julio F.; Springel, Volker; Jenkins, Adrian; Frenk, Carlos S.; Helmi, Amina

2009-01-01

We use a suite of cosmological N-body simulations to study the properties of substructure halos (subhalos) in galaxy-sized cold dark matter halos. We extend prior work on the subject by considering the whole population of subhalos physically associated with the main system. These are defined as

Systematic benchmark of substructure search in molecular graphs - From Ullmann to VF2

Directory of Open Access Journals (Sweden)

Ehrlich Hans-Christian

2012-07-01

Full Text Available Abstract Background Searching for substructures in molecules belongs to the most elementary tasks in cheminformatics and is nowadays part of virtually every cheminformatics software. The underlying algorithms, used over several decades, are designed for the application to general graphs. Applied on molecular graphs, little effort has been spend on characterizing their performance. Therefore, it is not clear how current substructure search algorithms behave on such special graphs. One of the main reasons why such an evaluation was not performed in the past was the absence of appropriate data sets. Results In this paper, we present a systematic evaluation of Ullmann’s and the VF2 subgraph isomorphism algorithms on molecular data. The benchmark set consists of a collection of 1235 SMARTS substructure expressions and selected molecules from the ZINC database. The benchmark evaluates substructures search times for complete database scans as well as individual substructure-molecule pairs. In detail, we focus on the influence of substructure formulation and size, the impact of molecule size, and the ability of both algorithms to be used on multiple cores. Conclusions The results show a clear superiority of the VF2 algorithm in all test scenarios. In general, both algorithms solve most instances in less than one millisecond, which we consider to be acceptable. Still, in direct comparison, the VF2 is most often several folds faster than Ullmann’s algorithm. Additionally, Ullmann’s algorithm shows a surprising number of run time outliers.

Structural analysis and optimization procedure of the TFTR device substructure

International Nuclear Information System (INIS)

Driesen, G.

1975-10-01

A structural evaluation of the TFTR device substructure is performed in order to verify the feasibility of the proposed design concept as well as to establish a design optimization procedure for minimizing the material and fabrication cost of the substructure members. A preliminary evaluation of the seismic capability is also presented. The design concept on which the analysis is based is consistent with that described in the Conceptual Design Status Briefing report dated June 18, 1975

Some sub-structures of many-particle correlation in nuclei

Energy Technology Data Exchange (ETDEWEB)

Chang, C; Chao, W; Li, K

1977-01-01

The coherent structures of two phonons were proposed as the sub-structure ..cap alpha..' of four-particle clusters for the light nuclei. In the same way the sub-structure ..beta../sup +/ of four-hole clusters can also be given. Based on this the sub-structures between particle clusters and hole clusters in /sup 16/O and /sup 18/O were chosen as examples for investigation. It is found that there is a very strong repulsive force between them. Therefore the loose structure between particle cluster and hole cluster is of the lowest energy state. In this way, the deformations of these states were explained from the microscopic structures. Moreover, these structures can coherently strengthen the E2 transition. Further in order to study the particle correlation in the medium nuclei, the L-S coupling coherent structure is extended to the pseudo L-S coupling coherent structure and the expressions are given in the j-j coupling representation. Some preliminary analyses are made for the nuclei around /sup 56/Ni by using these structures.

Jet Substructure at the Tevatron and LHC: New results, new tools, new benchmarks

CERN Document Server

Altheimer, A; Asquith, L; Brooijmans, G; Butterworth, J; Campanelli, M; Chapleau, B; Cholakian, A E; Chou, J P; Dasgupta, M; Davison, A; Dolen, J; Ellis, S D; Essig, R; Fan, J J; Field, R; Fregoso, A; Gallicchio, J; Gershtein, Y; Gomes, A; Haas, A; Halkiadakis, E; Halyo, V; Hoeche, S; Hook, A; Hornig, A; Huang, P; Izaguirre, E; Jankowiak, M; Kribs, G; Krohn, D; Larkoski, A J; Lath, A; Lee, C; Lee, S J; Loch, P; Maksimovic, P; Martinez, M; Miller, D W; Plehn, T; Prokofiev, K; Rahmat, R; Rappoccio, S; Safonov, A; Salam, G P; Schumann, S; Schwartz, M D; Schwartzman, A; Seymour, M; Shao, J; Sinervo, P; Son, M; Soper, D E; Spannowsky, M; Stewart, I W; Strassler, M; Strauss, E; Takeuchi, M; Thaler, J; Thomas, S; Tweedie, B; Vasquez Sierra, R; Vermilion, C K; Villaplana, M; Vos, M; Wacker, J; Walker, D; Walsh, J R; Wang, L-T; Wilbur, S; Yavin, I; Zhu, W

2012-01-01

In this report we review recent theoretical progress and the latest experimental results in jet substructure from the Tevatron and the LHC. We review the status of and outlook for calculation and simulation tools for studying jet substructure. Following up on the report of the Boost 2010 workshop, we present a new set of benchmark comparisons of substructure techniques, focusing on the set of variables and grooming methods that are collectively known as "top taggers". To facilitate further exploration, we have attempted to collect, harmonise, and publish software implementations of these techniques.

DARK MATTER SUBSTRUCTURE DETECTION USING SPATIALLY RESOLVED SPECTROSCOPY OF LENSED DUSTY GALAXIES

International Nuclear Information System (INIS)

Hezaveh, Yashar; Holder, Gilbert; Dalal, Neal; Kuhlen, Michael; Marrone, Daniel; Murray, Norman; Vieira, Joaquin

2013-01-01

We investigate how strong lensing of dusty, star-forming galaxies (DSFGs) by foreground galaxies can be used as a probe of dark matter halo substructure. We find that spatially resolved spectroscopy of lensed sources allows dramatic improvements to measurements of lens parameters. In particular, we find that modeling of the full, three-dimensional (angular position and radial velocity) data can significantly facilitate substructure detection, increasing the sensitivity of observables to lower mass subhalos. We carry out simulations of lensed dusty sources observed by early ALMA (Cycle 1) and use a Fisher matrix analysis to study the parameter degeneracies and mass detection limits of this method. We find that even with conservative assumptions, it is possible to detect galactic dark matter subhalos of ∼10 8 M ☉ with high significance in most lensed DSFGs. Specifically, we find that in typical DSFG lenses, there is a ∼55% probability of detecting a substructure with M > 10 8 M ☉ with more than 5σ detection significance in each lens, if the abundance of substructure is consistent with previous lensing results. The full ALMA array, with its significantly enhanced sensitivity and resolution, should improve these estimates considerably. Given the sample of ∼100 lenses provided by surveys such as the South Pole Telescope, our understanding of dark matter substructure in typical galaxy halos is poised to improve dramatically over the next few years.

The importance of calorimetry for highly-boosted jet substructure

Energy Technology Data Exchange (ETDEWEB)

Coleman, Evan [Brown U.; Freytsis, Marat [Oregon U.; Hinzmann, Andreas [Hamburg U.; Narain, Meenakshi [Brown U.; Thaler, Jesse [MIT, Cambridge, CTP; Tran, Nhan [Fermilab; Vernieri, Caterina [Fermilab

2017-09-25

Jet substructure techniques are playing an essential role in exploring the TeV scale at the Large Hadron Collider (LHC), since they facilitate the efficient reconstruction and identification of highly-boosted objects. Both for the LHC and for future colliders, there is a growing interest in using jet substructure methods based only on charged-particle information. The reason is that silicon-based tracking detectors offer excellent granularity and precise vertexing, which can improve the angular resolution on highly-collimated jets and mitigate the impact of pileup. In this paper, we assess how much jet substructure performance degrades by using track-only information, and we demonstrate physics contexts in which calorimetry is most beneficial. Specifically, we consider five different hadronic final states - W bosons, Z bosons, top quarks, light quarks, gluons - and test the pairwise discrimination power with a multi-variate combination of substructure observables. In the idealized case of perfect reconstruction, we quantify the loss in discrimination performance when using just charged particles compared to using all detected particles. We also consider the intermediate case of using charged particles plus photons, which provides valuable information about neutral pions. In the more realistic case of a segmented calorimeter, we assess the potential performance gains from improving calorimeter granularity and resolution, comparing a CMS-like detector to more ambitious future detector concepts. Broadly speaking, we find large performance gains from neutral-particle information and from improved calorimetry in cases where jet mass resolution drives the discrimination power, whereas the gains are more modest if an absolute mass scale calibration is not required.

CHEMTRAN and the Interconversion of Chemical Substructure Systems

Science.gov (United States)

Granito, Charles E.

1973-01-01

The need for the interconversion of chemical substructure systems is discussed and CHEMTRAN, a new service, designed especially for creating interconversion programs, is introduced. (7 references) (Author)

Substructure based modeling of nickel single crystals cycled at low plastic strain amplitudes

Science.gov (United States)

Zhou, Dong

In this dissertation a meso-scale, substructure-based, composite single crystal model is fully developed from the simple uniaxial model to the 3-D finite element method (FEM) model with explicit substructures and further with substructure evolution parameters, to simulate the completely reversed, strain controlled, low plastic strain amplitude cyclic deformation of nickel single crystals. Rate-dependent viscoplasticity and Armstrong-Frederick type kinematic hardening rules are applied to substructures on slip systems in the model to describe the kinematic hardening behavior of crystals. Three explicit substructure components are assumed in the composite single crystal model, namely "loop patches" and "channels" which are aligned in parallel in a "vein matrix," and persistent slip bands (PSBs) connected in series with the vein matrix. A magnetic domain rotation model is presented to describe the reverse magnetostriction of single crystal nickel. Kinematic hardening parameters are obtained by fitting responses to experimental data in the uniaxial model, and the validity of uniaxial assumption is verified in the 3-D FEM model with explicit substructures. With information gathered from experiments, all control parameters in the model including hardening parameters, volume fraction of loop patches and PSBs, and variation of Young's modulus etc. are correlated to cumulative plastic strain and/or plastic strain amplitude; and the whole cyclic deformation history of single crystal nickel at low plastic strain amplitudes is simulated in the uniaxial model. Then these parameters are implanted in the 3-D FEM model to simulate the formation of PSB bands. A resolved shear stress criterion is set to trigger the formation of PSBs, and stress perturbation in the specimen is obtained by several elements assigned with PSB material properties a priori. Displacement increment, plastic strain amplitude control and overall stress-strain monitor and output are carried out in the user

Improving jet substructure performance in ATLAS using Track-CaloClusters

CERN Document Server

The ATLAS collaboration

2017-01-01

Jet substructure techniques play a critical role in ATLAS in searches for new physics, are increasingly important in measurements of the Standard Model, and are being utilized in the trigger. To date, ATLAS has mostly focused on the use of calorimeter-based jet substructure, which works well for jets initiated by particles with low to moderate boost, but which lacks the angular resolution needed to resolve the desired substructure in the highly-boosted regime. We present a novel approach designed to mitigate the calorimeter angular resolution limitations, thus providing superior performance to prior methods. Similarly to the previously developed combined mass technique, the superior angular resolution of the tracker is combined with information from the calorimeters. However, the new method is fundamentally different, as it correlates low-level objects such as tracks and individual energy deposits in the calorimeter, before running any jet finding algorithms. The resulting objects are used as inputs to jet re...

Substructures in DAFT/FADA survey clusters based on XMM and optical data

Science.gov (United States)

Durret, F.; DAFT/FADA Team

2014-07-01

The DAFT/FADA survey was initiated to perform weak lensing tomography on a sample of 90 massive clusters in the redshift range [0.4,0.9] with HST imaging available. The complementary deep multiband imaging constitutes a high quality imaging data base for these clusters. In X-rays, we have analysed the XMM-Newton and/or Chandra data available for 32 clusters, and for 23 clusters we fit the X-ray emissivity with a beta-model and subtract it to search for substructures in the X-ray gas. This study was coupled with a dynamical analysis for the 18 clusters with at least 15 spectroscopic galaxy redshifts in the cluster range, based on a Serna & Gerbal (SG) analysis. We detected ten substructures in eight clusters by both methods (X-rays and SG). The percentage of mass included in substructures is found to be roughly constant with redshift, with values of 5-15%. Most of the substructures detected both in X-rays and with the SG method are found to be relatively recent infalls, probably at their first cluster pericenter approach.

Prediction of the vibroacoustic behavior of a submerged shell with non-axisymmetric internal substructures by a condensed transfer function method

Science.gov (United States)

Meyer, V.; Maxit, L.; Guyader, J.-L.; Leissing, T.

2016-01-01

The vibroacoustic behavior of axisymmetric stiffened shells immersed in water has been intensively studied in the past. On the contrary, little attention has been paid to the modeling of these shells coupled to non-axisymmetric internal frames. Indeed, breaking the axisymmetry couples the circumferential orders of the Fourier series and considerably increases the computational costs. In order to tackle this issue, we propose a sub-structuring approach called the Condensed Transfer Function (CTF) method that will allow assembling a model of axisymmetric stiffened shell with models of non-axisymmetric internal frames. The CTF method is developed in the general case of mechanical subsystems coupled along curves. A set of orthonormal functions called condensation functions, which depend on the curvilinear abscissa along the coupling line, is considered. This set is then used as a basis for approximating and decomposing the displacements and the applied forces at the line junctions. Thanks to the definition and calculation of condensed transfer functions for each uncoupled subsystem and by using the superposition principle for passive linear systems, the behavior of the coupled subsystems can be deduced. A plane plate is considered as a test case to study the convergence of the method with respect to the type and the number of condensation functions taken into account. The CTF method is then applied to couple a submerged non-periodically stiffened shell described using the Circumferential Admittance Approach (CAA) with internal substructures described by Finite Element Method (FEM). The influence of non-axisymmetric internal substructures can finally be studied and it is shown that it tends to increase the radiation efficiency of the shell and can modify the vibrational and acoustic energy distribution.

DARK MATTER SUBSTRUCTURE DETECTION USING SPATIALLY RESOLVED SPECTROSCOPY OF LENSED DUSTY GALAXIES

Energy Technology Data Exchange (ETDEWEB)

Hezaveh, Yashar; Holder, Gilbert [Department of Physics, McGill University, 3600 Rue University, Montreal, Quebec H3A 2T8 (Canada); Dalal, Neal [Astronomy Department, University of Illinois at Urbana-Champaign, 1002 West Green Street, Urbana, IL 61801 (United States); Kuhlen, Michael [Theoretical Astrophysics Center, University of California, Berkeley, CA 94720 (United States); Marrone, Daniel [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Murray, Norman [CITA, University of Toronto, 60 St. George Street, Toronto, ON M5S 3H8 (Canada); Vieira, Joaquin [California Institute of Technology, 1200 East California Blvd, MC 249-17, Pasadena, CA 91125 (United States)

2013-04-10

We investigate how strong lensing of dusty, star-forming galaxies (DSFGs) by foreground galaxies can be used as a probe of dark matter halo substructure. We find that spatially resolved spectroscopy of lensed sources allows dramatic improvements to measurements of lens parameters. In particular, we find that modeling of the full, three-dimensional (angular position and radial velocity) data can significantly facilitate substructure detection, increasing the sensitivity of observables to lower mass subhalos. We carry out simulations of lensed dusty sources observed by early ALMA (Cycle 1) and use a Fisher matrix analysis to study the parameter degeneracies and mass detection limits of this method. We find that even with conservative assumptions, it is possible to detect galactic dark matter subhalos of {approx}10{sup 8} M{sub Sun} with high significance in most lensed DSFGs. Specifically, we find that in typical DSFG lenses, there is a {approx}55% probability of detecting a substructure with M > 10{sup 8} M{sub Sun} with more than 5{sigma} detection significance in each lens, if the abundance of substructure is consistent with previous lensing results. The full ALMA array, with its significantly enhanced sensitivity and resolution, should improve these estimates considerably. Given the sample of {approx}100 lenses provided by surveys such as the South Pole Telescope, our understanding of dark matter substructure in typical galaxy halos is poised to improve dramatically over the next few years.

Smart variations: Functional substructures for part compatibility

KAUST Repository

Zheng, Youyi

2013-05-01

As collections of 3D models continue to grow, reusing model parts allows generation of novel model variations. Naïvely swapping parts across models, however, leads to implausible results, especially when mixing parts across different model families. Hence, the user has to manually ensure that the final model remains functionally valid. We claim that certain symmetric functional arrangements (sFarr-s), which are special arrangements among symmetrically related substructures, bear close relation to object functions. Hence, we propose a purely geometric approach based on such substructures to match, replace, and position triplets of parts to create non-trivial, yet functionally plausible, model variations. We demonstrate that starting even from a small set of models such a simple geometric approach can produce a diverse set of non-trivial and plausible model variations. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

A finite element based substructuring procedure for design analysis of large smart structural systems

International Nuclear Information System (INIS)

Ashwin, U; Raja, S; Dwarakanathan, D

2009-01-01

A substructuring based design analysis procedure is presented for large smart structural system using the Craig–Bampton method. The smart structural system is distinctively characterized as an active substructure, modelled as a design problem, and a passive substructure, idealized as an analysis problem. Furthermore, a novel thought has been applied by introducing the electro–elastic coupling into the reduction scheme to solve the global structural control problem in a local domain. As an illustration, a smart composite box beam with surface bonded actuators/sensors is considered, and results of the local to global control analysis are presented to show the potential use of the developed procedure. The present numerical scheme is useful for optimally designing the active substructures to study their locations, coupled structure–actuator interaction and provide a solution to the global design of large smart structural systems

Improving corrosion resistance of post-tensioned substructures emphasizing high performance grouts

Science.gov (United States)

Schokker, Andrea Jeanne

The use of post-tensioning in bridges can provide durability and structural benefits to the system while expediting the construction process. When post-tensioning is combined with precast elements, traffic interference can be greatly reduced through rapid construction. Post-tensioned concrete substructure elements such as bridge piers, hammerhead bents, and straddle bents have become more prevalent in recent years. Chloride induced corrosion of steel in concrete is one of the most costly forms of corrosion each year. Coastal substructure elements are exposed to seawater by immersion or spray, and inland bridges may also be at risk due to the application of deicing salts. Corrosion protection of the post-tensioning system is vital to the integrity of the structure because loss of post-tensioning can result in catastrophic failure. Documentation for durability design of the grout, ducts, and anchorage systems is very limited. The objective of this research is to evaluate the effectiveness of corrosion protection measures for post-tensioned concrete substructures by designing and testing specimens representative of typical substructure elements using state-of-the-art practices in aggressive chloride exposure environments. This was accomplished through exposure testing of twenty-seven large-scale beam specimens and ten large-scale column specimens. High performance grout for post-tensioning tendon injection was also developed through a series of fresh property tests, accelerated exposure tests, and a large-scale pumping test to simulate field conditions. A high performance fly ash grout was developed for applications with small vertical rises, and a high performance anti-bleed grout was developed for applications involving large vertical rises such as tall bridge piers. Long-term exposure testing of the beam and column specimens is ongoing, but preliminary findings indicate increased corrosion protection with increasing levels of post-tensioning, although traditional

DASS: efficient discovery and p-value calculation of substructures in unordered data.

Science.gov (United States)

Hollunder, Jens; Friedel, Maik; Beyer, Andreas; Workman, Christopher T; Wilhelm, Thomas

2007-01-01

Pattern identification in biological sequence data is one of the main objectives of bioinformatics research. However, few methods are available for detecting patterns (substructures) in unordered datasets. Data mining algorithms mainly developed outside the realm of bioinformatics have been adapted for that purpose, but typically do not determine the statistical significance of the identified patterns. Moreover, these algorithms do not exploit the often modular structure of biological data. We present the algorithm DASS (Discovery of All Significant Substructures) that first identifies all substructures in unordered data (DASS(Sub)) in a manner that is especially efficient for modular data. In addition, DASS calculates the statistical significance of the identified substructures, for sets with at most one element of each type (DASS(P(set))), or for sets with multiple occurrence of elements (DASS(P(mset))). The power and versatility of DASS is demonstrated by four examples: combinations of protein domains in multi-domain proteins, combinations of proteins in protein complexes (protein subcomplexes), combinations of transcription factor target sites in promoter regions and evolutionarily conserved protein interaction subnetworks. The program code and additional data are available at http://www.fli-leibniz.de/tsb/DASS

Revealing dark matter substructure with anisotropies in the diffuse gamma-ray background

International Nuclear Information System (INIS)

Siegal-Gaskins, Jennifer M

2008-01-01

The majority of gamma-ray emission from galactic dark matter annihilation is likely to be detected as a contribution to the diffuse gamma-ray background. I show that dark matter substructure in the halo of the Galaxy induces characteristic anisotropies in the diffuse background that could be used to determine the small-scale dark matter distribution. I calculate the angular power spectrum of the emission from dark matter substructure for several models of the subhalo population and show that features in the power spectrum can be used to infer the presence of substructure. The shape of the power spectrum is largely unaffected by the subhalo radial distribution and mass function, and for many scenarios I find that a measurement of the angular power spectrum by Fermi will be able to constrain the abundance of substructure. An anti-biased subhalo radial distribution is shown to produce emission that differs significantly in intensity and large-scale angular dependence from that of a subhalo distribution which traces the smooth dark matter halo, potentially impacting the detectability of the dark matter signal for a variety of targets and methods

Revealing dark matter substructure with anisotropies in the diffuse gamma-ray background

Energy Technology Data Exchange (ETDEWEB)

Siegal-Gaskins, Jennifer M, E-mail: jsg@kicp.uchicago.edu [Kavli Institute for Cosmological Physics and Department of Physics, University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637 (United States)

2008-10-15

The majority of gamma-ray emission from galactic dark matter annihilation is likely to be detected as a contribution to the diffuse gamma-ray background. I show that dark matter substructure in the halo of the Galaxy induces characteristic anisotropies in the diffuse background that could be used to determine the small-scale dark matter distribution. I calculate the angular power spectrum of the emission from dark matter substructure for several models of the subhalo population and show that features in the power spectrum can be used to infer the presence of substructure. The shape of the power spectrum is largely unaffected by the subhalo radial distribution and mass function, and for many scenarios I find that a measurement of the angular power spectrum by Fermi will be able to constrain the abundance of substructure. An anti-biased subhalo radial distribution is shown to produce emission that differs significantly in intensity and large-scale angular dependence from that of a subhalo distribution which traces the smooth dark matter halo, potentially impacting the detectability of the dark matter signal for a variety of targets and methods.

THEORY AND SIMULATIONS OF REFRACTIVE SUBSTRUCTURE IN RESOLVED SCATTER-BROADENED IMAGES

Energy Technology Data Exchange (ETDEWEB)

Johnson, Michael D. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Gwinn, Carl R., E-mail: mjohnson@cfa.harvard.edu [Department of Physics, University of California, Santa Barbara, CA 93106 (United States)

2015-06-01

At radio wavelengths, scattering in the interstellar medium distorts the appearance of astronomical sources. Averaged over a scattering ensemble, the result is a blurred image of the source. However, Narayan and Goodman and Goodman and Narayan showed that for an incomplete average, scattering introduces refractive substructure in the image of a point source that is both persistent and wideband. We show that this substructure is quenched but not smoothed by an extended source. As a result, when the scatter-broadening is comparable to or exceeds the unscattered source size, the scattering can introduce spurious compact features into images. In addition, we derive efficient strategies to numerically compute realistic scattered images, and we present characteristic examples from simulations. Our results show that refractive substructure is an important consideration for ongoing missions at the highest angular resolutions, and we discuss specific implications for RadioAstron and the Event Horizon Telescope.

Spatial Substructure in the M87 Globular Cluster System

Science.gov (United States)

Feng, Yuting; Zhang, Yunhao; Guhathakurta, Puragra; Peng, Eric; Lim, Sungsoon

2018-01-01

Based on the observation of Next Generation Virgo Cluster Survey (NGVS) project, we obtained the u,g,r,i,z and Ks band photometric information of all the objects in the 2 degree × 2 degree area (Pilot Region) around M87, the major subcluster of Virgo. By adapting an Extreme Deconvolution method, which classifies objects into Globular Clusters (GCs), galaxies and foreground stars with their color and morphology data, we got a purer-than-ever GC distribution map with a depth to gmag=25 in Pilot Region. After masking galaxy GCs, smoothing with a 10arcmin Gaussian kernel and performing a flat field correction, we show the GC density map of M87, and got a good sersic fitting of GC radial distribution with a sersic index~2.2 in the central ellipse part (45arcmin semi major axis area of M87). We quantitatively compared our GC sample with a substructure-free mock data set, which was generated from the smoothed density map as well as the sersic fitting, by calculating the 2 point correlation function (TPCF) value in different parts of the map. After separately performing such comparison with mocks based on different galaxy masking radii which vary from 4 times g band effective radius to 10, we found signals of remarkable spatial enhancement in certain directions in the central ellipse of M87, as well as halo substructures shown as lumpiness and holes in the outer region. We present the estimated scales of these substructures from the TPCF results, and, managed to locate them with a statistical analysis of the pixelized GC map. Apart from all results listed above, we discuss the constant, extra-galactic substructure signal at a scale of ~3kpc, which does not diminish with masking sizes, as the evidence of merging and accretion history of M87.

Observations of Cluster Substructure using Weakly Lensed Sextupole Moments

Energy Technology Data Exchange (ETDEWEB)

Irwin, John

2003-08-01

Since dark matter clusters and groups may have substructure, we have examined the sextupole content of Hubble images looking for a curvature signature in background galaxies that would arise from galaxy-galaxy lensing. We describe techniques for extracting and analyzing sextupole and higher weakly lensed moments. Indications of substructure, via spatial clumping of curved background galaxies, were observed in the image of CL0024 and then surprisingly in both Hubble deep fields. We estimate the dark cluster masses in the deep field. Alternatives to a lensing hypothesis appear improbable, but better statistics will be required to exclude them conclusively. Observation of sextupole moments would then provide a means to measure dark matter structure on smaller length scales than heretofore.

Rapid bridge construction technology : precast elements for substructures.

Science.gov (United States)

2011-06-01

The goal of this research was to propose an alternate system of precast bridge substructures which can : substitute for conventional cast in place systems in Wisconsin to achieve accelerated construction. : Three types of abutment modules (hollow wal...

Improving jet substructure in ATLAS using unified track and calorimeter information

CERN Document Server

Schramm, Steven; The ATLAS collaboration

2017-01-01

Jet substructure techniques play a critical role in ATLAS in searches for new physics, are increasingly important in measurements of the Standard Model, and are being utilized in the trigger. To date, ATLAS has mostly focused on the use of calorimeter-based jet substructure, which works well for jets initiated by particles with low to moderate boost, but which lacks the angular resolution needed to resolve the desired substructure in the highly-boosted regime. We will present a novel approach designed to mitigate the calorimeter angular resolution limitations, thus providing superior performance to prior methods. Similar to previous methods, the superior angular resolution of the tracker is combined with information from the calorimeters. However, the new method is fundamentally different, as it correlates low-level objects as tracks and individual energy deposits in the calorimeter, before running any jet finding algorithms. The resulting objects are used as inputs to jet reconstruction, and in turn result i...

Modeling of rail track substructure linear elastic coupling

Science.gov (United States)

2015-09-30

Most analyses of rail dynamics neglect contribution of the soil, or treat it in a very simple manner such as using spring elements. This can cause accuracy issues in examining dynamics for passenger comfort, derailment, substructure analysis, or othe...

New Developments for Jet Substructure Reconstruction in CMS

CERN Document Server

CMS Collaboration

2017-01-01

We present Monte Carlo based studies showcasing several developments for jet substructure reconstruction in CMS. This include Quark/Gluon tagging algorithms using Boosted Decision Trees and Deep Neural Networks, the XCone jet clustering algorithm and the Boosted Event Shape Tagger (BEST).

Towards an understanding of the correlations in jet substructure

Energy Technology Data Exchange (ETDEWEB)

Adams, D. [Brookhaven National Laboratory, Upton, NY (United States); Arce, A. [Duke University, Durham, NC (United States); Asquith, L. [University of Sussex, Brighton (United Kingdom); Backovic, M. [CP3, Universite catholique du Louvain, Louvain-la-Neuve (Belgium); Barillari, T.; Menke, S. [Max-Planck-Institute fuer Physik, Munich (Germany); Berta, P. [Charles University in Prague, FMP, Prague (Czech Republic); Bertolini, D. [University of California, Berkeley, CA (United States); Buckley, A.; Ferrando, J.; Pollard, C. [University of Glasgow, G12 8QQ (United Kingdom); Butterworth, J.; Cooper, B. [University College London, WC1E 6BT (United Kingdom); Camacho Toro, R.C.; Picazio, A. [University of Geneva, Geneva 4 (Switzerland); Caudron, J.; El Hedri, S.; Masetti, L. [Universitaet Mainz (Germany); Chien, Y.T.; Hornig, A.; Lee, C. [Los Alamos National Laboratory, Los Alamos, NM (United States); Cogan, J.; Nachman, B.; Nef, P.; Schwartzman, A.; Strauss, E.; Swiatlowski, M. [SLAC National Accelerator Laboratory, Menlo Park, CA (United States); Curtin, D. [University of Maryland, College Park, MD (United States); Debenedetti, C. [University of California, Santa Cruz, CA (United States); Dolen, J.; Rappoccio, S. [University at Buffalo, Buffalo, NY (United States); Eklund, M.; Embry, T.; Johns, K.; Lampl, W.; Leone, R.; Loch, P.; O' Grady, F.T.; Rutherfoord, J.; Veatch, J. [University of Arizona, Tucson, AZ (United States); Ellis, S.D. [University of Washington, Seattle, WA (United States); Ferencek, D. [Rutgers University, Piscataway, NJ (United States); Fleischmann, S. [Bergische Universitaet Wuppertal, Wuppertal (Germany); Freytsis, M.; Lopez Mateos, D.; Schwartz, M.D. [Harvard University, Cambridge, MA (United States); Giulini, M.; Sosa Corral, D.E. [Universitaet Heidelberg, Heidelberg (Germany); Han, Z.; Soper, D. [University of Oregon, Eugene, OR (United States); Hare, D.; Mishra, K.; Tran, N.V. [Fermi National Accelerator Laboratory, Batavia, IL (United States); Harris, P.; Potter-Landua, B.; Potter, C.; Thomas, C.; Young, C. [CERN, Geneva 23 (Switzerland); Hinzmann, A. [Universitaet Zuerich, Zurich (Switzerland); Hoing, R.; Kogler, R.; Marchesini, I.; Usai, E. [Universitaet Hamburg, Hamburg (Germany); Jankowiak, M. [New York University, New York, NY (United States); Kasieczka, G. [ETH Zuerich, Zurich (Switzerland); Larkoski, A.J.; Marzani, S.; Thaler, J. [Massachusetts Institute of Technology, Cambridge, MA (United States); Lou, H.K. [Princeton University, Princeton, NJ (United States); Low, M.; Miller, D.W. [University of Chicago, Zurich, IL (United States); Maksimovic, P. [Johns Hopkins University, Baltimore, MD (United States); McCarthy, R. [YITP, Stony Brook University, Stony Brook, NY (United States); Ovcharova, A. [University of California, Berkeley National Laboratory, Berkeley, CA (United States); Rojo, J.; Tseng, J. [University of Oxford, Oxford (United Kingdom); Salam, G.P. [CERN, Geneva 23 (Switzerland); LPTHE, UPMC Univ. Paris 6 and CNRS UMR, Paris (France); Schabinger, R.M. [Universidad Autonoma de Madrid, Madrid (Spain); Shuve, B. [Perimeter Institute for Theoretical Physics, ON (Canada); Sinervo, P. [University of Toronto, Toronto, ON (Canada); Spannowsky, M. [University of Durham, IPPP, Durham (United Kingdom); Thompson, E. [Columbia University, New York, NY (United States); Valery, L. [LPC Clermont-Ferrand, Aubiere Cedex (France); Vos, M. [Instituto de Fisica Corpuscular, IFIC/CSIC-UVEG, Valencia (Spain); Waalewijn, W. [University of Amsterdam, Amsterdam (Netherlands); Wacker, J. [Stanford Institute for Theoretical Physics, Stanford, CA (United States)

2015-09-15

Over the past decade, a large number of jet substructure observables have been proposed in the literature, and explored at the LHC experiments. Such observables attempt to utilize the internal structure of jets in order to distinguish those initiated by quarks, gluons, or by boosted heavy objects, such as top quarks and W bosons. This report, originating from and motivated by the BOOST2013 workshop, presents original particle-level studies that aim to improve our understanding of the relationships between jet substructure observables, their complementarity, and their dependence on the underlying jet properties, particularly the jet radius and jet transverse momentum. This is explored in the context of quark/gluon discrimination, boosted W boson tagging and boosted top quark tagging. (orig.)

Towards an understanding of the correlations in jet substructure

International Nuclear Information System (INIS)

Adams, D.; Arce, A.; Asquith, L.; Backovic, M.; Barillari, T.; Menke, S.; Berta, P.; Bertolini, D.; Buckley, A.; Ferrando, J.; Pollard, C.; Butterworth, J.; Cooper, B.; Camacho Toro, R.C.; Picazio, A.; Caudron, J.; El Hedri, S.; Masetti, L.; Chien, Y.T.; Hornig, A.; Lee, C.; Cogan, J.; Nachman, B.; Nef, P.; Schwartzman, A.; Strauss, E.; Swiatlowski, M.; Curtin, D.; Debenedetti, C.; Dolen, J.; Rappoccio, S.; Eklund, M.; Embry, T.; Johns, K.; Lampl, W.; Leone, R.; Loch, P.; O'Grady, F.T.; Rutherfoord, J.; Veatch, J.; Ellis, S.D.; Ferencek, D.; Fleischmann, S.; Freytsis, M.; Lopez Mateos, D.; Schwartz, M.D.; Giulini, M.; Sosa Corral, D.E.; Han, Z.; Soper, D.; Hare, D.; Mishra, K.; Tran, N.V.; Harris, P.; Potter-Landua, B.; Potter, C.; Thomas, C.; Young, C.; Hinzmann, A.; Hoing, R.; Kogler, R.; Marchesini, I.; Usai, E.; Jankowiak, M.; Kasieczka, G.; Larkoski, A.J.; Marzani, S.; Thaler, J.; Lou, H.K.; Low, M.; Miller, D.W.; Maksimovic, P.; McCarthy, R.; Ovcharova, A.; Rojo, J.; Tseng, J.; Salam, G.P.; Schabinger, R.M.; Shuve, B.; Sinervo, P.; Spannowsky, M.; Thompson, E.; Valery, L.; Vos, M.; Waalewijn, W.; Wacker, J.

2015-01-01

Over the past decade, a large number of jet substructure observables have been proposed in the literature, and explored at the LHC experiments. Such observables attempt to utilize the internal structure of jets in order to distinguish those initiated by quarks, gluons, or by boosted heavy objects, such as top quarks and W bosons. This report, originating from and motivated by the BOOST2013 workshop, presents original particle-level studies that aim to improve our understanding of the relationships between jet substructure observables, their complementarity, and their dependence on the underlying jet properties, particularly the jet radius and jet transverse momentum. This is explored in the context of quark/gluon discrimination, boosted W boson tagging and boosted top quark tagging. (orig.)

Power spectrum of dark matter substructure in strong gravitational lenses

Science.gov (United States)

Diaz Rivero, Ana; Cyr-Racine, Francis-Yan; Dvorkin, Cora

2018-01-01

Studying the smallest self-bound dark matter structure in our Universe can yield important clues about the fundamental particle nature of dark matter. Galaxy-scale strong gravitational lensing provides a unique way to detect and characterize dark matter substructures at cosmological distances from the Milky Way. Within the cold dark matter (CDM) paradigm, the number of low-mass subhalos within lens galaxies is expected to be large, implying that their contribution to the lensing convergence field is approximately Gaussian and could thus be described by their power spectrum. We develop here a general formalism to compute from first principles the substructure convergence power spectrum for different populations of dark matter subhalos. As an example, we apply our framework to two distinct subhalo populations: a truncated Navarro-Frenk-White subhalo population motivated by standard CDM, and a truncated cored subhalo population motivated by self-interacting dark matter (SIDM). We study in detail how the subhalo abundance, mass function, internal density profile, and concentration affect the amplitude and shape of the substructure power spectrum. We determine that the power spectrum is mostly sensitive to a specific combination of the subhalo abundance and moments of the mass function, as well as to the average tidal truncation scale of the largest subhalos included in the analysis. Interestingly, we show that the asymptotic slope of the substructure power spectrum at large wave number reflects the internal density profile of the subhalos. In particular, the SIDM power spectrum exhibits a characteristic steepening at large wave number absent in the CDM power spectrum, opening the possibility of using this observable, if at all measurable, to discern between these two scenarios.

Performance of Jet Substructure Techniques and Boosted Object Identification in ATLAS

CERN Document Server

Lacey, J; The ATLAS collaboration

2014-01-01

ATLAS has implemented and commissioned many new jet substructure techniques to aid in the identification and interpretation of hadronic final states originating from Lorentz-boosted heavy particles produced at the LHC. These techniques include quantum jets, jet charge, jet shapes, quark/gluon, boosted boson and top quark tagging, along with grooming methods such as pruning, trimming, and filtering. These techniques have been validated using the large 2012 ATLAS dataset. Presented here is a summary of the state of the art jet substructure and tagging techniques developed in ATLAS, their performance and recent results.

Effect of Soil-Structure Interaction on Seismic Performance of Long-Span Bridge Tested by Dynamic Substructuring Method

Directory of Open Access Journals (Sweden)

Zhenyun Tang

2017-01-01

Full Text Available Because of the limitations of testing facilities and techniques, the seismic performance of soil-structure interaction (SSI system can only be tested in a quite small scale model in laboratory. Especially for long-span bridge, a smaller tested model is required when SSI phenomenon is considered in the physical test. The scale effect resulting from the small scale model is always coupled with the dynamic performance, so that the seismic performance of bridge considering SSI effect cannot be uncovered accurately by the traditional testing method. This paper presented the implementation of real-time dynamic substructuring (RTDS, involving the combined use of shake table array and computational engines for the seismic simulation of SSI. In RTDS system, the bridge with soil-foundation system is divided into physical and numerical substructures, in which the bridge is seen as physical substructures and the remaining part is seen as numerical substructures. The interface response between the physical and numerical substructures is imposed by shake table and resulting reaction force is fed back to the computational engine. The unique aspect of the method is to simulate the SSI systems subjected to multisupport excitation in terms of a larger physical model. The substructuring strategy and the control performance associated with the real-time substructuring testing for SSI were performed. And the influence of SSI on a long-span bridge was tested by this novel testing method.

Revealing dark matter substructure with anisotropies in the diffuse gamma-ray background

OpenAIRE

Siegal-Gaskins, Jennifer M.

2008-01-01

The majority of gamma-ray emission from Galactic dark matter annihilation is likely to be detected as a contribution to the diffuse gamma-ray background. I show that dark matter substructure in the halo of the Galaxy induces characteristic anisotropies in the diffuse background that could be used to determine the small-scale dark matter distribution. I calculate the angular power spectrum of the emission from dark matter substructure for several models of the subhalo population, and show that...

Investigation Of Failure Mechanisms In A Wind Turbine Blade Root Sub-Structure

DEFF Research Database (Denmark)

Bender, Jens Jakob; Hallett, S.R.; Lindgaard, Esben

2017-01-01

and realistic results at the fraction of the cost of a full-scale test. Therefore, this work focuses on testing of sub-structures from the root end of wind turbine blades at the transition from the thick root laminate to the thinner main laminate. Some wind turbine blade manufacturers include pre-cured tapered...... beams in the root to reduce the time required to place the large quantity of material in the mould and to decrease manufacturing defects in these elements. However, this entails the risk of introducing other manufacturing defects during the Vacuum Assisted Resin Transfer Moulding process such as resin...... pockets and fibre wrinkles. Through this work it is sought to determine the effect that these manufacturing defects can have on the strength properties of the sub-structure. The sub-structures used in this work are cut out from actual wind turbine blades, meaning that the manufacturing defects...

A composite experimental dynamic substructuring method based on partitioned algorithms and localized Lagrange multipliers

Science.gov (United States)

Abbiati, Giuseppe; La Salandra, Vincenzo; Bursi, Oreste S.; Caracoglia, Luca

2018-02-01

Successful online hybrid (numerical/physical) dynamic substructuring simulations have shown their potential in enabling realistic dynamic analysis of almost any type of non-linear structural system (e.g., an as-built/isolated viaduct, a petrochemical piping system subjected to non-stationary seismic loading, etc.). Moreover, owing to faster and more accurate testing equipment, a number of different offline experimental substructuring methods, operating both in time (e.g. the impulse-based substructuring) and frequency domains (i.e. the Lagrange multiplier frequency-based substructuring), have been employed in mechanical engineering to examine dynamic substructure coupling. Numerous studies have dealt with the above-mentioned methods and with consequent uncertainty propagation issues, either associated with experimental errors or modelling assumptions. Nonetheless, a limited number of publications have systematically cross-examined the performance of the various Experimental Dynamic Substructuring (EDS) methods and the possibility of their exploitation in a complementary way to expedite a hybrid experiment/numerical simulation. From this perspective, this paper performs a comparative uncertainty propagation analysis of three EDS algorithms for coupling physical and numerical subdomains with a dual assembly approach based on localized Lagrange multipliers. The main results and comparisons are based on a series of Monte Carlo simulations carried out on a five-DoF linear/non-linear chain-like systems that include typical aleatoric uncertainties emerging from measurement errors and excitation loads. In addition, we propose a new Composite-EDS (C-EDS) method to fuse both online and offline algorithms into a unique simulator. Capitalizing from the results of a more complex case study composed of a coupled isolated tank-piping system, we provide a feasible way to employ the C-EDS method when nonlinearities and multi-point constraints are present in the emulated system.

Structural optimization of the fibre-reinforced composite substructure in a three-unit dental bridge.

Science.gov (United States)

Shi, Li; Fok, Alex S L

2009-06-01

Failures of fixed partial dentures (FPDs) made of fibre-reinforced composites (FRC) have been reported in many clinical and in vitro studies. The types of failure include debonding at the composite-tooth interface, delamination of the veneering material from the FRC substructure and fracture of the pontic. The design of the FRC substructure, i.e. the position and orientation of the fibres, will affect the fracture resistance of the FPD. The purpose of this study was to find an optimal arrangement of the FRC substructure, by means of structural optimization, which could minimize the failure-initiating stresses in a three-unit FPD. A structural optimization method mimicking biological adaptive growth was developed for orthotropic materials such as FRC and incorporated into the finite element (FE) program ABAQUS. Using the program, optimization of the fibre positions and directions in a three-unit FPD was carried out, the aim being to align the fibre directions with those of the maximum principal stresses. The optimized design was then modeled and analyzed to verify the improvements in mechanical performance of the FPD. Results obtained from the optimization suggested that the fibres should be placed at the bottom of the pontic, forming a U-shape substructure that extended into the connectors linking the teeth and the pontic. FE analyses of the optimized design indicated stress reduction in both the veneering composite and at the interface between the veneer and the FRC substructure. The optimized design obtained using FE-based structural optimization can potentially improve the fracture resistance of FPDs by reducing some of the failure-initiating stresses. Optimization methods can therefore be a useful tool to provide sound scientific guidelines for the design of FRC substructures in FPDs.

Utilizing multiple scale models to improve predictions of extra-axial hemorrhage in the immature piglet.

Science.gov (United States)

Scott, Gregory G; Margulies, Susan S; Coats, Brittany

2016-10-01

Traumatic brain injury (TBI) is a leading cause of death and disability in the USA. To help understand and better predict TBI, researchers have developed complex finite element (FE) models of the head which incorporate many biological structures such as scalp, skull, meninges, brain (with gray/white matter differentiation), and vasculature. However, most models drastically simplify the membranes and substructures between the pia and arachnoid membranes. We hypothesize that substructures in the pia-arachnoid complex (PAC) contribute substantially to brain deformation following head rotation, and that when included in FE models accuracy of extra-axial hemorrhage prediction improves. To test these hypotheses, microscale FE models of the PAC were developed to span the variability of PAC substructure anatomy and regional density. The constitutive response of these models were then integrated into an existing macroscale FE model of the immature piglet brain to identify changes in cortical stress distribution and predictions of extra-axial hemorrhage (EAH). Incorporating regional variability of PAC substructures substantially altered the distribution of principal stress on the cortical surface of the brain compared to a uniform representation of the PAC. Simulations of 24 non-impact rapid head rotations in an immature piglet animal model resulted in improved accuracy of EAH prediction (to 94 % sensitivity, 100 % specificity), as well as a high accuracy in regional hemorrhage prediction (to 82-100 % sensitivity, 100 % specificity). We conclude that including a biofidelic PAC substructure variability in FE models of the head is essential for improved predictions of hemorrhage at the brain/skull interface.

Floating substructure flexibility of large-volume 10MW offshore wind turbine platforms in dynamic calculations

DEFF Research Database (Denmark)

Borg, Michael; Hansen, Anders Melchior; Bredmose, Henrik

2016-01-01

to the extent that it becomes relevant to include in addition to the standard rigid body substructure modes which are typically described through linear radiation-diffraction theory. This paper describes a method for the inclusion of substructural flexibility in aero-hydro-servo-elastic dynamic simulations...

Chemical substructure analysis in toxicology

Energy Technology Data Exchange (ETDEWEB)

Beauchamp, R.O. Jr. [Center for Information on Toxicology and Environment, Raleigh, NC (United States)

1990-12-31

A preliminary examination of chemical-substructure analysis (CSA) demonstrates the effective use of the Chemical Abstracts compound connectivity file in conjunction with the bibliographic file for relating chemical structures to biological activity. The importance of considering the role of metabolic intermediates under a variety of conditions is illustrated, suggesting structures that should be examined that may exhibit potential activity. This CSA technique, which utilizes existing large files accessible with online personal computers, is recommended for use as another tool in examining chemicals in drugs. 2 refs., 4 figs.

Two innovative solutions based on fibre concrete blocks designed for building substructure

Science.gov (United States)

Pazderka, J.; Hájek, P.

2017-09-01

Using of fibers in a high-strength concrete allows reduction of the dimensions of small precast concrete elements, which opens up new ways of solution for traditional construction details in buildings. The paper presents two innovative technical solutions for building substructure: The special shaped plinth block from fibre concrete and the fibre concrete elements for new technical solution of ventilated floor. The main advantages of plinth block from fibre concrete blocks (compared with standard plinth solutions) is: easier and faster assembly, higher durability and thanks to the air cavity between the vertical part of the block, the building substructure reduced moisture level of structures under the waterproofing layer and a comprehensive solution to the final surface of building plinth as well as the surface of adjacent terrain. The ventilated floor based on fibre concrete precast blocks is an attractive structural alternative for tackling the problem of increased moisture in masonry in older buildings, lacking a functional waterproof layer in the substructure.

Earthquake analysis of structures including structure-soil interaction by a substructure method

International Nuclear Information System (INIS)

Chopra, A.K.; Guttierrez, J.A.

1977-01-01

A general substructure method for analysis of response of nuclear power plant structures to earthquake ground motion, including the effects of structure-soil interaction, is summarized. The method is applicable to complex structures idealized as finite element systems and the soil region treated as either a continuum, for example as a viscoelastic halfspace, or idealized as a finite element system. The halfspace idealization permits reliable analysis for sites where essentially similar soils extend to large depths and there is no rigid boundary such as soil-rock interface. For sites where layers of soft soil are underlain by rock at shallow depth, finite element idealization of the soil region is appropriate; in this case, the direct and substructure methods would lead to equivalent results but the latter provides the better alternative. Treating the free field motion directly as the earthquake input in the substructure eliminates the deconvolution calculations and the related assumption-regarding type and direction of earthquake waves-required in the direct method. (Auth.)

Improving jet substructure performance in ATLAS with unified tracking and calorimeter inputs

CERN Document Server

Jansky, Roland; The ATLAS collaboration

2018-01-01

Jet substructure techniques play a critical role in ATLAS in searches for new physics, and are being utilized in the trigger. They become increasingly important in detailed studies of the Standard Model, among them the inclusive search for the Higgs boson produced with high transverse momentum decaying to a bottom-antibottom quark pair. To date, ATLAS has mostly focused on the use of calorimeter-based jet substructure, which works well for jets initiated by particles with low to moderate boost, but which lacks the angular resolution needed to resolve the desired substructure in the highly-boosted regime. We will present a novel approach designed to mitigate the calorimeter angular resolution limitations, thus providing superior performance to prior methods. Similar to previous methods, the superior angular resolution of the tracker is combined with information from the calorimeters. However, the new method is fundamentally different, as it correlates low-level objects as tracks and individual energy deposits ...

Residuated lattices an algebraic glimpse at substructural logics

CERN Document Server

Galatos, Nikolaos; Kowalski, Tomasz; Ono, Hiroakira

2007-01-01

The book is meant to serve two purposes. The first and more obvious one is to present state of the art results in algebraic research into residuated structures related to substructural logics. The second, less obvious but equally important, is to provide a reasonably gentle introduction to algebraic logic. At the beginning, the second objective is predominant. Thus, in the first few chapters the reader will find a primer of universal algebra for logicians, a crash course in nonclassical logics for algebraists, an introduction to residuated structures, an outline of Gentzen-style calculi as well as some titbits of proof theory - the celebrated Hauptsatz, or cut elimination theorem, among them. These lead naturally to a discussion of interconnections between logic and algebra, where we try to demonstrate how they form two sides of the same coin. We envisage that the initial chapters could be used as a textbook for a graduate course, perhaps entitled Algebra and Substructural Logics. As the book progresses the f...

Influence of solidification parameters on the cellular sub-structure of tin and some tin alloys

International Nuclear Information System (INIS)

Milosavljevic, Dj.

1965-01-01

This paper describes an attempt to obtain qualitative data on sub-structure of samples solidified in contact with the cooler. The objective of experiments was to study micro segregation phenomena by investigating the substructure in the solidified sample obtained under experimental conditions which are similar to real solidification conditions

Replaceable Substructures for Efficient Part-Based Modeling

KAUST Repository

Liu, Han; Vimont, Ulysse; Wand, Michael; Cani, Marie Paule; Hahmann, Stefanie; Rohmer, Damien; Mitra, Niloy J.

2015-01-01

A popular mode of shape synthesis involves mixing and matching parts from different objects to form a coherent whole. The key challenge is to efficiently synthesize shape variations that are plausible, both locally and globally. A major obstacle is to assemble the objects with local consistency, i.e., all the connections between parts are valid with no dangling open connections. The combinatorial complexity of this problem limits existing methods in geometric and/or topological variations of the synthesized models. In this work, we introduce replaceable substructures as arrangements of parts that can be interchanged while ensuring boundary consistency. The consistency information is extracted from part labels and connections in the original source models. We present a polynomial time algorithm that discovers such substructures by working on a dual of the original shape graph that encodes inter-part connectivity. We demonstrate the algorithm on a range of test examples producing plausible shape variations, both from a geometric and from a topological viewpoint. © 2015 The Author(s) Computer Graphics Forum © 2015 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.

Replaceable Substructures for Efficient Part-Based Modeling

KAUST Repository

Liu, Han

2015-05-01

A popular mode of shape synthesis involves mixing and matching parts from different objects to form a coherent whole. The key challenge is to efficiently synthesize shape variations that are plausible, both locally and globally. A major obstacle is to assemble the objects with local consistency, i.e., all the connections between parts are valid with no dangling open connections. The combinatorial complexity of this problem limits existing methods in geometric and/or topological variations of the synthesized models. In this work, we introduce replaceable substructures as arrangements of parts that can be interchanged while ensuring boundary consistency. The consistency information is extracted from part labels and connections in the original source models. We present a polynomial time algorithm that discovers such substructures by working on a dual of the original shape graph that encodes inter-part connectivity. We demonstrate the algorithm on a range of test examples producing plausible shape variations, both from a geometric and from a topological viewpoint. © 2015 The Author(s) Computer Graphics Forum © 2015 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.

VARIATION OF SUBSTRUCTURES OF PEARLITIC HEAT RESISTANT STEEL AFTER HIGH TEMPERATURE AGING

Institute of Scientific and Technical Information of China (English)

R.C.Yang; K.Chen; H.X.Feng; H.Wang

2004-01-01

The observations of dislocations, substructures and other microstructural details were conducted mainly by means of transmission electron microscope (TEM) and scanning electron microscope (SEM) for 12Cr1Mo V pearlitic heat-resistant steel. It is shown that during the high temperature long-term aging, the disordered and jumbled phasetransformed dislocations caused by normalized cooling are recovered and rearranged into cell substructures, and then the dislocation density is reduced gradually. Finally a low density linear dislocation configuration and a stabler dislocation network are formed and ferritic grains grow considerably.

Structure and substructure analysis of DAFT/FADA galaxy clusters in the [0.4-0.9] redshift range

Science.gov (United States)

Guennou, L.; Adami, C.; Durret, F.; Lima Neto, G. B.; Ulmer, M. P.; Clowe, D.; LeBrun, V.; Martinet, N.; Allam, S.; Annis, J.; Basa, S.; Benoist, C.; Biviano, A.; Cappi, A.; Cypriano, E. S.; Gavazzi, R.; Halliday, C.; Ilbert, O.; Jullo, E.; Just, D.; Limousin, M.; Márquez, I.; Mazure, A.; Murphy, K. J.; Plana, H.; Rostagni, F.; Russeil, D.; Schirmer, M.; Slezak, E.; Tucker, D.; Zaritsky, D.; Ziegler, B.

2014-01-01

Context. The DAFT/FADA survey is based on the study of ~90 rich (masses found in the literature >2 × 1014 M⊙) and moderately distant clusters (redshifts 0.4 DAFT/FADA survey for which XMM-Newton and/or a sufficient number of galaxy redshifts in the cluster range are available, with the aim of detecting substructures and evidence for merging events. These properties are discussed in the framework of standard cold dark matter (ΛCDM) cosmology. Methods: In X-rays, we analysed the XMM-Newton data available, fit a β-model, and subtracted it to identify residuals. We used Chandra data, when available, to identify point sources. In the optical, we applied a Serna & Gerbal (SG) analysis to clusters with at least 15 spectroscopic galaxy redshifts available in the cluster range. We discuss the substructure detection efficiencies of both methods. Results: XMM-Newton data were available for 32 clusters, for which we derive the X-ray luminosity and a global X-ray temperature for 25 of them. For 23 clusters we were able to fit the X-ray emissivity with a β-model and subtract it to detect substructures in the X-ray gas. A dynamical analysis based on the SG method was applied to the clusters having at least 15 spectroscopic galaxy redshifts in the cluster range: 18 X-ray clusters and 11 clusters with no X-ray data. The choice of a minimum number of 15 redshifts implies that only major substructures will be detected. Ten substructures were detected both in X-rays and by the SG method. Most of the substructures detected both in X-rays and with the SG method are probably at their first cluster pericentre approach and are relatively recent infalls. We also find hints of a decreasing X-ray gas density profile core radius with redshift. Conclusions: The percentage of mass included in substructures was found to be roughly constant with redshift values of 5-15%, in agreement both with the general CDM framework and with the results of numerical simulations. Galaxies in substructures

Deliverable D74.2. Probabilistic analysis methods for support structures

DEFF Research Database (Denmark)

Gintautas, Tomas

2018-01-01

Relevant Description: Report describing the probabilistic analysis for offshore substructures and results attained. This includes comparison with experimental data and with conventional design. Specific targets: 1) Estimate current reliability level of support structures 2) Development of basis...... for probabilistic calculations and evaluation of reliability for offshore support structures (substructures) 3) Development of a probabilistic model for stiffness and strength of soil parameters and for modeling geotechnical load bearing capacity 4) Comparison between probabilistic analysis and deterministic...

The LabelHash algorithm for substructure matching

Directory of Open Access Journals (Sweden)

Bryant Drew H

2010-11-01

Full Text Available Abstract Background There is an increasing number of proteins with known structure but unknown function. Determining their function would have a significant impact on understanding diseases and designing new therapeutics. However, experimental protein function determination is expensive and very time-consuming. Computational methods can facilitate function determination by identifying proteins that have high structural and chemical similarity. Results We present LabelHash, a novel algorithm for matching substructural motifs to large collections of protein structures. The algorithm consists of two phases. In the first phase the proteins are preprocessed in a fashion that allows for instant lookup of partial matches to any motif. In the second phase, partial matches for a given motif are expanded to complete matches. The general applicability of the algorithm is demonstrated with three different case studies. First, we show that we can accurately identify members of the enolase superfamily with a single motif. Next, we demonstrate how LabelHash can complement SOIPPA, an algorithm for motif identification and pairwise substructure alignment. Finally, a large collection of Catalytic Site Atlas motifs is used to benchmark the performance of the algorithm. LabelHash runs very efficiently in parallel; matching a motif against all proteins in the 95% sequence identity filtered non-redundant Protein Data Bank typically takes no more than a few minutes. The LabelHash algorithm is available through a web server and as a suite of standalone programs at http://labelhash.kavrakilab.org. The output of the LabelHash algorithm can be further analyzed with Chimera through a plugin that we developed for this purpose. Conclusions LabelHash is an efficient, versatile algorithm for large-scale substructure matching. When LabelHash is running in parallel, motifs can typically be matched against the entire PDB on the order of minutes. The algorithm is able to identify

The angular power spectrum of the diffuse gamma-ray background as a probe of Galactic dark matter substructure

OpenAIRE

Siegal-Gaskins, Jennifer M.

2009-01-01

Dark matter annihilation in Galactic substructure produces diffuse gamma-ray emission of remarkably constant intensity across the sky, and in general this signal dominates over the smooth halo signal at angles greater than a few tens of degrees from the Galactic Center. The large-scale isotropy of the emission from substructure suggests that it may be difficult to extract this Galactic dark matter signal from the extragalactic gamma-ray background. I show that dark matter substructure induces...

On mechanism of substructure formation in SmS during isomorphic phase transformations

International Nuclear Information System (INIS)

Aptekar', I.L.; Ivanov, V.I.; Tonkov, E.Yu.; Shmyt'ko, I.M.

1986-01-01

X-ray diffraction study of substructure characteristics of SmS samples subjected to treatment at different temrerature and pressure in media with different viscosity ( graphite, silicon oil) for realization of P-M-P transformations ( p-semiconductor phase, M - high pressure phase) is performed. It is assumed that with M - phase formation P - matrix volume relaxation delays, therefore the new phase particles occupy smaller volume than the initial matrix which causes the M - phase disorientation. The difference between the phase transformation rate and deformation rate under the pressure in media with various viscosity results in arising different substructural characteristics

SPECTROSCOPIC OBSERVATIONS OF AN EVOLVING FLARE RIBBON SUBSTRUCTURE SUGGESTING ORIGIN IN CURRENT SHEET WAVES

Energy Technology Data Exchange (ETDEWEB)

Brannon, S. R.; Longcope, D. W.; Qiu, J. [Department of Physics, Montana State University, Bozeman, MT 59717 (United States)

2015-09-01

We present imaging and spectroscopic observations from the Interface Region Imaging Spectrograph of the evolution of the flare ribbon in the SOL2014-04-18T13:03 M-class flare event, at high spatial resolution and time cadence. These observations reveal small-scale substructure within the ribbon, which manifests as coherent quasi-periodic oscillations in both position and Doppler velocities. We consider various alternative explanations for these oscillations, including modulation of chromospheric evaporation flows. Among these, we find the best support for some form of wave localized to the coronal current sheet, such as a tearing mode or Kelvin–Helmholtz instability.

Prismatic substructure in metals; Prizmaticna substruktura kod metala

Energy Technology Data Exchange (ETDEWEB)

Milosavljevic, Dj [Institute of Nuclear Sciences Boris Kidric, Vinca, Beograd (Yugoslavia)

1965-11-15

The first step was the study of impurities behaviour during solidification of metals under equilibrium and non-equilibrium conditions. Impurities distribution and their structural shapes are dependent on conditions of solidification. These conditions are directly related to temperature and concentration issues on the solidification surface. Theoretical and experimental evaluated in this paper show the significance of subcooling in formation of cellular sub-structure.

Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd-27th of July 2012

International Nuclear Information System (INIS)

Altheimer, A.; Thompson, E.N.; Arce, A.; Bjergaard, D.; Asquith, L.; Backus Mayes, J.; Hook, A.; Izaguirre, E.; Jankowiak, M.; Larkoski, A.; Nef, P.; Schwartzman, A.; Swiatlowski, M.; Wacker, J.; Kuutmann, E.B.; Berger, J.; Bryngemark, L.; Buckley, A.; Debenedetti, C.; Butterworth, J.; Campanelli, M.; Davison, A.; Cacciari, M.; Carli, T.; Roeck, A. de; Chala, M.; Chapleau, B.; Chen, C.; Chou, J.P.; Cornelissen, T.; Fleischmann, S.; Curtin, D.; Dasgupta, M.; Almeida Dias, F. de; De Cosa, A.; Doglioni, C.; Guescini, F.; Ellis, S.D.; Hornig, A.; Scholtz, J.; Fassi, F.; Hoz, S.G. de la; Kaci, M.; Oliver Garcia, E.; Rodrigo, G.; Salt, J.; Sanchez Martinez, V.; Villaplana, M.; Vos, M.; Ferrando, J.; Kar, D.; Nordstrom, K.; Freytsis, M.; Gonzalez Silva, M.L.; Han, Z.; Lopez Mateos, D.; Schwartz, M.D.; Juknevich, J.; Kasieczka, G.; Plehn, T.; Schaetzel, S.; Takeuchi, M.; Kogler, R.; Loch, P.; Marzani, S.; Spannowsky, M.; Masetti, L.; Mateu, V.; Stewart, I.; Thaler, J.; Miller, D.W.; Mishra, K.; Tran, N.V.; Penwell, J.; Pilot, J.; Rappoccio, S.; Rizzi, A.; Safonov, A.; Salam, G.P.; Schioppa, M.; Schmidt, A.; Segala, M.; Son, M.; Soyez, G.; Strom, D.; Vermilion, C.; Walsh, J.

2014-01-01

This report of the BOOST2012 workshop presents the results of four working groups that studied key aspects of jet substructure. We discuss the potential of first-principle QCD calculations to yield a precise description of the substructure of jets and study the accuracy of state-of-the-art Monte Carlo tools. Limitations of the experiments' ability to resolve substructure are evaluated, with a focus on the impact of additional (pile-up) proton proton collisions on jet substructure performance in future LHC operating scenarios. A final section summarizes the lessons learnt from jet substructure analyses in searches for new physics in the production of boosted top quarks. (orig.)

Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd-27th of July 2012

Energy Technology Data Exchange (ETDEWEB)

Altheimer, A.; Thompson, E.N. [Columbia University, Nevis Laboratory, Irvington, NY (United States); Arce, A.; Bjergaard, D. [Duke University, Durham, NC (United States); Asquith, L. [Argonne National Laboratory, Lemont, IL (United States); Backus Mayes, J.; Hook, A.; Izaguirre, E.; Jankowiak, M.; Larkoski, A.; Nef, P.; Schwartzman, A.; Swiatlowski, M.; Wacker, J. [SLAC National Accelerator Laboratory, Menlo Park, CA (United States); Kuutmann, E.B. [Deutsches Elektronen-Synchrotron, DESY, Zeuthen (Germany); Humboldt University, Berlin (Germany); Berger, J. [Cornell University, Ithaca, NY (United States); Bryngemark, L. [Lund University, Lund (Sweden); Buckley, A.; Debenedetti, C. [University of Edinburgh, Edinburgh (United Kingdom); Butterworth, J.; Campanelli, M.; Davison, A. [University College London, London (United Kingdom); Cacciari, M. [CERN, Geneva 23 (Switzerland); Carli, T.; Roeck, A. de [LPTHE, UPMC Univ. Paris 6 et CNRS UMR, Paris (France); Chala, M. [CAFPE and Univ. of Granada, Granada (Spain); Chapleau, B. [McGill University, Montreal, QC (Canada); Chen, C. [Iowa State University, Ames, IA (United States); Chou, J.P. [Rutgers University, Piscataway, NJ (United States); Cornelissen, T.; Fleischmann, S. [Bergische Universitaet Wuppertal, Wuppertal (Germany); Curtin, D. [YITP, Stony Brook University, Stony Brook, NY (United States); Dasgupta, M. [University of Manchester, Manchester (United Kingdom); Almeida Dias, F. de [UNESP-Universidade Estadual Paulista, Sao Paulo (Brazil); De Cosa, A. [INFN, Naples (Italy); University of Naples, Naples (Italy); Doglioni, C.; Guescini, F. [University of Geneva, Geneva 4 (Switzerland); Ellis, S.D.; Hornig, A.; Scholtz, J. [University of Washington, Seattle, WA (United States); Fassi, F.; Hoz, S.G. de la; Kaci, M.; Oliver Garcia, E.; Rodrigo, G.; Salt, J.; Sanchez Martinez, V.; Villaplana, M.; Vos, M. [Instituto de Fisica Corpuscular, IFIC/CSIC-UVEG, Valencia (Spain); Ferrando, J.; Kar, D.; Nordstrom, K. [University of Glasgow, Glasgow (United Kingdom); Freytsis, M. [University of California, Lawrence Berkeley National Laboratory, Berkeley, CA (United States); University of California, Berkeley, CA (United States); Gonzalez Silva, M.L. [Universidad de Buenos Aires, Buenos Aires (Argentina); Han, Z.; Lopez Mateos, D.; Schwartz, M.D. [Harvard University, Cambridge, MA (United States); Juknevich, J. [Weizmann Institute, Rehovot (Israel); Kasieczka, G.; Plehn, T.; Schaetzel, S.; Takeuchi, M. [Universitaet Heidelberg, Heidelberg (Germany); Kogler, R. [Universitaet Hamburg, Hamburg (Germany); Loch, P. [University of Arizona, Tucson, AZ (United States); Marzani, S.; Spannowsky, M. [IPPP, University of Durham, Durham (United Kingdom); Masetti, L. [Universitaet Mainz, Mainz (Germany); Mateu, V.; Stewart, I.; Thaler, J. [MIT, Cambridge, MA (United States); Miller, D.W. [University of Chicago, Chicago, IL (United States); Mishra, K.; Tran, N.V. [Fermi National Accelerator Laboratory, Batavia, IL (United States); Penwell, J. [Indiana University, Bloomington, IN (United States); Pilot, J. [University of California, Davis, CA (United States); Rappoccio, S. [Johns Hopkins University, Baltimore, MD (United States); University at Buffalo, State University of New York, Buffalo, NY (United States); Rizzi, A. [INFN, Pisa (Italy); University of Pisa, Pisa (Italy); Safonov, A. [Texas A and M University, College Station, TX (United States); Salam, G.P. [CERN, Geneva 23 (Switzerland); LPTHE, UPMC Univ. Paris 6 et CNRS UMR, Paris (France); Schioppa, M. [INFN, Rende (IT); University of Calabria, Rende (IT); Schmidt, A. [Universitaet Hamburg, Hamburg (DE); Universitaet Heidelberg, Heidelberg (DE); Segala, M. [Brown University, Richmond, RI (US); Son, M. [Yale University, New Haven, CT (US); Soyez, G. [CEA Saclay, Gif-sur-Yvette (FR); Strom, D. [University of Illinois, Chicago, IL (US); Vermilion, C. [University of California, Lawrence Berkeley National Laboratory, Berkeley, CA (US); Walsh, J. [University of California, Berkeley, CA (US)

2014-03-15

This report of the BOOST2012 workshop presents the results of four working groups that studied key aspects of jet substructure. We discuss the potential of first-principle QCD calculations to yield a precise description of the substructure of jets and study the accuracy of state-of-the-art Monte Carlo tools. Limitations of the experiments' ability to resolve substructure are evaluated, with a focus on the impact of additional (pile-up) proton proton collisions on jet substructure performance in future LHC operating scenarios. A final section summarizes the lessons learnt from jet substructure analyses in searches for new physics in the production of boosted top quarks. (orig.)

A substructure method to compute the 3D fluid-structure interaction during blowdown

International Nuclear Information System (INIS)

Guilbaud, D.; Axisa, F.; Gantenbein, F.; Gibert, R.J.

1983-08-01

The waves generated by a sudden rupture of a PWR primary pipe have an important mechanical effect on the internal structures of the vessel. This fluid-structure interaction has a strong 3D aspect. 3D finite element explicit methods can be applied. These methods take into account the non linearities of the problem but the calculation is heavy and expensive. We describe in this paper another type of method based on a substructure procedure: the vessel, internals and contained fluid are axisymmetrically described (AQUAMODE computer code). The pipes and contained fluid are monodimensionaly described (TEDEL-FLUIDE Computer Code). These substructures are characterized by their natural modes. Then, they are connected to another (connection of both structural and fluid nodes) the TRISTANA Computer Code. This method allows to compute correctly and cheaply the 3D fluid-structure effects. The treatment of certain non linearities is difficult because of the modal characterization of the substructures. However variations of contact conditions versus time can be introduced. We present here some validation tests and comparison with experimental results of the litterature

Method for predicting enzyme-catalyzed reactions

Science.gov (United States)

Hlavacek, William S.; Unkefer, Clifford J.; Mu, Fangping; Unkefer, Pat J.

2013-03-19

The reactivity of given metabolites is assessed using selected empirical atomic properties in the potential reaction center. Metabolic reactions are represented as biotransformation rules. These rules are generalized from the patterns in reactions. These patterns are not unique to reactants but are widely distributed among metabolites. Using a metabolite database, potential substructures are identified in the metabolites for a given biotransformation. These substructures are divided into reactants or non-reactants, depending on whether they participate in the biotransformation or not. Each potential substructure is then modeled using descriptors of the topological and electronic properties of atoms in the potential reaction center; molecular properties can also be used. A Support Vector Machine (SVM) or classifier is trained to classify a potential reactant as a true or false reactant using these properties.

First attempts towards the early detection of fatigued substructures using cyclic-loaded 20 MnMoNi 5 5 steel

International Nuclear Information System (INIS)

Dobmann, G.; Seibold, A.

1992-01-01

Materials subjected to cyclic loading undergo substructural changes which may affect service life. The low alloy, fine-grained structural steel 20 MnMoNi 5 5 is used to demonstrate how substructural changes detected using TEM techniques are a function of the number of cycles undergone. For a given cyclic loading the usage factor η=N/N f =0.5 can be derived. Initial investigations using nondestructive examination methods have indicated that substructural changes and magnetic variables can be correlated. (orig.)

MS2Analyzer: A Software for Small Molecule Substructure Annotations from Accurate Tandem Mass Spectra

Science.gov (United States)

2015-01-01

Systematic analysis and interpretation of the large number of tandem mass spectra (MS/MS) obtained in metabolomics experiments is a bottleneck in discovery-driven research. MS/MS mass spectral libraries are small compared to all known small molecule structures and are often not freely available. MS2Analyzer was therefore developed to enable user-defined searches of thousands of spectra for mass spectral features such as neutral losses, m/z differences, and product and precursor ions from MS/MS spectra in MSP/MGF files. The software is freely available at http://fiehnlab.ucdavis.edu/projects/MS2Analyzer/. As the reference query set, 147 literature-reported neutral losses and their corresponding substructures were collected. This set was tested for accuracy of linking neutral loss analysis to substructure annotations using 19 329 accurate mass tandem mass spectra of structurally known compounds from the NIST11 MS/MS library. Validation studies showed that 92.1 ± 6.4% of 13 typical neutral losses such as acetylations, cysteine conjugates, or glycosylations are correct annotating the associated substructures, while the absence of mass spectra features does not necessarily imply the absence of such substructures. Use of this tool has been successfully demonstrated for complex lipids in microalgae. PMID:25263576

Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures.

Science.gov (United States)

Zhang, Bijun; Vogt, Martin; Maggiora, Gerald M; Bajorath, Jürgen

2015-10-01

Chemical space networks (CSNs) have recently been introduced as an alternative to other coordinate-free and coordinate-based chemical space representations. In CSNs, nodes represent compounds and edges pairwise similarity relationships. In addition, nodes are annotated with compound property information such as biological activity. CSNs have been applied to view biologically relevant chemical space in comparison to random chemical space samples and found to display well-resolved topologies at low edge density levels. The way in which molecular similarity relationships are assessed is an important determinant of CSN topology. Previous CSN versions were based on numerical similarity functions or the assessment of substructure-based similarity. Herein, we report a new CSN design that is based upon combined numerical and substructure similarity evaluation. This has been facilitated by calculating numerical similarity values on the basis of maximum common substructures (MCSs) of compounds, leading to the introduction of MCS-based CSNs (MCS-CSNs). This CSN design combines advantages of continuous numerical similarity functions with a robust and chemically intuitive substructure-based assessment. Compared to earlier version of CSNs, MCS-CSNs are characterized by a further improved organization of local compound communities as exemplified by the delineation of drug-like subspaces in regions of biologically relevant chemical space.

Comparison of Shade of Ceramic with Three Different Zirconia Substructures using Spectrophotometer.

Science.gov (United States)

Habib, Syed Rashid; Shiddi, Ibraheem F Al

2015-02-01

This study assessed how changing the Zirconia (Zr) substructure affected the color samples after they have been overlaid by the same shade of veneering ceramic. Three commercial Zr materials were tested in this study: Prettau(®) Zirconia (ZirKonZahn, Italy), Cercon (Dentsply, Germany) and InCoris ZI (Sirona, Germany). For each system, 15 disk-shaped specimens (10 × 1 mm) were fabricated. Three shades of A1, A2 and A3.5 of porcelain (IPS e.MaxCeram, IvoclarVivadent, USA) were used for layering the specimens. Five specimens from each type of Zr were layered with same shade of ceramic. Color measurements were recorderd by a spectrophotometer Color-Eye(®) 7000A (X-Rite, Grand Rapids, MI). Mean values of L, a, b color coordinates and ΔE were recorded and comparisons were made. Differences in the ΔE were recorded for the same porcelain shade with different Zr substructures and affected the color of the specimens (p < 0.01, ANOVA). The maximum difference between the ΔE values for the A1, A2 and A3.5 shades with three types of Zr substructures was found to be 1.59, 1.69 and 1.45 respectively. Multiple comparisons of the ΔE with PostHoc Tukey test revealed a statistically significant difference (p < 0.05) between the three types of Zr, except between Type 2 Zr and Type 3 Zr for the Shade A1. The mean values of L, a, b and ΔE for the Prettau(®) Zirconia substructure were found to be the least among the three types. The brand of Zr used influences the final color of the all ceramic Zr based restorations and this has clinical significance.

Development and Demonstration of a Magnesium-Intensive Vehicle Front-End Substructure

Energy Technology Data Exchange (ETDEWEB)

Logan, Stephen D. [United States Automotive Materials Partnership LLC, Southfield, MI (United States); Forsmark, Joy H. [United States Automotive Materials Partnership LLC, Southfield, MI (United States); Osborne, Richard [United States Automotive Materials Partnership LLC, Southfield, MI (United States)

2016-07-01

This project is the final phase (designated Phase III) of an extensive, nine-year effort with the objectives of developing a knowledge base and enabling technologies for the design, fabrication and performance evaluation of magnesium-intensive automotive front-end substructures intended to partially or completely replace all-steel comparators, providing a weight savings approaching 50% of the baseline. Benefits of extensive vehicle weight reduction in terms of fuel economy increase, extended vehicle range, vehicle performance and commensurate reductions in greenhouse gas emissions are well known. An exemplary vehicle substructure considered by the project is illustrated in Figure 1, along with the exterior vehicle appearance. This unibody front-end “substructure” is one physical objective of the ultimate design and engineering aspects established at the outset of the larger collective effort.

Face-based selection of corners in 3D substructuring

Czech Academy of Sciences Publication Activity Database

Šístek, Jakub; Čertíková, M.; Burda, P.; Novotný, J.

2012-01-01

Roč. 82, č. 10 (2012), s. 1799-1811 ISSN 0378-4754 R&D Projects: GA AV ČR IAA100760702 Institutional research plan: CEZ:AV0Z10190503 Keywords : domain decomposition * iterative substructuring * BDDC Subject RIV: BA - General Mathematics Impact factor: 0.836, year: 2012 http://www.sciencedirect.com/science/article/pii/S0378475411001820

PROXIMAL: a method for Prediction of Xenobiotic Metabolism.

Science.gov (United States)

Yousofshahi, Mona; Manteiga, Sara; Wu, Charmian; Lee, Kyongbum; Hassoun, Soha

2015-12-22

Contamination of the environment with bioactive chemicals has emerged as a potential public health risk. These substances that may cause distress or disease in humans can be found in air, water and food supplies. An open question is whether these chemicals transform into potentially more active or toxic derivatives via xenobiotic metabolizing enzymes expressed in the body. We present a new prediction tool, which we call PROXIMAL (Prediction of Xenobiotic Metabolism) for identifying possible transformation products of xenobiotic chemicals in the liver. Using reaction data from DrugBank and KEGG, PROXIMAL builds look-up tables that catalog the sites and types of structural modifications performed by Phase I and Phase II enzymes. Given a compound of interest, PROXIMAL searches for substructures that match the sites cataloged in the look-up tables, applies the corresponding modifications to generate a panel of possible transformation products, and ranks the products based on the activity and abundance of the enzymes involved. PROXIMAL generates transformations that are specific for the chemical of interest by analyzing the chemical's substructures. We evaluate the accuracy of PROXIMAL's predictions through case studies on two environmental chemicals with suspected endocrine disrupting activity, bisphenol A (BPA) and 4-chlorobiphenyl (PCB3). Comparisons with published reports confirm 5 out of 7 and 17 out of 26 of the predicted derivatives for BPA and PCB3, respectively. We also compare biotransformation predictions generated by PROXIMAL with those generated by METEOR and Metaprint2D-react, two other prediction tools. PROXIMAL can predict transformations of chemicals that contain substructures recognizable by human liver enzymes. It also has the ability to rank the predicted metabolites based on the activity and abundance of enzymes involved in xenobiotic transformation.

Predicting catalyst-support interactions between metal nanoparticles and amorphous silica supports

Science.gov (United States)

Ewing, Christopher S.; Veser, Götz; McCarthy, Joseph J.; Lambrecht, Daniel S.; Johnson, J. Karl

2016-10-01

Metal-support interactions significantly affect the stability and activity of supported catalytic nanoparticles (NPs), yet there is no simple and reliable method for estimating NP-support interactions, especially for amorphous supports. We present an approach for rapid prediction of catalyst-support interactions between Pt NPs and amorphous silica supports for NPs of various sizes and shapes. We use density functional theory calculations of 13 atom Pt clusters on model amorphous silica supports to determine linear correlations relating catalyst properties to NP-support interactions. We show that these correlations can be combined with fast discrete element method simulations to predict adhesion energy and NP net charge for NPs of larger sizes and different shapes. Furthermore, we demonstrate that this approach can be successfully transferred to Pd, Au, Ni, and Fe NPs. This approach can be used to quickly screen stability and net charge transfer and leads to a better fundamental understanding of catalyst-support interactions.

Design and Analysis of Jacket Substructures for Offshore Wind Turbines

Directory of Open Access Journals (Sweden)

I-Wen Chen

2016-04-01

Full Text Available This study focused on investigating various existing types of offshore jacket substructures along with a proposed twisted-tripod jacket type (modified jacket (MJ-structures. The architectures of the three-leg structure, as well as the patented twisted jacket structure motivated the design of the proposed MJ-structures. The dimensions of the structures were designed iteratively using static stress analysis to ensure that all structures had a similar level of load-carrying capability. The numerical global buckling analyses were performed for all structures after the validation by the scaled-down experiments. The local buckling strength of all compressive members was analyzed using the NORSOK standard. The results showed that the proposed MJ-structures possess excellent structural behavior and few structural nodes and components competitive with the patented twisted jacket structures, while still maintaining the advantages of low material usage similar to the three-leg jacket structures. This study provides alternatives for the initial selection and design of offshore wind turbine substructures for green energy applications.

Universal parametrization for quark and lepton substructure

International Nuclear Information System (INIS)

Akama, Keiichi; Terazawa, Hidezumi.

1994-01-01

A universal parametrization for possible quark and lepton substructure is advocated in terms of quark and lepton form factors. It is emphasized that the lower bounds on compositeness scale, Λ c , to be determined experimentally strongly depend on their definitions in composite models. From the recent HERA data, it is estimated to be Λ c > 50 GeV, 0.4 TeV and 10 TeV, depending on the parametrizations with a single-pole form factor, a contact interaction and a logarithmic form factor, respectively. (author)

Jacket Substructure Fatigue Mitigation through Active Control

DEFF Research Database (Denmark)

Hanis, Tomas; Natarajan, Anand

2014-01-01

to the fatigue design loads on the braces of the jacket. Since large wind turbines of 10MW rating have low rotor speeds (p), the modal frequencies of the sub structures approach 3p at low wind speeds, which leads to a modal coupling and resonance. Therefore an active control system is developed which provides...... sufficient structural damping and consequently a fatigue reduction at the substructure. The resulting reduction in fatigue design loads on the jacket structure based on the active control system is presented....

Morphology and substructure of lath martensites in dilute Zr--Nb alloys

International Nuclear Information System (INIS)

Srivastava, D.; Mukhopadhyay, P.; Banerjee, S.

2000-01-01

The morphology and substructure of lath martensites formed in β quenched dilute Zr--Nb alloys are described. The laths are arranged in a nearly parallel manner within any given colony or packet. Packets of alternately twin related laths and clusters of three mutually twin related lath martensite variants have been observed and the twinning plane is of {1 anti 101} H type. With increasing niobium content a continuous transition from large colonies of lath martensites, through smaller lath colonies, to individual plates of the acicular martensites occurs. The lath-lath interface consists of regularly spaced parallel arrays of dislocations of type. The habit plane traces of lath martensite lie close to {334} type poles and the operating lattice invariant shear mode is { anti 1101} H H shear system. This result is consistent with results predicted by the phenomenological theory. The preferred two and three habit plane variant grouping clustering is explained on the basis of self-accommodation effects. (orig.)

Observation of lateral substructures in EAS by measurement of the time distribution of atmospheric Cerenkov light

International Nuclear Information System (INIS)

Bosia, G.; Navarra, G.; Saavedra, O.

1975-01-01

The lateral structure of EAS is derived from the arrival time distribution of atmospheric Cerenkov light assuming a strict correlation between time structure and lateral particle distribution. Results of the Pic du Midi experiment are presented. Substructures in the time distribution of the Cerenkov light can be related to structures in the lateral density distribution of electrons. The frequency (a few %) of substructures can be explained within conventional models of high energy interactions. (orig.) [de

Orientation dependence of shock-induced twinning and substructures in a copper bicrystal

International Nuclear Information System (INIS)

Cao Fang; Beyerlein, Irene J.; Addessio, Francis L.; Sencer, Bulent H.; Trujillo, Carl P.; Cerreta, Ellen K.; Gray, George T. III

2010-01-01

Shock recovery experiments have been conducted to assess the role of shock stress and orientation dependence on substructure evolution and deformation twinning of a [1 0 0]/[011-bar] copper bicrystal. Transmission electron microscopy of the post-shock specimens revealed that well-defined dislocation cell structures developed in both grains and the average cell size decreased with increasing shock pressure from 5 to 10 GPa. Twinning occurred in the [1 0 0] grain, but not the [011-bar] grain, at the 10 GPa shock pressure. The stress and orientation dependence of incipient twinning can be predicted by the stress and orientation conditions required to dissociate slip dislocations into glissile twinning dislocations. The dynamic widths between the two partials are calculated considering the three-dimensional deviatoric stress state induced by the shock as calculated using plane-strain plate impact simulations and the relativistic and drag effects on dislocations moving at high speeds.

Halo substructure in the SDSS-Gaia catalogue: streams and clumps

Science.gov (United States)

Myeong, G. C.; Evans, N. W.; Belokurov, V.; Amorisco, N. C.; Koposov, S. E.

2018-04-01

We use the Sloan Digital Sky Survey (SDSS)-Gaia Catalogue to identify six new pieces of halo substructure. SDSS-Gaia is an astrometric catalogue that exploits SDSS data release 9 to provide first epoch photometry for objects in the Gaia source catalogue. We use a version of the catalogue containing 245 316 stars with all phase-space coordinates within a heliocentric distance of ˜10 kpc. We devise a method to assess the significance of halo substructures based on their clustering in velocity space. The two most substantial structures are multiple wraps of a stream which has undergone considerable phase mixing (S1, with 94 members) and a kinematically cold stream (S2, with 61 members). The member stars of S1 have a median position of (X, Y, Z) = (8.12, -0.22, 2.75) kpc and a median metallicity of [Fe/H] = -1.78. The stars of S2 have median coordinates (X, Y, Z) = (8.66, 0.30, 0.77) kpc and a median metallicity of [Fe/H] = -1.91. They lie in velocity space close to some of the stars in the stream reported by Helmi et al. By modelling, we estimate that both structures had progenitors with virial masses ≈1010M⊙ and infall times ≳ 9 Gyr ago. Using abundance matching, these correspond to stellar masses between 106 and 107M⊙. These are somewhat larger than the masses inferred through the mass-metallicity relation by factors of 5 to 15. Additionally, we identify two further substructures (S3 and S4 with 55 and 40 members) and two clusters or moving group (C1 and C2 with 24 and 12) members. In all six cases, clustering in kinematics is found to correspond to clustering in both configuration space and metallicity, adding credence to the reliability of our detections.

Prediction of Machine Tool Condition Using Support Vector Machine

International Nuclear Information System (INIS)

Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

2011-01-01

Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

Fast and accurate protein substructure searching with simulated annealing and GPUs

Directory of Open Access Journals (Sweden)

Stivala Alex D

2010-09-01

Full Text Available Abstract Background Searching a database of protein structures for matches to a query structure, or occurrences of a structural motif, is an important task in structural biology and bioinformatics. While there are many existing methods for structural similarity searching, faster and more accurate approaches are still required, and few current methods are capable of substructure (motif searching. Results We developed an improved heuristic for tableau-based protein structure and substructure searching using simulated annealing, that is as fast or faster and comparable in accuracy, with some widely used existing methods. Furthermore, we created a parallel implementation on a modern graphics processing unit (GPU. Conclusions The GPU implementation achieves up to 34 times speedup over the CPU implementation of tableau-based structure search with simulated annealing, making it one of the fastest available methods. To the best of our knowledge, this is the first application of a GPU to the protein structural search problem.

Guided Iterative Substructure Search (GI-SSS) - A New Trick for an Old Dog.

Science.gov (United States)

Weskamp, Nils

2016-07-01

Substructure search (SSS) is a fundamental technique supported by various chemical information systems. Many users apply it in an iterative manner: they modify their queries to shape the composition of the retrieved hit sets according to their needs. We propose and evaluate two heuristic extensions of SSS aimed at simplifying these iterative query modifications by collecting additional information during query processing and visualizing this information in an intuitive way. This gives the user a convenient feedback on how certain changes to the query would affect the retrieved hit set and reduces the number of trial-and-error cycles needed to generate an optimal search result. The proposed heuristics are simple, yet surprisingly effective and can be easily added to existing SSS implementations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ring and jet study on the azimuthal substructure of pions at CERN ...

Indian Academy of Sciences (India)

structures in the emission of secondary charged hadrons coming from 32S–Ag/Br interactions at 200 A GeV/c. Nuclear photographic emulsion technique has been employed to collect the experimental data. The presence of such substructures, ...

Substructure formation in iron-nickel monocrystals at cellular growth

International Nuclear Information System (INIS)

Agapova, E.V.; Tagirova, D.M.

1984-01-01

Substructural perfection of Fe-31 wt.% Ni alloy crystals prepared by the Bridgeman method is investigated. Characteristics of banded and cellular structures at different morphology of crystallization front corresponding to the rates of growth (7.0-24.7)x10 -4 cm/s are determined. Position of disorientation axis of banded fragments is shown to depend on orientation of a groWing crystal and its strong fragmentation results in formation of finer cellular structure

Analysis of the state of the art of precast concrete bridge substructure systems.

Science.gov (United States)

2013-10-01

Precasting of bridge substructure components holds potential for accelerating the construction of bridges,reducing : impacts to the traveling public on routes adjacent to construction sites, improving bridge durability and hence service : life, and r...

Prefabricated floor panels composed of fiber reinforced concrete and a steel substructure

DEFF Research Database (Denmark)

Lárusson, Lárus H.; Fischer, Gregor; Jönsson, Jeppe

2013-01-01

This paper reports on a study on prefabricated composite and modular floor deck panels composed of relatively thin fiber reinforced concrete slabs connected to steel substructures. The study focuses on the design, manufacturing, structural improvements and behavior of the floor systems during...

Exploring Milkyway Halo Substructures with Large-Area Sky Surveys

Energy Technology Data Exchange (ETDEWEB)

Li, Ting [Texas A & M Univ., College Station, TX (United States)

2016-01-01

Over the last two decades, our understanding of the Milky Way has been improved thanks to large data sets arising from large-area digital sky surveys. The stellar halo is now known to be inhabited by a variety of spatial and kinematic stellar substructures, including stellar streams and stellar clouds, all of which are predicted by hierarchical Lambda Cold Dark Matter models of galaxy formation. In this dissertation, we first present the analysis of spectroscopic observations of individual stars from the two candidate structures discovered using an M-giant catalog from the Two Micron All-Sky Survey. The follow-up observations show that one of the candidates is a genuine structure which might be associated with the Galactic Anticenter Stellar Structure, while the other one is a false detection due to the systematic photometric errors in the survey or dust extinction in low Galactic latitudes. We then presented the discovery of an excess of main sequence turn-off stars in the direction of the constellations of Eridanus and Phoenix from the first-year data of the Dark Energy Survey (DES) – a five-year, 5,000 deg2 optical imaging survey in the Southern Hemisphere. The Eridanus-Phoenix (EriPhe) overdensity is centered around l ~ 285° and b ~ -60° and the Poisson significance of the detection is at least 9σ. The EriPhe overdensity has a cloud-like morphology and the extent is at least ~ 4 kpc by ~ 3 kpc in projection, with a heliocentric distance of about d ~ 16 kpc. The EriPhe overdensity is morphologically similar to the previously-discovered Virgo overdensity and Hercules-Aquila cloud. These three overdensities lie along a polar plane separated by ~ 120° and may share a common origin. In addition to the scientific discoveries, we also present the work to improve the photometric calibration in DES using auxiliary calibration systems, since the photometric errors can cause false detection in first the halo substructure. We present a detailed description of the two

Indonesian Stock Prediction using Support Vector Machine (SVM

Directory of Open Access Journals (Sweden)

Santoso Murtiyanto

2018-01-01

Full Text Available This project is part of developing software to provide predictive information technology-based services artificial intelligence (Machine Intelligence or Machine Learning that will be utilized in the money market community. The prediction method used in this early stages uses the combination of Gaussian Mixture Model and Support Vector Machine with Python programming. The system predicts the price of Astra International (stock code: ASII.JK stock data. The data used was taken during 17 yr period of January 2000 until September 2017. Some data was used for training/modeling (80 % of data and the remainder (20 % was used for testing. An integrated model comprising Gaussian Mixture Model and Support Vector Machine system has been tested to predict stock market of ASII.JK for l d in advance. This model has been compared with the Market Cummulative Return. From the results, it is depicts that the Gaussian Mixture Model-Support Vector Machine based stock predicted model, offers significant improvement over the compared models resulting sharpe ratio of 3.22.

Updating failure probability of a welded joint in offshore wind turbine substructures

DEFF Research Database (Denmark)

Mai, Quang A.; Sørensen, John Dalsgaard; Rigo, Philippe

2016-01-01

The operation and maintenance cost of offshore wind turbine substructures contributes significantly in the cost of a kWh. That cost may be lowered by application of reliability- and risk based maintenance strategies and reliability updating based on inspections performed during the design lifetim...

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes.

Science.gov (United States)

Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-10-03

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.

Development of an expert system for the simulation model for casting metal substructure of a metal-ceramic crown design.

Science.gov (United States)

Matin, Ivan; Hadzistevic, Miodrag; Vukelic, Djordje; Potran, Michal; Brajlih, Tomaz

2017-07-01

Nowadays, the integrated CAD/CAE systems are favored solutions for the design of simulation models for casting metal substructures of metal-ceramic crowns. The worldwide authors have used different approaches to solve the problems using an expert system. Despite substantial research progress in the design of experts systems for the simulation model design and manufacturing have insufficiently considered the specifics of casting in dentistry, especially the need for further CAD, RE, CAE for the estimation of casting parameters and the control of the casting machine. The novel expert system performs the following: CAD modeling of the simulation model for casting, fast modeling of gate design, CAD eligibility and cast ability check of the model, estimation and running of the program code for the casting machine, as well as manufacturing time reduction of the metal substructure. The authors propose an integration method using common data model approach, blackboard architecture, rule-based reasoning and iterative redesign method. Arithmetic mean roughness values was determinated with constant Gauss low-pass filter (cut-off length of 2.5mm) according to ISO 4287 using Mahr MARSURF PS1. Dimensional deviation between the designed model and manufactured cast was determined using the coordinate measuring machine Zeiss Contura G2 and GOM Inspect software. The ES allows for obtaining the castings derived roughness grade number N7. The dimensional deviation between the simulation model of the metal substructure and the manufactured cast is 0.018mm. The arithmetic mean roughness values measured on the casting substructure are from 1.935µm to 2.778µm. The realized developed expert system with the integrated database is fully applicable for the observed hardware and software. Values of the arithmetic mean roughness and dimensional deviation indicate that casting substructures are surface quality, which is more than enough and useful for direct porcelain veneering. The

Reheating effects in the matter power spectrum and implications for substructure

International Nuclear Information System (INIS)

Erickcek, Adrienne L.; Sigurdson, Kris

2011-01-01

The thermal and expansion history of the Universe before big bang nucleosynthesis is unknown. We investigate the evolution of cosmological perturbations through the transition from an early matter era to radiation domination. We treat reheating as the perturbative decay of an oscillating scalar field into relativistic plasma and cold dark matter. After reheating, we find that subhorizon perturbations in the decay-produced dark matter density are significantly enhanced, while subhorizon radiation perturbations are instead suppressed. If dark matter originates in the radiation bath after reheating, this suppression may be the primary cutoff in the matter power spectrum. Conversely, for dark matter produced nonthermally from scalar decay, enhanced perturbations can drive structure formation during the cosmic dark ages and dramatically increase the abundance of compact substructures. For low reheat temperatures, we find that as much as 50% of all dark matter is in microhalos with M > or approx. 0.1M + at z≅100, compared to a fraction of ∼10 -10 in the standard case. In this scenario, ultradense substructures may constitute a large fraction of dark matter in galaxies today.

Substructures developed during creep and cyclic tests of type 304 stainless steel (heat 9T2796)

International Nuclear Information System (INIS)

Swindeman, R.W.; Bhargava, R.K.; Sikka, V.K.; Moteff, J.

1977-09-01

Substructures developed in tested specimens of a reference heat of type 304 stainless steel (heat 9T2796) are examined. Data include dislocation densities, cell and subgrain sizes, and carbide precipitate sizes. Testing conditions range for temperatures from 482 to 649 0 C, for stresses from 28 to 241 MPa, and for times from 4 to 15,000 hr. As expected, it is observed that temperature, stress, and time have strong influences on substructure. The change in the dislocation density is too small to measure for conditions which produce less than 1 percent monotonic strain. No cells form, and the major alteration of substructure is the precipitation of M 23 C 6 carbides on grain boundaries, on twin boundaries, and on some dislocations. At stresses ranging from 69 to 172 MPa and at temperatures ranging from 482 to 593 0 C, the dislocation density increases with increasing stress and is generally higher than expected from studies made at higher temperatures. Dislocations are arranged in fine networks stabilized by carbides. At stresses above 172 MPa and temperatures to 649 0 C, the dislocation density is too great to measure. Cells develop which are finer in size than cells developed at similar stresses but at higher temperatures. Dislocation densities and cell sizes for cyclic specimens are comparable to data for creep-tested specimens. On the basis of the observed substructures, recommendations are made regarding further studies which would assist in the development of constitutive equations for high-temperature inelastic analysis of reactor components

The Substructure of the Solar Corona Observed in the Hi-C Telescope

Science.gov (United States)

Winebarger, A.; Cirtain, J.; Golub, L.; DeLuca, E.; Savage, S.; Alexander, C.; Schuler, T.

2014-01-01

In the summer of 2012, the High-resolution Coronal Imager (Hi-C) flew aboard a NASA sounding rocket and collected the highest spatial resolution images ever obtained of the solar corona. One of the goals of the Hi-C flight was to characterize the substructure of the solar corona. We therefore calculate how the intensity scales from a low-resolution (AIA) pixels to high-resolution (Hi-C) pixels for both the dynamic events and "background" emission (meaning, the steady emission over the 5 minutes of data acquisition time). We find there is no evidence of substructure in the background corona; the intensity scales smoothly from low-resolution to high-resolution Hi-C pixels. In transient events, however, the intensity observed with Hi-C is, on average, 2.6 times larger than observed with AIA. This increase in intensity suggests that AIA is not resolving these events. This result suggests a finely structured dynamic corona embedded in a smoothly varying background.

THE NEXT GENERATION VIRGO CLUSTER SURVEY. XIX. TOMOGRAPHY OF MILKY WAY SUBSTRUCTURES IN THE NGVS FOOTPRINT

Energy Technology Data Exchange (ETDEWEB)

Lokhorst, Deborah; Starkenburg, Else; Navarro, Julio F. [Department of Physics and Astronomy, University of Victoria, Victoria, BC V8P 1A1, Canada (Canada); McConnachie, Alan W.; Ferrarese, Laura; Côté, Patrick; Gwyn, Stephen D. J. [National Research Council, Herzberg Astronomy and Astrophysics, 5071 West Saanich Road, Victoria, BC V9E 2E7 (Canada); Liu, Chengze [Center for Astronomy and Astrophysics, Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240 (China); Peng, Eric W. [Department of Astronomy, Peking University, Beijing 100871 (China); Cuillandre, Jean-Charles [CEA/IRFU/SAP, Laboratoire AIM Paris-Saclay, CNRS/INSU, Université Paris Diderot, Observatoire de Paris, PSL Research University, F-91191 Gif-sur-Yvette Cedex (France); Guhathakurta, Puragra, E-mail: dml@uvic.ca [Department of Astronomy and Astrophysics, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064 (United States)

2016-03-10

The Next Generation Virgo Cluster Survey (NGVS) is a deep u*giz survey targeting the Virgo Cluster of galaxies at 16.5 Mpc. This survey provides high-quality photometry over an ∼100 deg{sup 2} region straddling the constellations of Virgo and Coma Berenices. This sightline through the Milky Way is noteworthy in that it intersects two of the most prominent substructures in the Galactic halo: the Virgo overdensity (VOD) and Sagittarius stellar stream (close to its bifurcation point). In this paper, we use deep u*gi imaging from the NGVS to perform tomography of the VOD and Sagittarius stream using main-sequence turnoff (MSTO) stars as a halo tracer population. The VOD, whose centroid is known to lie at somewhat lower declinations (α ∼ 190°, δ ∼ −5°) than is covered by the NGVS, is nevertheless clearly detected in the NGVS footprint at distances between ∼8 and 25 kpc. By contrast, the Sagittarius stream is found to slice directly across the NGVS field at distances between 25 and 40 kpc, with a density maximum at ≃35 kpc. No evidence is found for new substructures beyond the Sagittarius stream, at least out to a distance of ∼90 kpc—the largest distance to which we can reliably trace the halo using MSTO stars. We find clear evidence for a distance gradient in the Sagittarius stream across the ∼30° of sky covered by the NGVS and its flanking fields. We compare our distance measurements along the stream with those predicted by leading stream models.

THE NEXT GENERATION VIRGO CLUSTER SURVEY. XIX. TOMOGRAPHY OF MILKY WAY SUBSTRUCTURES IN THE NGVS FOOTPRINT

International Nuclear Information System (INIS)

Lokhorst, Deborah; Starkenburg, Else; Navarro, Julio F.; McConnachie, Alan W.; Ferrarese, Laura; Côté, Patrick; Gwyn, Stephen D. J.; Liu, Chengze; Peng, Eric W.; Cuillandre, Jean-Charles; Guhathakurta, Puragra

2016-01-01

The Next Generation Virgo Cluster Survey (NGVS) is a deep u*giz survey targeting the Virgo Cluster of galaxies at 16.5 Mpc. This survey provides high-quality photometry over an ∼100 deg 2 region straddling the constellations of Virgo and Coma Berenices. This sightline through the Milky Way is noteworthy in that it intersects two of the most prominent substructures in the Galactic halo: the Virgo overdensity (VOD) and Sagittarius stellar stream (close to its bifurcation point). In this paper, we use deep u*gi imaging from the NGVS to perform tomography of the VOD and Sagittarius stream using main-sequence turnoff (MSTO) stars as a halo tracer population. The VOD, whose centroid is known to lie at somewhat lower declinations (α ∼ 190°, δ ∼ −5°) than is covered by the NGVS, is nevertheless clearly detected in the NGVS footprint at distances between ∼8 and 25 kpc. By contrast, the Sagittarius stream is found to slice directly across the NGVS field at distances between 25 and 40 kpc, with a density maximum at ≃35 kpc. No evidence is found for new substructures beyond the Sagittarius stream, at least out to a distance of ∼90 kpc—the largest distance to which we can reliably trace the halo using MSTO stars. We find clear evidence for a distance gradient in the Sagittarius stream across the ∼30° of sky covered by the NGVS and its flanking fields. We compare our distance measurements along the stream with those predicted by leading stream models

Decision Support for Flood Event Prediction and Monitoring

DEFF Research Database (Denmark)

Mioc, Darka; Anton, François; Liang, Gengsheng

2007-01-01

In this paper the development of Web GIS based decision support system for flood events is presented. To improve flood prediction we developed the decision support system for flood prediction and monitoring that integrates hydrological modelling and CARIS GIS. We present the methodology for data...... integration, floodplain delineation, and online map interfaces. Our Web-based GIS model can dynamically display observed and predicted flood extents for decision makers and the general public. The users can access Web-based GIS that models current flood events and displays satellite imagery and digital...... elevation model integrated with flood plain area. The system can show how the flooding prediction based on the output from hydrological modeling for the next 48 hours along the lower Saint John River Valley....

CLOSE STELLAR ENCOUNTERS IN YOUNG, SUBSTRUCTURED, DISSOLVING STAR CLUSTERS: STATISTICS AND EFFECTS ON PLANETARY SYSTEMS

International Nuclear Information System (INIS)

Craig, Jonathan; Krumholz, Mark R.

2013-01-01

Both simulations and observations indicate that stars form in filamentary, hierarchically clustered associations, most of which disperse into their galactic field once feedback destroys their parent clouds. However, during their early evolution in these substructured environments, stars can undergo close encounters with one another that might have significant impacts on their protoplanetary disks or young planetary systems. We perform N-body simulations of the early evolution of dissolving, substructured clusters with a wide range of properties, with the aim of quantifying the expected number and orbital element distributions of encounters as a function of cluster properties. We show that the presence of substructure both boosts the encounter rate and modifies the distribution of encounter velocities compared to what would be expected for a dynamically relaxed cluster. However, the boost only lasts for a dynamical time, and as a result the overall number of encounters expected remains low enough that gravitational stripping is unlikely to be a significant effect for the vast majority of star-forming environments in the Galaxy. We briefly discuss the implications of this result for models of the origin of the solar system, and of free-floating planets. We also provide tabulated encounter rates and orbital element distributions suitable for inclusion in population synthesis models of planet formation in a clustered environment.

CLOSE STELLAR ENCOUNTERS IN YOUNG, SUBSTRUCTURED, DISSOLVING STAR CLUSTERS: STATISTICS AND EFFECTS ON PLANETARY SYSTEMS

Energy Technology Data Exchange (ETDEWEB)

Craig, Jonathan; Krumholz, Mark R., E-mail: krumholz@ucolick.org [Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States)

2013-06-01

Both simulations and observations indicate that stars form in filamentary, hierarchically clustered associations, most of which disperse into their galactic field once feedback destroys their parent clouds. However, during their early evolution in these substructured environments, stars can undergo close encounters with one another that might have significant impacts on their protoplanetary disks or young planetary systems. We perform N-body simulations of the early evolution of dissolving, substructured clusters with a wide range of properties, with the aim of quantifying the expected number and orbital element distributions of encounters as a function of cluster properties. We show that the presence of substructure both boosts the encounter rate and modifies the distribution of encounter velocities compared to what would be expected for a dynamically relaxed cluster. However, the boost only lasts for a dynamical time, and as a result the overall number of encounters expected remains low enough that gravitational stripping is unlikely to be a significant effect for the vast majority of star-forming environments in the Galaxy. We briefly discuss the implications of this result for models of the origin of the solar system, and of free-floating planets. We also provide tabulated encounter rates and orbital element distributions suitable for inclusion in population synthesis models of planet formation in a clustered environment.

Close Stellar Encounters in Young, Substructured, Dissolving Star Clusters: Statistics and Effects on Planetary Systems

Science.gov (United States)

Craig, Jonathan; Krumholz, Mark R.

2013-06-01

Both simulations and observations indicate that stars form in filamentary, hierarchically clustered associations, most of which disperse into their galactic field once feedback destroys their parent clouds. However, during their early evolution in these substructured environments, stars can undergo close encounters with one another that might have significant impacts on their protoplanetary disks or young planetary systems. We perform N-body simulations of the early evolution of dissolving, substructured clusters with a wide range of properties, with the aim of quantifying the expected number and orbital element distributions of encounters as a function of cluster properties. We show that the presence of substructure both boosts the encounter rate and modifies the distribution of encounter velocities compared to what would be expected for a dynamically relaxed cluster. However, the boost only lasts for a dynamical time, and as a result the overall number of encounters expected remains low enough that gravitational stripping is unlikely to be a significant effect for the vast majority of star-forming environments in the Galaxy. We briefly discuss the implications of this result for models of the origin of the solar system, and of free-floating planets. We also provide tabulated encounter rates and orbital element distributions suitable for inclusion in population synthesis models of planet formation in a clustered environment.

Seasonal variations of radon concentrations in single-family houses with different sub-structures

DEFF Research Database (Denmark)

Majborn, B.

1992-01-01

Seasonal variations of indoor radon concentrations have been studied in 70 single-family houses selected according to the type of sub-structure and the type of soil underneath the house. Five categories of sub-structure were included - slab-on-grade, crawl space, basement, and combinations...... of basement with slab-on-grade or crawl space. Half of the houses are located on clayey till and the other half on glaciofluvial gravel. In each house radon was measured in a living room and a bedroom, in the basement if present, and in the crawl space if present and accessible. The measurements were made...... with track detectors on a quarterly basis throughout a year. For living rooms and bedrooms the seasonal variations range from being highly significant for the slab-on-grade houses to being insignificant for the crawl space houses. For basements and crawl spaces the geometric mean radon concentrations do...

Mechanical strenght and niobium and niobium-base alloys substructures

International Nuclear Information System (INIS)

Monteiro, W.A.; Andrade, A.H.P. de

1986-01-01

Niobium and some of its alloys have been used in several fields of technological applications such as the aerospace, chemical and nuclear industries. This is due to its excelent mechanical stringth at high temperatures and reasonable ductility at low temperatures. In this work, we review the main features of the relationship mechanical strength - substructure in niobium and its alloys, taking into account the presence of impurities, the influence of initial thermal and thermo - mechanical treatments as well as the irradiation by energetic particles. (Author) [pt

Searching for dwarf spheroidal galaxies and other galactic dark matter substructures with the Fermi large area telescope

Energy Technology Data Exchange (ETDEWEB)

Drlica-Wagner, Alex [Stanford Univ., CA (United States). Dept. of Physics

2013-08-01

Over the past century, it has become clear that about a quarter of the known universe is composed of an invisible, massive component termed ''dark matter''. Some of the most popular theories of physics beyond the Standard Model suggest that dark matter may be a new fundamental particle that could self-annihilate to produce γ rays. Nearby over-densities in the dark matter halo of our Milky Way present some of the most promising targets for detecting the annihilation of dark matter. We used the Large Area Telescope (LAT) on-board the Fermi Gamma-ray Space Telescope to search for γ rays produced by dark matter annihilation in Galactic dark matter substructures. We searched for γ-ray emission coincident with Milky Way dwarf spheroidal satellite galaxies, which trace the most massive Galactic dark matter substructures. We also sought to identify nearby dark matter substructures that lack all astrophysical tracers and would be detectable only through γ-ray emission from dark matter annihilation. We found no conclusive evidence for γ-ray emission from dark matter annihilation, and we set stringent and robust constraints on the dark matter annihilation cross section. While γ-ray searches for dark matter substructure are currently the most sensitive and robust probes of dark matter annihilation, they are just beginning to intersect the theoretically preferred region of dark matter parameter space. Thus, we consider future prospects for increasing the sensitivity of γ-ray searches through improvements to the LAT instrument performance and through upcoming wide- field optical surveys.

Polyamorphism and substructure of short-range order in amorphous boron films

International Nuclear Information System (INIS)

Palatnik, L.S.; Nechitajlo, A.A.; Koz'ma, A.A.

1981-01-01

The structure and substructure of boron amorphous films are studied in detail. Amorphous condensate of Bsup(a) boron is built of the same (but only disorientedly located) 12 B icosahedrons as boron crystalline modifications: B 105 -equilibrium β-rhombic, metastable: B 50 -tetragonal, B 12 -α-rhombohedral Coordination number for Bsup(a) (Z 1 =6.4) is lower than in B 105 (Z 1 =6.6) but higher than in B 50 modification (Z 1 =6.1). In crystalline modifications B 105 , B 50 , B 12 coordination numbers ω in first coordination spheres of icosahedrons are equal to ν 105 =6+4.6=10.6; ν 50 =10+3=14; ν 12 =6 respectively. Both amorphous modifications of boron Bsub(1)sup(a) and Bsub(15)sup(a) are analogs to B 50 in respect of the short-range order of icosahedron location. The difference between them is in ''substructure'' of short-range order: part of boron atoms (approximately 12%) do not occupy the vertices (so that vacancies appear) and enter the emptinesses between icosahedrons. In other words, the structure B 50 is the model basis of both amorphous phases [ru

3D Representative Volume Element Reconstruction of Fiber Composites via Orientation Tensor and Substructure Features

Energy Technology Data Exchange (ETDEWEB)

Li, Yi; Chen, Wei; Xu, Hongyi; Jin, Xuejun

2016-01-01

To provide a seamless integration of manufacturing processing simulation and fiber microstructure modeling, two new stochastic 3D microstructure reconstruction methods are proposed for two types of random fiber composites: random short fiber composites, and Sheet Molding Compounds (SMC) chopped fiber composites. A Random Sequential Adsorption (RSA) algorithm is first developed to embed statistical orientation information into 3D RVE reconstruction of random short fiber composites. For the SMC composites, an optimized Voronoi diagram based approach is developed for capturing the substructure features of SMC chopped fiber composites. The proposed methods are distinguished from other reconstruction works by providing a way of integrating statistical information (fiber orientation tensor) obtained from material processing simulation, as well as capturing the multiscale substructures of the SMC composites.

The Next Generation Virgo Cluster Survey (NGVS). XXXII. A Search for Globular Cluster Substructures in the Virgo Galaxy Cluster Core

Science.gov (United States)

Powalka, Mathieu; Puzia, Thomas H.; Lançon, Ariane; Longobardi, Alessia; Peng, Eric W.; Duc, Pierre-Alain; Alamo-Martínez, Karla; Blakeslee, John P.; Côté, Patrick; Cuillandre, Jean-Charles; Durrell, Patrick; Eigenthaler, Paul; Ferrarese, Laura; Guhathakurta, Puragra; Gwyn, S. D. J.; Hudelot, Patrick; Liu, Chengze; Mei, Simona; Muñoz, Roberto P.; Roediger, Joel; Sánchez-Janssen, Rubén; Toloba, Elisa; Zhang, Hongxin

2018-03-01

Substructure in globular cluster (GC) populations around large galaxies is expected in galaxy formation scenarios that involve accretion or merger events, and it has been searched for using direct associations between GCs and structure in the diffuse galaxy light, or with GC kinematics. Here, we present a search for candidate substructures in the GC population around the Virgo cD galaxy M87 through the analysis of the spatial distribution of the GC colors. The study is based on a sample of ∼1800 bright GCs with high-quality u, g, r, i, z, K s photometry, selected to ensure a low contamination by foreground stars or background galaxies. The spectral energy distributions of the GCs are associated with formal estimates of age and metallicity, which are representative of its position in a 4D color space relative to standard single stellar population models. Dividing the sample into broad bins based on the relative formal ages, we observe inhomogeneities that reveal signatures of GC substructures. The most significant of these is a spatial overdensity of GCs with relatively young age labels, of diameter ∼0.°1 (∼30 kpc), located to the south of M87. The significance of this detection is larger than about 5σ after accounting for estimates of random and systematic errors. Surprisingly, no large Virgo galaxy is present in this area that could potentially host these GCs. But candidate substructures in the M87 halo with equally elusive hosts have been described based on kinematic studies in the past. The number of GC spectra available around M87 is currently insufficient to clarify the nature of the new candidate substructure.

Performance of large-R jets and jet substructure reconstruction with the ATLAS detector

CERN Document Server

The ATLAS collaboration

2012-01-01

This paper presents the application of techniques to study jet substructure. The performance of modified jet algorithms for a variety of jet types and event topologies is investigated. Properties of jets subjected to the mass-drop filtering, trimming and pruning algorithms are found to have a reduced sensitivity to multiple proton-proton interactions and exhibit improved stability at high luminosity. Monte Carlo studies of the signal-background discrimination with jet grooming in new physics searches based on jet invariant mass and jet substructure properties are also presented. The application of jet trimming is shown to improve the robustness of large-R jet measurements, reduce sensitivity to the superfluous effects due to the intense environment of the high luminosity LHC, and improve the physics potential of searches for heavy boosted objects. The analyses presented in this note use the full 2011 ATLAS dataset, corresponding to an integrated luminosity of 4.7 \\pm 0.2 fb−1 .

Reduction of fatigue loads on jacket substructure through blade design optimization for multimegawatt wind turbines at 50 m water depths

DEFF Research Database (Denmark)

NJOMO WANDJI, Wilfried; Pavese, Christian; Natarajan, Anand

2016-01-01

This paper addresses the reduction of the fore-aft damage equivalent moment at the tower base for multi-megawatt offshore wind turbines mounted on jacket type substructures at 50 m water depths. The study investigates blade design optimization of a reference 10 MW wind turbine under standard wind...... conditions of onshore sites. The blade geometry and structure is optimized to yield a design that minimizes tower base fatigue loads without significant loss of power production compared to that of the reference setup. The resulting blade design is then mounted on a turbine supported by a jacket and placed...

Thinking outside the ROCs: Designing Decorrelated Taggers (DDT) for jet substructure

CERN Document Server

Dolen, James; Marzani, Simone; Rappoccio, Salvatore; Tran, Nhan

2016-01-01

We explore the scale-dependence and correlations of jet substructure observables to improve upon existing techniques in the identification of highly Lorentz-boosted objects. Modified observables are designed to remove correlations from existing theoretically well-understood observables, providing practical advantages for experimental measurements and searches for new phenomena. We study such observables in $W$ jet tagging and provide recommendations for observables based on considerations beyond signal and background efficiencies.

Thinking outside the ROCs: Designing decorrelated taggers (DDT) for jet substructure

International Nuclear Information System (INIS)

Dolen, James; Harris, Philip; Marzani, Simone; Rappoccio, Salvatore; Tran, Nhan

2016-01-01

Here, we explore the scale-dependence and correlations of jet substructure observables to improve upon existing techniques in the identification of highly Lorentz-boosted objects. Modified observables are designed to remove correlations from existing theoretically well-understood observables, providing practical advantages for experimental measurements and searches for new phenomena. We study such observables in W jet tagging and provide recommendations for observables based on considerations beyond signal and background efficiencies

Analysis of the forced vibration test of the Hualien large scale soil-structure interaction model using a flexible volume substructuring method

International Nuclear Information System (INIS)

Tang, H.T.; Nakamura, N.

1995-01-01

A 1/4-scale cylindrical reactor containment model was constructed in Hualien, Taiwan for foil-structure interaction (SSI) effect evaluation and SSI analysis procedure verification. Forced vibration tests were executed before backfill (FVT-1) and after backfill (FVT-2) to characterize soil-structure system characteristics under low excitations. A number of organizations participated in the pre-test blind prediction and post-test correlation analyses of the forced vibration test using various industry familiar methods. In the current study, correlation analyses were performed using a three-dimensional flexible volume substructuring method. The results are reported and soil property sensitivities are evaluated in the paper. (J.P.N.)

Slope Deformation Prediction Based on Support Vector Machine

Directory of Open Access Journals (Sweden)

Lei JIA

2013-07-01

Full Text Available This paper principally studies the prediction of slope deformation based on Support Vector Machine (SVM. In the prediction process，explore how to reconstruct the phase space. The geological body’s displacement data obtained from chaotic time series are used as SVM’s training samples. Slope displacement caused by multivariable coupling is predicted by means of single variable. Results show that this model is of high fitting accuracy and generalization, and provides reference for deformation prediction in slope engineering.

Toward Predicting Social Support Needs in Online Health Social Networks.

Science.gov (United States)

Choi, Min-Je; Kim, Sung-Hee; Lee, Sukwon; Kwon, Bum Chul; Yi, Ji Soo; Choo, Jaegul; Huh, Jina

2017-08-02

While online health social networks (OHSNs) serve as an effective platform for patients to fulfill their various social support needs, predicting the needs of users and providing tailored information remains a challenge. The objective of this study was to discriminate important features for identifying users' social support needs based on knowledge gathered from survey data. This study also provides guidelines for a technical framework, which can be used to predict users' social support needs based on raw data collected from OHSNs. We initially conducted a Web-based survey with 184 OHSN users. From this survey data, we extracted 34 features based on 5 categories: (1) demographics, (2) reading behavior, (3) posting behavior, (4) perceived roles in OHSNs, and (5) values sought in OHSNs. Features from the first 4 categories were used as variables for binary classification. For the prediction outcomes, we used features from the last category: the needs for emotional support, experience-based information, unconventional information, and medical facts. We compared 5 binary classifier algorithms: gradient boosting tree, random forest, decision tree, support vector machines, and logistic regression. We then calculated the scores of the area under the receiver operating characteristic (ROC) curve (AUC) to understand the comparative effectiveness of the used features. The best performance was AUC scores of 0.89 for predicting users seeking emotional support, 0.86 for experience-based information, 0.80 for unconventional information, and 0.83 for medical facts. With the gradient boosting tree as our best performing model, we analyzed the strength of individual features in predicting one's social support need. Among other discoveries, we found that users seeking emotional support tend to post more in OHSNs compared with others. We developed an initial framework for automatically predicting social support needs in OHSNs using survey data. Future work should involve nonsurvey

Dynamic analysis of clustered building structures using substructures methods

International Nuclear Information System (INIS)

Leimbach, K.R.; Krutzik, N.J.

1989-01-01

The dynamic substructure approach to the building cluster on a common base mat starts with the generation of Ritz-vectors for each building on a rigid foundation. The base mat plus the foundation soil is subjected to kinematic constraint modes, for example constant, linear, quadratic or cubic constraints. These constraint modes are also imposed on the buildings. By enforcing kinematic compatibility of the complete structural system on the basis of the constraint modes a reduced Ritz model of the complete cluster is obtained. This reduced model can now be analyzed by modal time history or response spectrum methods

Substructure analysis techniques and automation. [to eliminate logistical data handling and generation chores

Science.gov (United States)

Hennrich, C. W.; Konrath, E. J., Jr.

1973-01-01

A basic automated substructure analysis capability for NASTRAN is presented which eliminates most of the logistical data handling and generation chores that are currently associated with the method. Rigid formats are proposed which will accomplish this using three new modules, all of which can be added to level 16 with a relatively small effort.

Automatic identification of mobile and rigid substructures in molecular dynamics simulations and fractional structural fluctuation analysis.

Directory of Open Access Journals (Sweden)

Leandro Martínez

Full Text Available The analysis of structural mobility in molecular dynamics plays a key role in data interpretation, particularly in the simulation of biomolecules. The most common mobility measures computed from simulations are the Root Mean Square Deviation (RMSD and Root Mean Square Fluctuations (RMSF of the structures. These are computed after the alignment of atomic coordinates in each trajectory step to a reference structure. This rigid-body alignment is not robust, in the sense that if a small portion of the structure is highly mobile, the RMSD and RMSF increase for all atoms, resulting possibly in poor quantification of the structural fluctuations and, often, to overlooking important fluctuations associated to biological function. The motivation of this work is to provide a robust measure of structural mobility that is practical, and easy to interpret. We propose a Low-Order-Value-Optimization (LOVO strategy for the robust alignment of the least mobile substructures in a simulation. These substructures are automatically identified by the method. The algorithm consists of the iterative superposition of the fraction of structure displaying the smallest displacements. Therefore, the least mobile substructures are identified, providing a clearer picture of the overall structural fluctuations. Examples are given to illustrate the interpretative advantages of this strategy. The software for performing the alignments was named MDLovoFit and it is available as free-software at: http://leandro.iqm.unicamp.br/mdlovofit.

Lensing substructure quantification in RXJ1131-1231: a 2 keV lower bound on dark matter thermal relic mass

Energy Technology Data Exchange (ETDEWEB)

Birrer, Simon; Amara, Adam; Refregier, Alexandre, E-mail: simon.birrer@phys.ethz.ch, E-mail: adam.amara@phys.ethz.ch, E-mail: alexandre.refregier@phys.ethz.ch [Institute for Astronomy, Department of Physics, ETH Zurich, Wolfgang-Pauli-Strasse 27, 8093, Zurich (Switzerland)

2017-05-01

We study the substructure content of the strong gravitational lens RXJ1131-1231 through a forward modelling approach that relies on generating an extensive suite of realistic simulations. We use a semi-analytic merger tree prescription that allows us to stochastically generate substructure populations whose properties depend on the dark matter particle mass. These synthetic halos are then used as lenses to produce realistic mock images that have the same features, e.g. luminous arcs, quasar positions, instrumental noise and PSF, as the data. We then analyse the data and the simulations in the same way with summary statistics that are sensitive to the signal being targeted and are able to constrain models of dark matter statistically using Approximate Bayesian Computing (ABC) techniques. (In this work, we focus on the thermal relic mass estimate and fix the semi-analytic descriptions of the substructure evolution based on recent literature.) We are able, based on the HST data for RXJ1131-1231, to rule out a warm dark matter thermal relic mass below 2 keV at the 2σ confidence level.

THE BOLOCAM GALACTIC PLANE SURVEY. XI. TEMPERATURES AND SUBSTRUCTURE OF GALACTIC CLUMPS BASED ON 350 μM OBSERVATIONS

Energy Technology Data Exchange (ETDEWEB)

Merello, Manuel; Evans II, Neal J. [The University of Texas at Austin, Department of Astronomy, 2515 Speedway, Stop C1400, Austin, TX 78712-1205 (United States); Shirley, Yancy L. [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Rosolowsky, Erik [Department of Physics, 4-181 CCIS, University of Alberta, Edmonton, AB T6G 2E1 (Canada); Ginsburg, Adam [European Southern Observatory, ESO Headquarters, Karl-Schwarzschild-Strasse 2, D-95748 Garching bei Munchen (Germany); Bally, John [CASA, University of Colorado, 389-UCB, Boulder, CO 80309 (United States); Battersby, Cara; Dunham, Michael M., E-mail: manuel@astro.as.utexas.edu [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, MS 78, Cambridge, MA 02138 (United States)

2015-05-15

We present 107 maps of continuum emission at 350 μm from Galactic molecular clumps. Observed sources were mainly selected from the Bolocam Galactic Plane Survey (BGPS) catalog, with three additional maps covering star-forming regions in the outer Galaxy. The higher resolution of the SHARC-II images (8.″5 beam) compared with the 1.1 mm images from BGPS (33″ beam) allowed us to identify a large population of smaller substructures within the clumps. A catalog is presented for the 1386 sources extracted from the 350 μm maps. The color temperature distribution of clumps based on the two wavelengths has a median of 13.3 K and mean of 16.3 ± 0.4 K, assuming an opacity law index of 1.7. For the structures with good determination of color temperatures, the mean ratio of gas temperature, determined from NH{sub 3} observations, to dust color temperature is 0.88 and the median ratio is 0.76. About half the clumps have more than 2 substructures and 22 clumps have more than 10. The fraction of the mass in dense substructures seen at 350 μm compared to the mass of their parental clump is ∼0.19, and the surface densities of these substructures are, on average, 2.2 times those seen in the clumps identified at 1.1 mm. For a well-characterized sample, 88 structures (31%) exceed a surface density of 0.2 g cm{sup −2}, and 18 (6%) exceed 1.0 g cm{sup −2}, thresholds for massive star formation suggested by theorists.

On jet substructure methods for signal jets

Energy Technology Data Exchange (ETDEWEB)

Dasgupta, Mrinal [Consortium for Fundamental Physics, School of Physics & Astronomy, University of Manchester,Oxford Road, Manchester M13 9PL (United Kingdom); Powling, Alexander [School of Physics & Astronomy, University of Manchester,Oxford Road, Manchester M13 9PL (United Kingdom); Siodmok, Andrzej [Institute of Nuclear Physics, Polish Academy of Sciences,ul. Radzikowskiego 152, 31-342 Kraków (Poland); CERN, PH-TH,CH-1211 Geneva 23 (Switzerland)

2015-08-17

We carry out simple analytical calculations and Monte Carlo studies to better understand the impact of QCD radiation on some well-known jet substructure methods for jets arising from the decay of boosted Higgs bosons. Understanding differences between taggers for these signal jets assumes particular significance in situations where they perform similarly on QCD background jets. As an explicit example of this we compare the Y-splitter method to the more recently proposed Y-pruning technique. We demonstrate how the insight we gain can be used to significantly improve the performance of Y-splitter by combining it with trimming and show that this combination outperforms the other taggers studied here, at high p{sub T}. We also make analytical estimates for optimal parameter values, for a range of methods and compare to results from Monte Carlo studies.

A Wavelet Kernel-Based Primal Twin Support Vector Machine for Economic Development Prediction

Directory of Open Access Journals (Sweden)

Fang Su

2013-01-01

Full Text Available Economic development forecasting allows planners to choose the right strategies for the future. This study is to propose economic development prediction method based on the wavelet kernel-based primal twin support vector machine algorithm. As gross domestic product (GDP is an important indicator to measure economic development, economic development prediction means GDP prediction in this study. The wavelet kernel-based primal twin support vector machine algorithm can solve two smaller sized quadratic programming problems instead of solving a large one as in the traditional support vector machine algorithm. Economic development data of Anhui province from 1992 to 2009 are used to study the prediction performance of the wavelet kernel-based primal twin support vector machine algorithm. The comparison of mean error of economic development prediction between wavelet kernel-based primal twin support vector machine and traditional support vector machine models trained by the training samples with the 3–5 dimensional input vectors, respectively, is given in this paper. The testing results show that the economic development prediction accuracy of the wavelet kernel-based primal twin support vector machine model is better than that of traditional support vector machine.

Child Support Payment: A Structural Model of Predictive Variables.

Science.gov (United States)

Wright, David W.; Price, Sharon J.

A major area of concern in divorced families is compliance with child support payments. Aspects of the former spouse relationship that are predictive of compliance with court-ordered payment of child support were investigated in a sample of 58 divorced persons all of whom either paid or received child support. Structured interviews and…

Predicting Tunnel Squeezing Using Multiclass Support Vector Machines

Directory of Open Access Journals (Sweden)

Yang Sun

2018-01-01

Full Text Available Tunnel squeezing is one of the major geological disasters that often occur during the construction of tunnels in weak rock masses subjected to high in situ stresses. It could cause shield jamming, budget overruns, and construction delays and could even lead to tunnel instability and casualties. Therefore, accurate prediction or identification of tunnel squeezing is extremely important in the design and construction of tunnels. This study presents a modified application of a multiclass support vector machine (SVM to predict tunnel squeezing based on four parameters, that is, diameter (D, buried depth (H, support stiffness (K, and rock tunneling quality index (Q. We compiled a database from the literature, including 117 case histories obtained from different countries such as India, Nepal, and Bhutan, to train the multiclass SVM model. The proposed model was validated using 8-fold cross validation, and the average error percentage was approximately 11.87%. Compared with existing approaches, the proposed multiclass SVM model yields a better performance in predictive accuracy. More importantly, one could estimate the severity of potential squeezing problems based on the predicted squeezing categories/classes.

Correlation between the sub-structure parameters and the manufacturing technologies of metal threads in historical textiles using X-ray line profile analysis

Energy Technology Data Exchange (ETDEWEB)

Csiszar, Gabor; Ungar, Tamas [Eoetvoes University Budapest, Department of Materials Physics, Budapest (Hungary); Jaro, Marta [Hungarian National Museum, Budapest (Hungary)

2013-06-15

Micro-structure can talk when documentation is missing. In ancient Roman or medieval periods, kings, queens, or just rich people decorated their clothes or even their horse covers richly with miniature jewels or metal threads. The origin or the fabrication techniques of these ancient threads is often unknown. Thirteen thread samples made of gold or gilt silver manufactured during the last sixteen hundred years are investigated for the micro-structure in terms of dislocation density, crystallite size, and planar defects. In a few cases, these features are compared with sub-structure of similar metallic threads prepared in modern, twentieth century workshops. The sub-structure is determined by X-ray line profile analysis, using high resolution diffractograms with negligible instrumental broadening. On the basis of the sub-structure parameters, we attempt to assess the metal-threads manufacturing procedures on samples stemming from the fourth century A.D. until now. (orig.)

Precast concrete elements for accelerated bridge construction : laboratory testing of precast substructure components, Boone County bridge.

Science.gov (United States)

2009-01-01

Vol. 1-1: In July 2006, construction began on an accelerated bridge project in Boone County, Iowa that was composed of precast substructure : elements and an innovative, precast deck panel system. The superstructure system consisted of full-depth dec...

Convergence properties of halo merger trees; halo and substructure merger rates across cosmic history

Science.gov (United States)

Poole, Gregory B.; Mutch, Simon J.; Croton, Darren J.; Wyithe, Stuart

2017-12-01

We introduce GBPTREES: an algorithm for constructing merger trees from cosmological simulations, designed to identify and correct for pathological cases introduced by errors or ambiguities in the halo finding process. GBPTREES is built upon a halo matching method utilizing pseudo-radial moments constructed from radially sorted particle ID lists (no other information is required) and a scheme for classifying merger tree pathologies from networks of matches made to-and-from haloes across snapshots ranging forward-and-backward in time. Focusing on SUBFIND catalogues for this work, a sweep of parameters influencing our merger tree construction yields the optimal snapshot cadence and scanning range required for converged results. Pathologies proliferate when snapshots are spaced by ≲0.128 dynamical times; conveniently similar to that needed for convergence of semi-analytical modelling, as established by Benson et al. Total merger counts are converged at the level of ∼5 per cent for friends-of-friends (FoF) haloes of size np ≳ 75 across a factor of 512 in mass resolution, but substructure rates converge more slowly with mass resolution, reaching convergence of ∼10 per cent for np ≳ 100 and particle mass mp ≲ 109 M⊙. We present analytic fits to FoF and substructure merger rates across nearly all observed galactic history (z ≤ 8.5). While we find good agreement with the results presented by Fakhouri et al. for FoF haloes, a slightly flatter dependence on merger ratio and increased major merger rates are found, reducing previously reported discrepancies with extended Press-Schechter estimates. When appropriately defined, substructure merger rates show a similar mass ratio dependence as FoF rates, but with stronger mass and redshift dependencies for their normalization.

Substructure hybrid testing of reinforced concrete shear wall structure using a domain overlapping technique

Science.gov (United States)

Zhang, Yu; Pan, Peng; Gong, Runhua; Wang, Tao; Xue, Weichen

2017-10-01

An online hybrid test was carried out on a 40-story 120-m high concrete shear wall structure. The structure was divided into two substructures whereby a physical model of the bottom three stories was tested in the laboratory and the upper 37 stories were simulated numerically using ABAQUS. An overlapping domain method was employed for the bottom three stories to ensure the validity of the boundary conditions of the superstructure. Mixed control was adopted in the test. Displacement control was used to apply the horizontal displacement, while two controlled force actuators were applied to simulate the overturning moment, which is very large and cannot be ignored in the substructure hybrid test of high-rise buildings. A series of tests with earthquake sources of sequentially increasing intensities were carried out. The test results indicate that the proposed hybrid test method is a solution to reproduce the seismic response of high-rise concrete shear wall buildings. The seismic performance of the tested precast high-rise building satisfies the requirements of the Chinese seismic design code.

Substructural evolution during cyclic torsion of drawn low carbon steel bars

International Nuclear Information System (INIS)

Correa, E.C.S.; Aguilar, M.T.P.; Monteiro, W.A.; Cetlin, P.R.

2006-01-01

Strain softening effects have been previously observed in drawn low carbon steel bars as a result of cyclic torsion experiments. In this paper, the substructural aspects related to the phenomenon have been investigated. Single pass drawn bars were subjected to a quarter, to a half, to a full torsion cycle and to 10 such cycles. Transmission electron microscopy revealed the development of extended microbands crossing the former dislocation arrangement of the drawn metal, which evolves to a rectangular shaped subgrains structure as torsion deformation is conducted

Influence of solidification parameters on the cellular sub-structure of tin and some tin alloys; Uticaj nekih parametara ocvrscavanja na celularnu substrukturu kalaja i nekih njegovih legura

Energy Technology Data Exchange (ETDEWEB)

Milosavljevic, Dj [Institute of Nuclear Sciences Boris Kidric, Vinca, Beograd (Yugoslavia)

1965-11-15

This paper describes an attempt to obtain qualitative data on sub-structure of samples solidified in contact with the cooler. The objective of experiments was to study micro segregation phenomena by investigating the substructure in the solidified sample obtained under experimental conditions which are similar to real solidification conditions.

Distribution of distances between dislocations in different types of dislocation substructures in deformed Cu-Al alloys

Energy Technology Data Exchange (ETDEWEB)

Trishkina, L., E-mail: trishkina.53@mail.ru; Zboykova, N.; Koneva, N., E-mail: koneva@tsuab.ru; Kozlov, E. [Tomsk State University of Architecture and Building, 2 Solyanaya St., Tomsk, 634003 (Russian Federation); Cherkasova, T. [Tomsk State University of Architecture and Building, 2 Solyanaya St., Tomsk, 634003 (Russian Federation); National Research Tomsk Polytechnic University, 50 Lenin Ave., Tomsk, 634050 (Russian Federation)

2016-01-15

The aim of the investigation was the determination of the statistic description of dislocation distribution in each dislocation substructures component forming after different deformation degrees in the Cu-Al alloys. The dislocation structures were investigated by the transmission diffraction electron microscopy method. In the work the statistic description of distance distribution between the dislocations, dislocation barriers and dislocation tangles in the deformed Cu-Al alloys with different concentration of Al and test temperature at the grain size of 100 µm was carried out. It was established that the above parameters influence the dislocation distribution in different types of the dislocation substructures (DSS): dislocation chaos, dislocation networks without disorientation, nondisoriented and disoriented cells, in the walls and inside the cells. The distributions of the distances between dislocations in the investigated alloys for each DSS type formed at certain deformation degrees and various test temperatures were plotted.

Distribution of distances between dislocations in different types of dislocation substructures in deformed Cu-Al alloys

Science.gov (United States)

Trishkina, L.; Cherkasova, T.; Zboykova, N.; Koneva, N.; Kozlov, E.

2016-01-01

The aim of the investigation was the determination of the statistic description of dislocation distribution in each dislocation substructures component forming after different deformation degrees in the Cu-Al alloys. The dislocation structures were investigated by the transmission diffraction electron microscopy method. In the work the statistic description of distance distribution between the dislocations, dislocation barriers and dislocation tangles in the deformed Cu-Al alloys with different concentration of Al and test temperature at the grain size of 100 µm was carried out. It was established that the above parameters influence the dislocation distribution in different types of the dislocation substructures (DSS): dislocation chaos, dislocation networks without disorientation, nondisoriented and disoriented cells, in the walls and inside the cells. The distributions of the distances between dislocations in the investigated alloys for each DSS type formed at certain deformation degrees and various test temperatures were plotted.

Chemical composition of stars in kinematical substructures of the galactic disk

Directory of Open Access Journals (Sweden)

Gorbaneva T.I.

2012-02-01

Full Text Available The Y, Zr, La, Ce, Nd , Sm and Eu abundances were found in LTE approach, and the abundance of Ba was computed in NLTE approximation for 280 FGK dwarfs in the region of metallicity of − 1<[Fe]< + 0.3. The selection of stars belonging to thin and thick disks and the stream Hercules was made on kinematic criteria. The analysis of enrichment of the different substructures of the Galaxy with α-element (Mg, Si, the iron peak (Ni and neutron-capture elements was carried out.

Observation of the substructure in the electron bunch on the ACO storage ring

International Nuclear Information System (INIS)

Bergher, M.; Velghe, M.; Mialocq, J.P.

1984-09-01

In the future, one interesting point of the SRFEL at Orsay will be the microtemporal analysis of the laser beam correlated with that of the electron bunch. In a first time, we have only analysed the temporal structure of the electron bunch with an Electrophotonic streak camera. The first results seem to indicate that the bunch is not an homogeneous bunch but presents a substructure. We discuss with details this data

Substructuring preconditioners for an h-p domain decomposition method with interior penalty mortaring

KAUST Repository

Antonietti, P. F.; Ayuso Dios, Blanca; Bertoluzza, S.; Pennacchio, M.

2014-01-01

We propose and study an iterative substructuring method for an h-p Nitsche-type discretization, following the original approach introduced in Bramble et al. Math. Comp. 47(175):103–134, (1986) for conforming methods. We prove quasi-optimality with respect to the mesh size and the polynomial degree for the proposed preconditioner. Numerical experiments assess the performance of the preconditioner and verify the theory. © 2014, Springer-Verlag Italia.

Substructuring preconditioners for an h-p domain decomposition method with interior penalty mortaring

KAUST Repository

Antonietti, P. F.

2014-05-13

We propose and study an iterative substructuring method for an h-p Nitsche-type discretization, following the original approach introduced in Bramble et al. Math. Comp. 47(175):103–134, (1986) for conforming methods. We prove quasi-optimality with respect to the mesh size and the polynomial degree for the proposed preconditioner. Numerical experiments assess the performance of the preconditioner and verify the theory. © 2014, Springer-Verlag Italia.

What (if anything) can few-body strange systems teach us about quark-gluon hadronic substructure?

International Nuclear Information System (INIS)

Maltman, K.

1990-01-01

We discuss expectation, relevant to the proposed (π,K) program at PILAC, for the effects of hadronic quark-gluon substructure on the physics of few-body strangeness -1 systems, in the context of QCD-inspired models used previously to describe the hadron spectrum and short distance nucleon-nucleon scattering. 50 refs., 2 tabs

Microdistribution of phases and substructure of the composite electrolytic self-lubricating copper-molybdenite coating

International Nuclear Information System (INIS)

Pribysh, I.Z.; Bakakin, G.N.; Borzyak, A.G.; Sajfullin, R.S.

1978-01-01

The influence of MoS 2 particles on the substructure of a copper matrix was studied, and their location in the composition was established. It is shown that the presence of molybdenite causes a variation in the conditions of electrical crystallization of copper. The optimum composition has been found, which is used as a self-lubricating coating for friction machine parts

Decorrelated Jet Substructure Tagging using Adversarial Neural Networks

CERN Multimedia

CERN. Geneva

2017-01-01

We describe a strategy for constructing a neural network jet substructure tagger which powerfully discriminates boosted decay signals while remaining largely uncorrelated with the jet mass. This reduces the impact of systematic uncertainties in background modeling while enhancing signal purity, resulting in improved discovery significance relative to existing taggers. The network is trained using an adversarial strategy, resulting in a tagger that learns to balance classification accuracy with decorrelation. As a benchmark scenario, we consider the case where large-radius jets originating from a boosted Z' decay are discriminated from a background of nonresonant quark and gluon jets. We show that in the presence of systematic uncertainties on the background rate, our adversarially-trained, decorrelated tagger considerably outperforms a conventionally trained neural network, despite having a slightly worse signal-background separation power. We generalize the adversarial training technique to include a paramet...

AFM friction and adhesion mapping of the substructures of human hair cuticles

International Nuclear Information System (INIS)

Smith, James R.; Tsibouklis, John; Nevell, Thomas G.; Breakspear, Steven

2013-01-01

Using atomic force microscopy, values of the microscale friction coefficient, the tip (silicon nitride) - surface adhesion force and the corresponding adhesion energy, for the substructures that constitute the surface of human hair (European brown hair) have been determined from Amonton plots. The values, mapped for comparison with surface topography, corresponded qualitatively with the substructures’ plane surface characteristics. Localised maps and values of the frictional coefficient, extracted avoiding scale edge effects, are likely to inform the formulation of hair-care products and treatments.

RINGED SUBSTRUCTURE AND A GAP AT 1 au IN THE NEAREST PROTOPLANETARY DISK

Energy Technology Data Exchange (ETDEWEB)

Andrews, Sean M.; Wilner, David J.; Bai, Xue-Ning; Öberg, Karin I.; Ricci, Luca [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Zhu, Zhaohuan [Department of Astrophysical Sciences, Princeton University, 4 Ivy Lane, Peyton Hall, Princeton, NJ 08544 (United States); Birnstiel, Tilman [Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany); Carpenter, John M. [Joint ALMA Observatory (JAO), Alonso de Cordova 3107, Vitacura-Santiago de Chile (Chile); Pérez, Laura M. [Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69, D-53121 Bonn (Germany); Hughes, A. Meredith [Department of Astronomy, Wesleyan University, Van Vleck Observatory, 96 Foss Hill Drive, Middletown, CT 06457 (United States); Isella, Andrea, E-mail: sandrews@cfa.harvard.edu [Department of Physics and Astronomy, Rice University, 6100 Main Street, Houston, TX 77005 (United States)

2016-04-01

We present long baseline Atacama Large Millimeter/submillimeter Array (ALMA) observations of the 870 μm continuum emission from the nearest gas-rich protoplanetary disk, around TW Hya, that trace millimeter-sized particles down to spatial scales as small as 1 au (20 mas). These data reveal a series of concentric ring-shaped substructures in the form of bright zones and narrow dark annuli (1–6 au) with modest contrasts (5%–30%). We associate these features with concentrations of solids that have had their inward radial drift slowed or stopped, presumably at local gas pressure maxima. No significant non-axisymmetric structures are detected. Some of the observed features occur near temperatures that may be associated with the condensation fronts of major volatile species, but the relatively small brightness contrasts may also be a consequence of magnetized disk evolution (the so-called zonal flows). Other features, particularly a narrow dark annulus located only 1 au from the star, could indicate interactions between the disk and young planets. These data signal that ordered substructures on ∼au scales can be common, fundamental factors in disk evolution and that high-resolution microwave imaging can help characterize them during the epoch of planet formation.

DNBR Prediction Using a Support Vector Regression

International Nuclear Information System (INIS)

Yang, Heon Young; Na, Man Gyun

2008-01-01

PWRs (Pressurized Water Reactors) generally operate in the nucleate boiling state. However, the conversion of nucleate boiling into film boiling with conspicuously reduced heat transfer induces a boiling crisis that may cause the fuel clad melting in the long run. This type of boiling crisis is called Departure from Nucleate Boiling (DNB) phenomena. Because the prediction of minimum DNBR in a reactor core is very important to prevent the boiling crisis such as clad melting, a lot of research has been conducted to predict DNBR values. The object of this research is to predict minimum DNBR applying support vector regression (SVR) by using the measured signals of a reactor coolant system (RCS). The SVR has extensively and successfully been applied to nonlinear function approximation like the proposed problem for estimating DNBR values that will be a function of various input variables such as reactor power, reactor pressure, core mass flowrate, control rod positions and so on. The minimum DNBR in a reactor core is predicted using these various operating condition data as the inputs to the SVR. The minimum DBNR values predicted by the SVR confirm its correctness compared with COLSS values

Morality as the Substructure of Social Justice: Religion in Education as a Case in Point

Science.gov (United States)

Potgieter, Ferdinand J.

2011-01-01

Moral issues and principles do not only emerge in cases of conflict among, for instance, religious communities or political parties; indeed they form the moral substructure of notions of social justice. During periods of conflict each opponent claims justice for his/her side and bases the claim on certain principles. In this article, reference is…

Influence of ausforming on substructures and shape memory behavior in Fe-28Mn-6Si-5Cr alloy

International Nuclear Information System (INIS)

Wang, D.; Ji, W.; Han, M.; Jia, D.; Liu, W.

2000-01-01

The influence of ausforming (deformation of austenite at temperatures above Md) on shape memory effect (SME) and the substructures in Fe-28Mn-6Si-5Cr (wt.%) alloy were studied, intending to reveal the dominating factor for SME in terms of microstructural characteristics in comparison with the case of thermo-mechanical training. It was found that the SME in the studied alloy could be effectively improved by ausforming at 700 C for 9% tensile strain, in the process of which the oriented stacking faults and dislocations were evolved and regularly distributed in austenite. The improvement of SME by ausforming, as well as thermo-mechanical training, is attributed to the restored substructures in austenite; while there is no closely correspondent relation between SME and the strength of austenite matrix. (orig.)

Deformation behavior of a 16-8-2 GTA weld as influenced by its solidification substructure

International Nuclear Information System (INIS)

Foulds, J.R.; Moteff, J.; Sikka, V.K.; McEnerney, J.W.

1983-01-01

Weldment sections from formed and welded type 316 stainless steel pipe are characterized with respect to some time-independent (tensile) and time-dependent (creep) mechanical properties at temperatures between 25 0 C and 649 0 C. The GTA weldment, welded with 16-8-2 filler metal, is sectioned from pipe in the formed + welded + solution annealed + straightened condition, as well as in the same condition with an additional re-solution treatment. Detailed room temperature microhardness measurements on these sections before and after reannealing enable a determination of the different recovery characteristics of weld and base metal. The observed stable weld metal solidification dislocation substructure in comparison with the base metal random dislocation structure, in fact, adequately explains weld/base metal elevated temperature mechanical behavior differences from this recovery characteristic standpoint. The weld metal substructure is the only parameter common to the variety of austenitic stainless steel welds exhibiting the consistent parent/weld metal deformation behavior differences described. As such, it must be considered the key to understanding weldment mechanical behavior

Predictive Analytics to Support Real-Time Management in Pathology Facilities.

Science.gov (United States)

Lessard, Lysanne; Michalowski, Wojtek; Chen Li, Wei; Amyot, Daniel; Halwani, Fawaz; Banerjee, Diponkar

2016-01-01

Predictive analytics can provide valuable support to the effective management of pathology facilities. The introduction of new tests and technologies in anatomical pathology will increase the volume of specimens to be processed, as well as the complexity of pathology processes. In order for predictive analytics to address managerial challenges associated with the volume and complexity increases, it is important to pinpoint the areas where pathology managers would most benefit from predictive capabilities. We illustrate common issues in managing pathology facilities with an analysis of the surgical specimen process at the Department of Pathology and Laboratory Medicine (DPLM) at The Ottawa Hospital, which processes all surgical specimens for the Eastern Ontario Regional Laboratory Association. We then show how predictive analytics could be used to support management. Our proposed approach can be generalized beyond the DPLM, contributing to a more effective management of pathology facilities and in turn to quicker clinical diagnoses.

eMolTox: prediction of molecular toxicity with confidence.

Science.gov (United States)

Ji, Changge; Svensson, Fredrik; Zoufir, Azedine; Bender, Andreas

2018-03-07

In this work we present eMolTox, a web server for the prediction of potential toxicity associated with a given molecule. 174 toxicology-related in vitro/vivo experimental datasets were used for model construction and Mondrian conformal prediction was used to estimate the confidence of the resulting predictions. Toxic substructure analysis is also implemented in eMolTox. eMolTox predicts and displays a wealth of information of potential molecular toxicities for safety analysis in drug development. The eMolTox Server is freely available for use on the web at http://xundrug.cn/moltox. chicago.ji@gmail.com or ab454@cam.ac.uk. Supplementary data are available at Bioinformatics online.

Predicting Resilience via Social Support and Illness Perceptions Among Patients Undergoing Hemodialysis

Directory of Open Access Journals (Sweden)

Reihane Hajmohammadi

2017-07-01

Full Text Available Background and Objectives Chronic renal disease is a threatening condition for the health, economic, and social status of the affected person and his/her family. Patients undergoing hemodialysis encounter mental and health problems; the current study aimed at predicting resilience via social support and illness perceptions among patients undergoing hemodialysis. Methods The current descriptive-correlational study had a statistical population including 308 patients undergoing hemodialysis in Kerman, Iran, in 2017. Based on the Krejcie-Morgan table, the minimum required sample size was 169. The sample was selected using a convenience sampling method. Data collection tools were the Connor-Davidson resilience scale, the medical outcome study (MOS social support survey developed by Sherbourne and Stewart, and the brief illness perception questionnaire developed by Broadbent et al. Data were analyzed using a Pearson correlation coefficient and a stepwise regression analysis via SPSS version 19. Results Results indicated that resilience was significantly and positively related to social support (r = 0.318, P < 0.05 and illness perceptions (r = 0.165, P < 0.05. Among the subscales of social support, emotional support, tangible support, and social interaction could predict resilience, and among the subscales of illness perceptions, only cognitive representation could predict resilience. Conclusions The obtained results demonstrated that resilience was significantly and positively related to social support and illness perceptions. Additionally, the subscales of social support and illness perceptions could predict resilience among the patients undergoing hemodialysis.

Soil-structure interaction analysis of NPP containments: substructure and frequency domain methods

International Nuclear Information System (INIS)

Venancio-Filho, F.; Almeida, M.C.F.; Ferreira, W.G.; De Barros, F.C.P.

1997-01-01

Substructure and frequency domain methods for soil-structure interaction are addressed in this paper. After a brief description of mathematical models for the soil and of excitation, the equations for dynamic soil-structure interaction are developed for a rigid surface foundation and for an embedded foundation. The equations for the frequency domain analysis of MDOF systems are provided. An example of soil-structure interaction analysis with frequency-dependent soil properties is given and examples of identification of foundation impedance functions and soil properties are presented. (orig.)

Boosting the charged Higgs search prospects using jet substructure at the LHC

Energy Technology Data Exchange (ETDEWEB)

Li, Jinmian [Center of Excellence for Particle Physics at Terascale, University of Adelaide,Adelaide, 5005 South (Australia); School of Physics, Korea Institute for Advanced Study,Seoul, 130-722 (Korea, Republic of); Patrick, Riley; Sharma, Pankaj; Williams, Anthony G. [Center of Excellence for Particle Physics at Terascale, University of Adelaide,Adelaide, 5005 South (Australia)

2016-11-28

Charged Higgs bosons are predicted in variety of theoretically well-motivated new physics models with extended Higgs sectors. In this study, we focus on a type-II two Higgs doublet model (2HDM-II) and consider a heavy charged Higgs with its mass ranging from 500 GeV to 1 TeV as dictated by the b→sγ constraints which render M{sub H{sup ±}}>480 GeV. We study the dominant production mode H{sup ±}t associated production with H{sup ±}→W{sup ±}A being the dominant decay channel when the pseudoscalar A is considerably lighter. For such a heavy charged Higgs, both the decay products W{sup ±} and A are relatively boosted. In such a scenario, we apply the jet substructure analysis of tagging the fat pseudoscalar and W jets in order to eliminate the standard model background efficiently. We perform a detailed detector simulation for the signal and background processes at the 14 TeV LHC. We introduce various kinematical cuts to determine the signal significance for a number of benchmark points with charged Higgs boson mass from 500 GeV to 1 TeV in the W{sup ±}A decay channel. Finally we perform a multivariate analysis utilizing a boosted decision tree algorithm to optimize these significances.

Lithium-ion battery remaining useful life prediction based on grey support vector machines

Directory of Open Access Journals (Sweden)

Xiaogang Li

2015-12-01

Full Text Available In this article, an improved grey prediction model is proposed to address low-accuracy prediction issue of grey forecasting model. The first step is using a trigonometric function to transform the original data sequence to smooth the data, which is called smoothness of grey prediction model, and then a grey support vector machine model by integrating the improved grey model with support vector machine is introduced. At the initial stage of the model, trigonometric functions and accumulation generation operation can be used to preprocess the data, which enhances the smoothness of the data and reduces the associated randomness. In addition, support vector machine is implemented to establish a prediction model for the pre-processed data and select the optimal model parameters via genetic algorithms. Finally, the data are restored through the ‘regressive generate’ operation to obtain the forecasting data. To prove that the grey support vector machine model is superior to the other models, the battery life data from the Center for Advanced Life Cycle Engineering are selected, and the presented model is used to predict the remaining useful life of the battery. The predicted result is compared to that of grey model and support vector machines. For a more intuitive comparison of the three models, this article quantifies the root mean square errors for these three different models in the case of different ratio of training samples and prediction samples. The results show that the effect of grey support vector machine model is optimal, and the corresponding root mean square error is only 3.18%.

Predictive Analytics to Support Real-Time Management in Pathology Facilities

Science.gov (United States)

Lessard, Lysanne; Michalowski, Wojtek; Chen Li, Wei; Amyot, Daniel; Halwani, Fawaz; Banerjee, Diponkar

2016-01-01

Predictive analytics can provide valuable support to the effective management of pathology facilities. The introduction of new tests and technologies in anatomical pathology will increase the volume of specimens to be processed, as well as the complexity of pathology processes. In order for predictive analytics to address managerial challenges associated with the volume and complexity increases, it is important to pinpoint the areas where pathology managers would most benefit from predictive capabilities. We illustrate common issues in managing pathology facilities with an analysis of the surgical specimen process at the Department of Pathology and Laboratory Medicine (DPLM) at The Ottawa Hospital, which processes all surgical specimens for the Eastern Ontario Regional Laboratory Association. We then show how predictive analytics could be used to support management. Our proposed approach can be generalized beyond the DPLM, contributing to a more effective management of pathology facilities and in turn to quicker clinical diagnoses. PMID:28269873

Fault trend prediction of device based on support vector regression

International Nuclear Information System (INIS)

Song Meicun; Cai Qi

2011-01-01

The research condition of fault trend prediction and the basic theory of support vector regression (SVR) were introduced. SVR was applied to the fault trend prediction of roller bearing, and compared with other methods (BP neural network, gray model, and gray-AR model). The results show that BP network tends to overlearn and gets into local minimum so that the predictive result is unstable. It also shows that the predictive result of SVR is stabilization, and SVR is superior to BP neural network, gray model and gray-AR model in predictive precision. SVR is a kind of effective method of fault trend prediction. (authors)

Boosted Higgs boson tagging using jet substructures

CERN Document Server

Shvydkin, Pavel

2016-01-01

Searching BSM particles via the Higgs boson final state has now become common. The mass of desired BSM particle is more than 1 TeV, thereby its decay products are highly Lorentz-boosted. Hence the jets from b quark-antiquark pair - which the Higgs boson mostly decays into - are very closed to each other, and merged into one jet, that is typically reconstructed using large jet sizes (∆R = 0.8). In this work regression technique is applied to AK8 jets (which defined by anti-kT algorithm, using ΔR = 0.8). The regression makes use of boosted jets with substructure information, coupled with the pecularities of a b quark decay, like the presence of a soft lepton (SL) inside the jet. It has allowed to improve the resolution of the mass reconstruction and transverse momentum of the Higgs boson. This application results in improvement of the mass reconstruction by 3-4 percent. These result may be improved firstly by making more careful pileup rejection. Then it is possible to combine base regression train for dif...

Exclusive processes: Tests of coherent QCD phenomena and nucleon substructure at CEBAF

International Nuclear Information System (INIS)

Brodsky, S.J.

1994-07-01

Measurements of exclusive processes such as electroproduction, photoproduction, and Compton scattering are among the most sensitive probes of proton structure and coherent phenomena in quantum chromodynamics. The continuous electron beam at CEBAF, upgraded in laboratory energy to 10--12 GeV, will allow a systematic study of exclusive, semi-inclusive, and inclusive reactions in a kinematic range well-tuned to the study of fundamental nucleon and nuclear substructure. I also discuss the potential at CEBAF for studying novel QCD phenomena at the charm production threshold, including the possible production of nuclear-bound quarkonium

Prediction of Banking Systemic Risk Based on Support Vector Machine

Directory of Open Access Journals (Sweden)

Shouwei Li

2013-01-01

Full Text Available Banking systemic risk is a complex nonlinear phenomenon and has shed light on the importance of safeguarding financial stability by recent financial crisis. According to the complex nonlinear characteristics of banking systemic risk, in this paper we apply support vector machine (SVM to the prediction of banking systemic risk in an attempt to suggest a new model with better explanatory power and stability. We conduct a case study of an SVM-based prediction model for Chinese banking systemic risk and find the experiment results showing that support vector machine is an efficient method in such case.

Modeling and prediction of Turkey's electricity consumption using Support Vector Regression

International Nuclear Information System (INIS)

Kavaklioglu, Kadir

2011-01-01

Support Vector Regression (SVR) methodology is used to model and predict Turkey's electricity consumption. Among various SVR formalisms, ε-SVR method was used since the training pattern set was relatively small. Electricity consumption is modeled as a function of socio-economic indicators such as population, Gross National Product, imports and exports. In order to facilitate future predictions of electricity consumption, a separate SVR model was created for each of the input variables using their current and past values; and these models were combined to yield consumption prediction values. A grid search for the model parameters was performed to find the best ε-SVR model for each variable based on Root Mean Square Error. Electricity consumption of Turkey is predicted until 2026 using data from 1975 to 2006. The results show that electricity consumption can be modeled using Support Vector Regression and the models can be used to predict future electricity consumption. (author)

Alkoxyl- and carbon-centered radicals as primary agents for degrading non-phenolic lignin-substructure model compounds.

Science.gov (United States)

Ohashi, Yasunori; Uno, Yukiko; Amirta, Rudianto; Watanabe, Takahito; Honda, Yoichi; Watanabe, Takashi

2011-04-07

Lignin degradation by white-rot fungi proceeds via free radical reaction catalyzed by oxidative enzymes and metabolites. Basidiomycetes called selective white-rot fungi degrade both phenolic and non-phenolic lignin substructures without penetration of extracellular enzymes into the cell wall. Extracellular lipid peroxidation has been proposed as a possible ligninolytic mechanism, and radical species degrading the recalcitrant non-phenolic lignin substructures have been discussed. Reactions between the non-phenolic lignin model compounds and radicals produced from azo compounds in air have previously been analysed, and peroxyl radical (PR) is postulated to be responsible for lignin degradation (Kapich et al., FEBS Lett., 1999, 461, 115-119). However, because the thermolysis of azo compounds in air generates both a carbon-centred radical (CR) and a peroxyl radical (PR), we re-examined the reactivity of the three radicals alkoxyl radical (AR), CR and PR towards non-phenolic monomeric and dimeric lignin model compounds. The dimeric lignin model compound is degraded by CR produced by reaction of 2,2'-azobis(2-amidinopropane) dihydrochloride (AAPH), which under N(2) atmosphere cleaves the α-β bond in 1-(4-ethoxy-3-methoxyphenyl)-2-(2-methoxyphenoxy)-1,3-propanediol to yield 4-ethoxy-3-methoxybenzaldehyde. However, it is not degraded by the PR produced by reaction of Ce(4+)/tert-BuOOH. In addition, it is degraded by AR produced by reaction of Ti(3+)/tert-BuOOH. PR and AR are generated in the presence and absence of veratryl alcohol, respectively. Rapid-flow ESR analysis of the radical species demonstrates that AR but not PR reacts with the lignin model compound. Thus, AR and CR are primary agents for the degradation of non-phenolic lignin substructures.

Prediction of Spirometric Forced Expiratory Volume (FEV1) Data Using Support Vector Regression

Science.gov (United States)

Kavitha, A.; Sujatha, C. M.; Ramakrishnan, S.

2010-01-01

In this work, prediction of forced expiratory volume in 1 second (FEV1) in pulmonary function test is carried out using the spirometer and support vector regression analysis. Pulmonary function data are measured with flow volume spirometer from volunteers (N=175) using a standard data acquisition protocol. The acquired data are then used to predict FEV1. Support vector machines with polynomial kernel function with four different orders were employed to predict the values of FEV1. The performance is evaluated by computing the average prediction accuracy for normal and abnormal cases. Results show that support vector machines are capable of predicting FEV1 in both normal and abnormal cases and the average prediction accuracy for normal subjects was higher than that of abnormal subjects. Accuracy in prediction was found to be high for a regularization constant of C=10. Since FEV1 is the most significant parameter in the analysis of spirometric data, it appears that this method of assessment is useful in diagnosing the pulmonary abnormalities with incomplete data and data with poor recording.

Sub-structure formation in starless cores

Science.gov (United States)

Toci, C.; Galli, D.; Verdini, A.; Del Zanna, L.; Landi, S.

2018-02-01

Motivated by recent observational searches of sub-structure in starless molecular cloud cores, we investigate the evolution of density perturbations on scales smaller than the Jeans length embedded in contracting isothermal clouds, adopting the same formalism developed for the expanding Universe and the solar wind. We find that initially small amplitude, Jeans-stable perturbations (propagating as sound waves in the absence of a magnetic field) are amplified adiabatically during the contraction, approximately conserving the wave action density, until they either become non-linear and steepen into shocks at a time tnl, or become gravitationally unstable when the Jeans length decreases below the scale of the perturbations at a time tgr. We evaluate analytically the time tnl at which the perturbations enter the non-linear stage using a Burgers' equation approach, and we verify numerically that this time marks the beginning of the phase of rapid dissipation of the kinetic energy of the perturbations. We then show that for typical values of the rms Mach number in molecular cloud cores, tnl is smaller than tgr, and therefore density perturbations likely dissipate before becoming gravitational unstable. Solenoidal modes grow at a faster rate than compressible modes, and may eventually promote fragmentation through the formation of vortical structures.

Motion and deformation estimation from medical imagery by modeling sub-structure interaction and constraints

KAUST Repository

Sundaramoorthi, Ganesh

2012-09-13

This paper presents a novel medical image registration algorithm that explicitly models the physical constraints imposed by objects or sub-structures of objects that have differing material composition and border each other, which is the case in most medical registration applications. Typical medical image registration algorithms ignore these constraints and therefore are not physically viable, and to incorporate these constraints would require prior segmentation of the image into regions of differing material composition, which is a difficult problem in itself. We present a mathematical model and algorithm for incorporating these physical constraints into registration / motion and deformation estimation that does not require a segmentation of different material regions. Our algorithm is a joint estimation of different material regions and the motion/deformation within these regions. Therefore, the segmentation of different material regions is automatically provided in addition to the image registration satisfying the physical constraints. The algorithm identifies differing material regions (sub-structures or objects) as regions where the deformation has different characteristics. We demonstrate the effectiveness of our method on the analysis of cardiac MRI which includes the detection of the left ventricle boundary and its deformation. The experimental results indicate the potential of the algorithm as an assistant tool for the quantitative analysis of cardiac functions in the diagnosis of heart disease.

Quark substructure approach to 4He charge distribution

International Nuclear Information System (INIS)

Wilets, L.; Alberg, M.A.; Pepin, S.; Stancu, F.; Carlson, J.; Koepf, W.

1997-01-01

We present a study of the 4 He charge distribution based on realistic nucleonic wave functions and incorporation of quark substructure. Any central depression of the proton point density seen in modern four-body calculations is too small by itself to lead to a correct description of the charge distribution of 4 He if folded with a fixed proton size parameter, as is usually done. We utilize six-quark structures calculated in the chromodielectric model for N-N interactions to find a swelling of the proton size as the internucleon distance decreases. This swelling is a result of the short-range dynamics in the N-N system. Using the independent pair approximation, the corresponding charge distribution of the proton is folded with the two-nucleon distribution generated from Green's function Monte Carlo calculations of the 4 He nucleonic wave function. We obtain a reasonably good fit to the experimental charge distribution of 4 He. Meson-exchange currents have not been included. copyright 1997 The American Physical Society

Daily Autonomy Support and Sexual Identity Disclosure Predicts Daily Mental and Physical Health Outcomes.

Science.gov (United States)

Legate, Nicole; Ryan, Richard M; Rogge, Ronald D

2017-06-01

Using a daily diary methodology, we examined how social environments support or fail to support sexual identity disclosure, and associated mental and physical health outcomes. Results showed that variability in disclosure across the diary period related to greater psychological well-being and fewer physical symptoms, suggesting potential adaptive benefits to selectively disclosing. A multilevel path model indicated that perceiving autonomy support in conversations predicted more disclosure, which in turn predicted more need satisfaction, greater well-being, and fewer physical symptoms that day. Finally, mediation analyses revealed that disclosure and need satisfaction explained why perceiving autonomy support in a conversation predicted greater well-being and fewer physical symptoms. That is, perceiving autonomy support in conversations indirectly predicted greater wellness through sexual orientation disclosure, along with feeling authentic and connected in daily interactions with others. Discussion highlights the role of supportive social contexts and everyday opportunities to disclose in affecting sexual minority mental and physical health.

Mechanical properties and related substructure of TiNi shape memory alloys

International Nuclear Information System (INIS)

Filip, P.; Kneissl, A.C.

1995-01-01

The mechanical properties of binary near equiatomic TiNi shape memory alloys were investigated after different types of mechanical and heat treatments. The changes of deformation behaviour are explained on the basis of substructure differences after work hardening. The ''elastic moduli'' of both the high-temperature phase B2 and the martensite B19' as well as the ''easy stage of deformation'' are dependent on the work hardening intensity and these changes are related to the mobility of B2/B19' interfaces. The martensite changes its morphology after work hardening. In contrast to a twinned martensite, typical for annealed alloys, the internally slipped martensite was detected after work hardening. (orig.)

Discussion About Nonlinear Time Series Prediction Using Least Squares Support Vector Machine

International Nuclear Information System (INIS)

Xu Ruirui; Bian Guoxing; Gao Chenfeng; Chen Tianlun

2005-01-01

The least squares support vector machine (LS-SVM) is used to study the nonlinear time series prediction. First, the parameter γ and multi-step prediction capabilities of the LS-SVM network are discussed. Then we employ clustering method in the model to prune the number of the support values. The learning rate and the capabilities of filtering noise for LS-SVM are all greatly improved.

Estimation of the displacement of cardiac substructures and the motion of the coronary arteries using electrocardiographic gating

Directory of Open Access Journals (Sweden)

Tan W

2013-09-01

Full Text Available Wenyong Tan,1,* Liying Xu,2,* Xiaohong Wang,1 Dasheng Qiu,3 Guang Han,1 Desheng Hu1 1Department of Radiation Oncology, Hubei Cancer Hospital, Wuhan, People’s Republic of China; 2Department of Radiology, Zhongnan Hospital, Wuhan University, Wuhan, People’s Republic of China; 3PET-CT Center, Hubei Cancer Hospital, Wuhan, People’s Republic of China *These authors have contributed equally to this paper Purpose: The aim of this study was to quantify the displacement of cardiac substructures, including the anterior myocardial territory (AMT, left ventricle, and coronary arteries during a normal cardiac cycle. Materials and methods: Computed tomography (CT images with retrospective electrocardiographic gating of 17 eligible patients were obtained. All images were reconstructed automatically for the end-diastolic and end-systolic phases. CT scanning without contrast at a random phase and a selected vertebral body were used as references to measure three-dimensionaldisplacements of the cardiac substructures. Results: The displacement between the end-diastolic and end-systolic phases (Dd-s was greater than that between the end-systolic and random phases and between the end-diastolic and random cardiac phases. The largest displacements for the heart were in the left, posterior, and inferior directions with an average Dd-s of approximately 4–6 mm. The average Dd-s for the AMT and left ventricle was 1.2–2.7 mm in the anterior and right directions, 4.3–7.8 mm in left and posterior directions, and 4.9–6.3 mm in superior and inferior directions. For the coronary arteries, the average Dd-s was 2.8–5.9 mm in the anterior-posterior direction, 3.5–6.6 mm in left-right direction, and 3.8–5.3 mm in the superior-inferior direction. Inter-observer agreement was excellent for the heart, AMT, and left ventricle (kappa coefficient, >0.75 for all and good for most coronary arteries in three dimensions (kappa coefficient, 0.511–0.687. The Dd-s did not

Substructure method in high-speed monorail dynamic problems

Science.gov (United States)

Ivanchenko, I. I.

2008-12-01

combined schemes modeling a strained elastic compound moving structure and a monorail elevated track. The problems of development of methods for dynamic analysis of monorails are very topical, especially because of increasing speeds of the rolling stock motion. These structures are studied in [16-18]. In the present paper, the above problem is solved by using the method for the moving load analysis and a step procedure of integration with respect to time, which were proposed in [9, 19], respectively. Further, these components are used to enlarge the possibilities of the substructure method in problems of dynamics. In the approach proposed for moving load analysis of structures, for a substructure (having the shape of a boundary element or a superelement) we choose an object moving at a constant speed (a monorail rolling stock); in this case, we use rod boundary elements of large length, which are gathered in a system modeling these objects. In particular, sets of such elements form a model of a monorail rolling stock, namely, carriage hulls, wheeled carts, elements of the wheel spring suspension, models of continuous beams of monorail ways and piers with foundations admitting emergency subsidence and unilateral links. These specialized rigid finite elements with linear and nonlinear links, included into the set of earlier proposed finite elements [14, 19], permit studying unsteady vibrations in the "monorail train-elevated track" (MTET) system taking into account various irregularities on the beam-rail, the pier emergency subsidence, and their elastic support by the basement. In this case, a high degree of the structure spatial digitization is obtained by using rods with distributed parameters in the analysis. The displacements are approximated by linear functions and trigonometric Fourier series, which, as was already noted, permits increasing the number of degrees of freedom of the system under study simultaneously preserving the order of the resolving system of

Sensory predictions during action support perception of imitative reactions across suprasecond delays.

Science.gov (United States)

Yon, Daniel; Press, Clare

2018-04-01

Perception during action is optimized by sensory predictions about the likely consequences of our movements. Influential theories in social cognition propose that we use the same predictions during interaction, supporting perception of similar reactions in our social partners. However, while our own action outcomes typically occur at short, predictable delays after movement execution, the reactions of others occur at longer, variable delays in the order of seconds. To examine whether we use sensorimotor predictions to support perception of imitative reactions, we therefore investigated the temporal profile of sensory prediction during action in two psychophysical experiments. We took advantage of an influence of prediction on apparent intensity, whereby predicted visual stimuli appear brighter (more intense). Participants performed actions (e.g., index finger lift) and rated the brightness of observed outcomes congruent (index finger lift) or incongruent (middle finger lift) with their movements. Observed action outcomes could occur immediately after execution, or at longer delays likely reflective of those in natural social interaction (1800 or 3600 ms). Consistent with the previous literature, Experiment 1 revealed that congruent action outcomes were rated as brighter than incongruent outcomes. Importantly, this facilitatory perceptual effect was found irrespective of whether outcomes occurred immediately or at delay. Experiment 2 replicated this finding and demonstrated that it was not the result of response bias. These findings therefore suggest that visual predictions generated during action are sufficiently general across time to support our perception of imitative reactions in others, likely generating a range of benefits during social interaction. Copyright © 2017 Elsevier B.V. All rights reserved.

Study of a 900 MW PWR by a substructuring method - Spectral response to a seismic excitation and comparison with a beam model

International Nuclear Information System (INIS)

Rousseau, G.; Bianchini-Burlot, B.; Bosselut, D.; Jacquart, G.; Viallet, E.

1997-03-01

This report presents a three dimensional Finite Element Model (FEM) of a 900 MW Pressurized Water Reactor (PWR) which is described at first: its modal behaviour is computed by a sub-structuring method based upon a Component Mode Synthesis (CMS) method. All the substructures taken into account in the model are described. One model with equivalent beams is also described. Then, different approaches to take into account the fluid/structure interaction in the different models are investigated. Results of the modal analysis of each model are compared to each other and with experimental measures. This modal analysis is then used to compute the non linear and linear response of the PWR due to a seismic excitation. (author)

An algebraic substructuring using multiple shifts for eigenvalue computations

International Nuclear Information System (INIS)

Ko, Jin Hwan; Jung, Sung Nam; Byun, Do Young; Bai, Zhaojun

2008-01-01

Algebraic substructuring (AS) is a state-of-the-art method in eigenvalue computations, especially for large-sized problems, but originally it was designed to calculate only the smallest eigenvalues. Recently, an updated version of AS has been introduced to calculate the interior eigenvalues over a specified range by using a shift concept that is referred to as the shifted AS. In this work, we propose a combined method of both AS and the shifted AS by using multiple shifts for solving a considerable number of eigensolutions in a large-sized problem, which is an emerging computational issue of noise or vibration analysis in vehicle design. In addition, we investigated the accuracy of the shifted AS by presenting an error criterion. The proposed method has been applied to the FE model of an automobile body. The combined method yielded a higher efficiency without loss of accuracy in comparison to the original AS

ATLAS Standard Model Measurements Using Jet Grooming and Substructure

CERN Document Server

Ucchielli, Giulia; The ATLAS collaboration

2017-01-01

Boosted topologies allow to explore Standard Model processes in kinematical regimes never tested before. In such LHC challenging environments, standard reconstruction techniques quickly hit the wall. Targeting hadronic final states means to properly reconstruct energy and multiplicity of the jets in the event. In order to be able to identify the decay product of boosted objects, i.e. W bosons, $t\\bar{t}$ pairs or Higgs produced in association with $t\\bar{t}$ pairs, ATLAS experiment is currently exploiting several algorithms using jet grooming and jet substructure. This contribution will mainly cover the following ATLAS measurements: $t\\bar{t}$ differential cross section production and jet mass using the soft drop procedure. Standard Model measurements offer the perfect field to test the performances of new jet tagging techniques which will become even more important in the search for new physics in highly boosted topologies.”

The influence of peak stress on the mechanical behavior and the substructural evolution in shock-prestrained zirconium

International Nuclear Information System (INIS)

Cerreta, E.; Gray, G.T. III; Henrie, B.L.; Brown, D.W.; Hixson, R.S.; Rigg, P.A.

2004-01-01

The post shock mechanical behavior and substructure evolution of zirconium (Zr) under shock prestrained at 5.8 and 8 GPa, above and below the pressure induced α-ω phase transition, has been quantified. The reload yield stress of Zr shock prestrained to 8 GPa was found to exhibit enhanced shock hardening when compared to the flow stress measured quasi-statically at an equivalent strain. In contrast, the reload yield behavior of Zr specimens shocked to 5.8 GPa did not exhibit enhanced shock hardening. The microstructure of the as-annealed and shock prestrained materials were examined. The presence of a reduced available glide distance due to a relatively more well developed dislocation substructure and increased twinning over quasi-static specimens deformed to comparable strains correlates with the increased yield stresses after shock prestraining at 8 GPa. Additionally, the retention of ∼ 40% by volume metastable high-pressure ω-phase in specimens shocked to 8 GPa and its absence in the 5.8 GPa specimen, is thought to contribute to the increased yield stress in the 8 GPa specimens

Detailed Analysis of Japanese Population Substructure with a Focus on the Southwest Islands of Japan

Science.gov (United States)

Nishiyama, Takeshi; Kishino, Hirohisa; Suzuki, Sadao; Ando, Ryosuke; Niimura, Hideshi; Uemura, Hirokazu; Horita, Mikako; Ohnaka, Keizo; Kuriyama, Nagato; Mikami, Haruo; Takashima, Naoyuki; Mastuo, Keitaro; Guang, Yin; Wakai, Kenji; Hamajima, Nobuyuki; Tanaka, Hideo

2012-01-01

Uncovering population structure is important for properly conducting association studies and for examining the demographic history of a population. Here, we examined the Japanese population substructure using data from the Japan Multi-Institutional Collaborative Cohort (J-MICC), which covers all but the northern region of Japan. Using 222 autosomal loci from 4502 subjects, we investigated population substructure by estimating FST among populations, testing population differentiation, and performing principal component analysis (PCA) and correspondence analysis (CA). All analyses revealed a low but significant differentiation between the Amami Islanders and the mainland Japanese population. Furthermore, we examined the genetic differentiation between the mainland population, Amami Islanders and Okinawa Islanders using six loci included in both the Pan-Asian SNP (PASNP) consortium data and the J-MICC data. This analysis revealed that the Amami and Okinawa Islanders were differentiated from the mainland population. In conclusion, we revealed a low but significant level of genetic differentiation between the mainland population and populations in or to the south of the Amami Islands, although genetic variation between both populations might be clinal. Therefore, the possibility of population stratification must be considered when enrolling the islander population of this area, such as in the J-MICC study. PMID:22509376

Nuclear substructure reorganization during late stageerythropoiesis is selective and does not involve caspase cleavage ofmajor nuclear substructural proteins

Energy Technology Data Exchange (ETDEWEB)

Krauss, Sharon Wald; Lo, Annie J.; Short, Sarah A.; Koury, MarkJ.; Mohandas, Narla; Chasis, Joel Anne

2005-04-06

Enucleation, a rare feature of mammalian differentiation, occurs in three cell types: erythroblasts, lens epithelium and keratinocytes. Previous investigations suggest that caspase activation functions in lens epithelial and keratinocyte enucleation, as well as in early erythropoiesis encompassing BFU-E differentiation to proerythroblast. To determine whether caspase activation contributes to later erythropoiesis and whether nuclear substructures other than chromatin reorganize, we analyzed distributions of nuclear subcompartment proteins and assayed for caspase-induced cleavage of subcompartmental target proteins in mouse erythroblasts. We found that patterns of lamin B in the filamentous network interacting with both the nuclear envelope and DNA, nuclear matrix protein NuMA, and splicing factors Sm and SC35 persisted during nuclear condensation, consistent with effective transcription of genes expressed late in differentiation. Thus nuclear reorganization prior to enucleation is selective, allowing maintenance of critical transcriptional processes independent of extensive chromosomal reorganization. Consistent with these data, we found no evidence for caspase-induced cleavage of major nuclear subcompartment proteins during late erythropoiesis, in contrast to what has been observed in early erythropoiesis and in lens epithelial and keratinocyte differentiation. These findings imply that nuclear condensation and extrusion during terminal erythroid differentiation involve novel mechanisms that do not entail major activation of apoptotic machinery.

Direct observations and analyses of dislocation substructures in the α phase of an α/β Ti-alloy formed by nanoindentation

International Nuclear Information System (INIS)

Viswanathan, G.B.; Lee, Eunha; Maher, Dennis M.; Banerjee, S.; Fraser, Hamish L.

2005-01-01

The hardness of α-titanium grains as a function of both indentation depth and orientation has been assessed using nanoindentation. Direct observations and analyses of the dislocation substructures have been achieved by cutting thin-foil membranes exactly through given indents with a dual-beam focused-ion-beam instrument and from diffraction-contrast experiments in a transmission electron microscope. It was found, as expected, that the hardness varied with the depth of indentation. Regarding the orientation dependence of hardness, the nature of the statistically stored dislocations as well as that of the geometrically necessary dislocations has been identified. Thus, the occurrence of the majority of the former dislocations can be predicted on the basis of Schmid's law, while noting the presence of minor densities of other dislocations required presumably because of the arbitrary shape change imposed by the nanoindenter. The geometrically necessary dislocations have been identified as the appropriate combinations of slip dislocations such that an overall displacement parallel to the direction of the indentation results

"You've Changed": Low Self-Concept Clarity Predicts Lack of Support for Partner Change.

Science.gov (United States)

Emery, Lydia F; Gardner, Wendi L; Finkel, Eli J; Carswell, Kathleen L

2018-03-01

People often pursue self-change, and having a romantic partner who supports these changes increases relationship satisfaction. However, most existing research focuses only on the experience of the person who is changing. What predicts whether people support their partner's change? People with low self-concept clarity resist self-change, so we hypothesized that they would be unsupportive of their partner's changes. People with low self-concept clarity did not support their partner's change (Study 1a), because they thought they would have to change, too (Study 1b). Low self-concept clarity predicted failing to support a partner's change, but not vice versa (Studies 2 and 3), and only for larger changes (Study 3). Not supporting a partner's change predicted decreases in relationship quality for both members of the couple (Studies 2 and 3). This research underscores the role of partners in self-change, suggesting that failing to support a partner's change may stem from self-concept confusion.

Phase Space Prediction of Chaotic Time Series with Nu-Support Vector Machine Regression

International Nuclear Information System (INIS)

Ye Meiying; Wang Xiaodong

2005-01-01

A new class of support vector machine, nu-support vector machine, is discussed which can handle both classification and regression. We focus on nu-support vector machine regression and use it for phase space prediction of chaotic time series. The effectiveness of the method is demonstrated by applying it to the Henon map. This study also compares nu-support vector machine with back propagation (BP) networks in order to better evaluate the performance of the proposed methods. The experimental results show that the nu-support vector machine regression obtains lower root mean squared error than the BP networks and provides an accurate chaotic time series prediction. These results can be attributable to the fact that nu-support vector machine implements the structural risk minimization principle and this leads to better generalization than the BP networks.

Using support vector regression to predict PM10 and PM2.5

International Nuclear Information System (INIS)

Weizhen, Hou; Zhengqiang, Li; Yuhuan, Zhang; Hua, Xu; Ying, Zhang; Kaitao, Li; Donghui, Li; Peng, Wei; Yan, Ma

2014-01-01

Support vector machine (SVM), as a novel and powerful machine learning tool, can be used for the prediction of PM 10 and PM 2.5 (particulate matter less or equal than 10 and 2.5 micrometer) in the atmosphere. This paper describes the development of a successive over relaxation support vector regress (SOR-SVR) model for the PM 10 and PM 2.5 prediction, based on the daily average aerosol optical depth (AOD) and meteorological parameters (atmospheric pressure, relative humidity, air temperature, wind speed), which were all measured in Beijing during the year of 2010–2012. The Gaussian kernel function, as well as the k-fold crosses validation and grid search method, are used in SVR model to obtain the optimal parameters to get a better generalization capability. The result shows that predicted values by the SOR-SVR model agree well with the actual data and have a good generalization ability to predict PM 10 and PM 2.5 . In addition, AOD plays an important role in predicting particulate matter with SVR model, which should be included in the prediction model. If only considering the meteorological parameters and eliminating AOD from the SVR model, the prediction results of predict particulate matter will be not satisfying

Infinite ensemble of support vector machines for prediction of ...

African Journals Online (AJOL)

Many researchers have demonstrated the use of artificial neural networks (ANNs) to predict musculoskeletal disorders risk associated with occupational exposures. In order to improve the accuracy of LBDs risk classification, this paper proposes to use the support vector machines (SVMs), a machine learning algorithm used ...

Magnetic field influence on substructure formed by electric spark treatment

International Nuclear Information System (INIS)

Reza Rahbari, G.; Ivanov, A.N.

1996-01-01

The substructure of surface layer (about 10 microns thick) has been studied by x-ray line broadening technique in the samples of plain carbon steel (0.45%C) after electric spark doping with and without magnetic field (MF). The applied spark pulse energy was 0.12 J and MF induction varied from 0 to 0.08 T. The electrode material was the same as that of the treated sample. It has been observed that the MF reduces the tensile residual surface stresses from 660 ± 15MPa (no MF) to 260 ± 15MPa (B=0.053 T). The analysis of x-ray line broadening has revealed only the existence of microstrains, which are dependent of the MF magnitude. The microstrains have been related to the randomly distributed dislocation with the density of about 3x10 sup 11 cm sup -2

Definition of a concrete bio-decontamination process in nuclear substructures

International Nuclear Information System (INIS)

Jestin, A.

2005-05-01

The decontamination of sub-structural materials represents a stake of high-importance because of the high volume generated. It is agreed then to propose efficient and effective processes. The process of bio-decontamination of the hydraulic binders leans on the mechanisms of biodegradation of concretes, phenomenon characterized in the 40's by an indirect attack of the material by acids stem from the microbial metabolism: sulphuric acid (produced by Thiobacillus), nitric acid (produced by Nitrosomonas and Nitrobacter) and organic acids (produced by fungi). The principle of the bio-decontamination process is to apply those micro-organisms on the surface of the contaminated material, in order to damage its surface and to retrieve the radionuclides. One of the multiple approaches of the process is the use of a bio-gel that makes possible the micro-organisms application. (author)

Large-scale ligand-based predictive modelling using support vector machines.

Science.gov (United States)

Alvarsson, Jonathan; Lampa, Samuel; Schaal, Wesley; Andersson, Claes; Wikberg, Jarl E S; Spjuth, Ola

2016-01-01

The increasing size of datasets in drug discovery makes it challenging to build robust and accurate predictive models within a reasonable amount of time. In order to investigate the effect of dataset sizes on predictive performance and modelling time, ligand-based regression models were trained on open datasets of varying sizes of up to 1.2 million chemical structures. For modelling, two implementations of support vector machines (SVM) were used. Chemical structures were described by the signatures molecular descriptor. Results showed that for the larger datasets, the LIBLINEAR SVM implementation performed on par with the well-established libsvm with a radial basis function kernel, but with dramatically less time for model building even on modest computer resources. Using a non-linear kernel proved to be infeasible for large data sizes, even with substantial computational resources on a computer cluster. To deploy the resulting models, we extended the Bioclipse decision support framework to support models from LIBLINEAR and made our models of logD and solubility available from within Bioclipse.

ALMA OBSERVATIONS OF Ly α BLOB 1: HALO SUBSTRUCTURE ILLUMINATED FROM WITHIN

Energy Technology Data Exchange (ETDEWEB)

Geach, J. E. [Centre for Astrophysics Research, University of Hertfordshire, Hatfield, AL10 9AB (United Kingdom); Narayanan, D. [Dept. of Physics and Astronomy, Haverford College, PA 19041 (United States); Matsuda, Y.; Ao, Y.; Kubo, M. [National Astronomical Observatory of Japan, Osawa, Mitaka, Tokyo 181-8588 (Japan); Hayes, M. [Stockholm University, Dept. of Astronomy and Oskar Klein Centre for Cosmoparticle Physics, SE-10691, Stockholm (Sweden); Mas-Ribas, Ll.; Dijkstra, M. [Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029 Blindern, NO-0315 Oslo (Norway); Steidel, C. C. [California Institute of Technology, 1216 East California Boulevard, MS 249-17, Pasadena, CA 91125 (United States); Chapman, S. C. [Dept. of Physics and Atmospheric Science, Dalhousie University, Halifax, NS B3H 4R2 (Canada); Feldmann, R. [Dept. of Astronomy, University of California Berkeley, CA 94720 (United States); Avison, A. [UK ALMA Regional Centre Node, Manchester (United Kingdom); Agertz, O. [Dept. of Physics, University of Surrey, GU2 7XH, Surrey (United Kingdom); Birkinshaw, M.; Bremer, M. N. [H. H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol, BS8 1TL (United Kingdom); Clements, D. L. [Astrophysics Group, Imperial College London, Blackett Laboratory, Prince Consort Road, London SW7 2AZ (United Kingdom); Dannerbauer, H. [Instituto de Astrofísica de Canarias, La Laguna, Tenerife (Spain); Farrah, D. [Dept. of Physics, Virginia Tech, Blacksburg, VA 24061 (United States); Harrison, C. M. [Centre for Extragalactic Astronomy, Dept. of Physics, Durham University, South Road, Durham, DH1 3LE (United Kingdom); Michałowski, M. J., E-mail: j.geach@herts.ac.uk [Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh, EH9 3HJ (United Kingdom); and others

2016-11-20

We present new Atacama Large Millimeter/Submillimeter Array (ALMA) 850 μ m continuum observations of the original Ly α Blob (LAB) in the SSA22 field at z = 3.1 (SSA22-LAB01). The ALMA map resolves the previously identified submillimeter source into three components with a total flux density of S {sub 850} = 1.68 ± 0.06 mJy, corresponding to a star-formation rate of ∼150 M {sub ⊙} yr{sup -1}. The submillimeter sources are associated with several faint ( m ≈ 27 mag) rest-frame ultraviolet sources identified in Hubble Space Telescope Imaging Spectrograph (STIS) clear filter imaging ( λ ≈ 5850 Å). One of these companions is spectroscopically confirmed with the Keck Multi-Object Spectrometer For Infra-Red Exploration to lie within 20 projected kpc and 250 km s{sup -1} of one of the ALMA components. We postulate that some of these STIS sources represent a population of low-mass star-forming satellites surrounding the central submillimeter sources, potentially contributing to their growth and activity through accretion. Using a high-resolution cosmological zoom simulation of a 10{sup 13} M {sub ⊙} halo at z = 3, including stellar, dust, and Ly α radiative transfer, we can model the ALMA+STIS observations and demonstrate that Ly α photons escaping from the central submillimeter sources are expected to resonantly scatter in neutral hydrogen, the majority of which is predicted to be associated with halo substructure. We show how this process gives rise to extended Ly α emission with similar surface brightness and morphology to observed giant LABs.

Nuclear sub-structure in 112–122Ba nuclei within relativistic mean field theory

International Nuclear Information System (INIS)

Bhuyan, M.; Patra, S.K.; Arumugam, P.; Gupta, Raj K.

2011-01-01

Working within the framework of relativistic mean field theory, we study for the first time the clustering structure (nuclear sub-structure) of 112–122 Ba nuclei in an axially deformed cylindrical coordinate. We calculate the individual neutrons and protons density distributions for Ba-isotopes. From the analysis of the clustering configurations in total (neutrons-plus-protons) density distributions for various shapes of both the ground and excited states, we find different sub-structures inside the Ba nuclei considered here. The important step, carried out here for the first time, is the counting of number of protons and neutrons present in the clustering region(s). 12 C is shown to constitute the cluster configuration in prolate-deformed ground-states of 112–116 Ba and oblate-deformed first excited states of 118–122 Ba nuclei. Presence of other lighter clusters such as 2 H, 3 H and nuclei in the neighborhood of N = Z, 14 N, 34–36 Cl, 36 Ar and 42 Ca are also indicated in the ground and excited states of these nuclei. Cases with no cluster configuration are shown for 112–116 Ba in their first and second excited states. All these results are of interest for the observed intermediate-mass-fragments and fusion–fission processes, and the so far unobserved evaporation residues from the decaying Ba* compound nuclei formed in heavy ion reactions. (author)

Perceived support from a caregiver's social ties predicts subsequent care-recipient health

Directory of Open Access Journals (Sweden)

Dannielle E. Kelley

2017-12-01

Full Text Available Most social support research has examined support from an individual patient perspective and does not model the broader social context of support felt by caregivers. Understanding how social support networks may complement healthcare services is critical, considering the aging population, as social support networks may be a valuable resource to offset some of the demands placed on the healthcare system. We sought to identify how caregivers' perceived organizational and interpersonal support from their social support network influences care-recipient health.We created a dyadic dataset of care-recipient and caregivers from the first two rounds of the National Health and Aging Trends survey (2011, 2012 and the first round of the associated National Study of Caregivers survey (2011. Using structural equation modeling, we explored how caregivers' perceived social support is associated with caregiver confidence to provide care, and is associated with care-recipient health outcomes at two time points. All data were analyzed in 2016.Social engagement with members from caregivers' social support networks was positively associated with caregiver confidence, and social engagement and confidence were positively associated with care-recipient health at time 1. Social engagement positively predicted patient health at time 2 controlling for time 1. Conversely, use of organizational support negatively predicted care-recipient health at time 2.Care-recipients experience better health outcomes when caregivers are able to be more engaged with members of their social support network. Keywords: Informal caregiving, Social support, Social support network, Patient-caregiver dyads

Potential carcinogenicity predicted by computational toxicity evaluation of thiophosphate pesticides using QSTR/QSCarciAR model.

Science.gov (United States)

Petrescu, Alina-Maria; Ilia, Gheorghe

2017-07-01

This study presents in silico prediction of toxic activities and carcinogenicity, represented by the potential carcinogenicity DSSTox/DBS, based on vector regression with a new Kernel activity, and correlating the predicted toxicity values through a QSAR model, namely: QSTR/QSCarciAR (quantitative structure toxicity relationship/quantitative structure carcinogenicity-activity relationship) described by 2D, 3D descriptors and biological descriptors. The results showed a connection between carcinogenicity (compared to the structure of a compound) and toxicity, as a basis for future studies on this subject, but each prediction is based on structurally similar compounds and the reactivation of the substructures of these compounds.

On substructuring algorithms and solution techniques for the numerical approximation of partial differential equations

Science.gov (United States)

Gunzburger, M. D.; Nicolaides, R. A.

1986-01-01

Substructuring methods are in common use in mechanics problems where typically the associated linear systems of algebraic equations are positive definite. Here these methods are extended to problems which lead to nonpositive definite, nonsymmetric matrices. The extension is based on an algorithm which carries out the block Gauss elimination procedure without the need for interchanges even when a pivot matrix is singular. Examples are provided wherein the method is used in connection with finite element solutions of the stationary Stokes equations and the Helmholtz equation, and dual methods for second-order elliptic equations.

Gamma-ray signatures of annihilation to charged leptons in dark matter substructure

International Nuclear Information System (INIS)

Kistler, Matthew D.; Siegal-Gaskins, Jennifer M.

2010-01-01

Because of their higher concentrations and small internal velocities, Milky Way subhalos can be at least as important as the smooth halo in accounting for the GeV positron excess via dark matter annihilation. After showing how this can be achieved in various scenarios, including in Sommerfeld models, we demonstrate that, in this case, the diffuse inverse-Compton emission resulting from electrons and positrons produced in substructure leads to a nearly-isotropic signal close to the level of the isotropic GeV gamma-ray background seen by Fermi. Moreover, we show that HESS cosmic-ray electron measurements can be used to constrain multi-TeV internal bremsstrahlung gamma rays arising from annihilation to charged leptons.

In Silico Prediction of Chemicals Binding to Aromatase with Machine Learning Methods.

Science.gov (United States)

Du, Hanwen; Cai, Yingchun; Yang, Hongbin; Zhang, Hongxiao; Xue, Yuhan; Liu, Guixia; Tang, Yun; Li, Weihua

2017-05-15

Environmental chemicals may affect endocrine systems through multiple mechanisms, one of which is via effects on aromatase (also known as CYP19A1), an enzyme critical for maintaining the normal balance of estrogens and androgens in the body. Therefore, rapid and efficient identification of aromatase-related endocrine disrupting chemicals (EDCs) is important for toxicology and environment risk assessment. In this study, on the basis of the Tox21 10K compound library, in silico classification models for predicting aromatase binders/nonbinders were constructed by machine learning methods. To improve the prediction ability of the models, a combined classifier (CC) strategy that combines different independent machine learning methods was adopted. Performances of the models were measured by test and external validation sets containing 1336 and 216 chemicals, respectively. The best model was obtained with the MACCS (Molecular Access System) fingerprint and CC method, which exhibited an accuracy of 0.84 for the test set and 0.91 for the external validation set. Additionally, several representative substructures for characterizing aromatase binders, such as ketone, lactone, and nitrogen-containing derivatives, were identified using information gain and substructure frequency analysis. Our study provided a systematic assessment of chemicals binding to aromatase. The built models can be helpful to rapidly identify potential EDCs targeting aromatase.

Development of new methodologies to assess the structural integrity of the grouted joint of a 10MW wind turbine substructure

DEFF Research Database (Denmark)

Santos, Benjamin; Gintautas, Tomas; Sørensen, John Dalsgaard

2018-01-01

Monopiles are currently the most commonly used substructure in the offshore wind market due to their ease of installation in shallow to medium waters. The monopile and the transition piece are connected by a grouted joint. Fatigue and corrosion are two of the most important degradation mechanisms...

Perceived support from a caregiver's social ties predicts subsequent care-recipient health.

Science.gov (United States)

Kelley, Dannielle E; Lewis, Megan A; Southwell, Brian G

2017-12-01

Most social support research has examined support from an individual patient perspective and does not model the broader social context of support felt by caregivers. Understanding how social support networks may complement healthcare services is critical, considering the aging population, as social support networks may be a valuable resource to offset some of the demands placed on the healthcare system. We sought to identify how caregivers' perceived organizational and interpersonal support from their social support network influences care-recipient health. We created a dyadic dataset of care-recipient and caregivers from the first two rounds of the National Health and Aging Trends survey (2011, 2012) and the first round of the associated National Study of Caregivers survey (2011). Using structural equation modeling, we explored how caregivers' perceived social support is associated with caregiver confidence to provide care, and is associated with care-recipient health outcomes at two time points. All data were analyzed in 2016. Social engagement with members from caregivers' social support networks was positively associated with caregiver confidence, and social engagement and confidence were positively associated with care-recipient health at time 1. Social engagement positively predicted patient health at time 2 controlling for time 1. Conversely, use of organizational support negatively predicted care-recipient health at time 2. Care-recipients experience better health outcomes when caregivers are able to be more engaged with members of their social support network.

Measurement and prediction of voice support and room gain

DEFF Research Database (Denmark)

Pelegrin Garcia, David; Brunskog, Jonas; Lyberg-Åhlander, Viveka

2012-01-01

and good acoustical quality lies in the range between 14 and 9 dB, whereas the room gain is in the range between 0.2 and 0.5 dB. The prediction model for voice support describes the measurements in the classrooms with a coefficient of determination of 0.84 and a standard deviation of 1.2 dB....

Spin effects from quark and lepton substructure at future machines

International Nuclear Information System (INIS)

Rueckl, R.

1985-01-01

If quarks and leptons are composite on a distance scale Λ -1 the physics at energies larger than Λ will provide plenty of evidence for the new level of substructure. However, already at energies below Λ compositeness should become manifest in deviations from the standard model due to form factors, residual interactions and, possibly, new ''light'' states. I discuss the virtue of polarized lepton and hadron beams in searching for new interactions and exemplify the production of excited fermions and bosons focussing on spin properties. The detailed of the contact interactions and the spin of the excited fermions and bosons can give important clues on the basic preon structure and dynamics. Phenomenological studies show that polarization asymmetries and angular distributions of decay products probe most sensitively the chiral properties of contact interactions and the spin of new states. Thus, polarized beams and good angular coverage are of great advantage

An O(n(5)) algorithm for MFE prediction of kissing hairpins and 4-chains in nucleic acids.

Science.gov (United States)

Chen, Ho-Lin; Condon, Anne; Jabbari, Hosna

2009-06-01

Efficient methods for prediction of minimum free energy (MFE) nucleic secondary structures are widely used, both to better understand structure and function of biological RNAs and to design novel nano-structures. Here, we present a new algorithm for MFE secondary structure prediction, which significantly expands the class of structures that can be handled in O(n(5)) time. Our algorithm can handle H-type pseudoknotted structures, kissing hairpins, and chains of four overlapping stems, as well as nested substructures of these types.

Tidal stripping stellar substructures around four metal-poor globular clusters in the galactic bulge

International Nuclear Information System (INIS)

Chun, Sang-Hyun; Kang, Minhee; Jung, DooSeok; Sohn, Young-Jong

2015-01-01

We investigate the spatial density configuration of stars around four metal-poor globular clusters (NGC 6266, NGC 6626, NGC 6642, and NGC 6723) in the Galactic bulge region using wide-field deep J, H, and K imaging data obtained with the Wide Field Camera near-infrared array on the United Kingdom Infrared Telescope. A statistical weighted filtering algorithm for the stars on the color–magnitude diagram is applied in order to sort cluster member candidates from the field star contamination. In two-dimensional isodensity contour maps of the clusters, we find that all four of the globular clusters exhibit strong evidence of tidally stripped stellar features beyond the tidal radius in the form of tidal tails or small density lobes/chunks. The orientations of the extended stellar substructures are likely to be associated with the effect of dynamic interaction with the Galaxy and the cluster's space motion. The observed radial density profiles of the four globular clusters also describe the extended substructures; they depart from theoretical King and Wilson models and have an overdensity feature with a break in the slope of the profile at the outer region of clusters. The observed results could imply that four globular clusters in the Galactic bulge region have experienced strong environmental effects such as tidal forces or bulge/disk shocks of the Galaxy during the dynamical evolution of globular clusters. These observational results provide further details which add to our understanding of the evolution of clusters in the Galactic bulge region as well as the formation of the Galaxy.

Solving the Mystery of Galaxy Bulges and Bulge Substructure

Science.gov (United States)

Erwin, Peter

2017-08-01

Understanding galaxy bulges is crucial for understanding galaxy evolution and the growth of supermassive black holes (SMBHs). Recent studies have shown that at least some - perhaps most - disk-galaxy bulges are actually composite structures, with both classical-bulge (spheroid) and pseudobulge (disky) components; this calls into question the standard practice of using simple, low-resolution bulge/disk decompositions to determine spheroid and SMBH mass functions. We propose WFC3 optical and near-IR imaging of a volume- and mass-limited sample of local disk galaxies to determine the full range of pure-classical, pure-pseudobulge, and composite-bulge frequencies and parameters, including stellar masses for classical bulges, disky pseudobulges, and boxy/peanut-shaped bulges. We will combine this with ground-based spectroscopy to determine the stellar-kinematic and population characteristics of the different substructures revealed by our WFC3 imaging. This will help resolve growing uncertainties about the status and nature of bulges and their relation to SMBH masses, and will provide an essential local-universe reference for understanding bulge (and SMBH) formation and evolution.

Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Data Sets.

Science.gov (United States)

Marchese Robinson, Richard L; Palczewska, Anna; Palczewski, Jan; Kidley, Nathan

2017-08-28

The ability to interpret the predictions made by quantitative structure-activity relationships (QSARs) offers a number of advantages. While QSARs built using nonlinear modeling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modeling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting nonlinear QSAR models in general and Random Forest in particular. In the current work, we compare the performance of Random Forest to those of two widely used linear modeling approaches: linear Support Vector Machines (SVMs) (or Support Vector Regression (SVR)) and partial least-squares (PLS). We compare their performance in terms of their predictivity as well as the chemical interpretability of the predictions using novel scoring schemes for assessing heat map images of substructural contributions. We critically assess different approaches for interpreting Random Forest models as well as for obtaining predictions from the forest. We assess the models on a large number of widely employed public-domain benchmark data sets corresponding to regression and binary classification problems of relevance to hit identification and toxicology. We conclude that Random Forest typically yields comparable or possibly better predictive performance than the linear modeling approaches and that its predictions may also be interpreted in a chemically and biologically meaningful way. In contrast to earlier work looking at interpretation of nonlinear QSAR models, we directly compare two methodologically distinct approaches for interpreting Random Forest models. The approaches for interpreting Random Forest assessed in our article were implemented using open-source programs that we have made available to the community. These programs are the rfFC package ( https://r-forge.r-project.org/R/?group_id=1725 ) for the R statistical

Modeling and prediction of flotation performance using support vector regression

Directory of Open Access Journals (Sweden)

Despotović Vladimir

2017-01-01

Full Text Available Continuous efforts have been made in recent year to improve the process of paper recycling, as it is of critical importance for saving the wood, water and energy resources. Flotation deinking is considered to be one of the key methods for separation of ink particles from the cellulose fibres. Attempts to model the flotation deinking process have often resulted in complex models that are difficult to implement and use. In this paper a model for prediction of flotation performance based on Support Vector Regression (SVR, is presented. Representative data samples were created in laboratory, under a variety of practical control variables for the flotation deinking process, including different reagents, pH values and flotation residence time. Predictive model was created that was trained on these data samples, and the flotation performance was assessed showing that Support Vector Regression is a promising method even when dataset used for training the model is limited.

Crystal substructures of the rotation-twinned T (Al20Cu2Mn3) phase in 2024 aluminum alloy

International Nuclear Information System (INIS)

Feng, Z.Q.; Yang, Y.Q.; Huang, B.; Li, M.H.; Chen, Y.X.; Ru, J.G.

2014-01-01

Highlights: • The substructures in rotation-twinned T (Al 20 Cu 2 Mn 3 ) particles were investigated. • A flattened hexagonal structural subunit with 20 atomic columns was proposed. • The stacking mode of these subunits at APB and TB were revealed. • The transition structures at twin domain junctions were unraveled. -- Abstract: The substructures in rotation-twinned T (Al 20 Cu 2 Mn 3 ) particles were investigated by means of high resolution transmission electron microscopy (HRTEM) and high angle annular dark field scanning transmission electron microscopy (HAADF-STEM) in the present work. A flattened hexagonal structural subunit with 20 atomic columns was proposed. The stacking mode of these subunits in non-defective T phase was proved to be tessellation of many flattened hexagonal subunits with the same orientations, while the stacking modes near anti-phase boundary (APB) and twin boundary (TB) were tessellations of two differently oriented flattened hexagonal subunits. The transition region at twin domain junctions has hybrid structure and perfect or imperfect pentagram structure. Centered with the perfect pentagram transition structure, a rotation twin with ten fan-shaped domains and constituted by five twin variants can be deduced

Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

Science.gov (United States)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

European Population Genetic Substructure: Further Definition of Ancestry Informative Markers for Distinguishing Among Diverse European Ethnic Groups

Science.gov (United States)

Tian, Chao; Kosoy, Roman; Nassir, Rami; Lee, Annette; Villoslada, Pablo; Klareskog, Lars; Hammarström, Lennart; Garchon, Henri-Jean; Pulver, Ann E.; Ransom, Michael; Gregersen, Peter K.; Seldin, Michael F.

2009-01-01

The definition of European population genetic substructure and its application to understanding complex phenotypes is becoming increasingly important. In the current study using over 4000 subjects genotyped for 300 thousand SNPs we provide further insight into relationships among European population groups and identify sets of SNP ancestry informative markers (AIMs) for application in genetic studies. In general, the graphical description of these principal components analyses (PCA) of diverse European subjects showed a strong correspondence to the geographical relationships of specific countries or regions of origin. Clearer separation of different ethnic and regional populations was observed when northern and southern European groups were considered separately and the PCA results were influenced by the inclusion or exclusion of different self-identified population groups including Ashkenazi Jewish, Sardinian and Orcadian ethnic groups. SNP AIM sets were identified that could distinguish the regional and ethnic population groups. Moreover, the studies demonstrated that most allele frequency differences between different European groups could be effectively controlled in analyses using these AIM sets. The European substructure AIMs should be widely applicable to ongoing studies to confirm and delineate specific disease susceptibility candidate regions without the necessity to perform additional genome-wide SNP studies in additional subject sets. PMID:19707526

Jet substructure and probes of CP violation in Vh production

Energy Technology Data Exchange (ETDEWEB)

Godbole, R.M. [Centre for High Energy Physics, Indian Institute of Science,Sir C.V. Raman Road, Bangalore 560012 (India); Miller, D.J. [School of Physics and Astronomy, Scottish Universities Physics Alliance, University of Glasgow,University Avenue, Glasgow G12 8QQ, Scotland (United Kingdom); Mohan, K.A. [Centre for High Energy Physics, Indian Institute of Science,Sir C.V. Raman Road, Bangalore 560012 (India); White, C.D. [School of Physics and Astronomy, Scottish Universities Physics Alliance, University of Glasgow,University Avenue, Glasgow G12 8QQ, Scotland (United Kingdom)

2015-04-20

We analyse the hVV (V=W,Z) vertex in a model independent way using Vh production. To that end, we consider possible corrections to the Standard Model Higgs Lagrangian, in the form of higher dimensional operators which parametrise the effects of new physics. In our analysis, we pay special attention to linear observables that can be used to probe CP violation in the same. By considering the associated production of a Higgs boson with a vector boson (W or Z), we use jet substructure methods to define angular observables which are sensitive to new physics effects, including an asymmetry which is linearly sensitive to the presence of CP odd effects. We demonstrate how to use these observables to place bounds on the presence of higher dimensional operators, and quantify these statements using a log likelihood analysis. Our approach allows one to probe separately the hZZ and hWW vertices, involving arbitrary combinations of BSM operators, at the Large Hadron Collider.

Software Infrastructure to Support DSAP (Dynamic Situational Awareness and Prediction) Capabilities

National Research Council Canada - National Science Library

McGraw, Robert

2006-01-01

Today's C4I systems will be required to support faster-than-real-time predictive simulation that can determine possible outcomes by re-calibrating with real-time sensor data or extracted knowledge in real-time...

Prediction and analysis of beta-turns in proteins by support vector machine.

Science.gov (United States)

Pham, Tho Hoan; Satou, Kenji; Ho, Tu Bao

2003-01-01

Tight turn has long been recognized as one of the three important features of proteins after the alpha-helix and beta-sheet. Tight turns play an important role in globular proteins from both the structural and functional points of view. More than 90% tight turns are beta-turns. Analysis and prediction of beta-turns in particular and tight turns in general are very useful for the design of new molecules such as drugs, pesticides, and antigens. In this paper, we introduce a support vector machine (SVM) approach to prediction and analysis of beta-turns. We have investigated two aspects of applying SVM to the prediction and analysis of beta-turns. First, we developed a new SVM method, called BTSVM, which predicts beta-turns of a protein from its sequence. The prediction results on the dataset of 426 non-homologous protein chains by sevenfold cross-validation technique showed that our method is superior to the other previous methods. Second, we analyzed how amino acid positions support (or prevent) the formation of beta-turns based on the "multivariable" classification model of a linear SVM. This model is more general than the other ones of previous statistical methods. Our analysis results are more comprehensive and easier to use than previously published analysis results.

Search for vector-like T' quarks using tools for the analysis of jet substructure with the CMS experiment

International Nuclear Information System (INIS)

Hoeing, Rebekka Sophie

2015-01-01

A search for pairs of vector-like T' quark produced in proton-proton collisions recorded with the CMS experiment at √(s)=8 TeV is presented. The search is optimized for decays of T' quarks to top quarks and Higgs bosons, where the top quarks and Higgs bosons decay hadronically. The T'-quark mass range between 500 and 1000 GeV is investigated. The top quarks and Higgs bosons produced in decays of the heavy T' quarks acquire large Lorentz boosts. The signatures of these particles in the detector can overlap and are therefore difficult to resolve using classical jet reconstruction methods. Large-radius jets are reconstructed and subjets formed from their constituents. The decay products of particles with large Lorentz boosts are highly collimated and can all be found within a single one of these large-radius jets. Top jets containing hadronic top-quark decays are identified with a top-tagging algorithm that analyzes the jet substructure. A b-tagging algorithm is applied to the reconstructed subjets in order to find bottom quarks within the jet substructure. In order to identify Higgs bosons with large Lorentz boosts decaying to pairs of bottom quarks, the Higgs-tagging algorithm searches for two b-tagged subjets within a single jet. This is the first application of a top-tagging algorithm in conjunction with subjet b-tagging in an analysis of CMS data. Also, a Higgs-tagging algorithm is used for the first time in a search for new physics. The main background contributions to this analysis consist of pair-produced top quarks and QCD-multijet events. More than 99% of these events are rejected by the event selection based on the new jet-substructure methods, while 6-8% of the signal events are retained. A description for the QCD-multijet background is obtained from data in a method also using jet-substructure information. Bayesian exclusion limits are derived from a likelihood ratio in which two discriminating variables are combined. T' quarks

Predicting Social Support for Grieving Persons: A Theory of Planned Behavior Perspective

Science.gov (United States)

Bath, Debra M.

2009-01-01

Research has consistently reported that social support from family, friends, and colleagues is an important factor in the bereaved person's ability to cope after the loss of a loved one. This study used a Theory of Planned Behavior framework to identify those factors that predict a person's intention to interact with, and support, a grieving…

Perceived social support predicts increased conscientiousness during older adulthood.

Science.gov (United States)

Hill, Patrick L; Payne, Brennan R; Jackson, Joshua J; Stine-Morrow, Elizabeth A L; Roberts, Brent W

2014-07-01

This study examined whether perceived social support predicted adaptive personality change in older adulthood, focusing on the trait of conscientiousness. We tested this hypothesis both at the broad domain level and with respect to the specific lower order facets that comprise conscientiousness: order, self-control, industriousness, responsibility, and traditionalism. A sample of 143 older adults (aged 60-91) completed measures of conscientiousness and social support during 2 assessments 7 months apart. Social support and conscientiousness were positively correlated among older adults. Moreover, older adults who perceived greater social support at baseline were more likely to gain in conscientiousness over time. The magnitude of this effect was relatively similar across the order, self-control, and industriousness facets. Perceived social support provides multiple benefits later in life, and the current results add to this literature by showing that it also promotes conscientiousness. As conscientiousness is linked to a variety of positive outcomes later in life, including health, future research should examine whether conscientiousness change may be an important mechanism through which social support enhances resilience in older adulthood. © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The predictive role of support in the birth experience: A longitudinal cohort study.

Science.gov (United States)

Sigurdardottir, Valgerdur Lisa; Gamble, Jennifer; Gudmundsdottir, Berglind; Kristjansdottir, Hildur; Sveinsdottir, Herdis; Gottfredsdottir, Helga

2017-12-01

Several risk factors for negative birth experience have been identified, but little is known regarding the influence of social and midwifery support on the birth experience over time. The aim of this study was to describe women's birth experience up to two years after birth and to detect the predictive role of satisfaction with social and midwifery support in the birth experience. A longitudinal cohort study was conducted with a convenience sample of pregnant women from 26 community health care centres. Data was gathered using questionnaires at 11-16 weeks of pregnancy (T1, n=1111), at five to six months (T2, n=765), and at 18-24 months after birth (T3, n=657). Data about sociodemographic factors, reproductive history, birth outcomes, social and midwifery support, depressive symptoms, and birth experience were collected. The predictive role of midwifery support in the birth experience was examined using binary logistic regression. The prevalence of negative birth experience was 5% at T2 and 5.7% at T3. Women who were not satisfied with midwifery support during pregnancy and birth were more likely to have negative birth experience at T2 than women who were satisfied with midwifery support. Operative birth, perception of prolonged birth and being a student predicted negative birth experience at both T2 and T3. Perception of negative birth experience was relatively consistent during the study period and the role of support from midwives during pregnancy and birth had a significant impact on women's perception of birth experience. Copyright © 2017 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

Intelligent Quality Prediction Using Weighted Least Square Support Vector Regression

Science.gov (United States)

Yu, Yaojun

A novel quality prediction method with mobile time window is proposed for small-batch producing process based on weighted least squares support vector regression (LS-SVR). The design steps and learning algorithm are also addressed. In the method, weighted LS-SVR is taken as the intelligent kernel, with which the small-batch learning is solved well and the nearer sample is set a larger weight, while the farther is set the smaller weight in the history data. A typical machining process of cutting bearing outer race is carried out and the real measured data are used to contrast experiment. The experimental results demonstrate that the prediction accuracy of the weighted LS-SVR based model is only 20%-30% that of the standard LS-SVR based one in the same condition. It provides a better candidate for quality prediction of small-batch producing process.

Research on bearing life prediction based on support vector machine and its application

International Nuclear Information System (INIS)

Sun Chuang; Zhang Zhousuo; He Zhengjia

2011-01-01

Life prediction of rolling element bearing is the urgent demand in engineering practice, and the effective life prediction technique is beneficial to predictive maintenance. Support vector machine (SVM) is a novel machine learning method based on statistical learning theory, and is of advantage in prediction. This paper develops SVM-based model for bearing life prediction. The inputs of the model are features of bearing vibration signal and the output is the bearing running time-bearing failure time ratio. The model is built base on a few failed bearing data, and it can fuse information of the predicted bearing. So it is of advantage to bearing life prediction in practice. The model is applied to life prediction of a bearing, and the result shows the proposed model is of high precision.

Prediction of Hydrocarbon Reservoirs Permeability Using Support Vector Machine

Directory of Open Access Journals (Sweden)

R. Gholami

2012-01-01

Full Text Available Permeability is a key parameter associated with the characterization of any hydrocarbon reservoir. In fact, it is not possible to have accurate solutions to many petroleum engineering problems without having accurate permeability value. The conventional methods for permeability determination are core analysis and well test techniques. These methods are very expensive and time consuming. Therefore, attempts have usually been carried out to use artificial neural network for identification of the relationship between the well log data and core permeability. In this way, recent works on artificial intelligence techniques have led to introduce a robust machine learning methodology called support vector machine. This paper aims to utilize the SVM for predicting the permeability of three gas wells in the Southern Pars field. Obtained results of SVM showed that the correlation coefficient between core and predicted permeability is 0.97 for testing dataset. Comparing the result of SVM with that of a general regression neural network (GRNN revealed that the SVM approach is faster and more accurate than the GRNN in prediction of hydrocarbon reservoirs permeability.

Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression

International Nuclear Information System (INIS)

Riaz, Nadeem; Wiersma, Rodney; Mao Weihua; Xing Lei; Shanker, Piyush; Gudmundsson, Olafur; Widrow, Bernard

2009-01-01

Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

Profiled support vector machines for antisense oligonucleotide efficacy prediction

Directory of Open Access Journals (Sweden)

Martín-Guerrero José D

2004-09-01

Full Text Available Abstract Background This paper presents the use of Support Vector Machines (SVMs for prediction and analysis of antisense oligonucleotide (AO efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality. We propose a two-stage strategy to develop an optimal model: (1 feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE, and (2 AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to different parts of the training data to focus the training on the most important regions. Results In the first stage, the SVM-RFE technique was most efficient and robust in the presence of low number of samples and high input space dimension. This method yielded an optimal subset of 14 representative features, which were all related to energy and sequence motifs. The second stage evaluated the performance of the predictors (overall correlation coefficient between observed and predicted efficacy, r; mean error, ME; and root-mean-square-error, RMSE using 8-fold and minus-one-RNA cross-validation methods. The profiled SVM produced the best results (r = 0.44, ME = 0.022, and RMSE= 0.278 and predicted high (>75% inhibition of gene expression and low efficacy (http://aosvm.cgb.ki.se/. Conclusions The SVM approach is well suited to the AO prediction problem, and yields a prediction accuracy superior to previous methods. The profiled SVM was found to perform better than the standard SVM, suggesting that it could lead to improvements in other prediction problems as well.

Perceived Threat Associated with Police Officers and Black Men Predicts Support for Policing Policy Reform

Directory of Open Access Journals (Sweden)

Allison Louise Skinner

2016-07-01

Full Text Available Racial disparities in policing and recent high-profile incidents resulting in the deaths of Black men have ignited a national debate on policing policies. Given evidence that both police officers and Black men may be associated with threat, we examined the impact of perceived threat on support for reformed policing policies. Across three studies we found correlational evidence that perceiving police officers as threatening predicts increased support for reformed policing practices (e.g., limiting the use of lethal force and matching police force demographics to those of the community. In contrast, perceiving Black men as threatening predicted reduced support for policing policy reform. Perceived threat also predicted willingness to sign a petition calling for police reform. Experimental evidence indicated that priming participants to associate Black men with threat could also reduce support for policing policy reform, and this effect was moderated by internal motivation to respond without prejudice. Priming participants to associate police officers with threat did not increase support for policing policy reform. Results indicate that resistance to policing policy reform is associated with perceiving Black men as threatening. Moreover, findings suggest that publicizing racially charged police encounters, which may conjure associations between Black men and threat, could reduce support for policing policy reform.

Prediction of sport adherence through the influence of autonomy-supportive coaching among spanish adolescent athletes.

Science.gov (United States)

Almagro, Bartolomé J; Sáenz-López, Pedro; Moreno, Juan A

2010-01-01

The purpose of this study was to test a motivational model of the coach-athlete relationship, based on self-determination theory and on the hierarchical model of intrinsic and extrinsic motivation. The sample comprised of 608 athletes (ages of 12-17 years) completed the following measures: interest in athlete's input, praise for autonomous behavior, perceived autonomy, intrinsic motivation, and the intention to be physically active. Structural equation modeling results demonstrated that interest in athletes' input and praise for autonomous behavior predicted perceived autonomy, and perceived autonomy positively predicted intrinsic motivation. Finally, intrinsic motivation predicted the intention to be physically active in the future. The results are discussed in relation to the importance of the climate of autonomy support created by the coach on intrinsic motivation and adherence to sport by adolescent athletes. Further, the results provide information related to the possible objectives of future interventions for the education of coaches, with the goal of providing them with tools and strategies to favor the development of intrinsic motivation among their athletes. In conclusion, the climate of autonomy support created by the coach can predict the autonomy perceived by the athletes which predicts the intrinsic motivation experienced by the athletes, and therefore, their adherence to athletic practice. Key pointsImportance of the climate of autonomy support created by the coach on intrinsic motivation and adherence to sport by adolescent athletes.Interest in athletes' input and praise for autonomous behavior predicted perceived autonomy, and perceived autonomy positively predicted intrinsic motivation.Intrinsic motivation predicted the intention to be physically active in the future.

Antibodies directed to drug epitopes to investigate the structure of drug-protein photoadducts. Recognition of a common photobound substructure in tiaprofenic acid/ketoprofen cross-photoreactivity.

Science.gov (United States)

Lahoz, A; Hernández, D; Miranda, M A; Pérez-Prieto, J; Morera, I M; Castell, J V

2001-11-01

Drug-induced photoallergy is an immune adverse reaction to the combined effect of drugs and light. From the mechanistic point of view, it first involves covalent binding of drug to protein resulting in the formation of a photoantigen. Hence, determination of the structures of drug-protein photoadducts is of great relevance to understand the molecular basis of photoallergy and cross-immunoreactivity among drugs. Looking for new strategies to investigate the covalent photobinding of drugs to proteins, we generated highly specific antibodies to drug chemical substructures. The availability of such antibodies has allowed us to discriminate between the different modes by which tiaprofenic acid (TPA), suprofen (SUP), and ketoprofen (KTP) photobind to proteins. The finding that the vast majority of the TPA photoadduct can be accounted for by means of antibody anti-benzoyl strongly supports the view that the drug binds preferentially via the thiophene ring, leaving the benzene ring more accessible. By contrast, selective recognition of SUP-protein photoadducts by antibody anti-thenoyl evidences a preferential coupling via the benzene ring leaving the thiophene moiety more distant from the protein matrix. In the case of KTP, photoadducts are exclusively recognized by antibody anti-benzoyl, indicating that the benzene ring is again more accessible. As a result of this research, we have been able to identify a common substructure that is present in TPA-albumin and KTP-albumin photoadducts. This is remarkable since, at a first sight, the greatest structural similarities can be found between TPA and SUP as they share the same benzoylthiophene chromophore. These findings can explain the previously reported observations of cross-reactivity to KTP (or TPA) in patients photosensitized to TPA (or KTP).

X-ray and optical substructures of the DAFT/FADA survey clusters

Science.gov (United States)

Guennou, L.; Durret, F.; Adami, C.; Lima Neto, G. B.

2013-04-01

We have undertaken the DAFT/FADA survey with the double aim of setting constraints on dark energy based on weak lensing tomography and of obtaining homogeneous and high quality data for a sample of 91 massive clusters in the redshift range 0.4-0.9 for which there were HST archive data. We have analysed the XMM-Newton data available for 42 of these clusters to derive their X-ray temperatures and luminosities and search for substructures. Out of these, a spatial analysis was possible for 30 clusters, but only 23 had deep enough X-ray data for a really robust analysis. This study was coupled with a dynamical analysis for the 26 clusters having at least 30 spectroscopic galaxy redshifts in the cluster range. Altogether, the X-ray sample of 23 clusters and the optical sample of 26 clusters have 14 clusters in common. We present preliminary results on the coupled X-ray and dynamical analyses of these 14 clusters.

RESONANT CLUMPING AND SUBSTRUCTURE IN GALACTIC DISKS

International Nuclear Information System (INIS)

Molloy, Matthew; Smith, Martin C.; Shen, Juntai; Evans, N. Wyn

2015-01-01

We describe a method to extract resonant orbits from N-body simulations, exploiting the fact that they close in frames rotating with a constant pattern speed. Our method is applied to the N-body simulation of the Milky Way by Shen et al. This simulation hosts a massive bar, which drives strong resonances and persistent angular momentum exchange. Resonant orbits are found throughout the disk, both close to the bar and out to the very edges of the disk. Using Fourier spectrograms, we demonstrate that the bar is driving kinematic substructure even in the very outer parts of the disk. We identify two major orbit families in the outskirts of the disk, one of which makes significant contributions to the kinematic landscape, namely, the m:l = 3:−2 family, resonating with the bar. A mechanism is described that produces bimodal distributions of Galactocentric radial velocities at selected azimuths in the outer disk. It occurs as a result of the temporal coherence of particles on the 3:−2 resonant orbits, which causes them to arrive simultaneously at pericenter or apocenter. This resonant clumping, due to the in-phase motion of the particles through their epicycle, leads to both inward and outward moving groups that belong to the same orbital family and consequently produce bimodal radial velocity distributions. This is a possible explanation of the bimodal velocity distributions observed toward the Galactic anticenter by Liu et al. Another consequence is that transient overdensities appear and dissipate (in a symmetric fashion), resulting in a periodic pulsing of the disk’s surface density

RESONANT CLUMPING AND SUBSTRUCTURE IN GALACTIC DISKS

Energy Technology Data Exchange (ETDEWEB)

Molloy, Matthew [Kavli Institute for Astronomy and Astrophysics, Peking University, Yi He Yuan Lu 5, Hai Dian Qu, Beijing 100871 (China); Smith, Martin C.; Shen, Juntai [Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030 (China); Evans, N. Wyn, E-mail: matthewmolloy@gmail.com, E-mail: msmith@shao.ac.cn, E-mail: jshen@shao.ac.cn, E-mail: nwe@ast.cam.ac.uk [Institute of Astronomy, Madingley Road, Cambridge, CB3 0HA (United Kingdom)

2015-05-10

We describe a method to extract resonant orbits from N-body simulations, exploiting the fact that they close in frames rotating with a constant pattern speed. Our method is applied to the N-body simulation of the Milky Way by Shen et al. This simulation hosts a massive bar, which drives strong resonances and persistent angular momentum exchange. Resonant orbits are found throughout the disk, both close to the bar and out to the very edges of the disk. Using Fourier spectrograms, we demonstrate that the bar is driving kinematic substructure even in the very outer parts of the disk. We identify two major orbit families in the outskirts of the disk, one of which makes significant contributions to the kinematic landscape, namely, the m:l = 3:−2 family, resonating with the bar. A mechanism is described that produces bimodal distributions of Galactocentric radial velocities at selected azimuths in the outer disk. It occurs as a result of the temporal coherence of particles on the 3:−2 resonant orbits, which causes them to arrive simultaneously at pericenter or apocenter. This resonant clumping, due to the in-phase motion of the particles through their epicycle, leads to both inward and outward moving groups that belong to the same orbital family and consequently produce bimodal radial velocity distributions. This is a possible explanation of the bimodal velocity distributions observed toward the Galactic anticenter by Liu et al. Another consequence is that transient overdensities appear and dissipate (in a symmetric fashion), resulting in a periodic pulsing of the disk’s surface density.

The substructure of immunoglobulin G resolved to 25 kDa using amplitude modulation AFM in air

International Nuclear Information System (INIS)

Thomson, Neil H.

2005-01-01

Amplitude modulation (or tapping-mode) atomic force microscopy (AM AFM or TM AFM) in air can reveal sub-molecular details of isolated multi-subunit proteins, such as immunoglobulin G (IgG) antibodies, on atomically flat support surfaces such as mica [A. San Paulo, R. Garcia, Biophys. J. 78(3) (2000) 1599]. This is achieved by controlling the microscope imaging parameters (e.g. cantilever drive frequency and set-point amplitude) to keep the AFM tip predominantly in the attractive force regime. Under these conditions, the 50 kDa F c and F ab subunits can be resolved when the molecule has the appropriate orientation on the surface. The presence of a water layer on hydrophilic mica is an important factor affecting imaging contrast, a consequence of capillary neck formation between tip and surface [L. Zitzler, S. Herminghaus, F. Mugele, Phys. Rev. B 66(15) (2002) 155436]. Desiccation of samples to remove surface bound water layers can yield reproducible imaging of the IgG substructure [N.H. Thomson, J. Microsc. (Oxford) 217(3) (2004) 193]. This approach has also given higher resolution than previously achieved, down to about 25 kDa, and these data are detailed here. These subdomains are formed as two immunoglobulin folds from the light and heavy peptide chains of the IgG crossover. This result has been validated by comparing the AFM images with X-ray crystallography data from the protein data bank. These data show that the AFM can obtain 25 kDa resolution on isolated protein molecules with commercially available silicon tips, but, as expected for a local probe technique, resolution is highly dependent on the macromolecular orientation on the support surface

Performance of jet substructure techniques for large-R jets in proton-proton collisions at $\\sqrt{s}$ = 7 TeV using the ATLAS detector

CERN Document Server

Aad, Georges; Abbott, Brad; Abdallah, Jalal; Abdel Khalek, Samah; Abdelalim, Ahmed Ali; Abdinov, Ovsat; Aben, Rosemarie; Abi, Babak; Abolins, Maris; AbouZeid, Ossama; Abramowicz, Halina; Abreu, Henso; Abulaiti, Yiming; Acharya, Bobby Samir; Adamczyk, Leszek; Adams, David; Addy, Tetteh; Adelman, Jahred; Adomeit, Stefanie; Adye, Tim; Aefsky, Scott; Aguilar-Saavedra, Juan Antonio; Agustoni, Marco; Ahlen, Steven; Ahles, Florian; Ahmad, Ashfaq; Ahsan, Mahsana; Aielli, Giulio; Åkesson, Torsten Paul Ake; Akimoto, Ginga; Akimov, Andrei; Alam, Muhammad Aftab; Albert, Justin; Albrand, Solveig; Aleksa, Martin; Aleksandrov, Igor; Alessandria, Franco; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexopoulos, Theodoros; Alhroob, Muhammad; Aliev, Malik; Alimonti, Gianluca; Alison, John; Allbrooke, Benedict; Allison, Lee John; Allport, Phillip; Allwood-Spiers, Sarah; Almond, John; Aloisio, Alberto; Alon, Raz; Alonso, Alejandro; Alonso, Francisco; Altheimer, Andrew David; Alvarez Gonzalez, Barbara; Alviggi, Mariagrazia; Amako, Katsuya; Amaral Coutinho, Yara; Amelung, Christoph; Ammosov, Vladimir; Amor Dos Santos, Susana Patricia; Amorim, Antonio; Amoroso, Simone; Amram, Nir; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Anduaga, Xabier; Angelidakis, Stylianos; Anger, Philipp; Angerami, Aaron; Anghinolfi, Francis; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoki, Masato; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Arce, Ayana; Arfaoui, Samir; Arguin, Jean-Francois; Argyropoulos, Spyridon; Arik, Engin; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnal, Vanessa; Artamonov, Andrei; Artoni, Giacomo; Arutinov, David; Asai, Shoji; Asbah, Nedaa; Ask, Stefan; Åsman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astalos, Robert; Astbury, Alan; Atkinson, Markus; Auerbach, Benjamin; Auge, Etienne; Augsten, Kamil; Aurousseau, Mathieu; Avolio, Giuseppe; Axen, David; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baccaglioni, Giuseppe; Bacci, Cesare; Bach, Andre; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Backus Mayes, John; Badescu, Elisabeta; Bagiacchi, Paolo; Bagnaia, Paolo; Bai, Yu; Bailey, David; Bain, Travis; Baines, John; Baker, Oliver Keith; Baker, Sarah; Balek, Petr; Balli, Fabrice; Banas, Elzbieta; Banerjee, Piyali; Banerjee, Swagato; Banfi, Danilo; Bangert, Andrea Michelle; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Baranov, Sergei; Barber, Tom; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Bardin, Dmitri; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Bartoldus, Rainer; Barton, Adam Edward; Bartsch, Valeria; Basye, Austin; Bates, Richard; Batkova, Lucia; Batley, Richard; Battaglia, Andreas; Battistin, Michele; Bauer, Florian; Bawa, Harinder Singh; Beale, Steven; Beau, Tristan; Beauchemin, Pierre-Hugues; Beccherle, Roberto; Bechtle, Philip; Beck, Hans Peter; Becker, Anne Kathrin; Becker, Sebastian; Beckingham, Matthew; Becks, Karl-Heinz; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Beemster, Lars; Beermann, Thomas; Begel, Michael; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellerive, Alain; Bellomo, Massimiliano; Belloni, Alberto; Beloborodova, Olga; Belotskiy, Konstantin; Beltramello, Olga; Benary, Odette; Benchekroun, Driss; Bendtz, Katarina; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez Garcia, Jorge-Armando; Benjamin, Douglas; Bensinger, James; Benslama, Kamal; Bentvelsen, Stan; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Berglund, Elina; Beringer, Jürg; Bernat, Pauline; Bernhard, Ralf; Bernius, Catrin; Bernlochner, Florian Urs; Berry, Tracey; Bertella, Claudia; Bertolucci, Federico; Besana, Maria Ilaria; Besjes, Geert-Jan; Besson, Nathalie; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianchini, Louis; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Bittner, Bernhard; Black, Curtis; Black, James; Black, Kevin; Blair, Robert; Blanchard, Jean-Baptiste; Blazek, Tomas; Bloch, Ingo; Blocker, Craig; Blocki, Jacek; Blum, Walter; Blumenschein, Ulrike; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Boddy, Christopher Richard; Boehler, Michael; Boek, Jennifer; Boek, Thorsten Tobias; Boelaert, Nele; Bogaerts, Joannes Andreas; Bogdanchikov, Alexander; Bogouch, Andrei; Bohm, Christian; Bohm, Jan; Boisvert, Veronique; Bold, Tomasz; Boldea, Venera; Bolnet, Nayanka Myriam; Bomben, Marco; Bona, Marcella; Boonekamp, Maarten; Bordoni, Stefania; Borer, Claudia; Borisov, Anatoly; Borissov, Guennadi; Borri, Marcello; Borroni, Sara; Bortfeldt, Jonathan; Bortolotto, Valerio; Bos, Kors; Boscherini, Davide; Bosman, Martine; Boterenbrood, Hendrik; Bouchami, Jihene; Boudreau, Joseph; Bouhova-Thacker, Evelina Vassileva; Boumediene, Djamel Eddine; Bourdarios, Claire; Bousson, Nicolas; Boutouil, Sara; Boveia, Antonio; Boyd, James; Boyko, Igor; Bozovic-Jelisavcic, Ivanka; Bracinik, Juraj; Branchini, Paolo; Brandt, Andrew; Brandt, Gerhard; Brandt, Oleg; Bratzler, Uwe; Brau, Benjamin; Brau, James; Braun, Helmut; Brazzale, Simone Federico; Brelier, Bertrand; Bremer, Johan; Brendlinger, Kurt; Brenner, Richard; Bressler, Shikma; Bristow, Timothy Michael; Britton, Dave; Brochu, Frederic; Brock, Ian; Brock, Raymond; Broggi, Francesco; Bromberg, Carl; Bronner, Johanna; Brooijmans, Gustaaf; Brooks, Timothy; Brooks, William; Brown, Gareth; Bruckman de Renstrom, Pawel; Bruncko, Dusan; Bruneliere, Renaud; Brunet, Sylvie; Bruni, Alessia; Bruni, Graziano; Bruschi, Marco; Bryngemark, Lene; Buanes, Trygve; Buat, Quentin; Bucci, Francesca; Buchanan, James; Buchholz, Peter; Buckingham, Ryan; Buckley, Andrew; Buda, Stelian Ioan; Budagov, Ioulian; Budick, Burton; Bugge, Lars; Bulekov, Oleg; Bundock, Aaron Colin; Bunse, Moritz; Buran, Torleiv; Burckhart, Helfried; Burdin, Sergey; Burgess, Thomas; Burke, Stephen; Busato, Emmanuel; Büscher, Volker; Bussey, Peter; Buszello, Claus-Peter; Butler, Bart; Butler, John; Buttar, Craig; Butterworth, Jonathan; Buttinger, William; Byszewski, Marcin; Cabrera Urbán, Susana; Caforio, Davide; Cakir, Orhan; Calafiura, Paolo; Calderini, Giovanni; Calfayan, Philippe; Calkins, Robert; Caloba, Luiz; Caloi, Rita; Calvet, David; Calvet, Samuel; Camacho Toro, Reina; Camarri, Paolo; Cameron, David; Caminada, Lea Michaela; Caminal Armadans, Roger; Campana, Simone; Campanelli, Mario; Canale, Vincenzo; Canelli, Florencia; Canepa, Anadi; Cantero, Josu; Cantrill, Robert; Cao, Tingting; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capriotti, Daniele; Capua, Marcella; Caputo, Regina; Cardarelli, Roberto; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Sascha; Carquin, Edson; Carrillo-Montoya, German D; Carter, Antony; Carter, Janet; Carvalho, João; Casadei, Diego; Casado, Maria Pilar; Cascella, Michele; Caso, Carlo; Castaneda-Miranda, Elizabeth; Castelli, Angelantonio; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Cataldi, Gabriella; Catastini, Pierluigi; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Cattani, Giordano; Caughron, Seth; Cavaliere, Viviana; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Cerio, Benjamin; Santiago Cerqueira, Augusto; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cervelli, Alberto; Cetin, Serkant Ali; Chafaq, Aziz; Chakraborty, Dhiman; Chalupkova, Ina; Chan, Kevin; Chang, Philip; Chapleau, Bertrand; Chapman, John Derek; Chapman, John Wehrley; Charlton, Dave; Chavda, Vikash; Chavez Barajas, Carlos Alberto; Cheatham, Susan; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Shenjian; Chen, Xin; Chen, Yujiao; Cheng, Yangyang; Cheplakov, Alexander; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Cheung, Sing-Leung; Chevalier, Laurent; Chiarella, Vitaliano; Chiefari, Giovanni; Childers, John Taylor; Chilingarov, Alexandre; Chiodini, Gabriele; Chisholm, Andrew; Chislett, Rebecca Thalatta; Chitan, Adrian; Chizhov, Mihail; Choudalakis, Georgios; Chouridou, Sofia; Chow, Bonnie Kar Bo; Christidi, Ilektra-Athanasia; Christov, Asen; Chromek-Burckhart, Doris; Chu, Ming-Lee; Chudoba, Jiri; Ciapetti, Guido; Ciftci, Abbas Kenan; Ciftci, Rena; Cinca, Diane; Cindro, Vladimir; Ciocio, Alessandra; Cirilli, Manuela; Cirkovic, Predrag; Citron, Zvi Hirsh; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Philip James; Clarke, Robert; Clemens, Jean-Claude; Clement, Benoit; Clement, Christophe; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Coelli, Simone; Coffey, Laurel; Cogan, Joshua Godfrey; Coggeshall, James; Colas, Jacques; Cole, Stephen; Colijn, Auke-Pieter; Collins, Neil; Collins-Tooth, Christopher; Collot, Johann; Colombo, Tommaso; Colon, German; Compostella, Gabriele; Conde Muiño, Patricia; Coniavitis, Elias; Conidi, Maria Chiara; Consonni, Sofia Maria; Consorti, Valerio; Constantinescu, Serban; Conta, Claudio; Conti, Geraldine; Conventi, Francesco; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Cooper-Smith, Neil; Copic, Katherine; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Corso-Radu, Alina; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Côté, David; Cottin, Giovanna; Courneyea, Lorraine; Cowan, Glen; Cox, Brian; Cranmer, Kyle; Crépé-Renaudin, Sabine; Crescioli, Francesco; Cristinziani, Markus; Crosetti, Giovanni; Cuciuc, Constantin-Mihai; Cuenca Almenar, Cristóbal; Cuhadar Donszelmann, Tulay; Cummings, Jane; Curatolo, Maria; Curtis, Chris; Cuthbert, Cameron; Czirr, Hendrik; Czodrowski, Patrick; Czyczula, Zofia; D'Auria, Saverio; D'Onofrio, Monica; D'Orazio, Alessia; Da Cunha Sargedas De Sousa, Mario Jose; Da Via, Cinzia; Dabrowski, Wladyslaw; Dafinca, Alexandru; Dai, Tiesheng; Dallaire, Frederick; Dallapiccola, Carlo; Dam, Mogens; Damiani, Daniel; Daniells, Andrew Christopher; Danielsson, Hans Olof; Dao, Valerio; Darbo, Giovanni; Darlea, Georgiana Lavinia; Darmora, Smita; Dassoulas, James; Davey, Will; Davidek, Tomas; Davidson, Nadia; Davies, Eleanor; Davies, Merlin; Davignon, Olivier; Davison, Adam; Davygora, Yuriy; Dawe, Edmund; Dawson, Ian; Daya-Ishmukhametova, Rozmin; De, Kaushik; de Asmundis, Riccardo; De Castro, Stefano; De Cecco, Sandro; de Graat, Julien; De Groot, Nicolo; de Jong, Paul; De La Taille, Christophe; De la Torre, Hector; De Lorenzi, Francesco; De Nooij, Lucie; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vivie De Regie, Jean-Baptiste; De Zorzi, Guido; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dechenaux, Benjamin; Dedovich, Dmitri; Degenhardt, James; Del Peso, Jose; Del Prete, Tarcisio; Delemontex, Thomas; Deliyergiyev, Maksym; Dell'Acqua, Andrea; Dell'Asta, Lidia; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delsart, Pierre-Antoine; Deluca, Carolina; Demers, Sarah; Demichev, Mikhail; Demilly, Aurelien; Demirkoz, Bilge; Denisov, Sergey; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Deviveiros, Pier-Olivier; Dewhurst, Alastair; DeWilde, Burton; Dhaliwal, Saminder; Dhullipudi, Ramasudhakar; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Donato, Camilla; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Luise, Silvestro; Di Mattia, Alessandro; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Diaz, Marco Aurelio; Diehl, Edward; Dietrich, Janet; Dietzsch, Thorsten; Diglio, Sara; Dindar Yagci, Kamile; Dingfelder, Jochen; Dinut, Florin; Dionisi, Carlo; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; Barros do Vale, Maria Aline; Do Valle Wemans, André; Doan, Thi Kieu Oanh; Dobos, Daniel; Dobson, Ellie; Dodd, Jeremy; Doglioni, Caterina; Doherty, Tom; Dohmae, Takeshi; Doi, Yoshikuni; Dolejsi, Jiri; Dolezal, Zdenek; Dolgoshein, Boris; Donadelli, Marisilvia; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dos Anjos, Andre; Dotti, Andrea; Dova, Maria-Teresa; Doyle, Tony; Dris, Manolis; Dubbert, Jörg; Dube, Sourabh; Dubreuil, Emmanuelle; Duchovni, Ehud; Duckeck, Guenter; Duda, Dominik; Dudarev, Alexey; Dudziak, Fanny; Duflot, Laurent; Dufour, Marc-Andre; Duguid, Liam; Dührssen, Michael; Dunford, Monica; Duran Yildiz, Hatice; Düren, Michael; Dwuznik, Michal; Ebke, Johannes; Eckweiler, Sebastian; Edson, William; Edwards, Clive; Edwards, Nicholas Charles; Ehrenfeld, Wolfgang; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Eisenhandler, Eric; Ekelof, Tord; El Kacimi, Mohamed; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Ellis, Katherine; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Enari, Yuji; Endner, Oliver Chris; Engelmann, Roderich; Engl, Albert; Erdmann, Johannes; Ereditato, Antonio; Eriksson, Daniel; Ernst, Jesse; Ernst, Michael; Ernwein, Jean; Errede, Deborah; Errede, Steven; Ertel, Eugen; Escalier, Marc; Esch, Hendrik; Escobar, Carlos; Espinal Curull, Xavier; Esposito, Bellisario; Etienne, Francois; Etienvre, Anne-Isabelle; Etzion, Erez; Evangelakou, Despoina; Evans, Hal; Fabbri, Laura; Fabre, Caroline; Facini, Gabriel; Fakhrutdinov, Rinat; Falciano, Speranza; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farooque, Trisha; Farrell, Steven; Farrington, Sinead; Farthouat, Philippe; Fassi, Farida; Fassnacht, Patrick; Fassouliotis, Dimitrios; Fatholahzadeh, Baharak; Favareto, Andrea; Fayard, Louis; Federic, Pavol; Fedin, Oleg; Fedorko, Wojciech; Fehling-Kaschek, Mirjam; Feligioni, Lorenzo; Feng, Cunfeng; Feng, Eric; Feng, Haolu; Fenyuk, Alexander; Ferencei, Jozef; Fernando, Waruna; Ferrag, Samir; Ferrando, James; Ferrara, Valentina; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferreira de Lima, Danilo Enoque; Ferrer, Antonio; Ferrere, Didier; Ferretti, Claudio; Ferretto Parodi, Andrea; Fiascaris, Maria; Fiedler, Frank; Filipčič, Andrej; Filthaut, Frank; Fincke-Keeler, Margret; Finelli, Kevin Daniel; Fiolhais, Miguel; Fiorini, Luca; Firan, Ana; Fischer, Julia; Fisher, Matthew; Fitzgerald, Eric Andrew; Flechl, Martin; Fleck, Ivor; Fleischmann, Philipp; Fleischmann, Sebastian; Fletcher, Gareth Thomas; Fletcher, Gregory; Flick, Tobias; Floderus, Anders; Flores Castillo, Luis; Florez Bustos, Andres Carlos; Flowerdew, Michael; Fonseca Martin, Teresa; Formica, Andrea; Forti, Alessandra; Fortin, Dominique; Fournier, Daniel; Fox, Harald; Francavilla, Paolo; Franchini, Matteo; Franchino, Silvia; Francis, David; Franklin, Melissa; Franz, Sebastien; Fraternali, Marco; Fratina, Sasa; French, Sky; Friedrich, Conrad; Friedrich, Felix; Froidevaux, Daniel; Frost, James; Fukunaga, Chikara; Fullana Torregrosa, Esteban; Fulsom, Bryan Gregory; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gabrielli, Alessandro; Gabrielli, Andrea; Gadatsch, Stefan; Gadfort, Thomas; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Pauline; Galea, Cristina; Galhardo, Bruno; Gallas, Elizabeth; Gallo, Valentina Santina; Gallop, Bruce; Gallus, Petr; Gan, KK; Gandrajula, Reddy Pratap; Gao, Yongsheng; Gaponenko, Andrei; Garay Walls, Francisca; Garberson, Ford; García, Carmen; García Navarro, José Enrique; Garcia-Sciveres, Maurice; Gardner, Robert; Garelli, Nicoletta; Garonne, Vincent; Gatti, Claudio; Gaudio, Gabriella; Gaur, Bakul; Gauthier, Lea; Gauzzi, Paolo; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gazis, Evangelos; Ge, Peng; Gecse, Zoltan; Gee, Norman; Geerts, Daniël Alphonsus Adrianus; Geich-Gimbel, Christoph; Gellerstedt, Karl; Gemme, Claudia; Gemmell, Alistair; Genest, Marie-Hélène; Gentile, Simonetta; George, Matthias; George, Simon; Gerbaudo, Davide; Gershon, Avi; Ghazlane, Hamid; Ghodbane, Nabil; Giacobbe, Benedetto; Giagu, Stefano; Giangiobbe, Vincent; Gianotti, Fabiola; Gibbard, Bruce; Gibson, Adam; Gibson, Stephen; Gilchriese, Murdock; Gillam, Thomas; Gillberg, Dag; Gillman, Tony; Gingrich, Douglas; Giokaris, Nikos; Giordani, MarioPaolo; Giordano, Raffaele; Giorgi, Francesco Michelangelo; Giovannini, Paola; Giraud, Pierre-Francois; Giugni, Danilo; Giuliani, Claudia; Giunta, Michele; Gjelsten, Børge Kile; Gkialas, Ioannis; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glazov, Alexandre; Glonti, George; Goddard, Jack Robert; Godfrey, Jennifer; Godlewski, Jan; Goebel, Martin; Goeringer, Christian; Goldfarb, Steven; Golling, Tobias; Golubkov, Dmitry; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Gonçalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez Silva, Laura; Gonzalez-Sevilla, Sergio; Goodson, Jeremiah Jet; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorfine, Grant; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Goshaw, Alfred; Gössling, Claus; Gostkin, Mikhail Ivanovitch; Gough Eschrich, Ivo; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Gozpinar, Serdar; Graber, Lars; Grabowska-Bold, Iwona; Grafström, Per; Grahn, Karl-Johan; Gramstad, Eirik; Grancagnolo, Francesco; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Gray, Heather; Gray, Julia Ann; Graziani, Enrico; Grebenyuk, Oleg; Greenshaw, Timothy; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grigalashvili, Nugzar; Grillo, Alexander; Grimm, Kathryn; Grinstein, Sebastian; Gris, Philippe Luc Yves; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Grohs, Johannes Philipp; Grohsjean, Alexander; Gross, Eilam; Grosse-Knetter, Joern; Groth-Jensen, Jacob; Grybel, Kai; Guescini, Francesco; Guest, Daniel; Gueta, Orel; Guicheney, Christophe; Guido, Elisa; Guillemin, Thibault; Guindon, Stefan; Gul, Umar; Gunther, Jaroslav; Guo, Jun; Gutierrez, Phillip; Guttman, Nir; Gutzwiller, Olivier; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haas, Stefan; Haber, Carl; Hadavand, Haleh Khani; Haefner, Petra; Hajduk, Zbigniew; Hakobyan, Hrachya; Hall, David; Halladjian, Garabed; Hamacher, Klaus; Hamal, Petr; Hamano, Kenji; Hamer, Matthias; Hamilton, Andrew; Hamilton, Samuel; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Handel, Carsten; Hanke, Paul; Hansen, John Renner; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hansson, Per; Hara, Kazuhiko; Hard, Andrew; Harenberg, Torsten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Hartert, Jochen; Hartjes, Fred; Haruyama, Tomiyoshi; Harvey, Alex; Hasegawa, Satoshi; Hasegawa, Yoji; Hassani, Samira; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Anthony David; Hayakawa, Takashi; Hayashi, Takayasu; Hayden, Daniel; Hays, Chris; Hayward, Helen; Haywood, Stephen; Head, Simon; Heck, Tobias; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heinemann, Beate; Heisterkamp, Simon; Hejbal, Jiri; Helary, Louis; Heller, Claudio; Heller, Matthieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, James; Henderson, Robert; Henke, Michael; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Hensel, Carsten; Herbert, Geoffrey Henry; Medina Hernandez, Carlos; Hernández Jiménez, Yesenia; Herrberg-Schubert, Ruth; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Hickling, Robert; Higón-Rodriguez, Emilio; Hill, John; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoffman, Julia; Hoffmann, Dirk; Hofmann, Julia Isabell; Hohlfeld, Marc; Holmgren, Sven-Olof; Holzbauer, Jenny; Hong, Tae Min; Hooft van Huysduynen, Loek; Hostachy, Jean-Yves; Hou, Suen; Hoummada, Abdeslam; Howard, Jacob; Howarth, James; Hrabovsky, Miroslav; Hristova, Ivana; Hrivnac, Julius; Hryn'ova, Tetiana; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Hu, Diedi; Hu, Xueye; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huettmann, Antje; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Huhtinen, Mika; Hülsing, Tobias Alexander; Hurwitz, Martina; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibragimov, Iskander; Iconomidou-Fayard, Lydia; Idarraga, John; Iengo, Paolo; Igonkina, Olga; Ikegami, Yoichi; Ikematsu, Katsumasa; Ikeno, Masahiro; Iliadis, Dimitrios; Ilic, Nikolina; Ince, Tayfun; Ioannou, Pavlos; Iodice, Mauro; Iordanidou, Kalliopi; Ippolito, Valerio; Irles Quiles, Adrian; Isaksson, Charlie; Ishino, Masaya; Ishitsuka, Masaki; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Ivashin, Anton; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, John; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobs, Karl; Jakobsen, Sune; Jakoubek, Tomas; Jakubek, Jan; Jamin, David Olivier; Jana, Dilip; Jansen, Eric; Jansen, Hendrik; Janssen, Jens; Jantsch, Andreas; Janus, Michel; Jared, Richard; Jarlskog, Göran; Jeanty, Laura; Jeng, Geng-yuan; Jen-La Plante, Imai; Jennens, David; Jenni, Peter; Jentzsch, Jennifer; Jeske, Carl; Jež, Pavel; Jézéquel, Stéphane; Jha, Manoj Kumar; Ji, Haoshuang; Ji, Weina; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Shan; Jinnouchi, Osamu; Joergensen, Morten Dam; Joffe, David; Johansen, Marianne; Johansson, Erik; Johansson, Per; Johnert, Sebastian; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tim; Jorge, Pedro; Joshi, Kiran Daniel; Jovicevic, Jelena; Jovin, Tatjana; Ju, Xiangyang; Jung, Christian; Jungst, Ralph Markus; Jussel, Patrick; Juste Rozas, Aurelio; Kabana, Sonja; Kaci, Mohammed; Kaczmarska, Anna; Kadlecik, Peter; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kajomovitz, Enrique; Kalinin, Sergey; Kama, Sami; Kanaya, Naoko; Kaneda, Michiru; Kaneti, Steven; Kanno, Takayuki; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kar, Deepak; Karakostas, Konstantinos; Karnevskiy, Mikhail; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasieczka, Gregor; Kass, Richard; Kastanas, Alex; Kataoka, Yousuke; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kazama, Shingo; Kazanin, Vassili; Kazarinov, Makhail; Keeler, Richard; Keener, Paul; Kehoe, Robert; Keil, Markus; Keller, John; Keoshkerian, Houry; Kepka, Oldrich; Kerševan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Keung, Justin; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Kharchenko, Dmitri; Khodinov, Alexander; Khomich, Andrei; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kim, Hyeon Jin; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; King, Samuel Burton; Kirk, Julie; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kitamura, Takumi; Kittelmann, Thomas; Kiuchi, Kenji; Kladiva, Eduard; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klemetti, Miika; Klier, Amit; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klinger, Joel Alexander; Klinkby, Esben; Klioutchnikova, Tatiana; Klok, Peter; Kluge, Eike-Erik; Kluit, Peter; Kluth, Stefan; Kneringer, Emmerich; Knoops, Edith; Knue, Andrea; Ko, Byeong Rok; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Koenig, Sebastian; Koetsveld, Folkert; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kogan, Lucy Anne; Kohlmann, Simon; Kohn, Fabian; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kolanoski, Hermann; Koletsou, Iro; Koll, James; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Köneke, Karsten; König, Adriaan; Kono, Takanori; Kononov, Anatoly; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kopeliansky, Revital; Koperny, Stefan; Köpke, Lutz; Kopp, Anna Katharina; Korcyl, Krzysztof; Kordas, Kostantinos; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotov, Sergey; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kraus, Jana; Kravchenko, Anton; Kreiss, Sven; Kretzschmar, Jan; Kreutzfeldt, Kristof; Krieger, Nina; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Kruker, Tobias; Krumnack, Nils; Krumshteyn, Zinovii; Kruse, Amanda; Kruse, Mark; Kubota, Takashi; Kuday, Sinan; Kuehn, Susanne; Kugel, Andreas; Kuhl, Thorsten; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kuna, Marine; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurata, Masakazu; Kurochkin, Yurii; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; Kwee, Regina; La Rosa, Alessandro; La Rotonda, Laura; Labarga, Luis; Lablak, Said; Lacasta, Carlos; Lacava, Francesco; Lacey, James; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laier, Heiko; Laisne, Emmanuel; Lambourne, Luke; Lampen, Caleb; Lampl, Walter; Lançon, Eric; Landgraf, Ulrich; Landon, Murrough; Lang, Valerie Susanne; Lange, Clemens; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Lanza, Agostino; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Larner, Aimee; Lassnig, Mario; Laurelli, Paolo; Lavorini, Vincenzo; Lavrijsen, Wim; Laycock, Paul; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Menedeu, Eve; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Guillaume; Lefebvre, Michel; Legendre, Marie; Legger, Federica; Leggett, Charles; Lehmacher, Marc; Lehmann Miotto, Giovanna; Leister, Andrew Gerard; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Lemmer, Boris; Lendermann, Victor; Leney, Katharine; Lenz, Tatiana; Lenzen, Georg; Lenzi, Bruno; Leonhardt, Kathrin; Leontsinis, Stefanos; Lepold, Florian; Leroy, Claude; Lessard, Jean-Raphael; Lester, Christopher; Lester, Christopher Michael; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bing; Li, Bo; Li, Haifeng; Li, Ho Ling; Li, Shu; Li, Xuefei; Liang, Zhijun; Liao, Hongbo; Liberti, Barbara; Lichard, Peter; Lie, Ki; Liebal, Jessica; Liebig, Wolfgang; Limbach, Christian; Limosani, Antonio; Limper, Maaike; Lin, Simon; Linde, Frank; Lindquist, Brian Edward; Linnemann, James; Lipeles, Elliot; Lipniacka, Anna; Lisovyi, Mykhailo; Liss, Tony; Lissauer, David; Lister, Alison; Litke, Alan; Liu, Dong; Liu, Jianbei; Liu, Kun; Liu, Lulu; Liu, Miaoyuan; Liu, Minghui; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lo Sterzo, Francesco; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loddenkoetter, Thomas; Loebinger, Fred; Loevschall-Jensen, Ask Emil; Loginov, Andrey; Loh, Chang Wei; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Lombardo, Vincenzo Paolo; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Loscutoff, Peter; Losty, Michael; Lou, XinChou; Lounis, Abdenour; Loureiro, Karina; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Ludwig, Dörthe; Ludwig, Inga; Ludwig, Jens; Luehring, Frederick; Lukas, Wolfgang; Luminari, Lamberto; Lund, Esben; Lundberg, Johan; Lundberg, Olof; Lund-Jensen, Bengt; Lundquist, Johan; Lungwitz, Matthias; Lynn, David; Lysak, Roman; Lytken, Else; Ma, Hong; Ma, Lian Liang; Maccarrone, Giovanni; Macchiolo, Anna; Maček, Boštjan; Machado Miguens, Joana; Macina, Daniela; Mackeprang, Rasmus; Madar, Romain; Madaras, Ronald; Maddocks, Harvey Jonathan; Mader, Wolfgang; Madsen, Alexander; Maeno, Mayuko; Maeno, Tadashi; Magnoni, Luca; Magradze, Erekle; Mahboubi, Kambiz; Mahlstedt, Joern; Mahmoud, Sara; Mahout, Gilles; Maiani, Camilla; Maidantchik, Carmen; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malaescu, Bogdan; Malecki, Pawel; Malecki, Piotr; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mamuzic, Judita; Mandelli, Luciano; Mandić, Igor; Mandrysch, Rocco; Maneira, José; Manfredini, Alessandro; Manhaes de Andrade Filho, Luciano; Manjarres Ramos, Joany Andreina; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Mantifel, Rodger; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchese, Fabrizio; Marchiori, Giovanni; Marcisovsky, Michal; Marino, Christopher; Marques, Carlos; Marroquim, Fernando; Marshall, Zach; Marti, Lukas Fritz; Marti-Garcia, Salvador; Martin, Brian; Martin, Brian Thomas; Martin, Jean-Pierre; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martinez, Homero; Martinez, Mario; Martin-Haugh, Stewart; Martyniuk, Alex; Marx, Marilyn; Marzano, Francesco; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Matsunaga, Hiroyuki; Matsushita, Takashi; Mättig, Peter; Mättig, Stefan; Mattravers, Carly; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; Mazini, Rachid; Mazur, Michael; Mazzaferro, Luca; Mazzanti, Marcello; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McCubbin, Norman; McFarlane, Kenneth; Mcfayden, Josh; Mchedlidze, Gvantsa; Mclaughlan, Tom; McMahon, Steve; McPherson, Robert; Meade, Andrew; Mechnich, Joerg; Mechtel, Markus; Medinnis, Mike; Meehan, Samuel; Meera-Lebbai, Razzak; Meguro, Tatsuma; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meineck, Christian; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Meloni, Federico; Mendoza Navas, Luis; Mengarelli, Alberto; Menke, Sven; Meoni, Evelin; Mercurio, Kevin Michael; Meric, Nicolas; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Merritt, Hayes; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Meyer, Joerg; Michal, Sebastien; Middleton, Robin; Migas, Sylwia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Miller, David; Mills, Bill; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Miñano Moya, Mercedes; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mirabelli, Giovanni; Mitrevski, Jovan; Mitsou, Vasiliki A; Mitsui, Shingo; Miyagawa, Paul; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Moeller, Victoria; Mohapatra, Soumya; Mohr, Wolfgang; Moles-Valls, Regina; Molfetas, Angelos; Mönig, Klaus; Monini, Caterina; Monk, James; Monnier, Emmanuel; Montejo Berlingen, Javier; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Mora Herrera, Clemencia; Moraes, Arthur; Morange, Nicolas; Morel, Julien; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Marcus; Morii, Masahiro; Moritz, Sebastian; Morley, Anthony Keith; Mornacchi, Giuseppe; Morris, John; Morvaj, Ljiljana; Möser, Nicolas; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Mudd, Richard; Mueller, Felix; Mueller, James; Mueller, Klemens; Mueller, Thibaut; Mueller, Timo; Muenstermann, Daniel; Munwes, Yonathan; Murillo Quijada, Javier Alberto; Murray, Bill; Mussche, Ido; Musto, Elisa; Myagkov, Alexey; Myska, Miroslav; Nackenhorst, Olaf; Nadal, Jordi; Nagai, Koichi; Nagai, Ryo; Nagai, Yoshikazu; Nagano, Kunihiro; Nagarkar, Advait; Nagasaka, Yasushi; Nagel, Martin; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Namasivayam, Harisankar; Nanava, Gizo; Napier, Austin; Narayan, Rohin; Nash, Michael; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Neal, Homer; Nechaeva, Polina; Neep, Thomas James; Negri, Andrea; Negri, Guido; Negrini, Matteo; Nektarijevic, Snezana; Nelson, Andrew; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neumann, Manuel; Neusiedl, Andrea; Neves, Ricardo; Nevski, Pavel; Newcomer, Mitchel; Newman, Paul; Nguyen, Duong Hai; Nguyen Thi Hong, Van; Nickerson, Richard; Nicolaidou, Rosy; Nicquevert, Bertrand; Niedercorn, Francois; Nielsen, Jason; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nisius, Richard; Nobe, Takuya; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Norberg, Scarlet; Nordberg, Markus; Novakova, Jana; Nozaki, Mitsuaki; Nozka, Libor; Nuncio-Quiroz, Adriana-Elizabeth; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; O'Brien, Brendan Joseph; O'Neil, Dugan; O'Shea, Val; Oakes, Louise Beth; Oakham, Gerald; Oberlack, Horst; Ocariz, Jose; Ochi, Atsuhiko; Ochoa, Ines; Oda, Susumu; Odaka, Shigeru; Odier, Jerome; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohshima, Takayoshi; Okamura, Wataru; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Olchevski, Alexander; Olivares Pino, Sebastian Andres; Oliveira, Miguel Alfonso; Oliveira Damazio, Denis; Oliver Garcia, Elena; Olivito, Dominick; Olszewski, Andrzej; Olszowska, Jolanta; Onofre, António; Onyisi, Peter; Oram, Christopher; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlando, Nicola; Oropeza Barrera, Cristina; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Otero y Garzon, Gustavo; Ottersbach, John; Ouchrif, Mohamed; Ouellette, Eric; Ould-Saada, Farid; Ouraou, Ahmimed; Ouyang, Qun; Ovcharova, Ana; Owen, Mark; Owen, Simon; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pacheco Pages, Andres; Padilla Aranda, Cristobal; Pagan Griso, Simone; Paganis, Efstathios; Pahl, Christoph; Paige, Frank; Pais, Preema; Pajchel, Katarina; Palacino, Gabriel; Paleari, Chiara; Palestini, Sandro; Pallin, Dominique; Palma, Alberto; Palmer, Jody; Pan, Yibin; Panagiotopoulou, Evgenia; Panduro Vazquez, William; Pani, Priscilla; Panikashvili, Natalia; Panitkin, Sergey; Pantea, Dan; Papadelis, Aras; Papadopoulou, Theodora; Papageorgiou, Konstantinos; Paramonov, Alexander; Paredes Hernandez, Daniela; Park, Woochun; Parker, Michael Andrew; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pashapour, Shabnaz; Pasqualucci, Enrico; Passaggio, Stefano; Passeri, Antonio; Pastore, Fernanda; Pastore, Francesca; Pásztor, Gabriella; Pataraia, Sophio; Patel, Nikhul; Pater, Joleen; Patricelli, Sergio; Pauly, Thilo; Pearce, James; Pedersen, Maiken; Pedraza Lopez, Sebastian; Pedraza Morales, Maria Isabel; Peleganchuk, Sergey; Pelikan, Daniel; Peng, Haiping; Penning, Bjoern; Penson, Alexander; Penwell, John; Perez Cavalcanti, Tiago; Perez Codina, Estel; Pérez García-Estañ, María Teresa; Perez Reale, Valeria; Perini, Laura; Pernegger, Heinz; Perrino, Roberto; Perrodo, Pascal; Peshekhonov, Vladimir; Peters, Krisztian; Peters, Yvonne; Petersen, Brian; Petersen, Jorgen; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petrolo, Emilio; Petrucci, Fabrizio; Petschull, Dennis; Petteni, Michele; Pezoa, Raquel; Phan, Anna; Phillips, Peter William; Piacquadio, Giacinto; Pianori, Elisabetta; Picazio, Attilio; Piccaro, Elisa; Piccinini, Maurizio; Piec, Sebastian Marcin; Piegaia, Ricardo; Pignotti, David; Pilcher, James; Pilkington, Andrew; Pina, João Antonio; Pinamonti, Michele; Pinder, Alex; Pinfold, James; Pingel, Almut; Pinto, Belmiro; Pizio, Caterina; Pleier, Marc-Andre; Pleskot, Vojtech; Plotnikova, Elena; Plucinski, Pawel; Poblaguev, Andrei; Poddar, Sahill; Podlyski, Fabrice; Poettgen, Ruth; Poggioli, Luc; Pohl, David-leon; Pohl, Martin; Polesello, Giacomo; Policicchio, Antonio; Polifka, Richard; Polini, Alessandro; Polychronakos, Venetios; Pomeroy, Daniel; Pommès, Kathy; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Popovic, Dragan; Poppleton, Alan; Portell Bueso, Xavier; Pospelov, Guennady; Pospisil, Stanislav; Potrap, Igor; Potter, Christina; Potter, Christopher; Poulard, Gilbert; Poveda, Joaquin; Pozdnyakov, Valery; Prabhu, Robindra; Pralavorio, Pascal; Pranko, Aliaksandr; Prasad, Srivas; Pravahan, Rishiraj; Prell, Soeren; Pretzl, Klaus Peter; Price, Darren; Price, Joe; Price, Lawrence; Prieur, Damien; Primavera, Margherita; Proissl, Manuel; Prokofiev, Kirill; Prokoshin, Fedor; Protopapadaki, Eftychia-sofia; Protopopescu, Serban; Proudfoot, James; Prudent, Xavier; Przybycien, Mariusz; Przysiezniak, Helenka; Psoroulas, Serena; Ptacek, Elizabeth; Pueschel, Elisa; Puldon, David; Purohit, Milind; Puzo, Patrick; Pylypchenko, Yuriy; Qian, Jianming; Quadt, Arnulf; Quarrie, David; Quayle, William; Quilty, Donnchadha; Raas, Marcel; Radeka, Veljko; Radescu, Voica; Radloff, Peter; Ragusa, Francesco; Rahal, Ghita; Rajagopalan, Srinivasan; Rammensee, Michael; Rammes, Marcus; Randle-Conde, Aidan Sean; Randrianarivony, Koloina; Rangel-Smith, Camila; Rao, Kanury; Rauscher, Felix; Rave, Tobias Christian; Ravenscroft, Thomas; Raymond, Michel; Read, Alexander Lincoln; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Reinsch, Andreas; Reisinger, Ingo; Relich, Matthew; Rembser, Christoph; Ren, Zhongliang; Renaud, Adrien; Rescigno, Marco; Resconi, Silvia; Resende, Bernardo; Reznicek, Pavel; Rezvani, Reyhaneh; Richter, Robert; Richter-Was, Elzbieta; Ridel, Melissa; Rieck, Patrick; Rijssenbeek, Michael; Rimoldi, Adele; Rinaldi, Lorenzo; Rios, Ryan Randy; Ritsch, Elmar; Riu, Imma; Rivoltella, Giancesare; Rizatdinova, Flera; Rizvi, Eram; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robson, Aidan; Rocha de Lima, Jose Guilherme; Roda, Chiara; Roda Dos Santos, Denis; Roe, Adam; Roe, Shaun; Røhne, Ole; Rolli, Simona; Romaniouk, Anatoli; Romano, Marino; Romeo, Gaston; Romero Adam, Elena; Rompotis, Nikolaos; Roos, Lydia; Ros, Eduardo; Rosati, Stefano; Rosbach, Kilian; Rose, Anthony; Rose, Matthew; Rosenbaum, Gabriel; Rosendahl, Peter Lundgaard; Rosenthal, Oliver; Rossetti, Valerio; Rossi, Elvira; Rossi, Leonardo Paolo; Rotaru, Marina; Roth, Itamar; Rothberg, Joseph; Rousseau, David; Royon, Christophe; Rozanov, Alexandre; Rozen, Yoram; Ruan, Xifeng; Rubbo, Francesco; Rubinskiy, Igor; Ruckstuhl, Nicole; Rud, Viacheslav; Rudolph, Christian; Rudolph, Matthew Scott; Rühr, Frederik; Ruiz-Martinez, Aranzazu; Rumyantsev, Leonid; Rurikova, Zuzana; Rusakovich, Nikolai; Ruschke, Alexander; Rutherfoord, John; Ruthmann, Nils; Ruzicka, Pavel; Ryabov, Yury; Rybar, Martin; Rybkin, Grigori; Ryder, Nick; Saavedra, Aldo; Saddique, Asif; Sadeh, Iftach; Sadrozinski, Hartmut; Sadykov, Renat; Safai Tehrani, Francesco; Sakamoto, Hiroshi; Salamanna, Giuseppe; Salamon, Andrea; Saleem, Muhammad; Salek, David; Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvachua Ferrando, Belén; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sampsonidis, Dimitrios; Sanchez, Arturo; Sánchez, Javier; Sanchez Martinez, Victoria; Sandaker, Heidi; Sander, Heinz Georg; Sanders, Michiel; Sandhoff, Marisa; Sandoval, Tanya; Sandoval, Carlos; Sandstroem, Rikard; Sankey, Dave; Sansoni, Andrea; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Santoyo Castillo, Itzebelt; Sapp, Kevin; Saraiva, João; Sarangi, Tapas; Sarkisyan-Grinbaum, Edward; Sarrazin, Bjorn; Sarri, Francesca; Sartisohn, Georg; Sasaki, Osamu; Sasaki, Yuichi; Sasao, Noboru; Satsounkevitch, Igor; Sauvage, Gilles; Sauvan, Emmanuel; Sauvan, Jean-Baptiste; Savard, Pierre; Savinov, Vladimir; Savu, Dan Octavian; Sawyer, Craig; Sawyer, Lee; Saxon, David; Saxon, James; Sbarra, Carla; Sbrizzi, Antonio; Scannicchio, Diana; Scarcella, Mark; Schaarschmidt, Jana; Schacht, Peter; Schaefer, Douglas; Schaelicke, Andreas; Schaepe, Steffen; Schaetzel, Sebastian; Schäfer, Uli; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R. Dean; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Scherzer, Max; Schiavi, Carlo; Schieck, Jochen; Schillo, Christian; Schioppa, Marco; Schlenker, Stefan; Schmidt, Evelyn; Schmieden, Kristof; Schmitt, Christian; Schmitt, Christopher; Schmitt, Sebastian; Schneider, Basil; Schnellbach, Yan Jie; Schnoor, Ulrike; Schoeffel, Laurent; Schoening, Andre; Schorlemmer, Andre Lukas; Schott, Matthias; Schouten, Doug; Schovancova, Jaroslava; Schram, Malachi; Schroeder, Christian; Schroer, Nicolai; Schultens, Martin Johannes; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwartzman, Ariel; Schwegler, Philipp; Schwemling, Philippe; Schwienhorst, Reinhard; Schwindling, Jerome; Schwindt, Thomas; Schwoerer, Maud; Sciacca, Gianfranco; Scifo, Estelle; Sciolla, Gabriella; Scott, Bill; Scutti, Federico; Searcy, Jacob; Sedov, George; Sedykh, Evgeny; Seidel, Sally; Seiden, Abraham; Seifert, Frank; Seixas, José; Sekhniaidze, Givi; Sekula, Stephen; Selbach, Karoline Elfriede; Seliverstov, Dmitry; Sellers, Graham; Seman, Michal; Semprini-Cesari, Nicola; Serfon, Cedric; Serin, Laurent; Serkin, Leonid; Serre, Thomas; Seuster, Rolf; Severini, Horst; Sfyrla, Anna; Shabalina, Elizaveta; Shamim, Mansoora; Shan, Lianyou; Shank, James; Shao, Qi Tao; Shapiro, Marjorie; Shatalov, Pavel; Shaw, Kate; Sherwood, Peter; Shimizu, Shima; Shimojima, Makoto; Shin, Taeksu; Shiyakova, Mariya; Shmeleva, Alevtina; Shochet, Mel; Short, Daniel; Shrestha, Suyog; Shulga, Evgeny; Shupe, Michael; Sicho, Petr; Sidoti, Antonio; Siegert, Frank; Sijacki, Djordje; Silbert, Ohad; Silva, José; Silver, Yiftah; Silverstein, Daniel; Silverstein, Samuel; Simak, Vladislav; Simard, Olivier; Simic, Ljiljana; Simion, Stefan; Simioni, Eduard; Simmons, Brinick; Simoniello, Rosa; Simonyan, Margar; Sinervo, Pekka; Sinev, Nikolai; Sipica, Valentin; Siragusa, Giovanni; Sircar, Anirvan; Sisakyan, Alexei; Sivoklokov, Serguei; Sjölin, Jörgen; Sjursen, Therese; Skinnari, Louise Anastasia; Skottowe, Hugh Philip; Skovpen, Kirill; Skubic, Patrick; Slater, Mark; Slavicek, Tomas; Sliwa, Krzysztof; Smakhtin, Vladimir; Smart, Ben; Smestad, Lillian; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smith, Kenway; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snidero, Giacomo; Snow, Joel; Snyder, Scott; Sobie, Randall; Sodomka, Jaromir; Soffer, Abner; Soh, Dart-yin; Solans, Carlos; Solar, Michael; Solc, Jaroslav; Soldatov, Evgeny; Soldevila, Urmila; Solfaroli Camillocci, Elena; Solodkov, Alexander; Solovyanov, Oleg; Solovyev, Victor; Soni, Nitesh; Sood, Alexander; Sopko, Vit; Sopko, Bruno; Sosebee, Mark; Soualah, Rachik; Soueid, Paul; Soukharev, Andrey; South, David; Spagnolo, Stefania; Spanò, Francesco; Spighi, Roberto; Spigo, Giancarlo; Spiwoks, Ralf; Spousta, Martin; Spreitzer, Teresa; Spurlock, Barry; St Denis, Richard Dante; Stahlman, Jonathan; Stamen, Rainer; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stanescu-Bellu, Madalina; Stanitzki, Marcel Michael; Stapnes, Steinar; Starchenko, Evgeny; Stark, Jan; Staroba, Pavel; Starovoitov, Pavel; Staszewski, Rafal; Staude, Arnold; Stavina, Pavel; Steele, Genevieve; Steinbach, Peter; Steinberg, Peter; Stekl, Ivan; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stern, Sebastian; Stewart, Graeme; Stillings, Jan Andre; Stockton, Mark; Stoebe, Michael; Stoerig, Kathrin; Stoicea, Gabriel; Stonjek, Stefan; Stradling, Alden; Straessner, Arno; Strandberg, Jonas; Strandberg, Sara; Strandlie, Are; Strang, Michael; Strauss, Emanuel; Strauss, Michael; Strizenec, Pavol; Ströhmer, Raimund; Strom, David; Strong, John; Stroynowski, Ryszard; Stugu, Bjarne; Stumer, Iuliu; Stupak, John; Sturm, Philipp; Styles, Nicholas Adam; Su, Dong; Subramania, Halasya Siva; Subramaniam, Rajivalochan; Succurro, Antonella; Sugaya, Yorihito; Suhr, Chad; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Xiaohu; Sundermann, Jan Erik; Suruliz, Kerim; Susinno, Giancarlo; Sutton, Mark; Suzuki, Yu; Suzuki, Yuta; Svatos, Michal; Swedish, Stephen; Swiatlowski, Maximilian; Sykora, Ivan; Sykora, Tomas; Ta, Duc; Tackmann, Kerstin; Taffard, Anyes; Tafirout, Reda; Taiblum, Nimrod; Takahashi, Yuta; Takai, Helio; Takashima, Ryuichi; Takeda, Hiroshi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tam, Jason; Tamsett, Matthew; Tan, Kong Guan; Tanaka, Junichi; Tanaka, Reisaburo; Tanaka, Satoshi; Tanaka, Shuji; Tanasijczuk, Andres Jorge; Tani, Kazutoshi; Tannoury, Nancy; Tapprogge, Stefan; Tardif, Dominique; Tarem, Shlomit; Tarrade, Fabien; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tashiro, Takuya; Tassi, Enrico; Tayalati, Yahya; Taylor, Christopher; Taylor, Frank; Taylor, Geoffrey; Taylor, Wendy; Teinturier, Marthe; Teischinger, Florian Alfred; Teixeira Dias Castanheira, Matilde; Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Terada, Susumu; Terashi, Koji; Terron, Juan; Testa, Marianna; Teuscher, Richard; Therhaag, Jan; Theveneaux-Pelzer, Timothée; Thoma, Sascha; Thomas, Juergen; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Thong, Wai Meng; Thun, Rudolf; Tian, Feng; Tibbetts, Mark James; Tic, Tomáš; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tiouchichine, Elodie; Tipton, Paul; Tisserant, Sylvain; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokár, Stanislav; Tokushuku, Katsuo; Tollefson, Kirsten; Tomlinson, Lee; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Tonoyan, Arshak; Topfel, Cyril; Topilin, Nikolai; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Tran, Huong Lan; Trefzger, Thomas; Tremblet, Louis; Tricoli, Alessandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Tripiana, Martin; Triplett, Nathan; Trischuk, William; Trocmé, Benjamin; Troncon, Clara; Trottier-McDonald, Michel; Trovatelli, Monica; True, Patrick; Trzebinski, Maciej; Trzupek, Adam; Tsarouchas, Charilaos; Tseng, Jeffrey; Tsiakiris, Menelaos; Tsiareshka, Pavel; Tsionou, Dimitra; Tsipolitis, Georgios; Tsiskaridze, Shota; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsung, Jieh-Wen; Tsuno, Soshi; Tsybychev, Dmitri; Tua, Alan; Tudorache, Alexandra; Tudorache, Valentina; Tuggle, Joseph; Tuna, Alexander Naip; Turala, Michal; Turecek, Daniel; Turk Cakir, Ilkay; Turra, Ruggero; Tuts, Michael; Tykhonov, Andrii; Tylmad, Maja; Tyndel, Mike; Uchida, Kirika; Ueda, Ikuo; Ueno, Ryuichi; Ughetto, Michael; Ugland, Maren; Uhlenbrock, Mathias; Ukegawa, Fumihiko; Unal, Guillaume; Undrus, Alexander; Unel, Gokhan; Ungaro, Francesca; Unno, Yoshinobu; Urbaniec, Dustin; Urquijo, Phillip; Usai, Giulio; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Vahsen, Sven; Valencic, Nika; Valentinetti, Sara; Valero, Alberto; Valery, Loic; Valkar, Stefan; Valladolid Gallego, Eva; Vallecorsa, Sofia; Valls Ferrer, Juan Antonio; Van Berg, Richard; Van Der Deijl, Pieter; van der Geer, Rogier; van der Graaf, Harry; Van Der Leeuw, Robin; van der Ster, Daniel; van Eldik, Niels; van Gemmeren, Peter; Van Nieuwkoop, Jacobus; van Vulpen, Ivo; Vanadia, Marco; Vandelli, Wainer; Vaniachine, Alexandre; Vankov, Peter; Vannucci, Francois; Vari, Riccardo; Varnes, Erich; Varol, Tulin; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vassilakopoulos, Vassilios; Vazeille, Francois; Vazquez Schroeder, Tamara; Veloso, Filipe; Veneziano, Stefano; Ventura, Andrea; Ventura, Daniel; Venturi, Manuela; Venturi, Nicola; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Viel, Simon; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinogradov, Vladimir; Virzi, Joseph; Vitells, Ofer; Viti, Michele; Vivarelli, Iacopo; Vives Vaque, Francesc; Vlachos, Sotirios; Vladoiu, Dan; Vlasak, Michal; Vogel, Adrian; Vokac, Petr; Volpi, Guido; 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Wright, Michael; Wrona, Bozydar; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wulf, Evan; Wynne, Benjamin; Xella, Stefania; Xiao, Meng; Xie, Song; Xu, Chao; Xu, Da; Xu, Lailin; Yabsley, Bruce; Yacoob, Sahal; Yamada, Miho; Yamaguchi, Hiroshi; Yamaguchi, Yohei; Yamamoto, Akira; Yamamoto, Kyoko; Yamamoto, Shimpei; Yamamura, Taiki; Yamanaka, Takashi; Yamauchi, Katsuya; Yamazaki, Takayuki; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Hongtao; Yang, Un-Ki; Yang, Yi; Yang, Zhaoyu; Yanush, Serguei; Yao, Liwen; Yasu, Yoshiji; Yatsenko, Elena; Yau Wong, Kaven Henry; Ye, Jingbo; Ye, Shuwei; Yen, Andy L; Yildirim, Eda; Yilmaz, Metin; Yoosoofmiya, Reza; Yorita, Kohei; Yoshida, Rikutaro; Yoshihara, Keisuke; Young, Charles; Young, Christopher John; Youssef, Saul; Yu, Dantong; Yu, David Ren-Hwa; Yu, Jaehoon; Yu, Jie; Yuan, Li; Yurkewicz, Adam; Zabinski, Bartlomiej; Zaidan, Remi; Zaitsev, Alexander; Zambito, Stefano; Zanello, Lucia; Zanzi, Daniele; Zaytsev, Alexander; Zeitnitz, Christian; Zeman, Martin; Zemla, Andrzej; Zenin, Oleg; Ženiš, Tibor; Zerwas, Dirk; Zevi della Porta, Giovanni; Zhang, Dongliang; Zhang, Huaqiao; Zhang, Jinlong; Zhang, Lei; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Zhengguo; Zhemchugov, Alexey; Zhong, Jiahang; Zhou, Bing; Zhou, Ning; Zhou, Yue; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zibell, Andre; Zieminska, Daria; Zimin, Nikolai; Zimmermann, Christoph; Zimmermann, Robert; Zimmermann, Simone; Zimmermann, Stephanie; Zinonos, Zinonas; Ziolkowski, Michael; Zitoun, Robert; Živković, Lidija; Zmouchko, Viatcheslav; Zobernig, Georg; Zoccoli, Antonio; zur Nedden, Martin; Zutshi, Vishnu; Zwalinski, Lukasz

2013-09-13

This paper presents the application of a variety of techniques to study jet substructure. The performance of various modified jet algorithms, or jet grooming techniques, for several jet types and event topologies is investigated for jets with transverse momentum larger than 300 GeV. Properties of jets subjected to the mass-drop filtering, trimming, and pruning algorithms are found to have reduced sensitivity to multiple proton-proton interactions, are more stable at high luminosity and improve the physics potential of searches for heavy boosted objects. Studies of the expected discrimination power of jet mass and jet substructure observables in searches for new physics are also presented. Event samples enriched in boosted W and Z bosons and top-quark pairs are used to study both the individual jet invariant mass scales and the efficacy of algorithms to tag boosted hadronic objects. The analyses presented use the full 2011 ATLAS dataset, corresponding to an integrated luminosity of 4.7 $\\pm$ 0.1 /fb from proto...

A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

Science.gov (United States)

Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

2009-07-21

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.

Structural design and analysis for the ISX-C/ATF tokamak of the vacuum vessel, coil joints, and supports

International Nuclear Information System (INIS)

Mayhall, J.A.; Cain, W.D.; Hammonds, C.J.; Johnson, R.L.; Gray, W.H.

1981-01-01

The ISX-C/ATF is being designed as a test bed for advanced toroidal concepts. Because of numerous design concepts being evaluated, a flexible, easily changeable structural-design math-model was needed to afford quick evalution of the structural feasibility of the many proposed concepts. To satisfy this need, the NASTRAN Automated Multi-Stage Substructures technique was used to build a quick-changeable math model. This technique was especially needed because all the coils, first wall and diagnostic devices are to be supported by the vacuum vessel, requiring the entire structure to be analyzed as a system. Without the use of the substructuring technique, the required man hours and computer core would have made timely design analysis impossible. To illustrate the technique, the detailed design analysis of the concept Torsatron (with helical coils and T.F. coils) is presented

SHARP - IV. An apparent flux-ratio anomaly resolved by the edge-on disc in B0712+472

NARCIS (Netherlands)

Hsueh, J.-W.; Oldham, L.; Spingola, C.; Vegetti, S.; Fassnacht, C. D.; Auger, M. W.; Koopmans, L. V. E.; McKean, J. P.; Lagattuta, D. J.

2017-01-01

Flux-ratio anomalies in quasar lenses can be attributed to dark matter substructure surrounding the lensing galaxy and thus used to constrain the substructure mass fraction. Previous applications of this approach infer a substructure abundance that is potentially in tension with the predictions of Λ

Substructuring of multibody systems for numerical transfer path analysis in internal combustion engines

Science.gov (United States)

Acri, Antonio; Offner, Guenter; Nijman, Eugene; Rejlek, Jan

2016-10-01

Noise legislations and the increasing customer demands determine the Noise Vibration and Harshness (NVH) development of modern commercial vehicles. In order to meet the stringent legislative requirements for the vehicle noise emission, exact knowledge of all vehicle noise sources and their acoustic behavior is required. Transfer path analysis (TPA) is a fairly well established technique for estimating and ranking individual low-frequency noise or vibration contributions via the different transmission paths. Transmission paths from different sources to target points of interest and their contributions can be analyzed by applying TPA. This technique is applied on test measurements, which can only be available on prototypes, at the end of the designing process. In order to overcome the limits of TPA, a numerical transfer path analysis methodology based on the substructuring of a multibody system is proposed in this paper. Being based on numerical simulation, this methodology can be performed starting from the first steps of the designing process. The main target of the proposed methodology is to get information of noise sources contributions of a dynamic system considering the possibility to have multiple forces contemporary acting on the system. The contributions of these forces are investigated with particular focus on distribute or moving forces. In this paper, the mathematical basics of the proposed methodology and its advantages in comparison with TPA will be discussed. Then, a dynamic system is investigated with a combination of two methods. Being based on the dynamic substructuring (DS) of the investigated model, the methodology proposed requires the evaluation of the contact forces at interfaces, which are computed with a flexible multi-body dynamic (FMBD) simulation. Then, the structure-borne noise paths are computed with the wave based method (WBM). As an example application a 4-cylinder engine is investigated and the proposed methodology is applied on the

Chemical structure-based predictive model for methanogenic anaerobic biodegradation potential.

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Meylan, William; Boethling, Robert; Aronson, Dallas; Howard, Philip; Tunkel, Jay

2007-09-01

Many screening-level models exist for predicting aerobic biodegradation potential from chemical structure, but anaerobic biodegradation generally has been ignored by modelers. We used a fragment contribution approach to develop a model for predicting biodegradation potential under methanogenic anaerobic conditions. The new model has 37 fragments (substructures) and classifies a substance as either fast or slow, relative to the potential to be biodegraded in the "serum bottle" anaerobic biodegradation screening test (Organization for Economic Cooperation and Development Guideline 311). The model correctly classified 90, 77, and 91% of the chemicals in the training set (n = 169) and two independent validation sets (n = 35 and 23), respectively. Accuracy of predictions of fast and slow degradation was equal for training-set chemicals, but fast-degradation predictions were less accurate than slow-degradation predictions for the validation sets. Analysis of the signs of the fragment coefficients for this and the other (aerobic) Biowin models suggests that in the context of simple group contribution models, the majority of positive and negative structural influences on ultimate degradation are the same for aerobic and methanogenic anaerobic biodegradation.

A model for Quick Load Analysis for monopile-type offshore wind turbine substructures

DEFF Research Database (Denmark)

Schløer, Signe; Castillo, Laura Garcia; Fejerskov, Morten

2016-01-01

A model for Quick Load Analysis, QuLA, of an offshore wind turbine substructure is presented. The aerodynamic rotor loads and damping are precomputed for a load-based configuration. The dynamic structural response is represented by the first global fore-aft mode only and is computed...... in the frequency domain using the equation of motion. The model is compared against the state of the art aeroelastic code, Flex5, and both life time fatigue and extreme loads are considered in the comparison. In general there is good similarity between the two models. Some derivation for the sectional forces...... are explained in terms of the model simplifications. The difference in the sectional moments are found to be within 14% for the fatigue load case and 10% for the extreme load condition....

In silico prediction of ROCK II inhibitors by different classification approaches.

Science.gov (United States)

Cai, Chuipu; Wu, Qihui; Luo, Yunxia; Ma, Huili; Shen, Jiangang; Zhang, Yongbin; Yang, Lei; Chen, Yunbo; Wen, Zehuai; Wang, Qi

2017-11-01

ROCK II is an important pharmacological target linked to central nervous system disorders such as Alzheimer's disease. The purpose of this research is to generate ROCK II inhibitor prediction models by machine learning approaches. Firstly, four sets of descriptors were calculated with MOE 2010 and PaDEL-Descriptor, and optimized by F-score and linear forward selection methods. In addition, four classification algorithms were used to initially build 16 classifiers with k-nearest neighbors [Formula: see text], naïve Bayes, Random forest, and support vector machine. Furthermore, three sets of structural fingerprint descriptors were introduced to enhance the predictive capacity of classifiers, which were assessed with fivefold cross-validation, test set validation and external test set validation. The best two models, MFK + MACCS and MLR + SubFP, have both MCC values of 0.925 for external test set. After that, a privileged substructure analysis was performed to reveal common chemical features of ROCK II inhibitors. Finally, binding modes were analyzed to identify relationships between molecular descriptors and activity, while main interactions were revealed by comparing the docking interaction of the most potent and the weakest ROCK II inhibitors. To the best of our knowledge, this is the first report on ROCK II inhibitors utilizing machine learning approaches that provides a new method for discovering novel ROCK II inhibitors.

Transpiration cooling assisted ablative thermal protection of aerospace substructures

International Nuclear Information System (INIS)

Khan, M.B.; Iqbal, N.; Haider, Z.

2009-01-01

Ablatives are heat-shielding materials used to protect aerospace substructures. These materials are sacrificial in nature and provide protection primarily through the large endothermic transformation during exposure to hyper thermal environment such as encountered in re-entry modules. The performance of certain ablatives was reported in terms of their TGA/DTA in Advanced Materials-97 (pp 57-65). The focus of this earlier research resided in the consolidation of interface between the refractory inclusion and the host polymeric matrix to improve thermal resistance. In the present work we explore the scope of transpiration cooling in ablative performance through flash evaporation of liquid incorporated in the host EPDM (Ethylene Propylene Diene Monomer) matrix. The compression-molded specimens were exposed separately to plasma flame (15000 C) and oxyacetylene torch (3000 C) and the back face transient temperature is recorded in situ employing a thermocouple/data logger system. Both head on impingement (HOI) and parallel flow (PF) through a central cavity in the ablator were used. It is observed that transpiration cooling is effective and yields (a) rapid thermal equilibrium in the specimen, (b) lower back face temperature and (c) lower ablation rate, compared to conventional ablatives. SEM/EDS analysis is presented to amplify the point. (author)

Plastic deformation of uranium dioxide: observation of the sub-structures of dislocations

International Nuclear Information System (INIS)

Alamo, A.; Lefebvre, J.M.; Soullard, J.

1978-01-01

Single crystals of uranium dioxide were deformed in compression at imposed strain rates in the temperature range of 700 0 C to 1400 0 C. The crystals were oriented to promote slip over one or two slip systems of the family [100] and also on the [110] system. Thin films of the deformed specimens were examined by transmission electron microscopy. When [100] single glide system operates, the dislocation substructure consist of numerous dipoles, their edge components lying along directions. For the [100] double glide system the grain boundaries and dislocation hexagonal network are observed, the complexity of which increases with the nominal strain. Dislocation arrangments consisting of extensive cellular networks of tangling dislocations and hexagonal netting were detected for [110] system. The auxillary role of [111] planes on the dislocation cross slip from [100] and [110] system was demonstrated. Weak beam images suggest that dissociation of dislocations can occur. (Auth.)

The Substructure of a Flux Transfer Event Observed by the MMS Spacecraft

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Hwang, K.-J.; Sibeck, D. G.; Giles, B. L.; Pollock, C. J.; Gershman, D.; Avanov, L.; Paterson, W. R.; Dorelli, J. C.; Ergun, R. E.; Russel, C. T.;

PREDICTION OF SPORT ADHERENCE THROUGH THE INFLUENCE OF AUTONOMY-SUPPORTIVE COACHING AMONG SPANISH ADOLESCENT ATHLETES

Directory of Open Access Journals (Sweden)

Bartolomé J. Almagro

2010-03-01

Full Text Available The purpose of this study was to test a motivational model of the coach-athlete relationship, based on self-determination theory and on the hierarchical model of intrinsic and extrinsic motivation. The sample comprised of 608 athletes (ages of 12-17 years completed the following measures: interest in athlete's input, praise for autonomous behavior, perceived autonomy, intrinsic motivation, and the intention to be physically active. Structural equation modeling results demonstrated that interest in athletes' input and praise for autonomous behavior predicted perceived autonomy, and perceived autonomy positively predicted intrinsic motivation. Finally, intrinsic motivation predicted the intention to be physically active in the future. The results are discussed in relation to the importance of the climate of autonomy support created by the coach on intrinsic motivation and adherence to sport by adolescent athletes. Further, the results provide information related to the possible objectives of future interventions for the education of coaches, with the goal of providing them with tools and strategies to favor the development of intrinsic motivation among their athletes. In conclusion, the climate of autonomy support created by the coach can predict the autonomy perceived by the athletes which predicts the intrinsic motivation experienced by the athletes, and therefore, their adherence to athletic practice. Key words: Autonomy support, perceived autonomy, intrinsic motivation, sport adherence

Predictive validity of social support relative to psychological well-being in men with spinal cord injury.

Science.gov (United States)

Rintala, Diana H

2013-11-01

Compare predictive validity (relative to psychological well-being) of long and short versions of 2 measures of social support for persons with spinal cord injury (SCI). Sixty-nine men with SCI completed (a) a long and short version of the Interpersonal Support Evaluation List (ISEL), (b) a structured interview regarding the frequency with which a person receives 11 kinds of support from each of their most important supporters (maximum of 5), and (c) a global measure of the same 11 kinds of support. Approximately 3 years later they completed 4 measures of psychological well-being--the Center for Epidemiologic Studies Depression scale (CESD), the Life Satisfaction Index A (LSIA), the Perceived Stress Scale (PSS), and the Rosenberg Self-Esteem Scale (RSES). Comparisons were made among the social support measures with regard to their ability to predict each of the 4 measures of psychological well-being at a later point in time. The long version of the ISEL had more predictive power than the long version of the structured interview. The long version of the ISEL is a good choice for measuring social support in persons with SCI and the short ISEL may be an acceptable choice when minimizing respondent burden is critical if the number of response options is increased to 4. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

Science.gov (United States)

Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

2018-03-01

The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

Assessment of First- and Second-Order Wave-Excitation Load Models for Cylindrical Substructures: Preprint

Energy Technology Data Exchange (ETDEWEB)

Pereyra, Brandon; Wendt, Fabian; Robertson, Amy; Jonkman, Jason

2017-03-09

The hydrodynamic loads on an offshore wind turbine's support structure present unique engineering challenges for offshore wind. Two typical approaches used for modeling these hydrodynamic loads are potential flow (PF) and strip theory (ST), the latter via Morison's equation. This study examines the first- and second-order wave-excitation surge forces on a fixed cylinder in regular waves computed by the PF and ST approaches to (1) verify their numerical implementations in HydroDyn and (2) understand when the ST approach breaks down. The numerical implementation of PF and ST in HydroDyn, a hydrodynamic time-domain solver implemented as a module in the FAST wind turbine engineering tool, was verified by showing the consistency in the first- and second-order force output between the two methods across a range of wave frequencies. ST is known to be invalid at high frequencies, and this study investigates where the ST solution diverges from the PF solution. Regular waves across a range of frequencies were run in HydroDyn for a monopile substructure. As expected, the solutions for the first-order (linear) wave-excitation loads resulting from these regular waves are similar for PF and ST when the diameter of the cylinder is small compared to the length of the waves (generally when the diameter-to-wavelength ratio is less than 0.2). The same finding applies to the solutions for second-order wave-excitation loads, but for much smaller diameter-to-wavelength ratios (based on wavelengths of first-order waves).

Tyrosine Kinase Ligand-Receptor Pair Prediction by Using Support Vector Machine

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Masayuki Yarimizu

2015-01-01

Full Text Available Receptor tyrosine kinases are essential proteins involved in cellular differentiation and proliferation in vivo and are heavily involved in allergic diseases, diabetes, and onset/proliferation of cancerous cells. Identifying the interacting partner of this protein, a growth factor ligand, will provide a deeper understanding of cellular proliferation/differentiation and other cell processes. In this study, we developed a method for predicting tyrosine kinase ligand-receptor pairs from their amino acid sequences. We collected tyrosine kinase ligand-receptor pairs from the Database of Interacting Proteins (DIP and UniProtKB, filtered them by removing sequence redundancy, and used them as a dataset for machine learning and assessment of predictive performance. Our prediction method is based on support vector machines (SVMs, and we evaluated several input features suitable for tyrosine kinase for machine learning and compared and analyzed the results. Using sequence pattern information and domain information extracted from sequences as input features, we obtained 0.996 of the area under the receiver operating characteristic curve. This accuracy is higher than that obtained from general protein-protein interaction pair predictions.

Exploring halo substructure with giant stars. XIV. The nature of the Triangulum-Andromeda stellar features

Energy Technology Data Exchange (ETDEWEB)

Sheffield, Allyson A.; Johnston, Kathryn V. [Department of Astronomy, Columbia University, Mail Code 5246, New York, NY 10027 (United States); Majewski, Steven R.; Damke, Guillermo; Richardson, Whitney; Beaton, Rachael [Department of Astronomy, University of Virginia, P.O. Box 400325, Charlottesville, VA 22904 (United States); Rocha-Pinto, Helio J., E-mail: asheffield@astro.columbia.edu, E-mail: kvj@astro.columbia.edu, E-mail: srm4n@virginia.edu, E-mail: gjd3r@virginia.edu, E-mail: wwr2u@virginia.edu, E-mail: rlb9n@virginia.edu, E-mail: helio@astro.ufrj.br [Observatório do Valongo, Universidade Federal do Rio de Janeiro, Rio de Janeiro (Brazil)

2014-09-20

As large-scale stellar surveys have become available over the past decade, the ability to detect and characterize substructures in the Galaxy has increased dramatically. These surveys have revealed the Triangulum-Andromeda (TriAnd) region to be rich with substructures in the distance range 20-30 kpc, and the relation of these features to each other, if any, remains unclear. An exploration using Two Micron All Sky Survey (2MASS) photometry reveals not only the faint sequence in M giants detected by Rocha-Pinto et al. spanning the range 100° < l < 160° and –50° < b < –15°, but, in addition, a second, brighter and more densely populated sequence. These sequences are likely associated with the distinct main sequences (MSs) discovered (and labeled TriAnd1 and TriAnd2) by Martin et al. in an optical survey in the direction of M31, where TriAnd2 is the optical counterpart of the fainter red giant branch (RGB)/asymptotic giant branch sequence of Rocha-Pinto et al. Here, the age, distance, and metallicity ranges for TriAnd1 and TriAnd2 are estimated by simultaneously fitting isochrones to the 2MASS RGB tracks and the optical MS/MS turn-off features. The two populations are clearly distinct in age and distance: the brighter sequence (TriAnd1) is younger (6-10 Gyr) and closer (distance of ∼15-21 kpc), whereas the fainter sequence (TriAnd2) is older (10-12 Gyr) and at an estimated distance of ∼24-32 kpc. A comparison with simulations demonstrates that the differences and similarities between TriAnd1 and TriAnd2 can simultaneously be explained if they represent debris originating from the disruption of the same dwarf galaxy, but torn off during two distinct pericentric passages.

Prediction of Carbohydrate-Binding Proteins from Sequences Using Support Vector Machines

Directory of Open Access Journals (Sweden)

Seizi Someya

2010-01-01

Full Text Available Carbohydrate-binding proteins are proteins that can interact with sugar chains but do not modify them. They are involved in many physiological functions, and we have developed a method for predicting them from their amino acid sequences. Our method is based on support vector machines (SVMs. We first clarified the definition of carbohydrate-binding proteins and then constructed positive and negative datasets with which the SVMs were trained. By applying the leave-one-out test to these datasets, our method delivered 0.92 of the area under the receiver operating characteristic (ROC curve. We also examined two amino acid grouping methods that enable effective learning of sequence patterns and evaluated the performance of these methods. When we applied our method in combination with the homology-based prediction method to the annotated human genome database, H-invDB, we found that the true positive rate of prediction was improved.

Global Profiling and Novel Structure Discovery Using Multiple Neutral Loss/Precursor Ion Scanning Combined with Substructure Recognition and Statistical Analysis (MNPSS): Characterization of Terpene-Conjugated Curcuminoids in Curcuma longa as a Case Study.

Science.gov (United States)

Qiao, Xue; Lin, Xiong-hao; Ji, Shuai; Zhang, Zheng-xiang; Bo, Tao; Guo, De-an; Ye, Min

2016-01-05

To fully understand the chemical diversity of an herbal medicine is challenging. In this work, we describe a new approach to globally profile and discover novel compounds from an herbal extract using multiple neutral loss/precursor ion scanning combined with substructure recognition and statistical analysis. Turmeric (the rhizomes of Curcuma longa L.) was used as an example. This approach consists of three steps: (i) multiple neutral loss/precursor ion scanning to obtain substructure information; (ii) targeted identification of new compounds by extracted ion current and substructure recognition; and (iii) untargeted identification using total ion current and multivariate statistical analysis to discover novel structures. Using this approach, 846 terpecurcumins (terpene-conjugated curcuminoids) were discovered from turmeric, including a number of potentially novel compounds. Furthermore, two unprecedented compounds (terpecurcumins X and Y) were purified, and their structures were identified by NMR spectroscopy. This study extended the application of mass spectrometry to global profiling of natural products in herbal medicines and could help chemists to rapidly discover novel compounds from a complex matrix.

Predicting South Korean University Students' Happiness through Social Support and Efficacy Beliefs

Science.gov (United States)

Lee, Diane Sookyoung; Padilla, Amado M.

2016-01-01

This study investigated the adversity and coping experiences of 198 South Korean university students and takes a cultural lens in understanding how social and individual factors shape their happiness. Hierarchical linear regression analyses suggest that Korean students' perceptions of social support significantly predicted their happiness,…

Screw Remaining Life Prediction Based on Quantum Genetic Algorithm and Support Vector Machine

Directory of Open Access Journals (Sweden)

Xiaochen Zhang

2017-01-01

Full Text Available To predict the remaining life of ball screw, a screw remaining life prediction method based on quantum genetic algorithm (QGA and support vector machine (SVM is proposed. A screw accelerated test bench is introduced. Accelerometers are installed to monitor the performance degradation of ball screw. Combined with wavelet packet decomposition and isometric mapping (Isomap, the sensitive feature vectors are obtained and stored in database. Meanwhile, the sensitive feature vectors are randomly chosen from the database and constitute training samples and testing samples. Then the optimal kernel function parameter and penalty factor of SVM are searched with the method of QGA. Finally, the training samples are used to train optimized SVM while testing samples are adopted to test the prediction accuracy of the trained SVM so the screw remaining life prediction model can be got. The experiment results show that the screw remaining life prediction model could effectively predict screw remaining life.

THE FORNAX DWARF GALAXY AS A REMNANT OF RECENT DWARF-DWARF MERGING IN THE LOCAL GROUP

International Nuclear Information System (INIS)

Yozin, C.; Bekki, K.

2012-01-01

We present results from the first numerical analysis to support the hypothesis, first proposed in Coleman et al., that the Fornax dwarf galaxy was formed from the minor merging of two dwarfs about 2 Gyr ago. Using orbits for the Fornax dwarf that are consistent with the latest proper motion measurements, our dynamical evolution models show that the observed asymmetric shell-like substructures can be formed from the remnant of a smaller dwarf during minor merging. These models also predict the formation of diffuse stellar streams. We discuss how these stellar substructures depend on model parameters of dwarf-dwarf merging, and how the intermediate-age subpopulations found in the vicinity of these substructures may be formed from gas accretion in past merger events. We also suggest that one of Fornax's globular clusters originates from a merged dwarf companion, and demonstrate where as yet undetected tidal streams or H I gas formed from the dwarf merging may be found in the outer halo of the Galaxy.

Predicting SVOC Emissions into Air and Foods in Support of ...

Science.gov (United States)

The release of semi-volatile organic compounds (SVOCs) from consumer articles may be a critical human exposure pathway. In addition, the migration of SVOCs from food packaging materials into foods may also be a dominant source of exposure for some chemicals. Here we describe recent efforts to characterize emission-related parameters for these exposure pathways to support prediction of aggregate exposures for thousands of chemicals For chemicals in consumer articles, Little et al. (2012) developed a screening-level indoor exposure prediction model which, for a given SVOC, principally depends on steady-state gas-phase concentrations (y0). We have developed a model that predicts y0 for SVOCs in consumer articles, allowing exposure predictions for 274 ToxCast chemicals. Published emissions data for 31 SVOCs found in flooring materials, provided a training set where both chemical-specific physicochemical properties, article specific formulation properties, and experimental design aspects were available as modeling descriptors. A linear regression yielded R2- and p- values of approximately 0.62 and 3.9E-05, respectively. A similar model was developed based upon physicochemical properties alone, since article information is often not available for a given SVOC or product. This latter model yielded R2 - and p- values of approximately 0.47 and 1.2E-10, respectively. Many SVOCs are also used as additives (e.g. plasticizers, antioxidants, lubricants) in plastic food pac

Direct observations of dislocation substructures formed by nano-indentation of the α-phase in an α/β titanium alloy

International Nuclear Information System (INIS)

Viswanathan, G.B.; Lee, Eunha; Maher, Dennis M.; Banerjee, Srikumar; Fraser, Hamish L.

2005-01-01

Nano-indentation has been used to assess the hardness of equiaxed grains of α-Ti as a function of orientation. Surface normals of these grains in metallographic sections were assessed using orientation imaging microscopy. Thin membranes of material from below a series of nano-indentations were excised by use of a dual-beam focused ion beam instrument. In this way, the dislocation substructures beneath individual indentations were characterized using transmission electron microscopy, permitting an identification of both statistically stored and geometrically necessary dislocations

Aspects of dislocation substructures associated with the deformation stages of stainless steel AISI 304 at high temperatures

International Nuclear Information System (INIS)

Oliveira, J.L.L.; Reis Filho, J.A.B.S.; Almeida, L.H. de; Monteiro, S.N.

1978-07-01

The development of dislocation substrutures in type 304 austenitic stainless steel at high temperatures has been associated with the deformation stages through log dσ/d epsilon x log epsilon plots, which show the transition point independently. The mechanisms responsible for the Dynamic Strain Aging particulary the Portevin-LeChatelier effect were related to the appearence of the stages. The results indicate that the deformation stages can be divided into two distinct regions. Each one of these region show particular characteristics with respect to the stress level, transition point, developed substructure and type of crystalline defects interaction with dislocations. (Author) [pt

Perceived parenting and social support: can they predict academic achievement in Argentinean college students?

Science.gov (United States)

de la Iglesia, Guadalupe; Freiberg Hoffmann, Agustin; Fernández Liporace, Mercedes

2014-01-01

The aim of this study was to test the ability to predict academic achievement through the perception of parenting and social support in a sample of 354 Argentinean college students. Their mean age was 23.50 years (standard deviation =2.62 years) and most of them (83.3%) were females. As a prerequisite for admission to college, students are required to pass a series of mandatory core classes and are expected to complete them in two semesters. Delay in completing the curriculum is considered low academic achievement. Parenting was assessed taking into account the mother and the father and considering two dimensions: responsiveness and demandingness. Perceived social support was analyzed considering four sources: parents, teachers, classmates, and best friend or boyfriend/girlfriend. Path analysis showed that, as hypothesized, responsiveness had a positive indirect effect on the perception of social support and enhanced achievement. Demandingness had a different effect in the case of the mother as compared to the father. In the mother model, demandingness had a positive direct effect on achievement. In the case of the father, however, the effect of demandingness had a negative and indirect impact on the perception of social support. Teachers were the only source of perceived social support that significantly predicted achievement. The pathway that belongs to teachers as a source of support was positive and direct. Implications for possible interventions are discussed.

Building a Predictive Capability for Decision-Making that Supports MultiPEM

Energy Technology Data Exchange (ETDEWEB)

Carmichael, Joshua Daniel [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-11-20

Multi-phenomenological explosion monitoring (multiPEM) is a developing science that uses multiple geophysical signatures of explosions to better identify and characterize their sources. MultiPEM researchers seek to integrate explosion signatures together to provide stronger detection, parameter estimation, or screening capabilities between different sources or processes. This talk will address forming a predictive capability for screening waveform explosion signatures to support multiPEM.

Weighted K-means support vector machine for cancer prediction.

Science.gov (United States)

Kim, SungHwan

2016-01-01

To date, the support vector machine (SVM) has been widely applied to diverse bio-medical fields to address disease subtype identification and pathogenicity of genetic variants. In this paper, I propose the weighted K-means support vector machine (wKM-SVM) and weighted support vector machine (wSVM), for which I allow the SVM to impose weights to the loss term. Besides, I demonstrate the numerical relations between the objective function of the SVM and weights. Motivated by general ensemble techniques, which are known to improve accuracy, I directly adopt the boosting algorithm to the newly proposed weighted KM-SVM (and wSVM). For predictive performance, a range of simulation studies demonstrate that the weighted KM-SVM (and wSVM) with boosting outperforms the standard KM-SVM (and SVM) including but not limited to many popular classification rules. I applied the proposed methods to simulated data and two large-scale real applications in the TCGA pan-cancer methylation data of breast and kidney cancer. In conclusion, the weighted KM-SVM (and wSVM) increases accuracy of the classification model, and will facilitate disease diagnosis and clinical treatment decisions to benefit patients. A software package (wSVM) is publicly available at the R-project webpage (https://www.r-project.org).

Support vector machine incremental learning triggered by wrongly predicted samples

Science.gov (United States)

Tang, Ting-long; Guan, Qiu; Wu, Yi-rong

2018-05-01

According to the classic Karush-Kuhn-Tucker (KKT) theorem, at every step of incremental support vector machine (SVM) learning, the newly adding sample which violates the KKT conditions will be a new support vector (SV) and migrate the old samples between SV set and non-support vector (NSV) set, and at the same time the learning model should be updated based on the SVs. However, it is not exactly clear at this moment that which of the old samples would change between SVs and NSVs. Additionally, the learning model will be unnecessarily updated, which will not greatly increase its accuracy but decrease the training speed. Therefore, how to choose the new SVs from old sets during the incremental stages and when to process incremental steps will greatly influence the accuracy and efficiency of incremental SVM learning. In this work, a new algorithm is proposed to select candidate SVs and use the wrongly predicted sample to trigger the incremental processing simultaneously. Experimental results show that the proposed algorithm can achieve good performance with high efficiency, high speed and good accuracy.

Predictive value of age for coping: the role of self-efficacy, social support satisfaction and perceived stress.

Science.gov (United States)

Trouillet, Raphaël; Gana, Kamel; Lourel, Marcel; Fort, Isabelle

2009-05-01

The present study was prompted by the lack of agreement on how coping changes with age. We postulate that the effect of age on coping is mediated by coping resources, such as self-efficacy, perceived stress and social support satisfaction. The participants in the study were community dwelling and aged between 22 and 88 years old. Data were collected using the General Self Efficacy Scale, the Social Support Questionnaire, the Perceived Stress Scale, the Geriatric Depression Scale, the Social Readjustment Rating Scale (life-events) and the Way of Coping Checklist. We performed path analyses for two competitive structural models: M1 (age does not directly affect coping processes) and M2 (age directly affects coping processes). Our results supported a modified version of M2. Age was not found to predict either of two coping strategies: problem-focused coping is predicted by self-efficacy and social support satisfaction; emotion-focused coping is predicted by social support satisfaction and perceived stress. Changes in coping over the lifespan reflect the effectiveness with which a person's adaptive processes deal with age-associated changes in self-referred beliefs and environment perception.

SHARP - II. Mass structure in strong lenses is not necessarily dark matter substructure: a flux ratio anomaly from an edge-on disc in B1555+375

NARCIS (Netherlands)

Hsueh, J. -W; Fassnacht, C. D.; Vegetti, S.; McKean, J. P.; Spingola, C.; Auger, M. W.; Koopmans, L. V. E.; Lagattuta, D. J.

2016-01-01

Gravitational lens flux-ratio anomalies provide a powerful technique for measuring dark matter substructure in distant galaxies. However, before using these flux-ratio anomalies to test galaxy formation models, it is imperative to ascertain that the given anomalies are indeed due to the presence of

Probabilistic Calibration of Fatigue Design Factors for Offshore Wind Turbine Support Structures

DEFF Research Database (Denmark)

Ramirez, José Rangel; Sørensen, John Dalsgaard

2010-01-01

for the considered offshore wind turbines in such a way that the specific uncertainties for the fatigue life are accounted in a rational manner. Similar approaches have been used for offshore oil & gas sub-structures, but the required reliability level for offshore wind turbines is generally lower and the fatigue......This paper describes a reliability-based approach to determine fatigue design factors (FDF) for offshore wind turbine support structures made of steel. The FDF values are calibrated to a specific reliability level and linked to a specific inspection and maintenance (I&M) strategy used...

Predicting beta-turns in proteins using support vector machines with fractional polynomials.

Science.gov (United States)

Elbashir, Murtada; Wang, Jianxin; Wu, Fang-Xiang; Wang, Lusheng

2013-11-07

β-turns are secondary structure type that have essential role in molecular recognition, protein folding, and stability. They are found to be the most common type of non-repetitive structures since 25% of amino acids in protein structures are situated on them. Their prediction is considered to be one of the crucial problems in bioinformatics and molecular biology, which can provide valuable insights and inputs for the fold recognition and drug design. We propose an approach that combines support vector machines (SVMs) and logistic regression (LR) in a hybrid prediction method, which we call (H-SVM-LR) to predict β-turns in proteins. Fractional polynomials are used for LR modeling. We utilize position specific scoring matrices (PSSMs) and predicted secondary structure (PSS) as features. Our simulation studies show that H-SVM-LR achieves Qtotal of 82.87%, 82.84%, and 82.32% on the BT426, BT547, and BT823 datasets respectively. These values are the highest among other β-turns prediction methods that are based on PSSMs and secondary structure information. H-SVM-LR also achieves favorable performance in predicting β-turns as measured by the Matthew's correlation coefficient (MCC) on these datasets. Furthermore, H-SVM-LR shows good performance when considering shape strings as additional features. In this paper, we present a comprehensive approach for β-turns prediction. Experiments show that our proposed approach achieves better performance compared to other competing prediction methods.

Using support vector machine to predict beta- and gamma-turns in proteins.

Science.gov (United States)

Hu, Xiuzhen; Li, Qianzhong

2008-09-01

By using the composite vector with increment of diversity, position conservation scoring function, and predictive secondary structures to express the information of sequence, a support vector machine (SVM) algorithm for predicting beta- and gamma-turns in the proteins is proposed. The 426 and 320 nonhomologous protein chains described by Guruprasad and Rajkumar (Guruprasad and Rajkumar J. Biosci 2000, 25,143) are used for training and testing the predictive model of the beta- and gamma-turns, respectively. The overall prediction accuracy and the Matthews correlation coefficient in 7-fold cross-validation are 79.8% and 0.47, respectively, for the beta-turns. The overall prediction accuracy in 5-fold cross-validation is 61.0% for the gamma-turns. These results are significantly higher than the other algorithms in the prediction of beta- and gamma-turns using the same datasets. In addition, the 547 and 823 nonhomologous protein chains described by Fuchs and Alix (Fuchs and Alix Proteins: Struct Funct Bioinform 2005, 59, 828) are used for training and testing the predictive model of the beta- and gamma-turns, and better results are obtained. This algorithm may be helpful to improve the performance of protein turns' prediction. To ensure the ability of the SVM method to correctly classify beta-turn and non-beta-turn (gamma-turn and non-gamma-turn), the receiver operating characteristic threshold independent measure curves are provided. (c) 2008 Wiley Periodicals, Inc.

Coal demand prediction based on a support vector machine model

Energy Technology Data Exchange (ETDEWEB)

Jia, Cun-liang; Wu, Hai-shan; Gong, Dun-wei [China University of Mining & Technology, Xuzhou (China). School of Information and Electronic Engineering

2007-01-15

A forecasting model for coal demand of China using a support vector regression was constructed. With the selected embedding dimension, the output vectors and input vectors were constructed based on the coal demand of China from 1980 to 2002. After compared with lineal kernel and Sigmoid kernel, a radial basis function(RBF) was adopted as the kernel function. By analyzing the relationship between the error margin of prediction and the model parameters, the proper parameters were chosen. The support vector machines (SVM) model with multi-input and single output was proposed. Compared the predictor based on RBF neural networks with test datasets, the results show that the SVM predictor has higher precision and greater generalization ability. In the end, the coal demand from 2003 to 2006 is accurately forecasted. l0 refs., 2 figs., 4 tabs.

Prediction of backbone dihedral angles and protein secondary structure using support vector machines

Directory of Open Access Journals (Sweden)

Hirst Jonathan D

2009-12-01

Full Text Available Abstract Background The prediction of the secondary structure of a protein is a critical step in the prediction of its tertiary structure and, potentially, its function. Moreover, the backbone dihedral angles, highly correlated with secondary structures, provide crucial information about the local three-dimensional structure. Results We predict independently both the secondary structure and the backbone dihedral angles and combine the results in a loop to enhance each prediction reciprocally. Support vector machines, a state-of-the-art supervised classification technique, achieve secondary structure predictive accuracy of 80% on a non-redundant set of 513 proteins, significantly higher than other methods on the same dataset. The dihedral angle space is divided into a number of regions using two unsupervised clustering techniques in order to predict the region in which a new residue belongs. The performance of our method is comparable to, and in some cases more accurate than, other multi-class dihedral prediction methods. Conclusions We have created an accurate predictor of backbone dihedral angles and secondary structure. Our method, called DISSPred, is available online at http://comp.chem.nottingham.ac.uk/disspred/.

Predictive based monitoring of nuclear plant component degradation using support vector regression

International Nuclear Information System (INIS)

Agarwal, Vivek; Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

2015-01-01

Nuclear power plants (NPPs) are large installations comprised of many active and passive assets. Degradation monitoring of all these assets is expensive (labor cost) and highly demanding task. In this paper a framework based on Support Vector Regression (SVR) for online surveillance of critical parameter degradation of NPP components is proposed. In this case, on time replacement or maintenance of components will prevent potential plant malfunctions, and reduce the overall operational cost. In the current work, we apply SVR equipped with a Gaussian kernel function to monitor components. Monitoring includes the one-step-ahead prediction of the component's respective operational quantity using the SVR model, while the SVR model is trained using a set of previous recorded degradation histories of similar components. Predictive capability of the model is evaluated upon arrival of a sensor measurement, which is compared to the component failure threshold. A maintenance decision is based on a fuzzy inference system that utilizes three parameters: (i) prediction evaluation in the previous steps, (ii) predicted value of the current step, (iii) and difference of current predicted value with components failure thresholds. The proposed framework will be tested on turbine blade degradation data.

Blood glucose level prediction based on support vector regression using mobile platforms.

Science.gov (United States)

Reymann, Maximilian P; Dorschky, Eva; Groh, Benjamin H; Martindale, Christine; Blank, Peter; Eskofier, Bjoern M

2016-08-01

The correct treatment of diabetes is vital to a patient's health: Staying within defined blood glucose levels prevents dangerous short- and long-term effects on the body. Mobile devices informing patients about their future blood glucose levels could enable them to take counter-measures to prevent hypo or hyper periods. Previous work addressed this challenge by predicting the blood glucose levels using regression models. However, these approaches required a physiological model, representing the human body's response to insulin and glucose intake, or are not directly applicable to mobile platforms (smart phones, tablets). In this paper, we propose an algorithm for mobile platforms to predict blood glucose levels without the need for a physiological model. Using an online software simulator program, we trained a Support Vector Regression (SVR) model and exported the parameter settings to our mobile platform. The prediction accuracy of our mobile platform was evaluated with pre-recorded data of a type 1 diabetes patient. The blood glucose level was predicted with an error of 19 % compared to the true value. Considering the permitted error of commercially used devices of 15 %, our algorithm is the basis for further development of mobile prediction algorithms.

TU-H-CAMPUS-JeP2-05: Can Automatic Delineation of Cardiac Substructures On Noncontrast CT Be Used for Cardiac Toxicity Analysis?

Energy Technology Data Exchange (ETDEWEB)

Luo, Y; Liao, Z; Jiang, W; Gomez, D; Williamson, R; Court, L; Yang, J [MD Anderson Cancer Center, Houston, TX (United States)

2016-06-15

Purpose: To evaluate the feasibility of using an automatic segmentation tool to delineate cardiac substructures from computed tomography (CT) images for cardiac toxicity analysis for non-small cell lung cancer (NSCLC) patients after radiotherapy. Methods: A multi-atlas segmentation tool developed in-house was used to delineate eleven cardiac substructures including the whole heart, four heart chambers, and six greater vessels automatically from the averaged 4DCT planning images for 49 NSCLC patients. The automatic segmented contours were edited appropriately by two experienced radiation oncologists. The modified contours were compared with the auto-segmented contours using Dice similarity coefficient (DSC) and mean surface distance (MSD) to evaluate how much modification was needed. In addition, the dose volume histogram (DVH) of the modified contours were compared with that of the auto-segmented contours to evaluate the dosimetric difference between modified and auto-segmented contours. Results: Of the eleven structures, the averaged DSC values ranged from 0.73 ± 0.08 to 0.95 ± 0.04 and the averaged MSD values ranged from 1.3 ± 0.6 mm to 2.9 ± 5.1mm for the 49 patients. Overall, the modification is small. The pulmonary vein (PV) and the inferior vena cava required the most modifications. The V30 (volume receiving 30 Gy or above) for the whole heart and the mean dose to the whole heart and four heart chambers did not show statistically significant difference between modified and auto-segmented contours. The maximum dose to the greater vessels did not show statistically significant difference except for the PV. Conclusion: The automatic segmentation of the cardiac substructures did not require substantial modification. The dosimetric evaluation showed no statistically significant difference between auto-segmented and modified contours except for the PV, which suggests that auto-segmented contours for the cardiac dose response study are feasible in the clinical

TU-H-CAMPUS-JeP2-05: Can Automatic Delineation of Cardiac Substructures On Noncontrast CT Be Used for Cardiac Toxicity Analysis?

International Nuclear Information System (INIS)

Luo, Y; Liao, Z; Jiang, W; Gomez, D; Williamson, R; Court, L; Yang, J

2016-01-01

Purpose: To evaluate the feasibility of using an automatic segmentation tool to delineate cardiac substructures from computed tomography (CT) images for cardiac toxicity analysis for non-small cell lung cancer (NSCLC) patients after radiotherapy. Methods: A multi-atlas segmentation tool developed in-house was used to delineate eleven cardiac substructures including the whole heart, four heart chambers, and six greater vessels automatically from the averaged 4DCT planning images for 49 NSCLC patients. The automatic segmented contours were edited appropriately by two experienced radiation oncologists. The modified contours were compared with the auto-segmented contours using Dice similarity coefficient (DSC) and mean surface distance (MSD) to evaluate how much modification was needed. In addition, the dose volume histogram (DVH) of the modified contours were compared with that of the auto-segmented contours to evaluate the dosimetric difference between modified and auto-segmented contours. Results: Of the eleven structures, the averaged DSC values ranged from 0.73 ± 0.08 to 0.95 ± 0.04 and the averaged MSD values ranged from 1.3 ± 0.6 mm to 2.9 ± 5.1mm for the 49 patients. Overall, the modification is small. The pulmonary vein (PV) and the inferior vena cava required the most modifications. The V30 (volume receiving 30 Gy or above) for the whole heart and the mean dose to the whole heart and four heart chambers did not show statistically significant difference between modified and auto-segmented contours. The maximum dose to the greater vessels did not show statistically significant difference except for the PV. Conclusion: The automatic segmentation of the cardiac substructures did not require substantial modification. The dosimetric evaluation showed no statistically significant difference between auto-segmented and modified contours except for the PV, which suggests that auto-segmented contours for the cardiac dose response study are feasible in the clinical

Prediction of hourly PM2.5 using a space-time support vector regression model

Science.gov (United States)

Yang, Wentao; Deng, Min; Xu, Feng; Wang, Hang

2018-05-01

Real-time air quality prediction has been an active field of research in atmospheric environmental science. The existing methods of machine learning are widely used to predict pollutant concentrations because of their enhanced ability to handle complex non-linear relationships. However, because pollutant concentration data, as typical geospatial data, also exhibit spatial heterogeneity and spatial dependence, they may violate the assumptions of independent and identically distributed random variables in most of the machine learning methods. As a result, a space-time support vector regression model is proposed to predict hourly PM2.5 concentrations. First, to address spatial heterogeneity, spatial clustering is executed to divide the study area into several homogeneous or quasi-homogeneous subareas. To handle spatial dependence, a Gauss vector weight function is then developed to determine spatial autocorrelation variables as part of the input features. Finally, a local support vector regression model with spatial autocorrelation variables is established for each subarea. Experimental data on PM2.5 concentrations in Beijing are used to verify whether the results of the proposed model are superior to those of other methods.

Correlation of substructure with mechanical properties of plastically deformed reactor structural materials. Progress report, January 1, 1974--December 31, 1975

International Nuclear Information System (INIS)

Moteff, J.

1976-01-01

Ratio of the subgrain boundary dislocations to those contributing to creep deformation was found to be independent of applied stress and creep strain after the steady-state creep stage is reached. The observed cell or subgrain sizes are correlated with flow stress in Type 304 ss, and the deformation rate-stress relation obeys the equation epsilon =β lambda 3 (sigma/sub T//E)/sub n/ exp (-Q/sub c//RT), where lambda = subgrain size, sigma/sub T/ = effective true stress, E = Young modulus, and Q/sub c/ = 85 kcal/mole. Well-developed subgrains were observed in TEM on 304 ss tested in creep at 704 0 C. Role of twin boundary-grain boundary intersections in microcracking behavior of 304 ss deformed in slow tension and creep at 650 0 C was investigated. Grain shape analysis show that intragranular deformation becomes more predominant in the grains with the larger intercept distances, and that grain boundary sliding becomes important as the strain rate decreases. RT mechanical properties of austenitic ss are enhanced by subgrains formed during high-temperature deformation. The substructural development during high-temperature low-cycle fatigue of 304 ss was studied using TEM. Fatigue properties of Incoloy 800 tested in bend and push-pull modes are being compared. Effects of hold time on fatigue substructure and fracture of 304 ss are being studied. 31 figures, 53 references

A Bayesian least-squares support vector machine method for predicting the remaining useful life of a microwave component

Directory of Open Access Journals (Sweden)

Fuqiang Sun

2017-01-01

Full Text Available Rapid and accurate lifetime prediction of critical components in a system is important to maintaining the system’s reliable operation. To this end, many lifetime prediction methods have been developed to handle various failure-related data collected in different situations. Among these methods, machine learning and Bayesian updating are the most popular ones. In this article, a Bayesian least-squares support vector machine method that combines least-squares support vector machine with Bayesian inference is developed for predicting the remaining useful life of a microwave component. A degradation model describing the change in the component’s power gain over time is developed, and the point and interval remaining useful life estimates are obtained considering a predefined failure threshold. In our case study, the radial basis function neural network approach is also implemented for comparison purposes. The results indicate that the Bayesian least-squares support vector machine method is more precise and stable in predicting the remaining useful life of this type of components.

Nonlinear seismic response analysis of embedded reactor buildings based on the substructure approach in time domain

International Nuclear Information System (INIS)

Hasegawa, M.; Nakai, S.; Watanabe, T.

1985-01-01

A practical method for elasto-plastic seismic response analysis is described under considerations of nonlinear material law of a structure and dynamic soil-structure interaction. The method is essentially based on the substructure approach of time domain analysis. Verification of the present method is carried out for typical BWR-MARK II type reactor building which is embedded in a soil, and the results are compared with those of the frequency response analysis which gives good accuracy for linear system. As a result, the present method exhibits sufficient accuracy. Furthermore, elasto-plastic analyses considering the soil-structure interaction are made as an application of the present method, and nonlinear behaviors of the structure and embedment effects are discussed. (orig.)

Effect of the shades of background substructures on the overall color of zirconia-based all-ceramic crowns

Science.gov (United States)

Tulapornchai, Chantana; Mamani, Jatuphol; Kamchatphai, Wannaporn; Thongpun, Noparat

2013-01-01

PURPOSE The objective of this study was to determine the effect of the color of a background substructure on the overall color of a zirconia-based all-ceramic crown. MATERIALS AND METHODS Twenty one posterior zirconia crowns were made for twenty subjects. Seven premolar crowns and six molar crowns were cemented onto abutments with metal post and core in the first and second group. In the third group, eight molar crowns were cemented onto abutments with a prefabricated post and composite core build-up. The color measurements of all-ceramic crowns were made before try-in, before and after cementation. A repeated measure ANOVA was used for a statistical analysis of a color change of all-ceramic crowns at α=.05. Twenty four zirconia specimens, with different core thicknesses (0.4-1 mm) were also prepared to obtain the contrast ratio of zirconia materials after veneering. RESULTS L*, a*, and b* values of all-ceramic crowns cemented either on a metal cast post and core or on a prefabricated post did not show significant changes (P>.05). However, the slight color changes of zirconia crowns were detected and represented by ΔE*ab values, ranging from 1.2 to 3.1. The contrast ratios of zirconia specimens were 0.92-0.95 after veneering. CONCLUSION No significant differences were observed between the L*, a*, and b* values of zirconia crowns cemented either on a metal cast post and core or a prefabricated post and composite core. However, the color of a background substructure could affect the overall color of posterior zirconia restorations with clinically recommended core thickness according to ΔE*ab values. PMID:24049574

Support for the Logical Execution Time Model on a Time-predictable Multicore Processor

DEFF Research Database (Denmark)

Kluge, Florian; Schoeberl, Martin; Ungerer, Theo

2016-01-01

The logical execution time (LET) model increases the compositionality of real-time task sets. Removal or addition of tasks does not influence the communication behavior of other tasks. In this work, we extend a multicore operating system running on a time-predictable multicore processor to support...... the LET model. For communication between tasks we use message passing on a time-predictable network-on-chip to avoid the bottleneck of shared memory. We report our experiences and present results on the costs in terms of memory and execution time....

Prediction of toxicity of nitrobenzenes using ab initio and least squares support vector machines

International Nuclear Information System (INIS)

Niazi, Ali; Jameh-Bozorghi, Saeed; Nori-Shargh, Davood

2008-01-01

A quantitative structure-property relationship (QSPR) study is suggested for the prediction of toxicity (IGC 50 ) of nitrobenzenes. Ab initio theory was used to calculate some quantum chemical descriptors including electrostatic potentials and local charges at each atom, HOMO and LUMO energies, etc. Modeling of the IGC 50 of nitrobenzenes as a function of molecular structures was established by means of the least squares support vector machines (LS-SVM). This model was applied for the prediction of the toxicity (IGC 50 ) of nitrobenzenes, which were not in the modeling procedure. The resulted model showed high prediction ability with root mean square error of prediction of 0.0049 for LS-SVM. Results have shown that the introduction of LS-SVM for quantum chemical descriptors drastically enhances the ability of prediction in QSAR studies superior to multiple linear regression and partial least squares

Validation of Superelement Modelling of Complex Offshore Support Structures

DEFF Research Database (Denmark)

Wang, Shaofeng; Larsen, Torben J.; Hansen, Anders Melchior

2016-01-01

Modern large MW wind turbines today are installed at larger water depth than applicable for traditional monopile substructure. It appears that foundation types such as jacket and tripod are gaining more popularity for these locations. For certification purposes, a full set of design load calculat......Modern large MW wind turbines today are installed at larger water depth than applicable for traditional monopile substructure. It appears that foundation types such as jacket and tripod are gaining more popularity for these locations. For certification purposes, a full set of design load...

The End-Of-Substructure Card for the ATLAS ITk Strip Tracker

CERN Document Server

Goettlicher, Peter; The ATLAS collaboration

2018-01-01

The End-Of-Substructure Card (EoS) is the interface between the building block of the ITk Strip Tracker (staves and petals) and the outside world. In the ITk the modules consisting of the silicon sensor itself and the hybrids with the readout ASICS are placed on a common structure called a stave (in the barrel) and petal (in the end-cap). All module use a common bus-tape co-cured to carbon-fiber based structure to distribute power and signals. The data lines and command lines are then connected from the bus-tape to EoS. The power, both low and high voltage, are also distributed via the bus tape and coonected to the EoS. All these connections will be made using wire-bonds. The card concept is build around using the lpGBT chip set and the VTRx optical link, both common developments for the LHC Upgrades. The command signals will be coming in on a 10 Gbit/s link and will be de-multiplexed by the lpGBt and send to the stave/petal. The incoming data from the sensor, which depending on the type of stave or petal wil...

The Role of Family Expressed Emotion and Perceived Social Support in Predicting Addiction Relapse

OpenAIRE

Atadokht, Akbar; Hajloo, Nader; Karimi, Masoud; Narimani, Mohammad

2015-01-01

Background: Emotional conditions governing the family and patients? perceived social support play important roles in the treatment or relapse process of the chronic disease. Objectives: The current study aimed to investigate the role of family expressed emotion and perceived social support in prediction of addiction relapse. Patients and Methods: The descriptive-correlation method was used in the current study. The study population consisted of the individuals referred to the addiction treatm...

OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records.

Science.gov (United States)

Chen, Jonathan H; Podchiyska, Tanya; Altman, Russ B

2016-03-01

To answer a "grand challenge" in clinical decision support, the authors produced a recommender system that automatically data-mines inpatient decision support from electronic medical records (EMR), analogous to Netflix or Amazon.com's product recommender. EMR data were extracted from 1 year of hospitalizations (>18K patients with >5.4M structured items including clinical orders, lab results, and diagnosis codes). Association statistics were counted for the ∼1.5K most common items to drive an order recommender. The authors assessed the recommender's ability to predict hospital admission orders and outcomes based on initial encounter data from separate validation patients. Compared to a reference benchmark of using the overall most common orders, the recommender using temporal relationships improves precision at 10 recommendations from 33% to 38% (P < 10(-10)) for hospital admission orders. Relative risk-based association methods improve inverse frequency weighted recall from 4% to 16% (P < 10(-16)). The framework yields a prediction receiver operating characteristic area under curve (c-statistic) of 0.84 for 30 day mortality, 0.84 for 1 week need for ICU life support, 0.80 for 1 week hospital discharge, and 0.68 for 30-day readmission. Recommender results quantitatively improve on reference benchmarks and qualitatively appear clinically reasonable. The method assumes that aggregate decision making converges appropriately, but ongoing evaluation is necessary to discern common behaviors from "correct" ones. Collaborative filtering recommender algorithms generate clinical decision support that is predictive of real practice patterns and clinical outcomes. Incorporating temporal relationships improves accuracy. Different evaluation metrics satisfy different goals (predicting likely events vs. "interesting" suggestions). Published by Oxford University Press on behalf of the American Medical Informatics Association 2015. This work is written by US Government

Exploring a heavy charged Higgs using jet substructure in a fully hadronic channel

Directory of Open Access Journals (Sweden)

Riley Patrick

2017-04-01

Full Text Available In the framework of the type-II Two Higgs Doublet Model (2HDM-II a charged Higgs search strategy is presented for the dominant production mode gb→tH± at the 14 TeV LHC. We consider the decay process which includes t→bW± and H±→AW±, and a fully hadronic final state consisting of bbb¯+jets+X. Dictated by the b→sγ constraints which render MH±>480 GeV we study two scenarios in which the charged Higgs mass is 750 GeV and the pseudoscalar Higgs mass is 200 GeV and 500 GeV. In this mass scheme highly boosted final state objects are expected and handled with jet substructure techniques which also acts to suppress the standard model background. A detailed detector analysis is performed, followed by a multivariate analysis involving many kinematic variables to optimize signal to background significance. Finally the LHC search sensitivities for the two scenarios are presented for various integrated luminosities.

Computational Support for Creative Design

KAUST Repository

Liu, Han

2015-01-01

the structures of input models, we propose new automatic operations to discover replaceable substructures across models or within a model. We enforce a pair of subgraphs matching along their boundaries so that switching two subgraphs results in topological

Reservoir Inflow Prediction under GCM Scenario Downscaled by Wavelet Transform and Support Vector Machine Hybrid Models

Directory of Open Access Journals (Sweden)

Gusfan Halik

2015-01-01

Full Text Available Climate change has significant impacts on changing precipitation patterns causing the variation of the reservoir inflow. Nowadays, Indonesian hydrologist performs reservoir inflow prediction according to the technical guideline of Pd-T-25-2004-A. This technical guideline does not consider the climate variables directly, resulting in significant deviation to the observation results. This research intends to predict the reservoir inflow using the statistical downscaling (SD of General Circulation Model (GCM outputs. The GCM outputs are obtained from the National Center for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP/NCAR Reanalysis. A new proposed hybrid SD model named Wavelet Support Vector Machine (WSVM was utilized. It is a combination of the Multiscale Principal Components Analysis (MSPCA and nonlinear Support Vector Machine regression. The model was validated at Sutami Reservoir, Indonesia. Training and testing were carried out using data of 1991–2008 and 2008–2012, respectively. The results showed that MSPCA produced better extracting data than PCA. The WSVM generated better reservoir inflow prediction than the one of technical guideline. Moreover, this research also applied WSVM for future reservoir inflow prediction based on GCM ECHAM5 and scenario SRES A1B.

Perceived parenting and social support: can they predict academic achievement in Argentinean college students?

Directory of Open Access Journals (Sweden)

de la Iglesia G

2014-09-01

Full Text Available Guadalupe de la Iglesia,1,2 Agustin Freiberg Hoffmann,2 Mercedes Fernández Liporace1,2 1National Council of Scientific and Technical Research (CONICET, 2University of Buenos Aires, Buenos Aires, Argentina Abstract: The aim of this study was to test the ability to predict academic achievement through the perception of parenting and social support in a sample of 354 Argentinean college students. Their mean age was 23.50 years (standard deviation =2.62 years and most of them (83.3% were females. As a prerequisite for admission to college, students are required to pass a series of mandatory core classes and are expected to complete them in two semesters. Delay in completing the curriculum is considered low academic achievement. Parenting was assessed taking into account the mother and the father and considering two dimensions: responsiveness and demandingness. Perceived social support was analyzed considering four sources: parents, teachers, classmates, and best friend or boyfriend/girlfriend. Path analysis showed that, as hypothesized, responsiveness had a positive indirect effect on the perception of social support and enhanced achievement. Demandingness had a different effect in the case of the mother as compared to the father. In the mother model, demandingness had a positive direct effect on achievement. In the case of the father, however, the effect of demandingness had a negative and indirect impact on the perception of social support. Teachers were the only source of perceived social support that significantly predicted achievement. The pathway that belongs to teachers as a source of support was positive and direct. Implications for possible interventions are discussed. Keywords: academic achievement, parenting, social support, college

Computing confidence and prediction intervals of industrial equipment degradation by bootstrapped support vector regression

International Nuclear Information System (INIS)

Lins, Isis Didier; Droguett, Enrique López; Moura, Márcio das Chagas; Zio, Enrico; Jacinto, Carlos Magno

2015-01-01

Data-driven learning methods for predicting the evolution of the degradation processes affecting equipment are becoming increasingly attractive in reliability and prognostics applications. Among these, we consider here Support Vector Regression (SVR), which has provided promising results in various applications. Nevertheless, the predictions provided by SVR are point estimates whereas in order to take better informed decisions, an uncertainty assessment should be also carried out. For this, we apply bootstrap to SVR so as to obtain confidence and prediction intervals, without having to make any assumption about probability distributions and with good performance even when only a small data set is available. The bootstrapped SVR is first verified on Monte Carlo experiments and then is applied to a real case study concerning the prediction of degradation of a component from the offshore oil industry. The results obtained indicate that the bootstrapped SVR is a promising tool for providing reliable point and interval estimates, which can inform maintenance-related decisions on degrading components. - Highlights: • Bootstrap (pairs/residuals) and SVR are used as an uncertainty analysis framework. • Numerical experiments are performed to assess accuracy and coverage properties. • More bootstrap replications does not significantly improve performance. • Degradation of equipment of offshore oil wells is estimated by bootstrapped SVR. • Estimates about the scale growth rate can support maintenance-related decisions

Prediction of protein binding sites using physical and chemical descriptors and the support vector machine regression method

International Nuclear Information System (INIS)

Sun Zhong-Hua; Jiang Fan

2010-01-01

In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression (SVR) method than by the support vector classification method. (rapid communication)

Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model

Directory of Open Access Journals (Sweden)

Shaojiang Dong

2014-01-01

Full Text Available Predicting the degradation process of bearings before they reach the failure threshold is extremely important in industry. This paper proposed a novel method based on the support vector machine (SVM and the Markov model to achieve this goal. Firstly, the features are extracted by time and time-frequency domain methods. However, the extracted original features are still with high dimensional and include superfluous information, and the nonlinear multifeatures fusion technique LTSA is used to merge the features and reduces the dimension. Then, based on the extracted features, the SVM model is used to predict the bearings degradation process, and the CAO method is used to determine the embedding dimension of the SVM model. After the bearing degradation process is predicted by SVM model, the Markov model is used to improve the prediction accuracy. The proposed method was validated by two bearing run-to-failure experiments, and the results proved the effectiveness of the methodology.

A predictive ligand-based Bayesian model for human drug-induced liver injury.

Science.gov (United States)

Ekins, Sean; Williams, Antony J; Xu, Jinghai J

2010-12-01

Drug-induced liver injury (DILI) is one of the most important reasons for drug development failure at both preapproval and postapproval stages. There has been increased interest in developing predictive in vivo, in vitro, and in silico models to identify compounds that cause idiosyncratic hepatotoxicity. In the current study, we applied machine learning, a Bayesian modeling method with extended connectivity fingerprints and other interpretable descriptors. The model that was developed and internally validated (using a training set of 295 compounds) was then applied to a large test set relative to the training set (237 compounds) for external validation. The resulting concordance of 60%, sensitivity of 56%, and specificity of 67% were comparable to results for internal validation. The Bayesian model with extended connectivity functional class fingerprints of maximum diameter 6 (ECFC_6) and interpretable descriptors suggested several substructures that are chemically reactive and may also be important for DILI-causing compounds, e.g., ketones, diols, and α-methyl styrene type structures. Using Smiles Arbitrary Target Specification (SMARTS) filters published by several pharmaceutical companies, we evaluated whether such reactive substructures could be readily detected by any of the published filters. It was apparent that the most stringent filters used in this study, such as the Abbott alerts, which captures thiol traps and other compounds, may be of use in identifying DILI-causing compounds (sensitivity 67%). A significant outcome of the present study is that we provide predictions for many compounds that cause DILI by using the knowledge we have available from previous studies. These computational models may represent cost-effective selection criteria before in vitro or in vivo experimental studies.

Predicting suicide ideation through intrapersonal and interpersonal factors: The interplay of Big-Five personality traits and social support.

Science.gov (United States)

Ayub, Nailah

2015-11-01

While a specific personality trait may escalate suicide ideation, contextual factors such as social support, when provided effectively, may alleviate the effects of such personality traits. This study examined the moderating role of social support in the relationship between the Big-Five personality traits and suicide ideation. Significant interactions were found between social support and extraversion and emotional stability. Specifically, the relationship between emotional stability and extraversion to suicide ideation was exacerbated when social support was low. Slope analysis showed openness also interacted with low social support. Results were computed for frequency, duration and attitude dimensions of suicide ideation. Extraversion interacted with social support to predict all three dimensions. Social support moderated emotional stability to predict frequency and duration, moderated conscientiousness towards frequency and attitude, and moderated openness towards attitude. The results imply that whereas personality traits may be difficult to alter, social support may play a significant role in saving a life. Psychologists should include family and friends when treating a suicidal youth, guiding them to awareness of one's personality and being more supportive. Copyright © 2015 John Wiley & Sons, Ltd.

Predicting supportive behavior of parents and siblings to a family member with intellectual disability living in institutional care.

Science.gov (United States)

Rimmerman, Arie; Chen, Ariel

2012-01-01

This feasibility study examines whether the theory of planned behavior can predict supportive behavior provided by either parents to their offspring--or adult siblings to their brothers and sisters--with an intellectual disability living in 2 Israeli institutional care facilities. Participants were 67 parents and 63 siblings who were interviewed at baseline regarding their intentions to visit their offspring or sibling in the institutional care facility, to contact the caregiving staff, and to accept visits at home. Parents' and siblings' behavior regarding visitation and supportive behavior was examined after 6 months by caregiving staff. Core findings indicated that subjective norms in siblings and parents predicted frequency of home visits. Perceived behavioral control predicted frequency of contact between siblings and staff. Differences between parents and siblings regarding their supportive behaviors are discussed with respect to social work practice.

PREDICTIVE MODELS FOR SUPPORT OF INCIDENT MANAGEMENT PROCESS IN IT SERVICE MANAGEMENT

Directory of Open Access Journals (Sweden)

Martin SARNOVSKY

2018-03-01

Full Text Available ABSTRACT The work presented in this paper is focused on creating of predictive models that help in the process of incident resolution and implementation of IT infrastructure changes to increase the overall support of IT management. Our main objective was to build the predictive models using machine learning algorithms and CRISP-DM methodology. We used the incident and related changes database obtained from the IT environment of the Rabobank Group company, which contained information about the processing of the incidents during the incident management process. We decided to investigate the dependencies between the incident observation on particular infrastructure component and the actual source of the incident as well as the dependency between the incidents and related changes in the infrastructure. We used Random Forests and Gradient Boosting Machine classifiers in the process of identification of incident source as well as in the prediction of possible impact of the observed incident. Both types of models were tested on testing set and evaluated using defined metrics.

Efficient Prediction of Progesterone Receptor Interactome Using a Support Vector Machine Model

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Ji-Long Liu

2015-03-01

Full Text Available Protein-protein interaction (PPI is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, predicting protein partners for a single protein is likely a simpler problem. Given enough data for a particular protein, the results can be more accurate than general PPI predictors. In the present study, we assessed the potential of using the support vector machine (SVM model with selected features centered on a particular protein for PPI prediction. As a proof-of-concept study, we applied this method to identify the interactome of progesterone receptor (PR, a protein which is essential for coordinating female reproduction in mammals by mediating the actions of ovarian progesterone. We achieved an accuracy of 91.9%, sensitivity of 92.8% and specificity of 91.2%. Our method is generally applicable to any other proteins and therefore may be of help in guiding biomedical experiments.

Support vector machines for prediction and analysis of beta and gamma-turns in proteins.

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Pham, Tho Hoan; Satou, Kenji; Ho, Tu Bao

2005-04-01

Tight turns have long been recognized as one of the three important features of proteins, together with alpha-helix and beta-sheet. Tight turns play an important role in globular proteins from both the structural and functional points of view. More than 90% tight turns are beta-turns and most of the rest are gamma-turns. Analysis and prediction of beta-turns and gamma-turns is very useful for design of new molecules such as drugs, pesticides, and antigens. In this paper we investigated two aspects of applying support vector machine (SVM), a promising machine learning method for bioinformatics, to prediction and analysis of beta-turns and gamma-turns. First, we developed two SVM-based methods, called BTSVM and GTSVM, which predict beta-turns and gamma-turns in a protein from its sequence. When compared with other methods, BTSVM has a superior performance and GTSVM is competitive. Second, we used SVMs with a linear kernel to estimate the support of amino acids for the formation of beta-turns and gamma-turns depending on their position in a protein. Our analysis results are more comprehensive and easier to use than the previous results in designing turns in proteins.

Nonlinear seismic response analysis of an embedded reactor building based on the substructure approach

International Nuclear Information System (INIS)

Hasegawa, M.; Ichikawa, T.; Nakai, S.; Watanabe, T.

1987-01-01

A practical method to calculate the elasto-plastic seismic response of structures considering the dynamic soil-structure interaction is presented. The substructure technique in the time domain is utilized in the proposed method. A simple soil spring system with the coupling effects which are usually evaluated by the impedance matrix is introduced to consider the soil-structure interaction for embedded structures. As a numerical example, the response of a BWR-MARK II type reactor building embedded in the layered soil is calculated. The accuracy of the present method is verified by comparing its numerical results with exact solutions. The nonlinear behaivor and the soil-structure interaction effects on the response of the reactor building are also discussed in detail. It is concluded that the present method is effective for the aseismic design considering both the material nonlinearity of the nuclear reactor building and the dynamic soil-structure interaction. (orig.)

Hubble space telescope/advanced camera for surveys confirmation of the dark substructure in A520

International Nuclear Information System (INIS)

Jee, M. J.; Hoekstra, H.; Mahdavi, A.; Babul, A.

2014-01-01

We present a weak-lensing study of the cluster A520 based on Advanced Camera for Surveys (ACS) data. The excellent data quality provides a mean source density of ∼109 arcmin –2 , which improves both resolution and significance of the mass reconstruction compared to a previous study based on Wide Field Planetary Camera 2 (WFPC2) images. We take care in removing instrumental effects such as the charge trailing due to radiation damage of the detector and the position-dependent point-spread function. This new ACS analysis confirms the previous claims that a substantial amount of dark mass is present between two luminous subclusters where we observe very little light. The centroid of the dark peak in the current ACS analysis is offset to the southwest by ∼1' with respect to the centroid from the WFPC2 analysis. Interestingly, this new centroid is in better agreement with the location where the X-ray emission is strongest, and the mass-to-light ratio estimated with this centroid is much higher (813 ± 78 M ☉ /L R☉ ) than the previous value; the aperture mass with the WFPC2 centroid provides a consistent mass. Although we cannot provide a definite explanation for the dark peak, we discuss a revised scenario, wherein dark matter with a more conventional range (σ DM /m DM < 1 cm 2 g –1 ) of self-interacting cross-section can lead to the detection of this dark substructure. If supported by detailed numerical simulations, this hypothesis opens up the possibility that the A520 system can be used to establish a lower limit of the self-interacting cross-section of dark matter.

A dynamic particle filter-support vector regression method for reliability prediction

International Nuclear Information System (INIS)

Wei, Zhao; Tao, Tao; ZhuoShu, Ding; Zio, Enrico

2013-01-01

Support vector regression (SVR) has been applied to time series prediction and some works have demonstrated the feasibility of its use to forecast system reliability. For accuracy of reliability forecasting, the selection of SVR's parameters is important. The existing research works on SVR's parameters selection divide the example dataset into training and test subsets, and tune the parameters on the training data. However, these fixed parameters can lead to poor prediction capabilities if the data of the test subset differ significantly from those of training. Differently, the novel method proposed in this paper uses particle filtering to estimate the SVR model parameters according to the whole measurement sequence up to the last observation instance. By treating the SVR training model as the observation equation of a particle filter, our method allows updating the SVR model parameters dynamically when a new observation comes. Because of the adaptability of the parameters to dynamic data pattern, the new PF–SVR method has superior prediction performance over that of standard SVR. Four application results show that PF–SVR is more robust than SVR to the decrease of the number of training data and the change of initial SVR parameter values. Also, even if there are trends in the test data different from those in the training data, the method can capture the changes, correct the SVR parameters and obtain good predictions. -- Highlights: •A dynamic PF–SVR method is proposed to predict the system reliability. •The method can adjust the SVR parameters according to the change of data. •The method is robust to the size of training data and initial parameter values. •Some cases based on both artificial and real data are studied. •PF–SVR shows superior prediction performance over standard SVR

Freshwater Algal Bloom Prediction by Support Vector Machine in Macau Storage Reservoirs

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Zhengchao Xie

2012-01-01

Full Text Available Understanding and predicting dynamic change of algae population in freshwater reservoirs is particularly important, as algae-releasing cyanotoxins are carcinogens that would affect the health of public. However, the high complex nonlinearity of water variables and their interactions makes it difficult to model the growth of algae species. Recently, support vector machine (SVM was reported to have advantages of only requiring a small amount of samples, high degree of prediction accuracy, and long prediction period to solve the nonlinear problems. In this study, the SVM-based prediction and forecast models for phytoplankton abundance in Macau Storage Reservoir (MSR are proposed, in which the water parameters of pH, SiO2, alkalinity, bicarbonate (HCO3 -, dissolved oxygen (DO, total nitrogen (TN, UV254, turbidity, conductivity, nitrate, total nitrogen (TN, orthophosphate (PO4 3−, total phosphorus (TP, suspended solid (SS and total organic carbon (TOC selected from the correlation analysis of the 23 monthly water variables were included, with 8-year (2001–2008 data for training and the most recent 3 years (2009–2011 for testing. The modeling results showed that the prediction and forecast powers were estimated as approximately 0.76 and 0.86, respectively, showing that the SVM is an effective new way that can be used for monitoring algal bloom in drinking water storage reservoir.

Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset

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Yung-Fu Chen

2018-01-01

Full Text Available More than 1 billion people suffer from chronic respiratory diseases worldwide, accounting for more than 4 million deaths annually. Inhaled corticosteroid is a popular medication for treating chronic respiratory diseases. Its side effects include decreased bone mineral density and osteoporosis. The aims of this study are to investigate the association of inhaled corticosteroids and fracture and to design a clinical support system for fracture prediction. The data of patients aged 20 years and older, who had visited healthcare centers and been prescribed with inhaled corticosteroids within 2002–2010, were retrieved from the National Health Insurance Research Database (NHIRD. After excluding patients diagnosed with hip fracture or vertebrate fractures before using inhaled corticosteroid, a total of 11645 patients receiving inhaled corticosteroid therapy were included for this study. Among them, 1134 (9.7% were diagnosed with hip fracture or vertebrate fracture. The statistical results showed that demographic information, chronic respiratory diseases and comorbidities, and corticosteroid-related variables (cumulative dose, mean exposed daily dose, follow-up duration, and exposed duration were significantly different between fracture and nonfracture patients. The clinical decision support systems (CDSSs were designed with integrated genetic algorithm (GA and support vector machine (SVM by training and validating the models with balanced training sets obtained by random and cluster-based undersampling methods and testing with the imbalanced NHIRD dataset. Two different objective functions were adopted for obtaining optimal models with best predictive performance. The predictive performance of the CDSSs exhibits a sensitivity of 69.84–77.00% and an AUC of 0.7495–0.7590. It was concluded that long-term use of inhaled corticosteroids may induce osteoporosis and exhibit higher incidence of hip or vertebrate fractures. The accumulated dose of ICS and

Supporting change processes in design: Complexity, prediction and reliability

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Eckert, Claudia M. [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: cme26@cam.ac.uk; Keller, Rene [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: rk313@cam.ac.uk; Earl, Chris [Open University, Department of Design and Innovation, Walton Hall, Milton Keynes MK7 6AA (United Kingdom)]. E-mail: C.F.Earl@open.ac.uk; Clarkson, P. John [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: pjc10@cam.ac.uk

2006-12-15

Change to existing products is fundamental to design processes. New products are often designed through change or modification to existing products. Specific parts or subsystems are changed to similar ones whilst others are directly reused. Design by modification applies particularly to safety critical products where the reuse of existing working parts and subsystems can reduce cost and risk. However change is rarely a matter of just reusing or modifying parts. Changing one part can propagate through the entire design leading to costly rework or jeopardising the integrity of the whole product. This paper characterises product change based on studies in the aerospace and automotive industry and introduces tools to aid designers in understanding the potential effects of change. Two ways of supporting designers are described: probabilistic prediction of the effects of change and visualisation of change propagation through product connectivities. Change propagation has uncertainties which are amplified by the choices designers make in practice as they implement change. Change prediction and visualisation is discussed with reference to complexity in three areas of product development: the structural backcloth of connectivities in the existing product (and its processes), the descriptions of the product used in design and the actions taken to carry out changes.

A New Publicly Available Chemical Query Language, CSRML, to support Chemotype Representations for Application to Data-Mining and Modeling

Science.gov (United States)

A new XML-based query language, CSRML, has been developed for representing chemical substructures, molecules, reaction rules, and reactions. CSRML queries are capable of integrating additional forms of information beyond the simple substructure (e.g., SMARTS) or reaction transfor...

Discovering Higgs Bosons of the MSSM using Jet Substructure

International Nuclear Information System (INIS)

Kribs, Graham D.; Martin, Adam; Roy, Tuhin S.; Spannowsky, Michael

2010-01-01

We present a qualitatively new approach to discover Higgs bosons of the MSSM at the LHC using jet substructure techniques applied to boosted Higgs decays. These techniques are ideally suited to the MSSM, since the lightest Higgs boson overwhelmingly decays to b(bar b) throughout the entire parameter space, while the heavier neutral Higgs bosons, if light enough to be produced in a cascade, also predominantly decay to b(bar b). The Higgs production we consider arises from superpartner production where superpartners cascade decay into Higgs bosons. We study this mode of Higgs production for several superpartner hierarchies: m # tilde q#,m # tilde g# > m # tilde W#, # tilde B# > m h + μ; m(tilde q);m # tilde q#,m # tilde g# > m # tilde W#, # tilde B# > m h,H,A + μ; and m # tilde q#,m # tilde g# > m # tilde W# > m h + μ with m # tilde B# ∼ μ. In these cascades, the Higgs bosons are boosted, with pT > 200 GeV a large fraction of the time. Since Higgs bosons appear in cascades originating from squarks and/or gluinos, the cross section for events with at least one Higgs boson can be the same order as squark/gluino production. Given 10 fb -1 of 14 TeV LHC data, with m # tilde q# ∼< 1 TeV, and one of the above superpartner mass hierarchies, our estimate of S√ B of the Higgs signal is sufficiently high that the b(bar b) mode can become the discovery mode of the lightest Higgs boson of the MSSM.

Discovering Higgs bosons of the MSSM using jet substructure

International Nuclear Information System (INIS)

Kribs, Graham D.; Roy, Tuhin S.; Spannowsky, Michael; Martin, Adam

2010-01-01

We present a qualitatively new approach to discover Higgs bosons of the minimal supersymmetric standard model (MSSM) at the LHC using jet substructure techniques applied to boosted Higgs decays. These techniques are ideally suited to the MSSM, since the lightest Higgs boson overwhelmingly decays to bb throughout the entire parameter space, while the heavier neutral Higgs bosons, if light enough to be produced in a cascade, also predominantly decay to bb. The Higgs production we consider arises from superpartner production where superpartners cascade decay into Higgs bosons. We study this mode of Higgs production for several superpartner hierarchies: m q -tilde, m g -tilde>m W -tilde ,B -tilde>m h +μ; m q -tilde, m g -tilde>m W -tilde ,B -tilde>m h,H,A +μ; and m q -tilde, m g -tilde>m W -tilde>m h +μ with m B -tilde≅μ. In these cascades, the Higgs bosons are boosted, with p T >200 GeV a large fraction of the time. Since Higgses appear in cascades originating from squarks and/or gluinos, the cross section for events with at least one Higgs can be the same order as squark/gluino production. Given 10 fb -1 of 14 TeV LHC data, with m q -tilde < or approx. 1 TeV, and one of the above superpartner mass hierarchies, our estimate of S/√(B) of the Higgs signal is sufficiently high that the bb mode can become the discovery mode of the lightest Higgs boson of the MSSM.

Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach

International Nuclear Information System (INIS)

Chen, Kuilin; Yu, Jie

2014-01-01

Highlights: • A novel hybrid modeling method is proposed for short-term wind speed forecasting. • Support vector regression model is constructed to formulate nonlinear state-space framework. • Unscented Kalman filter is adopted to recursively update states under random uncertainty. • The new SVR–UKF approach is compared to several conventional methods for short-term wind speed prediction. • The proposed method demonstrates higher prediction accuracy and reliability. - Abstract: Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. In this study, unscented Kalman filter (UKF) is integrated with support vector regression (SVR) based state-space model in order to precisely update the short-term estimation of wind speed sequence. In the proposed SVR–UKF approach, support vector regression is first employed to formulate a nonlinear state-space model and then unscented Kalman filter is adopted to perform dynamic state estimation recursively on wind sequence with stochastic uncertainty. The novel SVR–UKF method is compared with artificial neural networks (ANNs), SVR, autoregressive (AR) and autoregressive integrated with Kalman filter (AR-Kalman) approaches for predicting short-term wind speed sequences collected from three sites in Massachusetts, USA. The forecasting results indicate that the proposed method has much better performance in both one-step-ahead and multi-step-ahead wind speed predictions than the other approaches across all the locations

Probing jet decoherence in heavy ion collisions

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Casalderrey-Solana, Jorge; Mehtar-Tani, Yacine; Salgado, Carlos A.; Tywoniuk, Konrad

2017-11-01

We suggest to use the SofDrop jet grooming technique to investigate the sensitivity of jet substructure to color decoherence in heavy ion collisions. We propose in particular to analyze the two-prong probability angular distribution as a probe of the transition between the coherent and incoherent energy loss regimes. We predict an increasing suppression of two-prong substructures with angle as the medium resolves more jet substructure.

The Role of Perceived Social Support and Coping Styles in Predicting Adolescents' Positivity

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Çevik, Gülsen Büyüksahin; Yildiz, Mehmet Ali

2017-01-01

The current research aims to examine the perceived social support and coping styles predicting positivity. Research participants included 268 adolescents, attending high school, with 147 females (54.9%) and 121 males (45.1%). Adolescents participating in the research were 14 to 18 years old and their average age was 16.12 with SD = 1.01. Research…

Predictive modeling of interfacial damage in substructured steels: application to martensitic microstructures

International Nuclear Information System (INIS)

Maresca, F; Kouznetsova, V G; Geers, M G D

2016-01-01

Metallic composite phases, like martensite present in conventional steels and new generation high strength steels exhibit microscale, locally lamellar microstructures characterized by alternating layers of phases or crystallographic variants. The layers can be sub-micron down to a few nanometers thick, and they are often characterized by high contrasts in plastic properties. As a consequence, fracture in these lamellar microstructures generally occurs along the layer interfaces or within one of the layers, typically parallel to the interface. This paper presents a computational framework that addresses the lamellar nature of these microstructures, by homogenizing the plastic deformation at the mesoscale by using the microscale response of the laminates. Failure is accounted for by introducing a family of damaging planes that are parallel to the layer interface. Mode I, mode II and mixed-mode opening are incorporated. The planes along which failure occurs are captured using a smeared damage approach. Coupling of damage with isotropic or anisotropic plasticity models, like crystal plasticity, is straightforward. The damaging planes and directions do not need to correspond to crystalline slip planes, and normal opening is also included. Focus is given on rate-dependent formulations of plasticity and damage, i.e. converged results can be obtained without further regularization techniques. The validation of the model using experimental observations in martensite-austenite lamellar microstructures in steels reveals that the model correctly predicts the main features of the onset of failure, e.g. the necking point, the failure initiation region and the failure mode. Finally, based on the qualitative results obtained, some material design guidelines are provided for martensitic and multi-phase steels. (paper)

Clinical Decision Support Model to Predict Occlusal Force in Bruxism Patients.

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Thanathornwong, Bhornsawan; Suebnukarn, Siriwan

2017-10-01

The aim of this study was to develop a decision support model for the prediction of occlusal force from the size and color of articulating paper markings in bruxism patients. We used the information from the datasets of 30 bruxism patients in which digital measurements of the size and color of articulating paper markings (12-µm Hanel; Coltene/Whaledent GmbH, Langenau, Germany) on canine protected hard stabilization splints were measured in pixels (P) and in red (R), green (G), and blue (B) values using Adobe Photoshop software (Adobe Systems, San Jose, CA, USA). The occlusal force (F) was measured using T-Scan III (Tekscan Inc., South Boston, MA, USA). The multiple regression equation was applied to predict F from the P and RGB. Model evaluation was performed using the datasets from 10 new patients. The patient's occlusal force measured by T-Scan III was used as a 'gold standard' to compare with the occlusal force predicted by the multiple regression model. The results demonstrate that the correlation between the occlusal force and the pixels and RGB of the articulating paper markings was positive (F = 1.62×P + 0.07×R -0.08×G + 0.08×B + 4.74; R 2 = 0.34). There was a high degree of agreement between the occlusal force of the patient measured using T-Scan III and the occlusal force predicted by the model (kappa value = 0.82). The results obtained demonstrate that the multiple regression model can predict the occlusal force using the digital values for the size and color of the articulating paper markings in bruxism patients.

Clinical Decision Support Model to Predict Occlusal Force in Bruxism Patients

Science.gov (United States)

Thanathornwong, Bhornsawan

2017-01-01

Objectives The aim of this study was to develop a decision support model for the prediction of occlusal force from the size and color of articulating paper markings in bruxism patients. Methods We used the information from the datasets of 30 bruxism patients in which digital measurements of the size and color of articulating paper markings (12-µm Hanel; Coltene/Whaledent GmbH, Langenau, Germany) on canine protected hard stabilization splints were measured in pixels (P) and in red (R), green (G), and blue (B) values using Adobe Photoshop software (Adobe Systems, San Jose, CA, USA). The occlusal force (F) was measured using T-Scan III (Tekscan Inc., South Boston, MA, USA). The multiple regression equation was applied to predict F from the P and RGB. Model evaluation was performed using the datasets from 10 new patients. The patient's occlusal force measured by T-Scan III was used as a ‘gold standard’ to compare with the occlusal force predicted by the multiple regression model. Results The results demonstrate that the correlation between the occlusal force and the pixels and RGB of the articulating paper markings was positive (F = 1.62×P + 0.07×R –0.08×G + 0.08×B + 4.74; R2 = 0.34). There was a high degree of agreement between the occlusal force of the patient measured using T-Scan III and the occlusal force predicted by the model (kappa value = 0.82). Conclusions The results obtained demonstrate that the multiple regression model can predict the occlusal force using the digital values for the size and color of the articulating paper markings in bruxism patients. PMID:29181234

Predicting sumoylation sites using support vector machines based on various sequence features, conformational flexibility and disorder.

Science.gov (United States)

Yavuz, Ahmet Sinan; Sezerman, Osman Ugur

2014-01-01

Sumoylation, which is a reversible and dynamic post-translational modification, is one of the vital processes in a cell. Before a protein matures to perform its function, sumoylation may alter its localization, interactions, and possibly structural conformation. Abberations in protein sumoylation has been linked with a variety of disorders and developmental anomalies. Experimental approaches to identification of sumoylation sites may not be effective due to the dynamic nature of sumoylation, laborsome experiments and their cost. Therefore, computational approaches may guide experimental identification of sumoylation sites and provide insights for further understanding sumoylation mechanism. In this paper, the effectiveness of using various sequence properties in predicting sumoylation sites was investigated with statistical analyses and machine learning approach employing support vector machines. These sequence properties were derived from windows of size 7 including position-specific amino acid composition, hydrophobicity, estimated sub-window volumes, predicted disorder, and conformational flexibility. 5-fold cross-validation results on experimentally identified sumoylation sites revealed that our method successfully predicts sumoylation sites with a Matthew's correlation coefficient, sensitivity, specificity, and accuracy equal to 0.66, 73%, 98%, and 97%, respectively. Additionally, we have showed that our method compares favorably to the existing prediction methods and basic regular expressions scanner. By using support vector machines, a new, robust method for sumoylation site prediction was introduced. Besides, the possible effects of predicted conformational flexibility and disorder on sumoylation site recognition were explored computationally for the first time to our knowledge as an additional parameter that could aid in sumoylation site prediction.

A STUDY OF PREDICTING THE NEED FOR VENTILATOR SUPPORT AND OUTCOME IN ORGANOPHOSPHORUS POISONING

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Kalinga Bommankatte Eranaik

2017-04-01

Full Text Available BACKGROUND Organophosphorus compound poisoning is the most common poisonings in India because of easy availability, often requiring ICU care and ventilator support. Clinical research has indicated that respiratory failure is the most important cause of death due to Organophosphorus poisoning. It results in respiratory muscle weakness, pulmonary oedema, respiratory depression, increased secretions and bronchospasm. These complications and death can be prevented with timely Institution of ventilator support. The aim of present study was to identify the factors and predicting the need for ventilator support and outcome. Aim of the Study- To predict the need for ventilator support and outcome in organophosphate poisoning. MATERIALS AND METHODS Seventy consecutive patients admitted with a history of organophosphorus poisoning at KIMS, Hubli were taken for study after considering the inclusion and exclusion criteria. Detailed history, confirmation of poisoning, examination and other than routine investigations serum pseudocholinesterase and arterial blood gas analysis was done. The severity of organophosphorus poisoning was graded as mild, moderate and severe based on the factors which influence the need for ventilator support. RESULTS This study was conducted in 70 patients, out of which 48 (68.6% were male patients and 22 (31.4% were female patients. Among them 37 (53% patients required ventilation and 33 (47% expired. Chlorpyrifos, Dichlorvos and Monocrotophos were most commonly consumed poisons. 74% patients who consumed these compounds required ventilator support and 73% patients expired. 100% of patients presented with pin point pupil, fasciculation score > 4, respiratory rate > 20, GCS score < 7 and severe grade of poisoning required ventilator support and pseudocholinesterase < 900 U/L, 70% of metabolic acidosis and atropine requirement more than 180 mg within 48 hours required ventilator support and associated with high mortality. CONCLUSION

Support vector regression model based predictive control of water level of U-tube steam generators

Energy Technology Data Exchange (ETDEWEB)

Kavaklioglu, Kadir, E-mail: kadir.kavaklioglu@pau.edu.tr

2014-10-15

Highlights: • Water level of U-tube steam generators was controlled in a model predictive fashion. • Models for steam generator water level were built using support vector regression. • Cost function minimization for future optimal controls was performed by using the steepest descent method. • The results indicated the feasibility of the proposed method. - Abstract: A predictive control algorithm using support vector regression based models was proposed for controlling the water level of U-tube steam generators of pressurized water reactors. Steam generator data were obtained using a transfer function model of U-tube steam generators. Support vector regression based models were built using a time series type model structure for five different operating powers. Feedwater flow controls were calculated by minimizing a cost function that includes the level error, the feedwater change and the mismatch between feedwater and steam flow rates. Proposed algorithm was applied for a scenario consisting of a level setpoint change and a steam flow disturbance. The results showed that steam generator level can be controlled at all powers effectively by the proposed method.

Personality predicts perceived availability of social support and satisfaction with social support in women with early stage breast cancer.

Science.gov (United States)

Den Oudsten, Brenda L; Van Heck, Guus L; Van der Steeg, Alida F W; Roukema, Jan A; De Vries, Jolanda

2010-04-01

This study examines the relationships between personality, on the one hand, and perceived availability of social support (PASS) and satisfaction with received social support (SRSS), on the other hand, in women with early stage breast cancer (BC). In addition, this study examined whether a stressful event (i.e., diagnosis) is associated with quality of life (QOL), when controlling for PASS and SRSS. Women were assessed on PASS and SRSS (World Health Organization QOL assessment instrument-100) before diagnosis (time 1) and 1 (time 2), 3 (time 3), 6 (time 4), 12 (time 5), and 24 months (time 6) after surgical treatment. Personality (neuroticism extraversion openness five-factor inventory and state trait anxiety inventory-trait scale) and fatigue (fatigue assessment scale) were assessed at time 1. Agreeableness and fatigue predicted PASS and SRSS at time 5 and time 6. Trait anxiety had a negative effect on SRSS (ss = -0.22, p personality factors substantially influence the way women with early stage BC perceive social support. Knowledge about these underlying mechanisms of social support is useful for the development of tailor-made interventions. Professionals should be aware of the importance of social support. They should check whether patients have sufficient significant others in their social environment and be sensitive to potential discrepancies patients might experience between availability and adequacy of social support.

Familial social support predicts a reduced cortisol response to stress in sexual minority young adults.

Science.gov (United States)

Burton, C L; Bonanno, G A; Hatzenbuehler, M L

2014-09-01

Social support has been repeatedly associated with mental and physical health outcomes, with hypothalamic-pituitary-adrenocortical (HPA) axis activity posited as a potential mechanism. The influence of social bonds appears particularly important in the face of stigma-related stress; however, there is a dearth of research examining social support and HPA axis response among members of a stigmatized group. To address this gap in the literature, we tested in a sample of 70 lesbian, gay, and bisexual (LGB) young adults whether family support or peer support differentially predict cortisol reactivity in response to a laboratory stressor, the Trier Social Stress Test. While greater levels of family support were associated with reduced cortisol reactivity, neither peer support nor overall support satisfaction was associated with cortisol response. These findings suggest that the association between social support and neuroendocrine functioning differs according to the source of support among members of one stigmatized group. Copyright © 2014 Elsevier Ltd. All rights reserved.

Pre-Operative Prediction of Advanced Prostatic Cancer Using Clinical Decision Support Systems: Accuracy Comparison between Support Vector Machine and Artificial Neural Network

Energy Technology Data Exchange (ETDEWEB)

Kim, Sang Youn; Moon, Sung Kyoung; Hwang, Sung Il; Sung, Chang Kyu; Cho, Jeong Yeon; Kim, Seung Hyup; Lee, Hak Jong [Seoul National University College of Medicine, Seoul (Korea, Republic of); Jung, Dae Chul [National Cancer Center, Ilsan (Korea, Republic of); Lee, Ji Won [Kangwon National University College of Medicine, Chuncheon (Korea, Republic of)

2011-10-15

The purpose of the current study was to develop support vector machine (SVM) and artificial neural network (ANN) models for the pre-operative prediction of advanced prostate cancer by using the parameters acquired from transrectal ultrasound (TRUS)-guided prostate biopsies, and to compare the accuracies between the two models. Five hundred thirty-two consecutive patients who underwent prostate biopsies and prostatectomies for prostate cancer were divided into the training and test groups (n = 300 versus n 232). From the data in the training group, two clinical decision support systems (CDSSs-[SVM and ANN]) were constructed with input (age, prostate specific antigen level, digital rectal examination, and five biopsy parameters) and output data (the probability for advanced prostate cancer [> pT3a]). From the data of the test group, the accuracy of output data was evaluated. The areas under the receiver operating characteristic (ROC) curve (AUC) were calculated to summarize the overall performances, and a comparison of the ROC curves was performed (p < 0.05). The AUC of SVM and ANN is 0.805 and 0.719, respectively (p = 0.020), in the pre-operative prediction of advanced prostate cancer. Te performance of SVM is superior to ANN in the pre-operative prediction of advanced prostate cancer.

Genetic Learning of Fuzzy Parameters in Predictive and Decision Support Modelling

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Nebot

2012-04-01

Full Text Available In this research a genetic fuzzy system (GFS is proposed that performs discretization parameter learning in the context of the Fuzzy Inductive Reasoning (FIR methodology and the Linguistic Rule FIR (LR-FIR algorithm. The main goal of the GFS is to take advantage of the potentialities of GAs to learn the fuzzification parameters of the FIR and LR-FIR approaches in order to obtain reliable and useful predictive (FIR models and decision support (LR-FIR models. The GFS is evaluated in an e-learning context.

Prediction of Agriculture Drought Using Support Vector Regression Incorporating with Climatology Indices

Science.gov (United States)

Tian, Y.; Xu, Y. P.

2017-12-01

In this paper, the Support Vector Regression (SVR) model incorporating climate indices and drought indices are developed to predict agriculture drought in Xiangjiang River basin, Central China. The agriculture droughts are presented with the Precipitation-Evapotranspiration Index (SPEI). According to the analysis of the relationship between SPEI with different time scales and soil moisture, it is found that SPEI of six months time scales (SPEI-6) could reflect the soil moisture better than that of three and one month time scale from the drought features including drought duration, severity and peak. Climate forcing like El Niño Southern Oscillation and western Pacific subtropical high (WPSH) are represented by climate indices such as MEI and series indices of WPSH. Ridge Point of WPSH is found to be the key factor that influences the agriculture drought mainly through the control of temperature. Based on the climate indices analysis, the predictions of SPEI-6 are conducted using the SVR model. The results show that the SVR model incorperating climate indices, especially ridge point of WPSH, could improve the prediction accuracy compared to that using drought index only. The improvement was more significant for the prediction of one month lead time than that of three months lead time. However, it needs to be cautious in selection of the input parameters, since adding more useless information could have a counter effect in attaining a better prediction.

The potential of predictive analytics to provide clinical decision support in depression treatment planning.

Science.gov (United States)

Kessler, Ronald C

2018-01-01

To review progress developing clinical decision support tools for personalized treatment of major depressive disorder (MDD). Over the years, a variety of individual indicators ranging from biomarkers to clinical observations and self-report scales have been used to predict various aspects of differential MDD treatment response. Most of this work focused on predicting remission either with antidepressant medications versus psychotherapy, some antidepressant medications versus others, some psychotherapies versus others, and combination therapies versus monotherapies. However, to date, none of the individual predictors in these studies has been strong enough to guide optimal treatment selection for most patients. Interest consequently turned to decision support tools made up of multiple predictors, but the development of such tools has been hampered by small study sample sizes. Design recommendations are made here for future studies to address this problem. Recommendations include using large prospective observational studies followed by pragmatic trials rather than smaller, expensive controlled treatment trials for preliminary development of decision support tools; basing these tools on comprehensive batteries of inexpensive self-report and clinical predictors (e.g., self-administered performance-based neurocognitive tests) versus expensive biomarkers; and reserving biomarker assessments for targeted studies of patients not well classified by inexpensive predictor batteries.

Exploring a Potential Bias in Dark Matter Investigations Using Strongly Lensed Quasars

NARCIS (Netherlands)

Hsueh, Jen-Wei; Fassnacht, Christopher; Vegetti, Simona; Springola, Cristiana; Oldham, Lindsay; Despali, Giulia; Auger, Matthew; Xu, Dandan; Metcalf, Benton; McKean, John; Koopmans, Leon; Lagattuta, David

2018-01-01

Simulations based on ΛCDM cosmology predict thousands of substructures under galactic scale have not been detected in the local universe. One hypothesis proposes that most of these substructures are dark for various astrophysical reasons. Gravitational lensing provides a powerful alternative way to

Cost-derived indices for building design and construction ...

African Journals Online (AJOL)

Also as multiples of gfi, substructure cost index, sci and roofing cost index, rci could predict componental costs of substructure and roofing for phased development purposes. Keywords: Cost Indices, Building Design, Building Construction Journal of Modeling, Design and Management of Engineering Systems, Vol.

PSR B0329+54: substructure in the scatter-broadened image discovered with RadioAstron on baselines up to 330 000 km

Science.gov (United States)

Popov, Mikhail V.; Bartel, Norbert; Gwinn, Carl R.; Johnson, Michael D.; Andrianov, Andrey; Fadeev, Evgeny; Joshi, Bhal Chandra; Kardashev, Nikolay; Karuppusamy, Ramesh; Kovalev, Yuri Y.; Kramer, Michael; Rudnitskiy, Alexey; Shishov, Vladimir; Smirnova, Tatiana; Soglasnov, Vladimir A.; Zensus, J. Anton

2017-02-01

We have resolved the scatter-broadened image of PSR B0329+54 and detected a substructure within it. These results are not influenced by any extended structure of a source but instead are directly attributed to the interstellar medium. We obtained these results at 324 MHz with the ground-space interferometer RadioAstron, which included the Space Radio Telescope, ground-based Westerbork Synthesis Radio Telescope and 64-m Kalyazin Radio Telescope on baseline projections up to 330 000 km in 2013 November 22 and 2014 January 1 to 2. At short 15 000 to 35 000 km ground-space baseline projections, the visibility amplitude decreases with baseline length, providing a direct measurement of the size of the scattering disc of 4.8 ± 0.8 mas. At longer baselines, no visibility detections from the scattering disc would be expected. However, significant detections were obtained with visibility amplitudes of 3 to 5 per cent of the maximum scattered around a mean and approximately constant up to 330 000 km. These visibilities reflect a substructure from scattering in the interstellar medium and offer a new probe of ionized interstellar material. The size of the diffraction spot near Earth is 17 000 ± 3 000 km. With the assumption of turbulent irregularities in the plasma of the interstellar medium, we estimate that the effective scattering screen is located 0.6 ± 0.1 of the distance from the Earth towards the pulsar.

The application of in-situ 3D X-ray diffraction in annealing experiments: First interpretation of substructure development in deformed NaCl

DEFF Research Database (Denmark)

Borthwick, Verity; Schmidt, Søren; Piazolo, Sandra

2012-01-01

In-situ 3D X-ray diffraction (3DXRD) annealing experiments were conducted at the ID-11 beamline at the European Synchrotron Radiation Facility in Grenoble. This allowed us to nondestructively document and subsequently analyse the development of substructures during heating, without the influence...... subgrain boundary formation. These results demonstrate that 3DXRD coupled with in-situ heating is a successful non-destructive technique for examining real-time postdeformational annealing in strongly deformed crystalline materials with complicated microstructures. © (2012) Trans Tech Publications...

Prediction on sunspot activity based on fuzzy information granulation and support vector machine

Science.gov (United States)

Peng, Lingling; Yan, Haisheng; Yang, Zhigang

2018-04-01

In order to analyze the range of sunspots, a combined prediction method of forecasting the fluctuation range of sunspots based on fuzzy information granulation (FIG) and support vector machine (SVM) was put forward. Firstly, employing the FIG to granulate sample data and extract va)alid information of each window, namely the minimum value, the general average value and the maximum value of each window. Secondly, forecasting model is built respectively with SVM and then cross method is used to optimize these parameters. Finally, the fluctuation range of sunspots is forecasted with the optimized SVM model. Case study demonstrates that the model have high accuracy and can effectively predict the fluctuation of sunspots.

LMethyR-SVM: Predict Human Enhancers Using Low Methylated Regions based on Weighted Support Vector Machines.

Science.gov (United States)

Xu, Jingting; Hu, Hong; Dai, Yang

The identification of enhancers is a challenging task. Various types of epigenetic information including histone modification have been utilized in the construction of enhancer prediction models based on a diverse panel of machine learning schemes. However, DNA methylation profiles generated from the whole genome bisulfite sequencing (WGBS) have not been fully explored for their potential in enhancer prediction despite the fact that low methylated regions (LMRs) have been implied to be distal active regulatory regions. In this work, we propose a prediction framework, LMethyR-SVM, using LMRs identified from cell-type-specific WGBS DNA methylation profiles and a weighted support vector machine learning framework. In LMethyR-SVM, the set of cell-type-specific LMRs is further divided into three sets: reliable positive, like positive and likely negative, according to their resemblance to a small set of experimentally validated enhancers in the VISTA database based on an estimated non-parametric density distribution. Then, the prediction model is obtained by solving a weighted support vector machine. We demonstrate the performance of LMethyR-SVM by using the WGBS DNA methylation profiles derived from the human embryonic stem cell type (H1) and the fetal lung fibroblast cell type (IMR90). The predicted enhancers are highly conserved with a reasonable validation rate based on a set of commonly used positive markers including transcription factors, p300 binding and DNase-I hypersensitive sites. In addition, we show evidence that the large fraction of the LMethyR-SVM predicted enhancers are not predicted by ChromHMM in H1 cell type and they are more enriched for the FANTOM5 enhancers. Our work suggests that low methylated regions detected from the WGBS data are useful as complementary resources to histone modification marks in developing models for the prediction of cell-type-specific enhancers.

Studying a denition for a boosted W/Z/H jet tagger at the FCChh, employing modern Machine Learning algorithms and customised features (beyond the usual substructure variables)

CERN Document Server

Brzhechko, Danyyl

2016-01-01

A jet is a spray of particles, usually produced by the hadronization of a quark or gluon in a particle physics or heavy ion experiment. Reconstructed particles are clustered into jets using one of the available jet clustering algorithms (kT, anti-kT etc.), which adopt dierent metrics to decide if two given particles belong to the same jet or not. Jets can also originate from the decay of high-momenta heavy particles, such as boosted vector boson. When these particles decay to quarks, the overlap of the hadronization products of each quark result into a single massive jet, dierent than the ordinary jets from quarks and gluons. These special jets can be identied using substructure algorithms. In this study, we consider the performances of a commonly used substructure variable, N-subjettiness, with two variants of an alternative approach, based on the momentum ow around the jet axis. I focused on high-energy collision in a hypothetical future circular collider (FCC) colliding protons at a center-of-mass energy 1...

Impact of Intragranular Substructure Parameters on the Forming Limit Diagrams of Single-Phase B.C.C. Steels

Directory of Open Access Journals (Sweden)

Gérald Franz

2013-11-01

Full Text Available An advanced elastic-plastic self-consistent polycrystalline model, accounting for intragranular microstructure development and evolution, is coupled with a bifurcation-based localization criterion and applied to the numerical investigation of the impact of microstructural patterns on ductility of single-phase steels. The proposed multiscale model, taking into account essential microstructural aspects, such as initial and induced textures, dislocation densities, and softening mechanisms, allows us to emphasize the relationship between intragranular microstructure of B.C.C. steels and their ductility. A qualitative study in terms of forming limit diagrams for various dislocation networks, during monotonic loading tests, is conducted in order to analyze the impact of intragranular substructure parameters on the formability of single-phase B.C.C. steels.

The predicting roles of reasons for living and social support on depression, anxiety and stress among young people in Malaysia.

Science.gov (United States)

Amit, N; Ibrahim, N; Aga Mohd Jaladin, R; Che Din, N

2017-10-01

This research examined the predicting roles of reasons for living and social support on depression, anxiety and stress in Malaysia. This research was carried out on a sample of 263 participants (age range 12-24 years old), from Klang Valley, Selangor. The survey package comprises demographic information, a measure of reasons for living, social support, depression, anxiety and stress. To analyse the data, correlation analysis and a series of linear multiple regression analysis were carried out. Findings showed that there were low negative relationships between all subdomains and the total score of reasons for living and depression. There were also low negative relationships between domain-specific of social support (family and friends) and total social support and depression. In terms of the family alliance, self-acceptance and total score of reasons for living, they were negatively associated with anxiety, whereas family social support was negatively associated with stress. The linear regression analysis showed that only future optimism and family social support found to be the significant predictors for depression. Family alliance and total reasons for living were significant in predicting anxiety, whereas family social support was significant in predicting stress. These findings have the potential to promote awareness related to depression, anxiety, and stress among youth in Malaysia.

The Weighted Support Vector Machine Based on Hybrid Swarm Intelligence Optimization for Icing Prediction of Transmission Line

Directory of Open Access Journals (Sweden)

Xiaomin Xu

2015-01-01

Full Text Available Not only can the icing coat on transmission line cause the electrical fault of gap discharge and icing flashover but also it will lead to the mechanical failure of tower, conductor, insulators, and others. It will bring great harm to the people’s daily life and work. Thus, accurate prediction of ice thickness has important significance for power department to control the ice disaster effectively. Based on the analysis of standard support vector machine, this paper presents a weighted support vector machine regression model based on the similarity (WSVR. According to the different importance of samples, this paper introduces the weighted support vector machine and optimizes its parameters by hybrid swarm intelligence optimization algorithm with the particle swarm and ant colony (PSO-ACO, which improves the generalization ability of the model. In the case study, the actual data of ice thickness and climate in a certain area of Hunan province have been used to predict the icing thickness of the area, which verifies the validity and applicability of this proposed method. The predicted results show that the intelligent model proposed in this paper has higher precision and stronger generalization ability.

Ductility prediction of substrate-supported metal layers based on rate-independent crystal plasticity theory

Directory of Open Access Journals (Sweden)

Akpama Holanyo K.

2016-01-01

Full Text Available In this paper, both the bifurcation theory and the initial imperfection approach are used to predict localized necking in substrate-supported metal layers. The self-consistent scale-transition scheme is used to derive the mechanical behavior of a representative volume element of the metal layer from the behavior of its microscopic constituents (the single crystals. The mechanical behavior of the elastomer substrate follows the neo-Hookean hyperelastic model. The adherence between the two layers is assumed to be perfect. Through numerical results, it is shown that the limit strains predicted by the initial imperfection approach tend towards the bifurcation predictions when the size of the geometric imperfection in the metal layer vanishes. Also, it is shown that the addition of an elastomer layer to a metal layer enhances ductility.

Applying a multi-replication framework to support dynamic situation assessment and predictive capabilities

Science.gov (United States)

Lammers, Craig; McGraw, Robert M.; Steinman, Jeffrey S.

2005-05-01

Technological advances and emerging threats reduce the time between target detection and action to an order of a few minutes. To effectively assist with the decision-making process, C4I decision support tools must quickly and dynamically predict and assess alternative Courses Of Action (COAs) to assist Commanders in anticipating potential outcomes. These capabilities can be provided through the faster-than-real-time predictive simulation of plans that are continuously re-calibrating with the real-time picture. This capability allows decision-makers to assess the effects of re-tasking opportunities, providing the decision-maker with tremendous freedom to make time-critical, mid-course decisions. This paper presents an overview and demonstrates the use of a software infrastructure that supports DSAP capabilities. These DSAP capabilities are demonstrated through the use of a Multi-Replication Framework that supports (1) predictivie simulations using JSAF (Joint Semi-Automated Forces); (2) real-time simulation, also using JSAF, as a state estimation mechanism; and, (3) real-time C4I data updates through TBMCS (Theater Battle Management Core Systems). This infrastructure allows multiple replications of a simulation to be executed simultaneously over a grid faster-than-real-time, calibrated with live data feeds. A cost evaluator mechanism analyzes potential outcomes and prunes simulations that diverge from the real-time picture. In particular, this paper primarily serves to walk a user through the process for using the Multi-Replication Framework providing an enhanced decision aid.

Computational Support for Creative Design

KAUST Repository

Liu, Han

2015-12-09

rooms, and fabrication considerations (i.e., economic construction cost). Secondly, we introduce replaceable substructures as arrangements of shape components that can be interchanged while ensuring boundary consistency. Based on the shape graphs that encode the structures of input models, we propose new automatic operations to discover replaceable substructures across models or within a model. We enforce a pair of subgraphs matching along their boundaries so that switching two subgraphs results in topological variations. Thirdly, we develop an interactive system that supports a freeform design by interpreting user sketches. 3D contents can be extracted from input strokes with or without user annotations. Our system accepts user strokes, analyzes their contacts and vanishing directions with respect to an anchored image, and projects 2D strokes to 3D space via a multi- stage optimization on spatial canvas selection. We demonstrate the computational approaches on a range of example models and design studies.

Decision support system in Predicting the Best teacher with Multi Atribute Decesion Making Weighted Product (MADMWP Method

Directory of Open Access Journals (Sweden)

Solikhun Solikhun

2017-06-01

Full Text Available Predicting of the best teacher in Indonesia aims to spur the development of the growth and improve the quality of the education. In this paper, the predicting  of the best teacher is implemented based on predefined criteria. To help the predicting process, a decision support system is needed. This paper employs Multi Atribute Decesion Making Weighted Product (MADMWP method. The result of this method is tested some teachers in  junior high school islamic boarding Al-Barokah school, Simalungun, North Sumatera, Indonesia. This system can be used to help in solving problems of the best teacher prediction.

Virtual-view PSNR prediction based on a depth distortion tolerance model and support vector machine.

Science.gov (United States)

Chen, Fen; Chen, Jiali; Peng, Zongju; Jiang, Gangyi; Yu, Mei; Chen, Hua; Jiao, Renzhi

2017-10-20

Quality prediction of virtual-views is important for free viewpoint video systems, and can be used as feedback to improve the performance of depth video coding and virtual-view rendering. In this paper, an efficient virtual-view peak signal to noise ratio (PSNR) prediction method is proposed. First, the effect of depth distortion on virtual-view quality is analyzed in detail, and a depth distortion tolerance (DDT) model that determines the DDT range is presented. Next, the DDT model is used to predict the virtual-view quality. Finally, a support vector machine (SVM) is utilized to train and obtain the virtual-view quality prediction model. Experimental results show that the Spearman's rank correlation coefficient and root mean square error between the actual PSNR and the predicted PSNR by DDT model are 0.8750 and 0.6137 on average, and by the SVM prediction model are 0.9109 and 0.5831. The computational complexity of the SVM method is lower than the DDT model and the state-of-the-art methods.

Jet substructure using semi-inclusive jet functions in SCET

International Nuclear Information System (INIS)

Kang, Zhong-Bo; Ringer, Felix; Vitev, Ivan

2016-01-01

We propose a new method to evaluate jet substructure observables in inclusive jet measurements, based upon semi-inclusive jet functions in the framework of Soft Collinear Effective Theory (SCET). As a first example, we consider the jet fragmentation function, where a hadron h is identified inside a fully reconstructed jet. We introduce a new semi-inclusive fragmenting jet function G_i"h(z=ω_J/ω,z_h=ω_h/ω_J,ω_J,R,μ), which depends on the jet radius R and the large light-cone momenta of the parton ‘i’ initiating the jet (ω), the jet (ω_J), and the hadron h (ω_h). The jet fragmentation function can then be expressed as a semi-inclusive observable, in the spirit of actual experimental measurements, rather than as an exclusive one. We demonstrate the consistency of the effective field theory treatment and standard perturbative QCD calculations of this observable at next-to-leading order (NLO). The renormalization group (RG) equation for the semi-inclusive fragmenting jet function G_i"h(z,z_h,ω_J,R,μ) are also derived and shown to follow exactly the usual timelike DGLAP evolution equations for fragmentation functions. The newly obtained RG equations can be used to perform the resummation of single logarithms of the jet radius parameter R up to next-to-leading logarithmic (NLL_R) accuracy. In combination with the fixed NLO calculation, we obtain NLO+NLL_R results for the hadron distribution inside the jet. We present numerical results for pp→(jet h)X in the new framework, and find excellent agreement with existing LHC experimental data.

Reservoir rock permeability prediction using support vector regression in an Iranian oil field

International Nuclear Information System (INIS)

Saffarzadeh, Sadegh; Shadizadeh, Seyed Reza

2012-01-01

Reservoir permeability is a critical parameter for the evaluation of hydrocarbon reservoirs. It is often measured in the laboratory from reservoir core samples or evaluated from well test data. The prediction of reservoir rock permeability utilizing well log data is important because the core analysis and well test data are usually only available from a few wells in a field and have high coring and laboratory analysis costs. Since most wells are logged, the common practice is to estimate permeability from logs using correlation equations developed from limited core data; however, these correlation formulae are not universally applicable. Recently, support vector machines (SVMs) have been proposed as a new intelligence technique for both regression and classification tasks. The theory has a strong mathematical foundation for dependence estimation and predictive learning from finite data sets. The ultimate test for any technique that bears the claim of permeability prediction from well log data is the accurate and verifiable prediction of permeability for wells where only the well log data are available. The main goal of this paper is to develop the SVM method to obtain reservoir rock permeability based on well log data. (paper)

Large-scale prediction of drug–target interactions using protein sequences and drug topological structures

International Nuclear Information System (INIS)

Cao Dongsheng; Liu Shao; Xu Qingsong; Lu Hongmei; Huang Jianhua; Hu Qiannan; Liang Yizeng

2012-01-01

Highlights: ► Drug–target interactions are predicted using an extended SAR methodology. ► A drug–target interaction is regarded as an event triggered by many factors. ► Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. ► Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug–target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug–target interactions in a timely manner. In this article, we aim at extending current structure–activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug–target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug–target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug–target interactions, and show a general compatibility between the new scheme and current SAR

Large-scale prediction of drug-target interactions using protein sequences and drug topological structures

Energy Technology Data Exchange (ETDEWEB)

Cao Dongsheng [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Liu Shao [Xiangya Hospital, Central South University, Changsha 410008 (China); Xu Qingsong [School of Mathematical Sciences and Computing Technology, Central South University, Changsha 410083 (China); Lu Hongmei; Huang Jianhua [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Hu Qiannan [Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, and Wuhan University School of Pharmaceutical Sciences, Wuhan 430071 (China); Liang Yizeng, E-mail: yizeng_liang@263.net [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China)

2012-11-08

Highlights: Black-Right-Pointing-Pointer Drug-target interactions are predicted using an extended SAR methodology. Black-Right-Pointing-Pointer A drug-target interaction is regarded as an event triggered by many factors. Black-Right-Pointing-Pointer Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. Black-Right-Pointing-Pointer Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug-target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug-target interactions in a timely manner. In this article, we aim at extending current structure-activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug-target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug-target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug

Do parents' support behaviours predict whether or not their children get sufficient sleep? A cross-sectional study.

Science.gov (United States)

Pyper, Evelyn; Harrington, Daniel; Manson, Heather

2017-05-24

Sleep is an essential component of healthy cognitive and physical development. Lack of sleep may put children at risk for a variety of mental and physical health outcomes, including overweight, obesity and related chronic diseases. Given that children's sleep duration has decreased in recent decades, there is a need to understand the determinants of child sleep, including the role of parental support behaviours. This study aims to determine the relative contribution of different types of parental support behaviours for predicting the likelihood that children meet recently established Canadian sleep guidelines. Data were collected using Computer Assisted Telephone Interviews (CATI) of parents or guardians with at least one child under the age of 18 living in Ontario, Canada. To align with sleep guidelines, parents included in this analysis had at least one child between 5 and 17 years of age (n = 1622). Two multivariable logistic regression models were built to predict whether or not parents reported their child was meeting sleep guidelines - one for weekday sleep and another for sleep on weekends. Independent variables included parent and child age and gender, motivational and regulatory parental support behaviours, and socio-demographic characteristics. On weekdays, enforcing rules about child bedtime was a significant positive predictor of children meeting sleep guidelines (OR: 1.59; 95% CI: 1.03-2.44); while encouraging the child to go to bed at a specific time was a significant negative predictor of child meeting sleep guidelines (OR: 0.29; 95% CI: 0.13-0.65). On weekends, none of the parental support behaviours contributed significantly to the predictions of child sleep. For both weekdays and weekends, the child's age group was an important predictor of children meeting sleep guidelines. The contribution of parental support behaviours to predictions of children meeting sleep guidelines varied with the type of support provided, and weekend versus weekday

Do parents’ support behaviours predict whether or not their children get sufficient sleep? A cross-sectional study

Directory of Open Access Journals (Sweden)

Evelyn Pyper

2017-05-01

Full Text Available Abstract Background Sleep is an essential component of healthy cognitive and physical development. Lack of sleep may put children at risk for a variety of mental and physical health outcomes, including overweight, obesity and related chronic diseases. Given that children’s sleep duration has decreased in recent decades, there is a need to understand the determinants of child sleep, including the role of parental support behaviours. This study aims to determine the relative contribution of different types of parental support behaviours for predicting the likelihood that children meet recently established Canadian sleep guidelines. Methods Data were collected using Computer Assisted Telephone Interviews (CATI of parents or guardians with at least one child under the age of 18 living in Ontario, Canada. To align with sleep guidelines, parents included in this analysis had at least one child between 5 and 17 years of age (n = 1622. Two multivariable logistic regression models were built to predict whether or not parents reported their child was meeting sleep guidelines – one for weekday sleep and another for sleep on weekends. Independent variables included parent and child age and gender, motivational and regulatory parental support behaviours, and socio-demographic characteristics. Results On weekdays, enforcing rules about child bedtime was a significant positive predictor of children meeting sleep guidelines (OR: 1.59; 95% CI: 1.03–2.44; while encouraging the child to go to bed at a specific time was a significant negative predictor of child meeting sleep guidelines (OR: 0.29; 95% CI: 0.13–0.65. On weekends, none of the parental support behaviours contributed significantly to the predictions of child sleep. For both weekdays and weekends, the child’s age group was an important predictor of children meeting sleep guidelines. Conclusions The contribution of parental support behaviours to predictions of children meeting sleep

A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

Directory of Open Access Journals (Sweden)

Hojung Nam

2014-09-01

Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

Weak lensing study of 16 DAFT/FADA clusters: Substructures and filaments

Science.gov (United States)

Martinet, Nicolas; Clowe, Douglas; Durret, Florence; Adami, Christophe; Acebrón, Ana; Hernandez-García, Lorena; Márquez, Isabel; Guennou, Loic; Sarron, Florian; Ulmer, Mel

2016-05-01

While our current cosmological model places galaxy clusters at the nodes of a filament network (the cosmic web), we still struggle to detect these filaments at high redshifts. We perform a weak lensing study for a sample of 16 massive, medium-high redshift (0.4 DAFT/FADA survey, which are imaged in at least three optical bands with Subaru/Suprime-Cam or CFHT/MegaCam. We estimate the cluster masses using an NFW fit to the shear profile measured in a KSB-like method, adding our contribution to the calibration of the observable-mass relation required for cluster abundance cosmological studies. We compute convergence maps and select structures within these maps, securing their detection with noise resampling techniques. Taking advantage of the large field of view of our data, we study cluster environment, adding information from galaxy density maps at the cluster redshift and from X-ray images when available. We find that clusters show a large variety of weak lensing maps at large scales and that they may all be embedded in filamentary structures at megaparsec scale. We classify these clusters in three categories according to the smoothness of their weak lensing contours and to the amount of substructures: relaxed (~7%), past mergers (~21.5%), and recent or present mergers (~71.5%). The fraction of clusters undergoing merging events observationally supports the hierarchical scenario of cluster growth, and implies that massive clusters are strongly evolving at the studied redshifts. Finally, we report the detection of unusually elongated structures in CLJ0152, MACSJ0454, MACSJ0717, A851, BMW1226, MACSJ1621, and MS1621. This study is based on observations obtained with MegaCam, a joint project of CFHT and CEA/IRFU, at the Canada-France-Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii

Predicting Career Adaptability through Self-Esteem and Social Support: A Research on Young Adults

Science.gov (United States)

Ataç, Lale Oral; Dirik, Deniz; Tetik, Hilmiye Türesin

2018-01-01

The purpose of this study is to investigate the relationship between career adaptability and self-esteem, and analyze the moderating role of social support in this relationship on a sample of 313 young adults. The results of the study confirm that career adaptability is significantly predicted by self-esteem. Moreover, findings suggest that (1)…

Towards Accurate Prediction of Unbalance Response, Oil Whirl and Oil Whip of Flexible Rotors Supported by Hydrodynamic Bearings

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Rob Eling

2016-09-01

Full Text Available Journal bearings are used to support rotors in a wide range of applications. In order to ensure reliable operation, accurate analyses of these rotor-bearing systems are crucial. Coupled analysis of the rotor and the journal bearing is essential in the case that the rotor is flexible. The accuracy of prediction of the model at hand depends on its comprehensiveness. In this study, we construct three bearing models of increasing modeling comprehensiveness and use these to predict the response of two different rotor-bearing systems. The main goal is to evaluate the correlation with measurement data as a function of modeling comprehensiveness: 1D versus 2D pressure prediction, distributed versus lumped thermal model, Newtonian versus non-Newtonian fluid description and non-mass-conservative versus mass-conservative cavitation description. We conclude that all three models predict the existence of critical speeds and whirl for both rotor-bearing systems. However, the two more comprehensive models in general show better correlation with measurement data in terms of frequency and amplitude. Furthermore, we conclude that a thermal network model comprising temperature predictions of the bearing surroundings is essential to obtain accurate predictions. The results of this study aid in developing accurate and computationally-efficient models of flexible rotors supported by plain journal bearings.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

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Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

2012-08-01

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.

Operational Precipitation prediction in Support of Real-Time Flash Flood Prediction and Reservoir Management

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Georgakakos, K. P.

2006-05-01

The presentation will outline the implementation and performance evaluation of a number of national and international projects pertaining to operational precipitation estimation and prediction in the context of hydrologic warning systems and reservoir management support. In all cases, uncertainty measures of the estimates and predictions are an integral part of the precipitation models. Outstanding research issues whose resolution is likely to lead to improvements in the operational environment are presented. The presentation draws from the experience of the Hydrologic Research Center (http://www.hrc-lab.org) prototype implementation projects at the Panama Canal, Central America, Northern California, and South-Central US. References: Carpenter, T.M, and K.P. Georgakakos, "Discretization Scale Dependencies of the Ensemble Flow Range versus Catchment Area Relationship in Distributed Hydrologic Modeling," Journal of Hydrology, 2006, in press. Carpenter, T.M., and K.P. Georgakakos, "Impacts of Parametric and Radar Rainfall Uncertainty on the Ensemble Streamflow Simulations of a Distributed Hydrologic Model," Journal of Hydrology, 298, 202-221, 2004. Georgakakos, K.P., Graham, N.E., Carpenter, T.M., Georgakakos, A.P., and H. Yao, "Integrating Climate- Hydrology Forecasts and Multi-Objective Reservoir Management in Northern California," EOS, 86(12), 122,127, 2005. Georgakakos, K.P., and J.A. Sperfslage, "Operational Rainfall and Flow Forecasting for the Panama Canal Watershed," in The Rio Chagres: A Multidisciplinary Profile of a Tropical Watershed, R.S. Harmon, ed., Kluwer Academic Publishers, The Netherlands, Chapter 16, 323-334, 2005. Georgakakos, K. P., "Analytical results for operational flash flood guidance," Journal of Hydrology, doi:10.1016/j.jhydrol.2005.05.009, 2005.

Evaluation and comparison of the marginal adaptation of two different substructure materials.

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Karaman, Tahir; Ulku, Sabiha Zelal; Zengingul, Ali Ihsan; Guven, Sedat; Eratilla, Veysel; Sumer, Ebru

2015-06-01

In this study, we aimed to evaluate the amount of marginal gap with two different substructure materials using identical margin preparations. Twenty stainless steel models with a chamfer were prepared with a CNC device. Marginal gap measurements of the galvano copings on these stainless steel models and Co-Cr copings obtained by a laser-sintering method were made with a stereomicroscope device before and after the cementation process and surface properties were evaluated by scanning electron microscopy (SEM). A dependent t-test was used to compare the mean of the two groups for normally distributed data, and two-way variance analysis was used for more than two data sets. Pearson's correlation analysis was also performed to assess relationships between variables. According to the results obtained, the marginal gap in the galvano copings before cementation was measured as, on average, 24.47 ± 5.82 µm before and 35.11 ± 6.52 µm after cementation; in the laser-sintered Co-Cr structure, it was, on average, 60.45 ± 8.87 µm before and 69.33 ± 9.03 µm after cementation. A highly significant difference (Pcementation were within the clinically acceptable level. The smallest marginal gaps occurred with the use of galvano copings.

Association of systemic lupus erythematosus clinical features with European population genetic substructure.

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Elisa Alonso-Perez

Full Text Available Systemic Lupus Erythematosus (SLE is an autoimmune disease with a very varied spectrum of clinical manifestations that could be partly determined by genetic factors. We aimed to determine the relationship between prevalence of 11 clinical features and age of disease onset with European population genetic substructure. Data from 1413 patients of European ancestry recruited in nine countries was tested for association with genotypes of top ancestry informative markers. This analysis was done with logistic regression between phenotypes and genotypes or principal components extracted from them. We used a genetic additive model and adjusted for gender and disease duration. Three clinical features showed association with ancestry informative markers: autoantibody production defined as immunologic disorder (P = 6.8×10(-4, oral ulcers (P = 6.9×10(-4 and photosensitivity (P = 0.002. Immunologic disorder was associated with genotypes more common in Southern European ancestries, whereas the opposite trend was observed for photosensitivity. Oral ulcers were specifically more common in patients of Spanish and Portuguese self-reported ancestry. These results should be taken into account in future research and suggest new hypotheses and possible underlying mechanisms to be investigated. A first hypothesis linking photosensitivity with variation in skin pigmentation is suggested.

On the sound insulation of acoustic metasurface using a sub-structuring approach

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Yu, Xiang; Lu, Zhenbo; Cheng, Li; Cui, Fangsen

2017-08-01

The feasibility of using an acoustic metasurface (AMS) with acoustic stop-band property to realize sound insulation with ventilation function is investigated. An efficient numerical approach is proposed to evaluate its sound insulation performance. The AMS is excited by a reverberant sound source and the standardized sound reduction index (SRI) is numerically investigated. To facilitate the modeling, the coupling between the AMS and the adjacent acoustic fields is formulated using a sub-structuring approach. A modal based formulation is applied to both the source and receiving room, enabling an efficient calculation in the frequency range from 125 Hz to 2000 Hz. The sound pressures and the velocities at the interface are matched by using a transfer function relation based on ;patches;. For illustration purposes, numerical examples are investigated using the proposed approach. The unit cell constituting the AMS is constructed in the shape of a thin acoustic chamber with tailored inner structures, whose stop-band property is numerically analyzed and experimentally demonstrated. The AMS is shown to provide effective sound insulation of over 30 dB in the stop-band frequencies from 600 to 1600 Hz. It is also shown that the proposed approach has the potential to be applied to a broad range of AMS studies and optimization problems.

Association of Systemic Lupus Erythematosus Clinical Features with European Population Genetic Substructure

Science.gov (United States)

Calaza, Manuel; Witte, Torsten; Papasteriades, Chryssa; Marchini, Maurizio; Migliaresi, Sergio; Kovacs, Attila; Ordi-Ros, Josep; Bijl, Marc; Santos, Maria Jose; Ruzickova, Sarka; Pullmann, Rudolf; Carreira, Patricia; Skopouli, Fotini N.; D'Alfonso, Sandra; Sebastiani, Gian Domenico; Suarez, Ana; Blanco, Francisco J.; Gomez-Reino, Juan J.; Gonzalez, Antonio

2011-01-01

Systemic Lupus Erythematosus (SLE) is an autoimmune disease with a very varied spectrum of clinical manifestations that could be partly determined by genetic factors. We aimed to determine the relationship between prevalence of 11 clinical features and age of disease onset with European population genetic substructure. Data from 1413 patients of European ancestry recruited in nine countries was tested for association with genotypes of top ancestry informative markers. This analysis was done with logistic regression between phenotypes and genotypes or principal components extracted from them. We used a genetic additive model and adjusted for gender and disease duration. Three clinical features showed association with ancestry informative markers: autoantibody production defined as immunologic disorder (P = 6.8×10−4), oral ulcers (P = 6.9×10−4) and photosensitivity (P = 0.002). Immunologic disorder was associated with genotypes more common in Southern European ancestries, whereas the opposite trend was observed for photosensitivity. Oral ulcers were specifically more common in patients of Spanish and Portuguese self-reported ancestry. These results should be taken into account in future research and suggest new hypotheses and possible underlying mechanisms to be investigated. A first hypothesis linking photosensitivity with variation in skin pigmentation is suggested. PMID:22194982

Short-term traffic flow prediction model using particle swarm optimization–based combined kernel function-least squares support vector machine combined with chaos theory

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Qiang Shang

2016-08-01

Full Text Available Short-term traffic flow prediction is an important part of intelligent transportation systems research and applications. For further improving the accuracy of short-time traffic flow prediction, a novel hybrid prediction model (multivariate phase space reconstruction–combined kernel function-least squares support vector machine based on multivariate phase space reconstruction and combined kernel function-least squares support vector machine is proposed. The C-C method is used to determine the optimal time delay and the optimal embedding dimension of traffic variables’ (flow, speed, and occupancy time series for phase space reconstruction. The G-P method is selected to calculate the correlation dimension of attractor which is an important index for judging chaotic characteristics of the traffic variables’ series. The optimal input form of combined kernel function-least squares support vector machine model is determined by multivariate phase space reconstruction, and the model’s parameters are optimized by particle swarm optimization algorithm. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. The experimental results suggest that the new proposed model yields better predictions compared with similar models (combined kernel function-least squares support vector machine, multivariate phase space reconstruction–generalized kernel function-least squares support vector machine, and phase space reconstruction–combined kernel function-least squares support vector machine, which indicates that the new proposed model exhibits stronger prediction ability and robustness.

Computational Prediction of Blood-Brain Barrier Permeability Using Decision Tree Induction

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Jörg Huwyler

2012-08-01

Full Text Available Predicting blood-brain barrier (BBB permeability is essential to drug development, as a molecule cannot exhibit pharmacological activity within the brain parenchyma without first transiting this barrier. Understanding the process of permeation, however, is complicated by a combination of both limited passive diffusion and active transport. Our aim here was to establish predictive models for BBB drug permeation that include both active and passive transport. A database of 153 compounds was compiled using in vivo surface permeability product (logPS values in rats as a quantitative parameter for BBB permeability. The open source Chemical Development Kit (CDK was used to calculate physico-chemical properties and descriptors. Predictive computational models were implemented by machine learning paradigms (decision tree induction on both descriptor sets. Models with a corrected classification rate (CCR of 90% were established. Mechanistic insight into BBB transport was provided by an Ant Colony Optimization (ACO-based binary classifier analysis to identify the most predictive chemical substructures. Decision trees revealed descriptors of lipophilicity (aLogP and charge (polar surface area, which were also previously described in models of passive diffusion. However, measures of molecular geometry and connectivity were found to be related to an active drug transport component.

Maternal Support of Children's Early Numerical Concept Learning Predicts Preschool and First-Grade Math Achievement.

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Casey, Beth M; Lombardi, Caitlin M; Thomson, Dana; Nguyen, Hoa Nha; Paz, Melissa; Theriault, Cote A; Dearing, Eric

2018-01-01

The primary goal in this study was to examine maternal support of numerical concepts at 36 months as predictors of math achievement at 4½ and 6-7 years. Observational measures of mother-child interactions (n = 140) were used to examine type of support for numerical concepts. Maternal support that involved labeling the quantities of sets of objects was predictive of later child math achievement. This association was significant for preschool (d = .45) and first-grade math (d = .49), controlling for other forms of numerical support (identifying numerals, one-to-one counting) as well as potential confounding factors. The importance of maternal support of labeling set sizes at 36 months is discussed as a precursor to children's eventual understanding of the cardinal principle. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

Predicting metabolic syndrome using decision tree and support vector machine methods

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Farzaneh Karimi-Alavijeh

2016-06-01

Full Text Available BACKGROUND: Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome. METHODS: This study aims to employ decision tree and support vector machine (SVM to predict the 7-year incidence of metabolic syndrome. This research is a practical one in which data from 2107 participants of Isfahan Cohort Study has been utilized. The subjects without metabolic syndrome according to the ATPIII criteria were selected. The features that have been used in this data set include: gender, age, weight, body mass index, waist circumference, waist-to-hip ratio, hip circumference, physical activity, smoking, hypertension, antihypertensive medication use, systolic blood pressure (BP, diastolic BP, fasting blood sugar, 2-hour blood glucose, triglycerides (TGs, total cholesterol, low-density lipoprotein, high density lipoprotein-cholesterol, mean corpuscular volume, and mean corpuscular hemoglobin. Metabolic syndrome was diagnosed based on ATPIII criteria and two methods of decision tree and SVM were selected to predict the metabolic syndrome. The criteria of sensitivity, specificity and accuracy were used for validation. RESULTS: SVM and decision tree methods were examined according to the criteria of sensitivity, specificity and accuracy. Sensitivity, specificity and accuracy were 0.774 (0.758, 0.74 (0.72 and 0.757 (0.739 in SVM (decision tree method. CONCLUSION: The results show that SVM method sensitivity, specificity and accuracy is more efficient than decision tree. The results of decision tree method show that the TG is the most

Predicting metabolic syndrome using decision tree and support vector machine methods.

Science.gov (United States)

Karimi-Alavijeh, Farzaneh; Jalili, Saeed; Sadeghi, Masoumeh

2016-05-01

Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome. This study aims to employ decision tree and support vector machine (SVM) to predict the 7-year incidence of metabolic syndrome. This research is a practical one in which data from 2107 participants of Isfahan Cohort Study has been utilized. The subjects without metabolic syndrome according to the ATPIII criteria were selected. The features that have been used in this data set include: gender, age, weight, body mass index, waist circumference, waist-to-hip ratio, hip circumference, physical activity, smoking, hypertension, antihypertensive medication use, systolic blood pressure (BP), diastolic BP, fasting blood sugar, 2-hour blood glucose, triglycerides (TGs), total cholesterol, low-density lipoprotein, high density lipoprotein-cholesterol, mean corpuscular volume, and mean corpuscular hemoglobin. Metabolic syndrome was diagnosed based on ATPIII criteria and two methods of decision tree and SVM were selected to predict the metabolic syndrome. The criteria of sensitivity, specificity and accuracy were used for validation. SVM and decision tree methods were examined according to the criteria of sensitivity, specificity and accuracy. Sensitivity, specificity and accuracy were 0.774 (0.758), 0.74 (0.72) and 0.757 (0.739) in SVM (decision tree) method. The results show that SVM method sensitivity, specificity and accuracy is more efficient than decision tree. The results of decision tree method show that the TG is the most important feature in predicting metabolic syndrome. According

Jet substructure using semi-inclusive jet functions in SCET

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Kang, Zhong-Bo [Theoretical Division, Los Alamos National Laboratory,Los Alamos, NM 87545 (United States); Department of Physics and Astronomy, University of California,Los Angeles, CA 90095 (United States); Ringer, Felix; Vitev, Ivan [Theoretical Division, Los Alamos National Laboratory,Los Alamos, NM 87545 (United States)

2016-11-25

We propose a new method to evaluate jet substructure observables in inclusive jet measurements, based upon semi-inclusive jet functions in the framework of Soft Collinear Effective Theory (SCET). As a first example, we consider the jet fragmentation function, where a hadron h is identified inside a fully reconstructed jet. We introduce a new semi-inclusive fragmenting jet function G{sub i}{sup h}(z=ω{sub J}/ω,z{sub h}=ω{sub h}/ω{sub J},ω{sub J},R,μ), which depends on the jet radius R and the large light-cone momenta of the parton ‘i’ initiating the jet (ω), the jet (ω{sub J}), and the hadron h (ω{sub h}). The jet fragmentation function can then be expressed as a semi-inclusive observable, in the spirit of actual experimental measurements, rather than as an exclusive one. We demonstrate the consistency of the effective field theory treatment and standard perturbative QCD calculations of this observable at next-to-leading order (NLO). The renormalization group (RG) equation for the semi-inclusive fragmenting jet function G{sub i}{sup h}(z,z{sub h},ω{sub J},R,μ) are also derived and shown to follow exactly the usual timelike DGLAP evolution equations for fragmentation functions. The newly obtained RG equations can be used to perform the resummation of single logarithms of the jet radius parameter R up to next-to-leading logarithmic (NLL{sub R}) accuracy. In combination with the fixed NLO calculation, we obtain NLO+NLL{sub R} results for the hadron distribution inside the jet. We present numerical results for pp→(jet h)X in the new framework, and find excellent agreement with existing LHC experimental data.

Social support for healthy behaviors: Scale psychometrics and prediction of weight loss among women in a behavioral program

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Kiernan, Michaela; Moore, Susan D.; Schoffman, Danielle E.; Lee, Katherine; King, Abby C.; Taylor, C. Barr; Kiernan, Nancy Ellen; Perri, Michael G.

2015-01-01

Social support could be a powerful weight-loss treatment moderator or mediator but is rarely assessed. We assessed the psychometric properties, initial levels, and predictive validity of a measure of perceived social support and sabotage from friends and family for healthy eating and physical activity (eight subscales). Overweight/obese women randomized to one of two 6-month, group-based behavioral weight-loss programs (N=267; mean BMI 32.1±3.5; 66.3% White) completed subscales at baseline, and weight loss was assessed at 6 months. Internal consistency, discriminant validity, and content validity were excellent for support subscales and adequate for sabotage subscales; qualitative responses revealed novel deliberate instances not reflected in current sabotage items. Most women (>75%) “never” or “rarely” experienced support from friends or family. Using non-parametric classification methods, we identified two subscales—support from friends for healthy eating and support from family for physical activity—that predicted three clinically meaningful subgroups who ranged in likelihood of losing ≥5% of initial weight at 6 months. Women who “never” experienced family support were least likely to lose weight (45.7% lost weight) whereas women who experienced both frequent friend and family support were more likely to lose weight (71.6% lost weight). Paradoxically, women who “never” experienced friend support were most likely to lose weight (80.0% lost weight), perhaps because the group-based programs provided support lacking from friendships. Psychometrics for support subscales were excellent; initial support was rare; and the differential roles of friend versus family support could inform future targeted weight-loss interventions to subgroups at risk. PMID:21996661

Constructing and predicting solitary pattern solutions for nonlinear time-fractional dispersive partial differential equations

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Arqub, Omar Abu; El-Ajou, Ahmad; Momani, Shaher

2015-07-01

Building fractional mathematical models for specific phenomena and developing numerical or analytical solutions for these fractional mathematical models are crucial issues in mathematics, physics, and engineering. In this work, a new analytical technique for constructing and predicting solitary pattern solutions of time-fractional dispersive partial differential equations is proposed based on the generalized Taylor series formula and residual error function. The new approach provides solutions in the form of a rapidly convergent series with easily computable components using symbolic computation software. For method evaluation and validation, the proposed technique was applied to three different models and compared with some of the well-known methods. The resultant simulations clearly demonstrate the superiority and potentiality of the proposed technique in terms of the quality performance and accuracy of substructure preservation in the construct, as well as the prediction of solitary pattern solutions for time-fractional dispersive partial differential equations.

BacHbpred: Support Vector Machine Methods for the Prediction of Bacterial Hemoglobin-Like Proteins

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MuthuKrishnan Selvaraj

2016-01-01

Full Text Available The recent upsurge in microbial genome data has revealed that hemoglobin-like (HbL proteins may be widely distributed among bacteria and that some organisms may carry more than one HbL encoding gene. However, the discovery of HbL proteins has been limited to a small number of bacteria only. This study describes the prediction of HbL proteins and their domain classification using a machine learning approach. Support vector machine (SVM models were developed for predicting HbL proteins based upon amino acid composition (AC, dipeptide composition (DC, hybrid method (AC + DC, and position specific scoring matrix (PSSM. In addition, we introduce for the first time a new prediction method based on max to min amino acid residue (MM profiles. The average accuracy, standard deviation (SD, false positive rate (FPR, confusion matrix, and receiver operating characteristic (ROC were analyzed. We also compared the performance of our proposed models in homology detection databases. The performance of the different approaches was estimated using fivefold cross-validation techniques. Prediction accuracy was further investigated through confusion matrix and ROC curve analysis. All experimental results indicate that the proposed BacHbpred can be a perspective predictor for determination of HbL related proteins. BacHbpred, a web tool, has been developed for HbL prediction.

Highly Tissue Substructure-Specific Effects of Human Papilloma Virus in Mucosa of HIV-Infected Patients Revealed by Laser-Dissection Microscopy-Assisted Gene Expression Profiling

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Baumgarth, Nicole; Szubin, Richard; Dolganov, Greg M.; Watnik, Mitchell R.; Greenspan, Deborah; Da Costa, Maria; Palefsky, Joel M.; Jordan, Richard; Roederer, Mario; Greenspan, John S.

2004-01-01

Human papilloma virus (HPV) causes focal infections of epithelial layers in skin and mucosa. HIV-infected patients on highly active antiretroviral therapy (HAART) appear to be at increased risk of developing HPV-induced oral warts. To identify the mechanisms that allow long-term infection of oral epithelial cells in these patients, we used a combination of laser-dissection microscopy (LDM) and highly sensitive and quantitative, non-biased, two-step multiplex real-time RT-PCR to study pathogen-induced alterations of specific tissue subcompartments. Expression of 166 genes was compared in three distinct epithelial and subepithelial compartments isolated from biopsies of normal mucosa from HIV-infected and non-infected patients and of HPV32-induced oral warts from HIV-infected patients. In contrast to the underlying HIV infection and/or HAART, which did not significantly elaborate tissue substructure-specific effects, changes in oral warts were strongly tissue substructure-specific. HPV 32 seems to establish infection by selectively enhancing epithelial cell growth and differentiation in the stratum spinosum and to evade the immune system by actively suppressing inflammatory responses in adjacent underlying tissues. With this highly sensitive and quantitative method tissue-specific expression of hundreds of genes can be studied simultaneously in a few cells. Because of its large dynamic measurement range it could also become a method of choice to confirm and better quantify results obtained by microarray analysis. PMID:15331396

Home Away Home: Better Understanding of the Role of Social Support in Predicting Cross-Cultural Adjustment among International Students

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Baba, Yoko; Hosoda, Megumi

2014-01-01

Numerous studies have examined international students' adjustment problems, yet, these studies have not explored the mechanisms through which social support operates in the context of stressful events in predicting cross-cultural adjustment among international students. Using Barrera's (1988) models of social support, the present study…

Predicting nonstationary flood frequencies: Evidence supports an updated stationarity thesis in the United States

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Luke, Adam; Vrugt, Jasper A.; AghaKouchak, Amir; Matthew, Richard; Sanders, Brett F.

2017-07-01

Nonstationary extreme value analysis (NEVA) can improve the statistical representation of observed flood peak distributions compared to stationary (ST) analysis, but management of flood risk relies on predictions of out-of-sample distributions for which NEVA has not been comprehensively evaluated. In this study, we apply split-sample testing to 1250 annual maximum discharge records in the United States and compare the predictive capabilities of NEVA relative to ST extreme value analysis using a log-Pearson Type III (LPIII) distribution. The parameters of the LPIII distribution in the ST and nonstationary (NS) models are estimated from the first half of each record using Bayesian inference. The second half of each record is reserved to evaluate the predictions under the ST and NS models. The NS model is applied for prediction by (1) extrapolating the trend of the NS model parameters throughout the evaluation period and (2) using the NS model parameter values at the end of the fitting period to predict with an updated ST model (uST). Our analysis shows that the ST predictions are preferred, overall. NS model parameter extrapolation is rarely preferred. However, if fitting period discharges are influenced by physical changes in the watershed, for example from anthropogenic activity, the uST model is strongly preferred relative to ST and NS predictions. The uST model is therefore recommended for evaluation of current flood risk in watersheds that have undergone physical changes. Supporting information includes a MATLAB® program that estimates the (ST/NS/uST) LPIII parameters from annual peak discharge data through Bayesian inference.

Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules.

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Konda Leela Sarath Kumar

Full Text Available Skin sensitization forms a major toxicological endpoint for dermatology and cosmetic products. Recent ban on animal testing for cosmetics demands for alternative methods. We developed an integrated computational solution (SkinSense that offers a robust solution and addresses the limitations of existing computational tools i.e. high false positive rate and/or limited coverage.The key components of our solution include: QSAR models selected from a combinatorial set, similarity information and literature-derived sub-structure patterns of known skin protein reactive groups. Its prediction performance on a challenge set of molecules showed accuracy = 75.32%, CCR = 74.36%, sensitivity = 70.00% and specificity = 78.72%, which is better than several existing tools including VEGA (accuracy = 45.00% and CCR = 54.17% with 'High' reliability scoring, DEREK (accuracy = 72.73% and CCR = 71.44% and TOPKAT (accuracy = 60.00% and CCR = 61.67%. Although, TIMES-SS showed higher predictive power (accuracy = 90.00% and CCR = 92.86%, the coverage was very low (only 10 out of 77 molecules were predicted reliably.Owing to improved prediction performance and coverage, our solution can serve as a useful expert system towards Integrated Approaches to Testing and Assessment for skin sensitization. It would be invaluable to cosmetic/ dermatology industry for pre-screening their molecules, and reducing time, cost and animal testing.

Searches for heavy resonances in all-jet final states with top quarks using jet substructure techniques with the CMS experiment

Energy Technology Data Exchange (ETDEWEB)

Usai, Emanuele

2017-12-15

While the Standard Model is very successful in describing subnuclear phenomena, it is not a complete theory of particle physics. Several new theories have been developed to address its issues. Many extensions of the Standard Model predict the existence of high-mass resonances. In some cases these resonances have an enhanced coupling to third generation quarks or to a hypothetical new generation of heavy non-chiral quarks. This thesis describes two searches for new phenomena compatible with these theories, in particular a search is presented for resonant top-antitop production, and the first search for heavy resonances decaying to a top quark and a heavy top quark partner T is shown. The searches target the all-jets decay channels and use data collected by the CMS Experiment at the CERN LHC between 2012 and 2015 at a center-of-mass energy of 8 TeV and 13 TeV. Due to the high mass of the resonances considered, the final state particles have a high Lorentz-boost. To reconstruct the hadronic decay of the top quarks and W bosons, jet substructure techniques such as top quark and W boson tagging algorithms, and boosted b jet identification are employed. These algorithms are studied with a particular focus on their validation and performance assessment. No signs of physics beyond the Standard Model are observed, but stringent limits are placed on the production of heavy resonances decaying to top-antitop quark pairs or a top quark and a heavy T quark.

Searches for heavy resonances in all-jet final states with top quarks using jet substructure techniques with the CMS experiment

International Nuclear Information System (INIS)

Usai, Emanuele

2017-12-01

While the Standard Model is very successful in describing subnuclear phenomena, it is not a complete theory of particle physics. Several new theories have been developed to address its issues. Many extensions of the Standard Model predict the existence of high-mass resonances. In some cases these resonances have an enhanced coupling to third generation quarks or to a hypothetical new generation of heavy non-chiral quarks. This thesis describes two searches for new phenomena compatible with these theories, in particular a search is presented for resonant top-antitop production, and the first search for heavy resonances decaying to a top quark and a heavy top quark partner T is shown. The searches target the all-jets decay channels and use data collected by the CMS Experiment at the CERN LHC between 2012 and 2015 at a center-of-mass energy of 8 TeV and 13 TeV. Due to the high mass of the resonances considered, the final state particles have a high Lorentz-boost. To reconstruct the hadronic decay of the top quarks and W bosons, jet substructure techniques such as top quark and W boson tagging algorithms, and boosted b jet identification are employed. These algorithms are studied with a particular focus on their validation and performance assessment. No signs of physics beyond the Standard Model are observed, but stringent limits are placed on the production of heavy resonances decaying to top-antitop quark pairs or a top quark and a heavy T quark.

The Roles of Perceived Social Support, Coping, and Loneliness in Predicting Internet Addiction in Adolescents

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Çevik, Gülsen Büyüksahin; Yildiz, Mehmet Ali

2017-01-01

The current research aims to examine the roles of perceived social support, coping, and loneliness when predicting the Internet addiction in adolescents. The research participants included 300 high school students, with an average age of 16.49 and SD = 1.27, attending schools in a city in Southeastern Anatolian Region during 2015-2016 academic…

Predicting quality of life and self-management from dyadic support and overprotection after myocardial infarction.

Science.gov (United States)

Joekes, Katherine; Maes, Stan; Warrens, Matthijs

2007-11-01

Using a self-regulatory framework, this study aims to identify how couples perceive a partner's support style after myocardial infarction (MI), and whether this predicts the patient's health-related quality of life (HR-QoL) and self-management (S-M) 9 months later. This longitudinal dyadic study includes 73 couples (86% of patients were men), recruited from two cardiac rehabilitation programmes in the Netherlands. Mean age of patients was 54.8 (SD=9.6) and of partners 52.5 (SD=9.8). Participants were interviewed and completed questionnaires at baseline (T1). Repeat questionnaires were returned by 69 and 67 couples after 3 (T2) and 9 months (T3), respectively. Support by partners is conceptualized in this study as 'active engagement' (AE), which involves the extent to which a partner engages the patient in conversations which focus on emotional support and problem solving. Levels of AE do not change over time, nor do they differ between members of the dyad. Levels of overprotection (OP) diminish with time, whilst patients consistently perceive more OP than partners report providing. Patients' experience of goal hindrance (at T3) due to the MI is associated with a decreased HR-QoL at T3 (controlling for baseline measures). The perception of having a supportive (AE) partner at T1 contributes to enhanced patient HR-QoL at each subsequent time point, although not to physical functioning. Perceiving a partner as overprotective (at T1) predicts worsened physical functioning in patients (at T3). Improvements in S-M at T3 (controlling for baseline measures) are reported by patients whose partner displays active engagement at T1. Cardiac rehabilitation should aim to redress the experience of goal disturbance and advise partners on how to provide support.

[Predictive values of different critical scoring systems for mortality in patients with severe acute respiratory failure supported by extracorporeal membrane oxygenation].

Science.gov (United States)

Wang, R; Sun, B; Li, X Y; He, H Y; Tang, X; Zhan, Q Y; Tong, Z H

2016-09-01

To investigate the predictive values of different critical scoring systems for mortality in patients with severe acute respiratory failure (ARF) supported by venovenous extracorporeal membrane oxygenation (VV-ECMO). Forty-two patients with severe ARF supported by VV-ECMO were enrolled from November 2009 to July 2015.There were 25 males and 17 females. The mean age was (44±18) years (rang 18-69 years). Acute Physiology and Chronic Health Evaluation (APACHE) Ⅱ, Ⅲ, Ⅳ, Simplified Acute Physiology Score Ⅱ (SAPS) Ⅱ, Sequential Organ Failure Assessment (SOFA), ECMO net, PRedicting dEath for SEvere ARDS on VVECMO (PRESERVE), and Respiratory ECMO Survival Prediction (RESP) scores were collected within 6 hours before VV-ECMO support. The patients were divided into the survivors group (n=17) and the nonsurvivors group (n=25) by survival at 180 d after receiving VV-ECMO. The patient clinical characteristics and aforementioned scoring systems were compared between groups. Scoring systems for predicting prognosis were assessed using the area under the receiver-operating characteristic (ROC) curve. The Kaplan-Meier method was used to draw the surviving curve, and the survival of the patients was analyzed by the Log-rank test. The risk factors were assessed for prognosis by multiple logistic regression analysis. (1) Positive end expiratory pressure (PEEP) 6 hours prior to VV-ECMO support in the survivors group [(9.7±5.0)cmH2O, (1 cmH2O=0.098 kPa)] was lower than that in the nonsurvivors group [(13.2±5.4)cmH2O, t=-2.134, P=0.039]. VV-ECMO combination with continuous renal replacement therapy(CRRT) in the nonsurvivors group (32%) was used more than in the survivors group (6%, χ(2)=4.100, P=0.043). Duration of VV-ECMO support in the nonsurvivors group [(15±13) d] was longer than that in the survivors group [(12±11)d, t=-2.123, P=0.041]. APACHE Ⅱ, APACHE Ⅲ, APACHE Ⅳ, ECMO net, PRESERVE, and RESP scores in the survivors group were superior to the nonsurvivors

Quantitative prediction of drug side effects based on drug-related features.

Science.gov (United States)

Niu, Yanqing; Zhang, Wen

2017-09-01

Unexpected side effects of drugs are great concern in the drug development, and the identification of side effects is an important task. Recently, machine learning methods are proposed to predict the presence or absence of interested side effects for drugs, but it is difficult to make the accurate prediction for all of them. In this paper, we transform side effect profiles of drugs as their quantitative scores, by summing up their side effects with weights. The quantitative scores may measure the dangers of drugs, and thus help to compare the risk of different drugs. Here, we attempt to predict quantitative scores of drugs, namely the quantitative prediction. Specifically, we explore a variety of drug-related features and evaluate their discriminative powers for the quantitative prediction. Then, we consider several feature combination strategies (direct combination, average scoring ensemble combination) to integrate three informative features: chemical substructures, targets, and treatment indications. Finally, the average scoring ensemble model which produces the better performances is used as the final quantitative prediction model. Since weights for side effects are empirical values, we randomly generate different weights in the simulation experiments. The experimental results show that the quantitative method is robust to different weights, and produces satisfying results. Although other state-of-the-art methods cannot make the quantitative prediction directly, the prediction results can be transformed as the quantitative scores. By indirect comparison, the proposed method produces much better results than benchmark methods in the quantitative prediction. In conclusion, the proposed method is promising for the quantitative prediction of side effects, which may work cooperatively with existing state-of-the-art methods to reveal dangers of drugs.

Prediction of biochar yield from cattle manure pyrolysis via least squares support vector machine intelligent approach.

Science.gov (United States)

Cao, Hongliang; Xin, Ya; Yuan, Qiaoxia

2016-02-01

To predict conveniently the biochar yield from cattle manure pyrolysis, intelligent modeling approach was introduced in this research. A traditional artificial neural networks (ANN) model and a novel least squares support vector machine (LS-SVM) model were developed. For the identification and prediction evaluation of the models, a data set with 33 experimental data was used, which were obtained using a laboratory-scale fixed bed reaction system. The results demonstrated that the intelligent modeling approach is greatly convenient and effective for the prediction of the biochar yield. In particular, the novel LS-SVM model has a more satisfying predicting performance and its robustness is better than the traditional ANN model. The introduction and application of the LS-SVM modeling method gives a successful example, which is a good reference for the modeling study of cattle manure pyrolysis process, even other similar processes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of Polymorphisms in the Merozoite Surface Protein-3a Gene and Two Microsatellite Loci in Sri Lankan Plasmodium vivax: Evidence of Population Substructure in Sri Lanka

DEFF Research Database (Denmark)

Schousboe, Mette L; Rajakaruna, Rupika S; Amerasinghe, Priyanie H

2011-01-01

Abstract. The geographical distribution of genetic variation in Plasmodium vivax samples (N = 386) from nine districts across Sri Lanka is described using three markers; the P. vivax merozoite surface protein-3a (Pvmsp-3a) gene, and the two microsatellites m1501 and m3502. At Pvmsp-3a, 11 alleles....... The results show evidence of high genetic diversity and possible population substructure of P. vivax populations in Sri Lanka....

Prediction of Quality of Life of Non–Insulin-Dependent Diabetic Patients Based on Perceived Social Support

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Hossein Shareh

2012-04-01

Full Text Available Background: The objective of this study was to predic quality of life based on perceived social support components in non–insulin-dependent diabetic patients.Materials and Method: Fifty patients with non–insulin-dependent diabetes mellitus from Al-Zahra diabetic center in Shiraz participated in a cross-sectional study via survey instrument. All subjects completed multidimensional scale of perceived social support (MSPSS and world health organization quality of life- brief (WHOQOL-BREF questionnaires. Results: On the basis of stepwise multiple regression analysis friends and family dimensions of perceived social support were the best predictors of the quality of life and its dimensions (p<0.01.Conclusion: Friends and family dimensions of perceived social support have significant contributions in predicting quality of life of patients with non–insulin-dependent diabetes mellitus.

Probabilistic source term predictions for use with decision support systems

International Nuclear Information System (INIS)

Grindon, E.; Kinniburgh, C.G.

2003-01-01

Full text: Decision Support Systems for use in off-site emergency management, following an incident at a Nuclear Power Plant (NPP) within Europe, are becoming accepted as a useful and appropriate tool to aid decision makers. An area which is not so well developed is the 'upstream' prediction of the source term released into the environment. Rapid prediction of this source term is crucial to the appropriate early management of a nuclear emergency. The initial source term prediction would today be typically based on simple tabulations taking little, or no, account of plant status. It is the interface between the inward looking plant control room team and the outward looking off-site emergency management team that needs to be addressed. This is not an easy proposition as these two distinct disciplines have little common basis from which to communicate their immediate findings and concerns. Within the Euratom Fifth Framework Programme (FP5), complementary approaches are being developed to the pre-release stage; each based on software tools to help bridge this gap. Traditionally source terms (or releases into the environment) provided for use with Decision Support Systems are estimated on a deterministic basis. These approaches use a single, deterministic assumption about plant status. The associated source term represents the 'best estimate' based an available information. No information is provided an the potential for uncertainty in the source term estimate. Using probabilistic methods the outcome is typically a number of possible plant states each with an associated source term and probability. These represent both the best estimate and the spread of the likely source term. However, this is a novel approach and the usefulness of such source term prediction tools is yet to be tested on a wide scale. The benefits of probabilistic source term estimation are presented here; using, as an example, the SPRINT tool developed within the FP5 STERPS project. System for the

Transport and stability analyses supporting disruption prediction in high beta KSTAR plasmas

Science.gov (United States)

Ahn, J.-H.; Sabbagh, S. A.; Park, Y. S.; Berkery, J. W.; Jiang, Y.; Riquezes, J.; Lee, H. H.; Terzolo, L.; Scott, S. D.; Wang, Z.; Glasser, A. H.

2017-10-01

KSTAR plasmas have reached high stability parameters in dedicated experiments, with normalized beta βN exceeding 4.3 at relatively low plasma internal inductance li (βN/li>6). Transport and stability analyses have begun on these plasmas to best understand a disruption-free path toward the design target of βN = 5 while aiming to maximize the non-inductive fraction of these plasmas. Initial analysis using the TRANSP code indicates that the non-inductive current fraction in these plasmas has exceeded 50 percent. The advent of KSTAR kinetic equilibrium reconstructions now allows more accurate computation of the MHD stability of these plasmas. Attention is placed on code validation of mode stability using the PEST-3 and resistive DCON codes. Initial evaluation of these analyses for disruption prediction is made using the disruption event characterization and forecasting (DECAF) code. The present global mode kinetic stability model in DECAF developed for low aspect ratio plasmas is evaluated to determine modifications required for successful disruption prediction of KSTAR plasmas. Work supported by U.S. DoE under contract DE-SC0016614.

Predicting hourly cooling load in the building: A comparison of support vector machine and different artificial neural networks

International Nuclear Information System (INIS)

Li Qiong; Meng Qinglin; Cai Jiejin; Yoshino, Hiroshi; Mochida, Akashi

2009-01-01

This study presents four modeling techniques for the prediction of hourly cooling load in the building. In addition to the traditional back propagation neural network (BPNN), the radial basis function neural network (RBFNN), general regression neural network (GRNN) and support vector machine (SVM) are considered. All the prediction models have been applied to an office building in Guangzhou, China. Evaluation of the prediction accuracy of the four models is based on the root mean square error (RMSE) and mean relative error (MRE). The simulation results demonstrate that the four discussed models can be effective for building cooling load prediction. The SVM and GRNN methods can achieve better accuracy and generalization than the BPNN and RBFNN methods

Development of a Decision Support System to Predict Physicians' Rehabilitation Protocols for Patients with Knee Osteoarthritis

Science.gov (United States)

Hawamdeh, Ziad M.; Alshraideh, Mohammad A.; Al-Ajlouni, Jihad M.; Salah, Imad K.; Holm, Margo B.; Otom, Ali H.

2012-01-01

To design a medical decision support system (MDSS) that would accurately predict the rehabilitation protocols prescribed by the physicians for patients with knee osteoarthritis (OA) using only their demographic and clinical characteristics. The demographic and clinical variables for 170 patients receiving one of three treatment protocols for knee…

Opportune maintenance and predictive maintenance decision support

OpenAIRE

Thomas , Edouard; Levrat , Eric; Iung , Benoît; Cocheteux , Pierre

2009-01-01

International audience; Conventional maintenance strategies on a single component are being phased out in favour of more predictive maintenance actions. These new kinds of actions are performed in order to control the global performances of the whole industrial system. They are anticipative in nature, which allows a maintenance expert to consider non-already-planned maintenance actions. Two questions naturally emerge: when to perform a predictive maintenance action; how a maintenance expert c...

Toward interplay between substructure evolution, dislocation configuration, and yield strength in a microalloyed steel

International Nuclear Information System (INIS)

Venkatsurya, P.K.C.; Misra, R.D.K.; Mulholland, M.D.; Manohar, M.; Hartmann, J.E.

2014-01-01

We focus our attention here on the directional dependence of yield strength in high strength microalloyed steel using transmission electron microscopy and x-ray diffraction. The primary objective is to study the interplay between substructural evolution, notably cell size, dense dislocation walls (DDWs), dislocation tangle zones (DTZs), lamellar boundaries, crystallographic texture, and yield strength. The study elucidates for the first time the strong impact of thermo-mechanical deformation-induced dislocation and lamellar structures, which are likely to modify the slip pattern, leading to directional dependence of yield strength. Majority of the dislocations tend to pile along the {110} slip planes as dense dislocation walls. At low strains, grains are first divided into cell blocks that are nearly dislocation-free. At higher strains and with progress in thermo-mechanical processing dislocation tangled zones and lamellar boundaries develop. It is hypothesized that the differences in dislocation configurations, dislocations cells and cell blocks, and lamellar boundaries synergistically contribute to directional dependence of the yield strength in the high strength ferrous alloy. The presumption is envisaged on the basis of observations that the microstructural constituents were similar in the entire plane of the hot rolled strip and the crystallographic texture was weak

The role of family expressed emotion and perceived social support in predicting addiction relapse.

Science.gov (United States)

Atadokht, Akbar; Hajloo, Nader; Karimi, Masoud; Narimani, Mohammad

2015-03-01

Emotional conditions governing the family and patients' perceived social support play important roles in the treatment or relapse process of the chronic disease. The current study aimed to investigate the role of family expressed emotion and perceived social support in prediction of addiction relapse. The descriptive-correlation method was used in the current study. The study population consisted of the individuals referred to the addiction treatment centers in Ardabil from October 2013 to January 2014. The subjects (n = 80) were randomly selected using cluster sampling method. To collect data, expressed emotion test by Cole and Kazaryan, and Multidimensional Scale of Perceived Social Support (MSPSS) were used, and the obtained data was analyzed using the Pearson's correlation coefficient and multiple regression analyses. Results showed a positive relationship between family expressed emotions and the frequency of relapse (r = 0.26, P = 0.011) and a significant negative relationship between perceived social support and the frequency of relapse (r = -0.34, P = 0.001). Multiple regression analysis also showed that perceived social support from family and the family expressed emotions significantly explained 12% of the total variance of relapse frequency. These results have implications for addicted people, their families and professionals working in addiction centers to use the emotional potential of families especially their expressed emotions and the perceived social support of addicts to increase the success rate of addiction treatment.

A framework for multiple kernel support vector regression and its applications to siRNA efficacy prediction.

Science.gov (United States)

Qiu, Shibin; Lane, Terran

2009-01-01

The cell defense mechanism of RNA interference has applications in gene function analysis and promising potentials in human disease therapy. To effectively silence a target gene, it is desirable to select appropriate initiator siRNA molecules having satisfactory silencing capabilities. Computational prediction for silencing efficacy of siRNAs can assist this screening process before using them in biological experiments. String kernel functions, which operate directly on the string objects representing siRNAs and target mRNAs, have been applied to support vector regression for the prediction and improved accuracy over numerical kernels in multidimensional vector spaces constructed from descriptors of siRNA design rules. To fully utilize information provided by string and numerical data, we propose to unify the two in a kernel feature space by devising a multiple kernel regression framework where a linear combination of the kernels is used. We formulate the multiple kernel learning into a quadratically constrained quadratic programming (QCQP) problem, which although yields global optimal solution, is computationally demanding and requires a commercial solver package. We further propose three heuristics based on the principle of kernel-target alignment and predictive accuracy. Empirical results demonstrate that multiple kernel regression can improve accuracy, decrease model complexity by reducing the number of support vectors, and speed up computational performance dramatically. In addition, multiple kernel regression evaluates the importance of constituent kernels, which for the siRNA efficacy prediction problem, compares the relative significance of the design rules. Finally, we give insights into the multiple kernel regression mechanism and point out possible extensions.

PREDICTED SIZES OF PRESSURE-SUPPORTED HI CLOUDS IN THE OUTSKIRTS OF THE VIRGO CLUSTER

Energy Technology Data Exchange (ETDEWEB)

Burkhart, Blakesley; Loeb, Abraham [Harvard-Smithsonian Center for Astrophysics, 60 Garden St. Cambridge, MA (United States)

2016-06-10

Using data from the ALFALFA AGES Arecibo HI survey of galaxies and the Virgo cluster X-ray pressure profiles from XMM-Newton , we investigate the possibility that starless dark HI clumps, also known as “dark galaxies,” are supported by external pressure in the surrounding intercluster medium. We find that the starless HI clump masses, velocity dispersions, and positions allow these clumps to be in pressure equilibrium with the X-ray gas near the virial radius of the Virgo cluster. We predict the sizes of these clumps to range from 1 to 10 kpc, in agreement with the range of sizes found for spatially resolved HI starless clumps outside of Virgo. Based on the predicted HI surface density of the Virgo sources, as well as a sample of other similar resolved ALFALFA HI dark clumps with follow-up optical/radio observations, we predict that most of the HI dark clumps are on the cusp of forming stars. These HI sources therefore mark the transition between starless HI clouds and dwarf galaxies with stars.

Prediction of endoplasmic reticulum resident proteins using fragmented amino acid composition and support vector machine

Directory of Open Access Journals (Sweden)

Ravindra Kumar

2017-09-01

Full Text Available Background The endoplasmic reticulum plays an important role in many cellular processes, which includes protein synthesis, folding and post-translational processing of newly synthesized proteins. It is also the site for quality control of misfolded proteins and entry point of extracellular proteins to the secretory pathway. Hence at any given point of time, endoplasmic reticulum contains two different cohorts of proteins, (i proteins involved in endoplasmic reticulum-specific function, which reside in the lumen of the endoplasmic reticulum, called as endoplasmic reticulum resident proteins and (ii proteins which are in process of moving to the extracellular space. Thus, endoplasmic reticulum resident proteins must somehow be distinguished from newly synthesized secretory proteins, which pass through the endoplasmic reticulum on their way out of the cell. Approximately only 50% of the proteins used in this study as training data had endoplasmic reticulum retention signal, which shows that these signals are not essentially present in all endoplasmic reticulum resident proteins. This also strongly indicates the role of additional factors in retention of endoplasmic reticulum-specific proteins inside the endoplasmic reticulum. Methods This is a support vector machine based method, where we had used different forms of protein features as inputs for support vector machine to develop the prediction models. During training leave-one-out approach of cross-validation was used. Maximum performance was obtained with a combination of amino acid compositions of different part of proteins. Results In this study, we have reported a novel support vector machine based method for predicting endoplasmic reticulum resident proteins, named as ERPred. During training we achieved a maximum accuracy of 81.42% with leave-one-out approach of cross-validation. When evaluated on independent dataset, ERPred did prediction with sensitivity of 72.31% and specificity of 83

Coping Styles, Social Support, Relational Self-Construal, and Resilience in Predicting Students' Adjustment to University Life

Science.gov (United States)

Rahat, Enes; Ilhan, Tahsin

2016-01-01

The purpose of the present study is to investigate how well coping styles, social support, relational self-construal, and resilience characteristics predict first year university students' ability to adjust to university life. Participants consisted of 527 at-risk students attending a state university in Turkey. The Personal Information Form, Risk…

Termination of Resuscitation Rules to Predict Neurological Outcomes in Out-of-Hospital Cardiac Arrest for an Intermediate Life Support Prehospital System.

Science.gov (United States)

Cheong, Randy Wang Long; Li, Huihua; Doctor, Nausheen Edwin; Ng, Yih Yng; Goh, E Shaun; Leong, Benjamin Sieu-Hon; Gan, Han Nee; Foo, David; Tham, Lai Peng; Charles, Rabind; Ong, Marcus Eng Hock

2016-01-01

Futile resuscitation can lead to unnecessary transports for out-of-hospital cardiac arrest (OHCA). The Basic Life Support (BLS) and Advanced Life Support (ALS) termination of resuscitation (TOR) guidelines have been validated with good results in North America. This study aims to evaluate the performance of these two rules in predicting neurological outcomes of OHCA patients in Singapore, which has an intermediate life support Emergency Medical Services (EMS) system. A retrospective cohort study was carried out on Singapore OHCA data collected from April 2010 to May 2012 for the Pan-Asian Resuscitation Outcomes Study (PAROS). The outcomes of each rule were compared to the actual neurological outcomes of the patients. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and predicted transport rates of each test were evaluated. A total of 2,193 patients had cardiac arrest of presumed cardiac etiology. TOR was recommended for 1,411 patients with the BLS-TOR rule, with a specificity of 100% (91.9, 100.0) for predicting poor neurological outcomes, PPV 100% (99.7, 100.0), sensitivity 65.7% (63.6, 67.7), NPV 5.6% (4.1, 7.5), and transportation rate 35.6%. Using the ALS-TOR rule, TOR was recommended for 587 patients, specificity 100% (91.9, 100.0) for predicting poor neurological outcomes, PPV 100% (99.4, 100.0), sensitivity 27.3% (25.4, 29.3), NPV 2.7% (2.0, 3.7), and transportation rate 73.2%. BLS-TOR predicted survival (any neurological outcome) with specificity 93.4% (95% CI 85.3, 97.8) versus ALS-TOR 98.7% (95% CI 92.9, 99.8). Both the BLS and ALS-TOR rules had high specificities and PPV values in predicting neurological outcomes, the BLS-TOR rule had a lower predicted transport rate while the ALS-TOR rule was more accurate in predicting futility of resuscitation. Further research into unique local cultural issues would be useful to evaluate the feasibility of any system-wide implementation of TOR.

Sensitivity of nonlinear photoionization to resonance substructure in collective excitation

Science.gov (United States)

Mazza, T.; Karamatskou, A.; Ilchen, M.; Bakhtiarzadeh, S.; Rafipoor, A. J.; O'Keeffe, P.; Kelly, T. J.; Walsh, N.; Costello, J. T.; Meyer, M.; Santra, R.

2015-01-01

Collective behaviour is a characteristic feature in many-body systems, important for developments in fields such as magnetism, superconductivity, photonics and electronics. Recently, there has been increasing interest in the optically nonlinear response of collective excitations. Here we demonstrate how the nonlinear interaction of a many-body system with intense XUV radiation can be used as an effective probe for characterizing otherwise unresolved features of its collective response. Resonant photoionization of atomic xenon was chosen as a case study. The excellent agreement between experiment and theory strongly supports the prediction that two distinct poles underlie the giant dipole resonance. Our results pave the way towards a deeper understanding of collective behaviour in atoms, molecules and solid-state systems using nonlinear spectroscopic techniques enabled by modern short-wavelength light sources. PMID:25854939

Prediction of Five Softwood Paper Properties from its Density using Support Vector Machine Regression Techniques

Directory of Open Access Journals (Sweden)

Esperanza García-Gonzalo

2016-01-01

Full Text Available Predicting paper properties based on a limited number of measured variables can be an important tool for the industry. Mathematical models were developed to predict mechanical and optical properties from the corresponding paper density for some softwood papers using support vector machine regression with the Radial Basis Function Kernel. A dataset of different properties of paper handsheets produced from pulps of pine (Pinus pinaster and P. sylvestris and cypress species (Cupressus lusitanica, C. sempervirens, and C. arizonica beaten at 1000, 4000, and 7000 revolutions was used. The results show that it is possible to obtain good models (with high coefficient of determination with two variables: the numerical variable density and the categorical variable species.

Predicting Child Physical Activity and Screen Time: Parental Support for Physical Activity and General Parenting Styles

Science.gov (United States)

Crain, A. Lauren; Senso, Meghan M.; Levy, Rona L.; Sherwood, Nancy E.

2014-01-01

Objective: To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Methods: Participants were children (6.9 ± 1.8 years) with a body mass index in the 70–95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Results: Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Conclusions: Parenting practices and styles should be considered jointly, offering implications for tailored interventions. PMID:24812256

Landslide susceptibility mapping & prediction using Support Vector Machine for Mandakini River Basin, Garhwal Himalaya, India

Science.gov (United States)

Kumar, Deepak; Thakur, Manoj; Dubey, Chandra S.; Shukla, Dericks P.

2017-10-01

In recent years, various machine learning techniques have been applied for landslide susceptibility mapping. In this study, three different variants of support vector machine viz., SVM, Proximal Support Vector Machine (PSVM) and L2-Support Vector Machine - Modified Finite Newton (L2-SVM-MFN) have been applied on the Mandakini River Basin in Uttarakhand, India to carry out the landslide susceptibility mapping. Eight thematic layers such as elevation, slope, aspect, drainages, geology/lithology, buffer of thrusts/faults, buffer of streams and soil along with the past landslide data were mapped in GIS environment and used for landslide susceptibility mapping in MATLAB. The study area covering 1625 km2 has merely 0.11% of area under landslides. There are 2009 pixels for past landslides out of which 50% (1000) landslides were considered as training set while remaining 50% as testing set. The performance of these techniques has been evaluated and the computational results show that L2-SVM-MFN obtains higher prediction values (0.829) of receiver operating characteristic curve (AUC-area under the curve) as compared to 0.807 for PSVM model and 0.79 for SVM. The results obtained from L2-SVM-MFN model are found to be superior than other SVM prediction models and suggest the usefulness of this technique to problem of landslide susceptibility mapping where training data is very less. However, these techniques can be used for satisfactory determination of susceptible zones with these inputs.

Effects of subordinate feedback to the supervisor and participation in decision-making in the prediction of organizational support.

Science.gov (United States)

1992-03-01

The present study tested the hypothesis that participation in decision-making (PDM) and perceived effectiveness of subordinate feedback to the supervisor would contribute unique variance in the prediction of perceptions of organizational support. In ...

Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.

LENUS (Irish Health Repository)

Mourao-Miranda, J

2012-05-01

To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.

Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

Science.gov (United States)

Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

2009-01-01

Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

Consecutive thiophene-annulation approach to π-extended thienoacene-based organic semiconductors with [1]benzothieno[3,2-b][1]benzothiophene (BTBT) substructure.

Science.gov (United States)

Mori, Takamichi; Nishimura, Takeshi; Yamamoto, Tatsuya; Doi, Iori; Miyazaki, Eigo; Osaka, Itaru; Takimiya, Kazuo

2013-09-18

We describe a new synthetic route to the [1]benzothieno[3,2-b][1]benzothiophene (BTBT) substructure featuring two consecutive thiophene-annulation reactions from o-ethynyl-thioanisole substrates and arylsulfenyl chloride reagents that can be easily derived from arylthiols. The method is particularly suitable for the synthesis of unsymmetrical derivatives, e.g., [1]benzothieno[3,2-b]naphtho[2,3-b]thiophene, [1]benzothieno[3,2-b]anthra[2,3-b]thiophene, and naphtho[3,2-b]thieno[3,2-b]anthra[2,3-b]thiophene, a selenium-containing derivative, [1]benzothieno[3,2-b][1]benzoselenophene. It also allows us to access largely π-extended derivatives with two BTBT substructures, e.g., bis[1]benzothieno[2,3-d:2',3'-d']benzo[1,2-b:4,5-b']dithiophene and bis[1]benzothieno[2,3-d:2',3'-d']naphtho[2,3-b:6,7-b']dithiophene (BBTNDT). It should be emphasized that these new BTBT derivatives are otherwise difficult to be synthesized. In addition, since various substrates and reagents, o-ethynyl-thioanisoles and arylthiols, respectively, can be combined, the method can be regarded as a versatile tool for the development of thienoacene-based organic semiconductors in this class. Among the newly synthesized materials, highly π-extended BBTNDT afforded very high mobility (>5 cm(2) V(-1) s(-1)) in its vapor-deposited organic field-effect transistors (OFETs), which is among the highest for unsubstituted acene- or thienoacenes-based organic semiconductors. In fact, the structural analyses of BBTNDT both in the single crystal and thin-film state indicated that an interactive two-dimensional molecular array is realized in the solid state, which rationalize the higher carrier mobility in the BBTNDT-based OFETs.

Rehabilitation of Nose following Chemical Burn Using CAD/CAM Made Substructure for Implant Retained Nasal Prosthesis: A Clinical Report

Directory of Open Access Journals (Sweden)

Saurabh Chaturvedi

2017-01-01

Full Text Available Insufficient knowledge of medical chemicals and their improper use have destructive effects. Accidental exposure to chemicals on facial tissue may result in large facial defect. For ages the tradition of piercing nose is common but improper use of unknown chemical for piercing has deleterious effect. Mostly rhinectomy defects are acquired caused by trauma or malignant diseases. Prosthetic rehabilitation is the preferred treatment of choice for any large rhinectomy defects as medical and surgical interventions are ineffective in developing esthetics. Main concern with the prosthesis for such defects is retention. This article describes rehabilitation of a patient with large size nasal defect created by chemical burn in childhood during piercing. Implant retained customized silicone nasal prosthesis was fabricated using simple O-ring attachments and innovative modified polyamide acrylic resin substructure acting as skeleton.

Harnessing Facebook for Smoking Reduction and Cessation Interventions: Facebook User Engagement and Social Support Predict Smoking Reduction

Science.gov (United States)

Marsch, Lisa A; Brunette, Mary F; Dallery, Jesse

2017-01-01

Background Social media technologies offer a novel opportunity for scalable health interventions that can facilitate user engagement and social support, which in turn may reinforce positive processes for behavior change. Objective By using principles from health communication and social support literature, we implemented a Facebook group–based intervention that targeted smoking reduction and cessation. This study hypothesized that participants’ engagement with and perceived social support from our Facebook group intervention would predict smoking reduction. Methods We recruited 16 regular smokers who live in the United States and who were motivated in quitting smoking at screening. We promoted message exposure as well as engagement and social support systems throughout the intervention. For message exposure, we posted prevalidated, antismoking messages (such as national antismoking campaigns) on our smoking reduction and cessation Facebook group. For engagement and social support systems, we delivered a high degree of engagement and social support systems during the second and third week of the intervention and a low degree of engagement and social support systems during the first and fourth week. A total of six surveys were conducted via Amazon Mechanical Turk (MTurk) at baseline on a weekly basis and at a 2-week follow-up. Results Of the total 16 participants, most were female (n=13, 81%), white (n=15, 94%), and between 25 and 50 years of age (mean 34.75, SD 8.15). There was no study attrition throughout the 6-time-point baseline, weekly, and follow-up surveys. We generated Facebook engagement and social support composite scores (mean 19.19, SD 24.35) by combining the number of likes each participant received and the number of comments or wall posts each participant posted on our smoking reduction and cessation Facebook group during the intervention period. The primary outcome was smoking reduction in the past 7 days measured at baseline and at the two

Ranking of hair dye substances according to predicted sensitization potency

DEFF Research Database (Denmark)

Søsted, H; Basketter, D A; Estrada, E

2004-01-01

Allergic contact dermatitis following the use of hair dyes is well known. Many chemicals are used in hair dyes and it is unlikely that all cases of hair dye allergy can be diagnosed by means of patch testing with p-phenylenediamine (PPD). The objectives of this study are to identify all hair dye...... in order to help select a number of chemically diverse hair dye substances that could be used in subsequent clinical work. Various information sources, including the Inventory of Cosmetics Ingredients, new regulations on cosmetics, data on total use and ChemId (the Chemical Search Input website provided...... by the National Library of Medicine), were used in order to identify the names and structures of the hair dyes. A QSAR model, developed with the help of experimental local lymph node assay data and topological sub-structural molecular descriptors (TOPS-MODE), was used in order to predict the likely sensitization...

Perceived parenting and social support: can they predict academic achievement in Argentinean college students?

OpenAIRE

de la Iglesia, Guadalupe; Freiberg Hoffmann, Agustin; Fernández Liporace, Mercedes

2014-01-01

Guadalupe de la Iglesia,1,2 Agustin Freiberg Hoffmann,2 Mercedes Fernández Liporace1,2 1National Council of Scientific and Technical Research (CONICET), 2University of Buenos Aires, Buenos Aires, Argentina Abstract: The aim of this study was to test the ability to predict academic achievement through the perception of parenting and social support in a sample of 354 Argentinean college students. Their mean age was 23.50 years (standard deviation =2.62 years) and most of them (83.3%...

Performance Comparison Between Support Vector Regression and Artificial Neural Network for Prediction of Oil Palm Production

Directory of Open Access Journals (Sweden)

Mustakim Mustakim

2016-02-01

Full Text Available The largest region that produces oil palm in Indonesia has an important role in improving the welfare of society and economy. Oil palm has increased significantly in Riau Province in every period, to determine the production development for the next few years with the functions and benefits of oil palm carried prediction production results that were seen from time series data last 8 years (2005-2013. In its prediction implementation, it was done by comparing the performance of Support Vector Regression (SVR method and Artificial Neural Network (ANN. From the experiment, SVR produced the best model compared with ANN. It is indicated by the correlation coefficient of 95% and 6% for MSE in the kernel Radial Basis Function (RBF, whereas ANN produced only 74% for R2 and 9% for MSE on the 8th experiment with hiden neuron 20 and learning rate 0,1. SVR model generates predictions for next 3 years which increased between 3% - 6% from actual data and RBF model predictions.

Failure and reliability prediction by support vector machines regression of time series data

International Nuclear Information System (INIS)

Chagas Moura, Marcio das; Zio, Enrico; Lins, Isis Didier; Droguett, Enrique

2011-01-01

Support Vector Machines (SVMs) are kernel-based learning methods, which have been successfully adopted for regression problems. However, their use in reliability applications has not been widely explored. In this paper, a comparative analysis is presented in order to evaluate the SVM effectiveness in forecasting time-to-failure and reliability of engineered components based on time series data. The performance on literature case studies of SVM regression is measured against other advanced learning methods such as the Radial Basis Function, the traditional MultiLayer Perceptron model, Box-Jenkins autoregressive-integrated-moving average and the Infinite Impulse Response Locally Recurrent Neural Networks. The comparison shows that in the analyzed cases, SVM outperforms or is comparable to other techniques. - Highlights: → Realistic modeling of reliability demands complex mathematical formulations. → SVM is proper when the relation input/output is unknown or very costly to be obtained. → Results indicate the potential of SVM for reliability time series prediction. → Reliability estimates support the establishment of adequate maintenance strategies.

Predicting child physical activity and screen time: parental support for physical activity and general parenting styles.

Science.gov (United States)

Langer, Shelby L; Crain, A Lauren; Senso, Meghan M; Levy, Rona L; Sherwood, Nancy E

2014-07-01

To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Participants were children (6.9 ± 1.8 years) with a body mass index in the 70-95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Parenting practices and styles should be considered jointly, offering implications for tailored interventions. © The Author 2014. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Optimally matching support and perceived spousal sensitivity.

Science.gov (United States)

Cutrona, Carolyn E; Shaffer, Philip A; Wesner, Kristin A; Gardner, Kelli A

2007-12-01

Partner sensitivity is an important antecedent of both intimacy (H. T. Reis & P. Shaver, 1988) and attachment (M. D. S. Ainsworth, 1989). On the basis of the optimal matching model of social support (C. E. Cutrona & D. Russell, 1990), support behaviors that "matched" the support goals of the stressed individual were predicted to lead to the perception of partner sensitivity. Predictions were tested with 59 married couples, who engaged in a videotaped self-disclosure task. Matching support was defined as the disclosure of emotions followed by emotional support or a request for information followed by informational support. Partial evidence was found for the predictions. Matching support following the disclosure of emotions was predictive of perceived partner sensitivity. Mismatched support following the disclosure of emotions predicted lower marital satisfaction, through the mediation of partner sensitivity. Matching support following a request for information was not predictive of perceived partner sensitivity, but negative partner responses (e.g., criticism or sarcasm) following a request for information negatively predicted perceptions of partner sensitivity. The importance of considering the context of support transactions is discussed.

The predictive factors for perceived social support among cancer patients and caregiver burden of their family caregivers in Turkish population.

Science.gov (United States)

Oven Ustaalioglu, Basak; Acar, Ezgi; Caliskan, Mecit

2018-03-01

We aimed to identify the predictive factors for the perceived family social support among cancer patients and caregiver burden of their family caregivers. Participants were 302 cancer patients and their family caregivers. Family social support scale was used for cancer patients, burden interview was used for family caregivers.All subjects also completed Beck depression invantery. The related socio-demographical factors with perceived social support (PSS) and caregiver burden were evaluated by correlation analysis. To find independent factors predicting caregiver burden and PSS, logistic regression analysis were conducted. Depression scores was higher among patients than their family caregivers (12.5 vs. 8). PSS was lower in depressed patients (p Family caregiver burden were also higher in depressive groups (p family caregiver role was negatively correlated (p caregiver burden. Presence of depression was the independent predictor for both, lower PSS for patients and higher burden for caregivers. The results of this study is noteworthy because it may help for planning any supportive care program not only for patients but together with their caregiver at the same time during chemotherapy period in Turkish population.

Application of Artificial Neural Network and Support Vector Machines in Predicting Metabolizable Energy in Compound Feeds for Pigs.

Science.gov (United States)

Ahmadi, Hamed; Rodehutscord, Markus

2017-01-01

In the nutrition literature, there are several reports on the use of artificial neural network (ANN) and multiple linear regression (MLR) approaches for predicting feed composition and nutritive value, while the use of support vector machines (SVM) method as a new alternative approach to MLR and ANN models is still not fully investigated. The MLR, ANN, and SVM models were developed to predict metabolizable energy (ME) content of compound feeds for pigs based on the German energy evaluation system from analyzed contents of crude protein (CP), ether extract (EE), crude fiber (CF), and starch. A total of 290 datasets from standardized digestibility studies with compound feeds was provided from several institutions and published papers, and ME was calculated thereon. Accuracy and precision of developed models were evaluated, given their produced prediction values. The results revealed that the developed ANN [ R 2  = 0.95; root mean square error (RMSE) = 0.19 MJ/kg of dry matter] and SVM ( R 2  = 0.95; RMSE = 0.21 MJ/kg of dry matter) models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR ( R 2  = 0.89; RMSE = 0.27 MJ/kg of dry matter). The developed ANN and SVM models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR; however, there were not obvious differences between performance of ANN and SVM models. Thus, SVM model may also be considered as a promising tool for modeling the relationship between chemical composition and ME of compound feeds for pigs. To provide the readers and nutritionist with the easy and rapid tool, an Excel ® calculator, namely, SVM_ME_pig, was created to predict the metabolizable energy values in compound feeds for pigs using developed support vector machine model.

Influence of fractal substructures of the percolating cluster on transferring processes in macroscopically disordered environments

Science.gov (United States)

Kolesnikov, B. P.

2017-11-01

The presented work belongs to the issue of searching for the effective kinetic properties of macroscopically disordered environments (MDE). These properties characterize MDE in general on the sizes which significantly exceed the sizes of macro inhomogeneity. The structure of MDE is considered as a complex of interpenetrating percolating and finite clusters consolidated from homonymous components, topological characteristics of which influence on the properties of the whole environment. The influence of percolating clusters’ fractal substructures (backbone, skeleton of backbone, red bonds) on the transfer processes during crossover (a structure transition from fractal to homogeneous condition) is investigated based on the offered mathematical approach for finding the effective conductivity of MDEs and on the percolating cluster model. The nature of the change of the critical conductivity index t during crossover from the characteristic value for the area close to percolation threshold to the value corresponded to homogeneous condition is demonstrated. The offered model describes the transfer processes in MDE with the finite conductivity relation of «conductive» and «low conductive» phases above and below percolation threshold and in smearing area (an analogue of a blur area of the second-order phase transfer).

Harnessing Facebook for Smoking Reduction and Cessation Interventions: Facebook User Engagement and Social Support Predict Smoking Reduction.

Science.gov (United States)

Kim, Sunny Jung; Marsch, Lisa A; Brunette, Mary F; Dallery, Jesse

2017-05-23

Social media technologies offer a novel opportunity for scalable health interventions that can facilitate user engagement and social support, which in turn may reinforce positive processes for behavior change. By using principles from health communication and social support literature, we implemented a Facebook group-based intervention that targeted smoking reduction and cessation. This study hypothesized that participants' engagement with and perceived social support from our Facebook group intervention would predict smoking reduction. We recruited 16 regular smokers who live in the United States and who were motivated in quitting smoking at screening. We promoted message exposure as well as engagement and social support systems throughout the intervention. For message exposure, we posted prevalidated, antismoking messages (such as national antismoking campaigns) on our smoking reduction and cessation Facebook group. For engagement and social support systems, we delivered a high degree of engagement and social support systems during the second and third week of the intervention and a low degree of engagement and social support systems during the first and fourth week. A total of six surveys were conducted via Amazon Mechanical Turk (MTurk) at baseline on a weekly basis and at a 2-week follow-up. Of the total 16 participants, most were female (n=13, 81%), white (n=15, 94%), and between 25 and 50 years of age (mean 34.75, SD 8.15). There was no study attrition throughout the 6-time-point baseline, weekly, and follow-up surveys. We generated Facebook engagement and social support composite scores (mean 19.19, SD 24.35) by combining the number of likes each participant received and the number of comments or wall posts each participant posted on our smoking reduction and cessation Facebook group during the intervention period. The primary outcome was smoking reduction in the past 7 days measured at baseline and at the two-week follow-up. Compared with the baseline

Development of ANN Model for Wind Speed Prediction as a Support for Early Warning System

Directory of Open Access Journals (Sweden)

Ivan Marović

2017-01-01

Full Text Available The impact of natural disasters increases every year with more casualties and damage to property and the environment. Therefore, it is important to prevent consequences by implementation of the early warning system (EWS in order to announce the possibility of the harmful phenomena occurrence. In this paper, focus is placed on the implementation of the EWS on the micro location in order to announce possible harmful phenomena occurrence caused by wind. In order to predict such phenomena (wind speed, an artificial neural network (ANN prediction model is developed. The model is developed on the basis of the input data obtained by local meteorological station on the University of Rijeka campus area in the Republic of Croatia. The prediction model is validated and evaluated by visual and common calculation approaches, after which it was found that it is possible to perform very good wind speed prediction for time steps Δt=1 h, Δt=3 h, and Δt=8 h. The developed model is implemented in the EWS as a decision support for improvement of the existing “procedure plan in a case of the emergency caused by stormy wind or hurricane, snow and occurrence of the ice on the University of Rijeka campus.”

Support vector regression for porosity prediction in a heterogeneous reservoir: A comparative study

Science.gov (United States)

Al-Anazi, A. F.; Gates, I. D.

2010-12-01

In wells with limited log and core data, porosity, a fundamental and essential property to characterize reservoirs, is challenging to estimate by conventional statistical methods from offset well log and core data in heterogeneous formations. Beyond simple regression, neural networks have been used to develop more accurate porosity correlations. Unfortunately, neural network-based correlations have limited generalization ability and global correlations for a field are usually less accurate compared to local correlations for a sub-region of the reservoir. In this paper, support vector machines are explored as an intelligent technique to correlate porosity to well log data. Recently, support vector regression (SVR), based on the statistical learning theory, have been proposed as a new intelligence technique for both prediction and classification tasks. The underlying formulation of support vector machines embodies the structural risk minimization (SRM) principle which has been shown to be superior to the traditional empirical risk minimization (ERM) principle employed by conventional neural networks and classical statistical methods. This new formulation uses margin-based loss functions to control model complexity independently of the dimensionality of the input space, and kernel functions to project the estimation problem to a higher dimensional space, which enables the solution of more complex nonlinear problem optimization methods to exist for a globally optimal solution. SRM minimizes an upper bound on the expected risk using a margin-based loss function ( ɛ-insensitivity loss function for regression) in contrast to ERM which minimizes the error on the training data. Unlike classical learning methods, SRM, indexed by margin-based loss function, can also control model complexity independent of dimensionality. The SRM inductive principle is designed for statistical estimation with finite data where the ERM inductive principle provides the optimal solution (the

Definition of a concrete bio-decontamination process in nuclear substructures; Biodegradation de matrices cimentaires en vue de leur decontamination

Energy Technology Data Exchange (ETDEWEB)

Jestin, A

2005-05-15

The decontamination of sub-structural materials represents a stake of high-importance because of the high volume generated. It is agreed then to propose efficient and effective processes. The process of bio-decontamination of the hydraulic binders leans on the mechanisms of biodegradation of concretes, phenomenon characterized in the 40's by an indirect attack of the material by acids stem from the microbial metabolism: sulphuric acid (produced by Thiobacillus), nitric acid (produced by Nitrosomonas and Nitrobacter) and organic acids (produced by fungi). The principle of the bio-decontamination process is to apply those micro-organisms on the surface of the contaminated material, in order to damage its surface and to retrieve the radionuclides. One of the multiple approaches of the process is the use of a bio-gel that makes possible the micro-organisms application. (author)

A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

Science.gov (United States)

Wang, Jun; Wang, Yang; Zeng, Hui

2016-01-01

A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

BLProt: Prediction of bioluminescent proteins based on support vector machine and relieff feature selection

KAUST Repository

Kandaswamy, Krishna Kumar

2011-08-17

Background: Bioluminescence is a process in which light is emitted by a living organism. Most creatures that emit light are sea creatures, but some insects, plants, fungi etc, also emit light. The biotechnological application of bioluminescence has become routine and is considered essential for many medical and general technological advances. Identification of bioluminescent proteins is more challenging due to their poor similarity in sequence. So far, no specific method has been reported to identify bioluminescent proteins from primary sequence.Results: In this paper, we propose a novel predictive method that uses a Support Vector Machine (SVM) and physicochemical properties to predict bioluminescent proteins. BLProt was trained using a dataset consisting of 300 bioluminescent proteins and 300 non-bioluminescent proteins, and evaluated by an independent set of 141 bioluminescent proteins and 18202 non-bioluminescent proteins. To identify the most prominent features, we carried out feature selection with three different filter approaches, ReliefF, infogain, and mRMR. We selected five different feature subsets by decreasing the number of features, and the performance of each feature subset was evaluated.Conclusion: BLProt achieves 80% accuracy from training (5 fold cross-validations) and 80.06% accuracy from testing. The performance of BLProt was compared with BLAST and HMM. High prediction accuracy and successful prediction of hypothetical proteins suggests that BLProt can be a useful approach to identify bioluminescent proteins from sequence information, irrespective of their sequence similarity. 2011 Kandaswamy et al; licensee BioMed Central Ltd.

BLProt: Prediction of bioluminescent proteins based on support vector machine and relieff feature selection

KAUST Repository

Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Hazrati, Mehrnaz Khodam; Kalies, Kai-Uwe; Martinetz, Thomas

2011-01-01

Background: Bioluminescence is a process in which light is emitted by a living organism. Most creatures that emit light are sea creatures, but some insects, plants, fungi etc, also emit light. The biotechnological application of bioluminescence has become routine and is considered essential for many medical and general technological advances. Identification of bioluminescent proteins is more challenging due to their poor similarity in sequence. So far, no specific method has been reported to identify bioluminescent proteins from primary sequence.Results: In this paper, we propose a novel predictive method that uses a Support Vector Machine (SVM) and physicochemical properties to predict bioluminescent proteins. BLProt was trained using a dataset consisting of 300 bioluminescent proteins and 300 non-bioluminescent proteins, and evaluated by an independent set of 141 bioluminescent proteins and 18202 non-bioluminescent proteins. To identify the most prominent features, we carried out feature selection with three different filter approaches, ReliefF, infogain, and mRMR. We selected five different feature subsets by decreasing the number of features, and the performance of each feature subset was evaluated.Conclusion: BLProt achieves 80% accuracy from training (5 fold cross-validations) and 80.06% accuracy from testing. The performance of BLProt was compared with BLAST and HMM. High prediction accuracy and successful prediction of hypothetical proteins suggests that BLProt can be a useful approach to identify bioluminescent proteins from sequence information, irrespective of their sequence similarity. 2011 Kandaswamy et al; licensee BioMed Central Ltd.

First report on the structural exploration and prediction of new BPTES analogs as glutaminase inhibitors

Science.gov (United States)

Amin, Sk. Abdul; Adhikari, Nilanjan; Gayen, Shovanlal; Jha, Tarun

2017-09-01

Glutaminase is one of the important key enzymes regulating cellular metabolism, growth, and proliferation in cancer. Therefore, it is being explored as a crucial target regarding anticancer drug design and development. However, none of the potent and selective glutaminase inhibitors is available in the market though two prototype glutaminase inhibitors are reported namely DON as well as BPTES. Due to severe toxicity in clinical trials, the use of DON is restricted. However, BPTES is an allosteric glutaminase inhibitor with less toxic profile and, therefore, lead optimization of BPTES may be a good option to develop newer drug candidates. In this study, a multi-QSAR modeling is carried out on a series of BPTES analogs. A significant connection between different descriptors and the glutaminase inhibitory activities is noticed by employing multiple linear regression, artificial neural network and support vector machine techniques. The classification-based QSAR such as linear discriminant analysis and Bayesian classification modeling are also performed to search important molecular fingerprints or substructures that may help in classifying the probability of finding 'active' and 'inactive' BPTES analogs. Moreover, HQSAR and Topomer CoMFA analyses are also performed. In addition, the SAR observations are interpreted with all these validated computational models along with the structure-based contours. Finally, new twenty two compounds are designed and predicted for their probable glutaminase inhibitory activity.

Comparison of Design Methods for Axially Loaded Driven Piles in Cohesionless Soil

DEFF Research Database (Denmark)

Thomassen, Kristina; Andersen, Lars Vabbersgaard; Ibsen, Lars Bo

2012-01-01

For offshore wind turbines on deeper waters, a jacket sub-structure supported by axially loaded piles is thought to be the most suitable solution. The design method recommended by API and two CPT-based design methods are compared for two uniform sand profiles. The analysis show great difference...... in the predictions of bearing capacities calculated by means of the three methods for piles loaded in both tension and compression. This implies that further analysis of the bearing capacity of axially loaded piles in sand should be conducted....

Combined prediction model for supply risk in nuclear power equipment manufacturing industry based on support vector machine and decision tree

International Nuclear Information System (INIS)

Shi Chunsheng; Meng Dapeng

2011-01-01

The prediction index for supply risk is developed based on the factor identifying of nuclear equipment manufacturing industry. The supply risk prediction model is established with the method of support vector machine and decision tree, based on the investigation on 3 important nuclear power equipment manufacturing enterprises and 60 suppliers. Final case study demonstrates that the combination model is better than the single prediction model, and demonstrates the feasibility and reliability of this model, which provides a method to evaluate the suppliers and measure the supply risk. (authors)

A carbon risk prediction model for Chinese heavy-polluting industrial enterprises based on support vector machine

International Nuclear Information System (INIS)

Zhou, Zhifang; Xiao, Tian; Chen, Xiaohong; Wang, Chang

2016-01-01

Chinese heavy-polluting industrial enterprises, especially petrochemical or chemical industry, labeled low carbon efficiency and high emission load, are facing the tremendous pressure of emission reduction under the background of global shortage of energy supply and constrain of carbon emission. However, due to the limited amount of theoretic and practical research in this field, problems like lacking prediction indicators or models, and the quantified standard of carbon risk remain unsolved. In this paper, the connotation of carbon risk and an assessment index system for Chinese heavy-polluting industrial enterprises (eg. coal enterprise, petrochemical enterprises, chemical enterprises et al.) based on support vector machine are presented. By using several heavy-polluting industrial enterprises’ related data, SVM model is trained to predict the carbon risk level of a specific enterprise, which allows the enterprise to identify and manage its carbon risks. The result shows that this method can predict enterprise’s carbon risk level in an efficient, accurate way with high practical application and generalization value.

Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines

Directory of Open Access Journals (Sweden)

Chi-Man Vong

2012-01-01

Full Text Available Forecasting of air pollution is a popular and important topic in recent years due to the health impact caused by air pollution. It is necessary to build an early warning system, which provides forecast and also alerts health alarm to local inhabitants by medical practitioners and the local government. Meteorological and pollutions data collected daily at monitoring stations of Macau can be used in this study to build a forecasting system. Support vector machines (SVMs, a novel type of machine learning technique based on statistical learning theory, can be used for regression and time series prediction. SVM is capable of good generalization while the performance of the SVM model is often hinged on the appropriate choice of the kernel.

A prediction model of drug-induced ototoxicity developed by an optimal support vector machine (SVM) method.

Science.gov (United States)

Zhou, Shu; Li, Guo-Bo; Huang, Lu-Yi; Xie, Huan-Zhang; Zhao, Ying-Lan; Chen, Yu-Zong; Li, Lin-Li; Yang, Sheng-Yong

2014-08-01

Drug-induced ototoxicity, as a toxic side effect, is an important issue needed to be considered in drug discovery. Nevertheless, current experimental methods used to evaluate drug-induced ototoxicity are often time-consuming and expensive, indicating that they are not suitable for a large-scale evaluation of drug-induced ototoxicity in the early stage of drug discovery. We thus, in this investigation, established an effective computational prediction model of drug-induced ototoxicity using an optimal support vector machine (SVM) method, GA-CG-SVM. Three GA-CG-SVM models were developed based on three training sets containing agents bearing different risk levels of drug-induced ototoxicity. For comparison, models based on naïve Bayesian (NB) and recursive partitioning (RP) methods were also used on the same training sets. Among all the prediction models, the GA-CG-SVM model II showed the best performance, which offered prediction accuracies of 85.33% and 83.05% for two independent test sets, respectively. Overall, the good performance of the GA-CG-SVM model II indicates that it could be used for the prediction of drug-induced ototoxicity in the early stage of drug discovery. Copyright © 2014 Elsevier Ltd. All rights reserved.

Why and when social support predicts older adults' pain-related disability: a longitudinal study.

Science.gov (United States)

Matos, Marta; Bernardes, Sónia F; Goubert, Liesbet

2017-10-01

Pain-related social support has been shown to be directly associated with pain-related disability, depending on whether it promotes functional autonomy or dependence. However, previous studies mostly relied on cross-sectional methods, precluding conclusions on the temporal relationship between pain-related social support and disability. Also, research on the behavioral and psychological processes that account for such a relationship is scarce. Therefore, this study aimed at investigating the following longitudinally: (1) direct effects of social support for functional autonomy/dependence on pain-related disability, (2) mediating role of physical functioning, pain-related self-efficacy, and fear, and (3) whether pain duration and pain intensity moderate such mediating processes. A total of 168 older adults (Mage = 78.3; SDage = 8.7) participated in a 3-month prospective design, with 3 moments of measurement, with a 6-week lag between them. Participants completed the Formal Social Support for Autonomy and Dependence in Pain Inventory, the Brief Pain Inventory, the 36-SF Health Survey, behavioral tasks from the Senior Fitness Test, the Pain Self-Efficacy Questionnaire, and the Tampa Scale for Kinesiophobia. Moderated mediation analyses showed that formal social support for functional dependence (T1) predicted an increase in pain-related disability (T3), that was mediated by self-reported physical functioning (T2) and by pain-related self-efficacy (T2) at short to moderate pain duration and at low to moderate pain intensity, but not at higher levels. Findings emphasized that social support for functional dependence is a risk factor for pain-related disability and uncovered the "why" and "when" of this relationship. Implications for the design of social support interventions aiming at promoting older adults' healthy aging despite chronic pain are drawn.

Adaptive Encoding of Outcome Prediction by Prefrontal Cortex Ensembles Supports Behavioral Flexibility.