Renormalization shielding effect on the Wannier-ridge mode for double-electron continua in partially ionized dense hydrogen plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Myoung-Jae; Jung, Young-Dae, E-mail: ydjung@hanyang.ac.kr; Department of Physics, Applied Physics, and Astronomy, Rensselaer Polytechnic Institute, 110 8th Street, Troy, New York 12180-3590

2016-01-15

The influence of renormalization shielding on the Wannier threshold law for the double-electron escapes by the electron-impact ionization is investigated in partially ionized dense plasmas. The renormalized electron charge and Wannier exponent are obtained by considering the equation of motion in the Wannier-ridge including the renormalization shielding effect. It is found that the renormalization shielding effect reduces the magnitude of effective electron charge, especially, within the Bohr radius in partially ionized dense plasmas. The maximum position of the renormalized electron charge approaches to the center of the target atom with an increase of the renormalization parameter. In addition, the Wanniermore » exponent increases with an increase of the renormalization parameter. The variations of the renormalized electron charge and Wannier exponent due to the renormalization shielding effect are also discussed.« less

Multi-orbital non-crossing approximation from maximally localized Wannier functions: the Kondo signature of copper phthalocyanine on Ag(100).

PubMed

Korytár, Richard; Lorente, Nicolás

2011-09-07

We have developed a multi-orbital approach to compute the electronic structure of a quantum impurity using the non-crossing approximation. The calculation starts with a mean-field evaluation of the system's electronic structure using a standard quantum chemistry code; here we use density functional theory (DFT). We transformed the one-electron structure into an impurity Hamiltonian by using maximally localized Wannier functions. Hence, we have developed a method to study the Kondo effect in systems based on an initial one-electron calculation. We have applied our methodology to a copper phthalocyanine molecule chemisorbed on Ag(100), and we have described its spectral function for three different cases where the molecule presents a single spin or two spins with ferro- and anti-ferromagnetic exchange couplings. We find that the use of broken-symmetry mean-field theories such as Kohn-Sham DFT cannot deal with the complexity of the spin of open-shell molecules on metal surfaces and extra modeling is needed. © 2011 IOP Publishing Ltd

First principles calculations for liquids and solids using maximally localized Wannier functions

NASA Astrophysics Data System (ADS)

Swartz, Charles W., VI

The field of condensed matter computational physics has seen an explosion of applicability over the last 50+ years. Since the very first calculations with ENIAC and MANIAC the field has continued to pushed the boundaries of what is possible; from the first large-scale molecular dynamics simulation, to the implementation of Density Functional Theory and large scale Car-Parrinello molecular dynamics, to million-core turbulence calculations by Standford. These milestones represent not only technological advances but theoretical breakthroughs and algorithmic improvements as well. The work in this thesis was completed in the hopes of furthering such advancement, even by a small fraction. Here we will focus mainly on the calculation of electronic and structural properties of solids and liquids, where we shall implement a wide range of novel approaches that are both computational efficient and physically enlightening. To this end we routinely will work with maximally localized Wannier functions (MLWFs) which have recently seen a revival in mainstream scientific literature. MLWFs present us with interesting opportunity to calculate a localized orbital within the planewave formalism of atomistic simulations. Such a localization will prove to be invaluable in the construction of layer-based superlattice models, linear scaling hybrid functional schemes and model quasiparticle calculations. In the first application of MLWF we will look at modeling functional piezoelectricity in superlattices. Based on the locality principle of insulating superlattices, we apply the method of Wu et al to the piezoelectric strains of individual layers under iifixed displacement field. For a superlattice of arbitrary stacking sequence an accurate model is acquired for predicting piezoelectricity. By applying the model in the superlattices where ferroelectric and antiferrodistortive modes are in competition, functional piezoelectricity can be achieved. A strong nonlinear effect is observed and can

Local representation of the electronic dielectric response function

DOE PAGES

Lu, Deyu; Ge, Xiaochuan

2015-12-11

We present a local representation of the electronic dielectric response function, based on a spatial partition of the dielectric response into contributions from each occupied Wannier orbital using a generalized density functional perturbation theory. This procedure is fully ab initio, and therefore allows us to rigorously define local metrics, such as “bond polarizability,” on Wannier centers. We show that the locality of the bare response function is determined by the locality of three quantities: Wannier functions of the occupied manifold, the density matrix, and the Hamiltonian matrix. Furthermore, in systems with a gap, the bare dielectric response is exponentially localized,more » which supports the physical picture of the dielectric response function as a collection of interacting local responses that can be captured by a tight-binding model.« less

Higher-dimensional Wannier Interpolation for the Modern Theory of the Dzyaloshinskii-Moriya Interaction: Application to Co-based Trilayers

NASA Astrophysics Data System (ADS)

Hanke, Jan-Philipp; Freimuth, Frank; Blügel, Stefan; Mokrousov, Yuriy

2018-04-01

We present an advanced first-principles formalism to evaluate the Dzyaloshinskii-Moriya interaction (DMI) in its modern theory as well as Berry curvatures in complex spaces based on a higher-dimensional Wannier interpolation. Our method is applied to the Co-based trilayer systems IrδPt1-δ/Co/Pt and AuγPt1-γ/Co/Pt, where we gain insights into the correlations between the electronic structure and the DMI, and we uncover prominent sign changes of the chiral interaction with the overlayer composition. Beyond the discussed phenomena, the scope of applications of our Wannier-based scheme is particularly broad as it is ideally suited to study efficiently the Hamiltonian evolution under the slow variation of very general parameters.

Inelastic light scattering from plasmons tunneling between Wannier-Stark states

NASA Astrophysics Data System (ADS)

Fluegel, B.; Pfeiffer, L. N.; West, K.; Mascarenhas, A.

2018-06-01

Using inelastic light scattering, we measure the zone-center electronic excitation modes in a set of multiple quantum wells. The width of the wavefunction barriers was chosen such that it prevents significant coupling of the electron ground states between wells yet is transparent to electron tunneling under an electric field. Under these conditions, we find charge-density-like and spin-density-like plasmons whose energies do not correspond to the excitations calculated for either a single well or a set of Coulomb-coupled wells. The observed energies are proportional to the electric field strength and the lower energy modes agree with predictions for plasmons tunneling between the Wannier-Stark ladder states.

Control of Wannier orbitals for generating tunable Ising interactions of ultracold atoms in an optical lattice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inaba, Kensuke; Tamaki, Kiyoshi; Igeta, Kazuhiro

2014-12-04

In this study, we propose a method for generating cluster states of atoms in an optical lattice. By utilizing the quantum properties of Wannier orbitals, we create an tunable Ising interaction between atoms without inducing the spin-exchange interactions. We investigate the cause of errors that occur during entanglement generations, and then we propose an error-management scheme, which allows us to create high-fidelity cluster states in a short time.

Phonon assisted carrier motion on the Wannier-Stark ladder

NASA Astrophysics Data System (ADS)

Cheung, Alfred; Berciu, Mona

2014-03-01

It is well known that at zero temperature and in the absence of electron-phonon coupling, the presence of an electric field leads to localization of carriers residing in a single band of finite bandwidth. In this talk, we will present an implementation of the self-consistent Born approximation (SCBA) to study the effect of weak electron-phonon coupling on the motion of a carrier in a biased system. At moderate and strong electron-phonon coupling, we supplement the SCBA, describing the string of phonons left behind by the carrier, with the momentum average approximation to describe the phonon cloud that accompanies the resulting polaron. We find that coupling to the lattice delocalizes the carrier, as expected, although long-lived resonances resulting from the Wannier-Stark states of the polaron may appear in certain regions of the parameter space. We end with a discussion of how our method can be improved to model disorder, other types of electron-phonon coupling, and electron-hole pair dissociation in a biased system.

Nearly Perfect Triplet-Triplet Energy Transfer from Wannier Excitons to Naphthalene in Organic-Inorganic Hybrid Quantum-Well Materials

NASA Astrophysics Data System (ADS)

Ema, K.; Inomata, M.; Kato, Y.; Kunugita, H.; Era, M.

2008-06-01

We report the observation of extremely efficient energy transfer (greater than 99%) in an organic-inorganic hybrid quantum-well structure consisting of perovskite-type lead bromide well layers and naphthalene-linked ammonium barrier layers. Time-resolved photoluminescence measurements confirm that the transfer is triplet-triplet Dexter-type energy transfer from Wannier excitons in the inorganic well to the triplet state of naphthalene molecules in the organic barrier. Using measurements in the 10 300 K temperature range, we also investigated the temperature dependence of the energy transfer.

Interaction-induced effects on Bose-Hubbard parameters

NASA Astrophysics Data System (ADS)

Kremer, Mark; Sachdeva, Rashi; Benseny, Albert; Busch, Thomas

2017-12-01

We study the effects of repulsive on-site interactions on the broadening of the localized Wannier functions used for calculating the parameters to describe ultracold atoms in optical lattices. For this, we replace the common single-particle Wannier functions, which do not contain any information about the interactions, by two-particle Wannier functions obtained from an exact solution which takes the interactions into account. We then use these interaction-dependent basis functions to calculate the Bose-Hubbard model parameters, showing that they are substantially different both at low and high lattice depths from the ones calculated using single-particle Wannier functions. Our results suggest that density effects are not negligible for many parameter ranges and need to be taken into account in metrology experiments.

Z2Pack: Numerical implementation of hybrid Wannier centers for identifying topological materials

NASA Astrophysics Data System (ADS)

Gresch, Dominik; Autès, Gabriel; Yazyev, Oleg V.; Troyer, Matthias; Vanderbilt, David; Bernevig, B. Andrei; Soluyanov, Alexey A.

2017-02-01

The intense theoretical and experimental interest in topological insulators and semimetals has established band structure topology as a fundamental material property. Consequently, identifying band topologies has become an important, but often challenging, problem, with no exhaustive solution at the present time. In this work we compile a series of techniques, some previously known, that allow for a solution to this problem for a large set of the possible band topologies. The method is based on tracking hybrid Wannier charge centers computed for relevant Bloch states, and it works at all levels of materials modeling: continuous k .p models, tight-binding models, and ab initio calculations. We apply the method to compute and identify Chern, Z2, and crystalline topological insulators, as well as topological semimetal phases, using real material examples. Moreover, we provide a numerical implementation of this technique (the Z2Pack software package) that is ideally suited for high-throughput screening of materials databases for compounds with nontrivial topologies. We expect that our work will allow researchers to (a) identify topological materials optimal for experimental probes, (b) classify existing compounds, and (c) reveal materials that host novel, not yet described, topological states.

Including screening in van der Waals corrected density functional theory calculations: the case of atoms and small molecules physisorbed on graphene.

PubMed

Silvestrelli, Pier Luigi; Ambrosetti, Alberto

2014-03-28

The Density Functional Theory (DFT)/van der Waals-Quantum Harmonic Oscillator-Wannier function (vdW-QHO-WF) method, recently developed to include the vdW interactions in approximated DFT by combining the quantum harmonic oscillator model with the maximally localized Wannier function technique, is applied to the cases of atoms and small molecules (X=Ar, CO, H2, H2O) weakly interacting with benzene and with the ideal planar graphene surface. Comparison is also presented with the results obtained by other DFT vdW-corrected schemes, including PBE+D, vdW-DF, vdW-DF2, rVV10, and by the simpler Local Density Approximation (LDA) and semilocal generalized gradient approximation approaches. While for the X-benzene systems all the considered vdW-corrected schemes perform reasonably well, it turns out that an accurate description of the X-graphene interaction requires a proper treatment of many-body contributions and of short-range screening effects, as demonstrated by adopting an improved version of the DFT/vdW-QHO-WF method. We also comment on the widespread attitude of relying on LDA to get a rough description of weakly interacting systems.

Interacting dynamic Wannier-Stark ladder driven by a periodic pulse train

NASA Astrophysics Data System (ADS)

Hino, Ken-Ichi; Tong, Xiao Min; Toshima, Nobuyuki

2008-01-01

The electronic structures of the Floquet states of the dynamic Wannier-Stark ladder (DWSL) are examined, where the DWSL is formed by driving the biased superlattices (SLs) by the periodic pulse train (PPT) with the electric field F(t) —with time t —and the temporal period 2π/ω . For a strong F(t) , interminiband interactions, namely, the ac-Zener tunneling (ac-ZT), are predominantly caused in the DWSL. Such a system is termed the interacting DWSL. In order to understand the details of the Floquet states and the modulation patterns by alteration of a couple of the PPT laser parameters, the linear absorption spectra, αabs(ωp;ω) , of optical interband transitions invoked by the monochromatic probe laser fp(t) with the frequency ωp are calculated, where the spectra are not only linear in fp(t) but also nonlinear in F(t) . The exciton effect is not included for the sake of simplicity. For the PPT driving with unit-pulse shapes largely deviated from the square and saw-toothed profiles, the spectra show unexpected dent structures, differing a great deal from the corresponding ac-ZT-free spectra basically similar to those of the original SLs just showing the ascending steplike structure. To deepen the understanding of this anomaly, the spectra of αabs0(ωp;ω)∝∂αabs(ωp;ω)/∂ωp are also calculated, whereby the dent structures become spectral dips showing the negative absorption. It is found that such anomalous behavior is attributed to the ac-ZT between different minibands that accompanies emission/absorption of the nonzero net number of photons with Jω (with J a nonzero integer). This anomaly also shows the unusual time dependence in the dual-time optical susceptibility associated with αabs0(ωp;ω) . Moreover, the possibility of existence of the negative absorption in the more realistic excitonic spectra is speculated.

Interpretation of scanning tunneling quasiparticle interference and impurity states in cuprates

DOE PAGES

Kreisel, Andreas; Choubey, Peayush; Berlijn, Tom; ...

2015-05-27

We apply a recently developed method combining first principles based Wannier functions with solutions to the Bogoliubov–de Gennes equations to the problem of interpreting STM data in cuprate superconductors. We show that the observed images of Zn on the surface of Bi 2Sr 2CaCu 2O 8 can only be understood by accounting for the tails of the Cu Wannier functions, which include significant weight on apical O sites in neighboring unit cells. This calculation thus puts earlier crude “filter” theories on a microscopic foundation and solves a long-standing puzzle. We then study quasiparticle interference phenomena induced by out-of-plane weak potentialmore » scatterers, and show how patterns long observed in cuprates can be understood in terms of the interference of Wannier functions above the surface. Furthermore, our results show excellent agreement with experiment and enable a better understanding of novel phenomena in the cuprates via STM imaging.« less

Interpretation of scanning tunneling quasiparticle interference and impurity states in cuprates.

PubMed

Kreisel, A; Choubey, Peayush; Berlijn, T; Ku, W; Andersen, B M; Hirschfeld, P J

2015-05-29

We apply a recently developed method combining first principles based Wannier functions with solutions to the Bogoliubov-de Gennes equations to the problem of interpreting STM data in cuprate superconductors. We show that the observed images of Zn on the surface of Bi_{2}Sr_{2}CaCu_{2}O_{8} can only be understood by accounting for the tails of the Cu Wannier functions, which include significant weight on apical O sites in neighboring unit cells. This calculation thus puts earlier crude "filter" theories on a microscopic foundation and solves a long-standing puzzle. We then study quasiparticle interference phenomena induced by out-of-plane weak potential scatterers, and show how patterns long observed in cuprates can be understood in terms of the interference of Wannier functions above the surface. Our results show excellent agreement with experiment and enable a better understanding of novel phenomena in the cuprates via STM imaging.

Local electric dipole moments for periodic systems via density functional theory embedding.

PubMed

Luber, Sandra

2014-12-21

We describe a novel approach for the calculation of local electric dipole moments for periodic systems. Since the position operator is ill-defined in periodic systems, maximally localized Wannier functions based on the Berry-phase approach are usually employed for the evaluation of local contributions to the total electric dipole moment of the system. We propose an alternative approach: within a subsystem-density functional theory based embedding scheme, subset electric dipole moments are derived without any additional localization procedure, both for hybrid and non-hybrid exchange-correlation functionals. This opens the way to a computationally efficient evaluation of local electric dipole moments in (molecular) periodic systems as well as their rigorous splitting into atomic electric dipole moments. As examples, Infrared spectra of liquid ethylene carbonate and dimethyl carbonate are presented, which are commonly employed as solvents in Lithium ion batteries.

Many-Body Theory of Pyrochlore Iridates and Related Materials

NASA Astrophysics Data System (ADS)

Wang, Runzhi

In this thesis we focus on two problems. First we propose a numerical method for generating optimized Wannier functions with desired properties. Second we perform the state of the art density functional plus dynamical mean-field calculations in pyrochlore iridates, to investigate the physics induced by the cooperation of spin-orbit coupling and electron correlation. We begin with the introduction for maximally localized Wannier functions and other related extensions. Then we describe the current research in the field of spin-orbit coupling and its interplay with correlation effects, followed by a brief introduction of the `hot' materials of iridates. Before the end of the introduction, we discuss the numerical methods employed in our work, including the density functional theory; dynamical mean-field theory and its combination with the exact diagonalization impurity solver. Then we propose our approach for constructing an optimized set of Wannier functions, which is a generalization of the functionality of the classic maximal localization method put forward by Marzari and Vanderbilt. Our work is motivated by the requirement of the effective description of the local subspace of the Hamiltonian by the beyond density functional theory methods. In extensions of density functional theory such as dynamical mean-field theory, one may want highly accurate description of particular local orbitals, including correct centers and symmetries; while the basis for the remaining degrees of freedom is unimportant. Therefore, we develop the selectively localized Wannier function approach which allows for a greater localization in the selected subset of Wannier functions and at the same time allows us to fix the centers and ensure the point symmetries. Applications in real materials are presented to demonstrate the power of our approach. Next we move to the investigation of pyrochlore iridates, focussing on the metal-insulator transition and material dependence in these compounds. We

Edge-entanglement spectrum correspondence in a nonchiral topological phase and Kramers-Wannier duality

NASA Astrophysics Data System (ADS)

Ho, Wen Wei; Cincio, Lukasz; Moradi, Heidar; Gaiotto, Davide; Vidal, Guifre

2015-03-01

cut are governed by Kramers-Wannier self-dual Hamiltonians, in addition to them being Z2 symmetric, which is imposed by the topological order. Thus, by considering the Wen-plaquette model as a SET, the topological order in the bulk together with the translation invariance of the perturbations along the edge/cut imply an edge-ES correspondence at least in some finite domain in Hamiltonian space.

Dispersion interactions in Density Functional Theory

NASA Astrophysics Data System (ADS)

Andrinopoulos, Lampros; Hine, Nicholas; Mostofi, Arash

2012-02-01

Semilocal functionals in Density Functional Theory (DFT) achieve high accuracy simulating a wide range of systems, but miss the effect of dispersion (vdW) interactions, important in weakly bound systems. We study two different methods to include vdW in DFT: First, we investigate a recent approach [1] to evaluate the vdW contribution to the total energy using maximally-localized Wannier functions. Using a set of simple dimers, we show that it has a number of shortcomings that hamper its predictive power; we then develop and implement a series of improvements [2] and obtain binding energies and equilibrium geometries in closer agreement to quantum-chemical coupled-cluster calculations. Second, we implement the vdW-DF functional [3], using Soler's method [4], within ONETEP [5], a linear-scaling DFT code, and apply it to a range of systems. This method within a linear-scaling DFT code allows the simulation of weakly bound systems of larger scale, such as organic/inorganic interfaces, biological systems and implicit solvation models. [1] P. Silvestrelli, JPC A 113, 5224 (2009). [2] L. Andrinopoulos et al, JCP 135, 154105 (2011). [3] M. Dion et al, PRL 92, 246401 (2004). [4] G. Rom'an-P'erez, J.M. Soler, PRL 103, 096102 (2009). [5] C. Skylaris et al, JCP 122, 084119 (2005).

What is the valence of Mn in GaMnN?

NASA Astrophysics Data System (ADS)

Nelson, Ryky; Berlijn, Tom; Moreno, Juana; Jarrell, Mark; Ku, Wei

2014-03-01

Motivated by the potential high Curie temperature of GaMnN, we investigate the controversial Mn-valence in this diluted magnetic semiconductor. From a first-principles Wannier functions analysis of the high energy Hilbert space we find unambiguously the charge state of Mn to be close to 2 + (d5), but in a mixed spin configuration with average magnetic moments of 4 μB. Using more extended Wannier orbitals to capture the lower-energy physics, we further demonstrate the feasibility of both the effective d4 description (appropriate to deal with the local magnetic moment and Jahn-Teller distortion), and the effective d5 description (relevant to study long-range magnetic order). Our derivation highlights the general richness of low-energy sectors in interacting many-body systems and the generic need for multiple effective descriptions, and advocates for a diminished relevance of atomic valence measured by various experimental probes. This research is supported in part by LA-SiGMA, NSF Award Number #EPS-1003897. TB was supported by DOE CMCSN and as a Wigner Fellow at the Oak Ridge National Laboratory.

Natural bond orbital analysis in the ONETEP code: applications to large protein systems.

PubMed

Lee, Louis P; Cole, Daniel J; Payne, Mike C; Skylaris, Chris-Kriton

2013-03-05

First principles electronic structure calculations are typically performed in terms of molecular orbitals (or bands), providing a straightforward theoretical avenue for approximations of increasing sophistication, but do not usually provide any qualitative chemical information about the system. We can derive such information via post-processing using natural bond orbital (NBO) analysis, which produces a chemical picture of bonding in terms of localized Lewis-type bond and lone pair orbitals that we can use to understand molecular structure and interactions. We present NBO analysis of large-scale calculations with the ONETEP linear-scaling density functional theory package, which we have interfaced with the NBO 5 analysis program. In ONETEP calculations involving thousands of atoms, one is typically interested in particular regions of a nanosystem whilst accounting for long-range electronic effects from the entire system. We show that by transforming the Non-orthogonal Generalized Wannier Functions of ONETEP to natural atomic orbitals, NBO analysis can be performed within a localized region in such a way that ensures the results are identical to an analysis on the full system. We demonstrate the capabilities of this approach by performing illustrative studies of large proteins--namely, investigating changes in charge transfer between the heme group of myoglobin and its ligands with increasing system size and between a protein and its explicit solvent, estimating the contribution of electronic delocalization to the stabilization of hydrogen bonds in the binding pocket of a drug-receptor complex, and observing, in situ, the n → π* hyperconjugative interactions between carbonyl groups that stabilize protein backbones. Copyright © 2012 Wiley Periodicals, Inc.

Microscopic theory of the superconducting gap in the quasi-one-dimensional organic conductor (TMTSF) 2ClO4 : Model derivation and two-particle self-consistent analysis

NASA Astrophysics Data System (ADS)

Aizawa, Hirohito; Kuroki, Kazuhiko

2018-03-01

We present a first-principles band calculation for the quasi-one-dimensional (Q1D) organic superconductor (TMTSF) 2ClO4 . An effective tight-binding model with the TMTSF molecule to be regarded as the site is derived from a calculation based on maximally localized Wannier orbitals. We apply a two-particle self-consistent (TPSC) analysis by using a four-site Hubbard model, which is composed of the tight-binding model and an onsite (intramolecular) repulsive interaction, which serves as a variable parameter. We assume that the pairing mechanism is mediated by the spin fluctuation, and the sign of the superconducting gap changes between the inner and outer Fermi surfaces, which correspond to a d -wave gap function in a simplified Q1D model. With the parameters we adopt, the critical temperature for superconductivity estimated by the TPSC approach is approximately 1 K, which is consistent with experiment.

A Primer on Functional Analysis

ERIC Educational Resources Information Center

Yoman, Jerome

2008-01-01

This article presents principles and basic steps for practitioners to complete a functional analysis of client behavior. The emphasis is on application of functional analysis to adult mental health clients. The article includes a detailed flow chart containing all major functional diagnoses and behavioral interventions, with functional assessment…

Functional Multiple-Set Canonical Correlation Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

2012-01-01

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

Excitons in boron nitride single layer

NASA Astrophysics Data System (ADS)

Galvani, Thomas; Paleari, Fulvio; Miranda, Henrique P. C.; Molina-Sánchez, Alejandro; Wirtz, Ludger; Latil, Sylvain; Amara, Hakim; Ducastelle, François

2016-09-01

Boron nitride single layer belongs to the family of two-dimensional materials whose optical properties are currently receiving considerable attention. Strong excitonic effects have already been observed in the bulk and still stronger effects are predicted for single layers. We present here a detailed study of these properties by combining ab initio calculations and a tight-binding Wannier analysis in both real and reciprocal space. Due to the simplicity of the band structure with single valence (π ) and conduction (π*) bands the tight-binding analysis becomes quasiquantitative with only two adjustable parameters and provides tools for a detailed analysis of the exciton properties. Strong deviations from the usual hydrogenic model are evidenced. The ground-state exciton is not a genuine Frenkel exciton, but a very localized tightly bound one. The other ones are similar to those found in transition-metal dichalcogenides and, although more localized, can be described within a Wannier-Mott scheme.

Triple Photoionization of Neon and Argon Near Threshold

NASA Astrophysics Data System (ADS)

Bluett, Jaques B.; Lukić, Dragan; Sellin, Ivan A.; Whitfield, Scott B.; Wehlitz, Ralf

2003-05-01

The threshold behavior of the triple ionization cross-section of neon and argon was investigated using monochromatized synchrotron radiation and ion time-of-flight spectrometry. The Ne^3+ and Ar^3+ cross-sections are found to follow the Wannier power law(G.H. Wannier, Phys. Rev. 90), 817 (1953). consistent with a Wannier exponent of 2.162 predicted by theory. This is also consistent with the findings of Samson and Angel(J.A.R. Samson and G.C. Angel, Phys. Lett. 61), 1584 (1988). for the case of Ne. In the case of argon we find a much shorter range of validity than for neon.

Differential Item Functioning Analysis Using Rasch Item Information Functions

ERIC Educational Resources Information Center

Wyse, Adam E.; Mapuranga, Raymond

2009-01-01

Differential item functioning (DIF) analysis is a statistical technique used for ensuring the equity and fairness of educational assessments. This study formulates a new DIF analysis method using the information similarity index (ISI). ISI compares item information functions when data fits the Rasch model. Through simulations and an international…

Functional Generalized Structured Component Analysis.

PubMed

Suk, Hye Won; Hwang, Heungsun

2016-12-01

An extension of Generalized Structured Component Analysis (GSCA), called Functional GSCA, is proposed to analyze functional data that are considered to arise from an underlying smooth curve varying over time or other continua. GSCA has been geared for the analysis of multivariate data. Accordingly, it cannot deal with functional data that often involve different measurement occasions across participants and a large number of measurement occasions that exceed the number of participants. Functional GSCA addresses these issues by integrating GSCA with spline basis function expansions that represent infinite-dimensional curves onto a finite-dimensional space. For parameter estimation, functional GSCA minimizes a penalized least squares criterion by using an alternating penalized least squares estimation algorithm. The usefulness of functional GSCA is illustrated with gait data.

Functional Analysis and Treatment of Nail Biting

ERIC Educational Resources Information Center

Dufrene, Brad A.; Watson, T. Steuart; Kazmerski, Jennifer S.

2008-01-01

This study applied functional analysis methodology to nail biting exhibited by a 24-year-old female graduate student. Results from the brief functional analysis indicated variability in nail biting across assessment conditions. Functional analysis data were then used to guide treatment development and implementation. Treatment included a…

Functional Extended Redundancy Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Suk, Hye Won; Lee, Jang-Han; Moskowitz, D. S.; Lim, Jooseop

2012-01-01

We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous…

FGWAS: Functional genome wide association analysis.

PubMed

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

Electronic Structure and Transport in Solids from First Principles

NASA Astrophysics Data System (ADS)

Mustafa, Jamal Ibrahim

The focus of this dissertation is the determination of the electronic structure and trans- port properties of solids. We first review some of the theory and computational methodology used in the calculation of electronic structure and materials properties. Throughout the dissertation, we make extensive use of state-of-the-art software packages that implement density functional theory, density functional perturbation theory, and the GW approximation, in addition to specialized methods for interpolating matrix elements for extremely accurate results. The first application of the computational framework introduced is the determination of band offsets in semiconductor heterojunctions using a theory of quantum dipoles at the interface. This method is applied to the case of heterojunction formed between a new metastable phase of silicon, with a rhombohedral structure, and cubic silicon. Next, we introduce a novel method for the construction of localized Wannier functions, which we have named the optimized projection functions method (OPFM). We illustrate the method on a variety of systems and find that it can reliably construct localized Wannier functions with minimal user intervention. We further develop the OPFM to investigate a class of materials called topological insulators, which are insulating in the bulk but have conductive surface states. These properties are a result of a nontrivial topology in their band structure, which has interesting effects on the character of the Wannier functions. In the last sections of the main text, the noble metals are studied in great detail, including their electronic properties and carrier dynamics. In particular, we investigate, the Fermi surface properties of the noble metals, specifically electron-phonon scattering lifetimes, and subsequently the transport properties determined by carriers on the Fermi surface. To achieve this, a novel sampling technique is developed, with wide applicability to transport calculations

Functional analysis and treatment of diurnal bruxism.

PubMed

Lang, Russell; Davenport, Katy; Britt, Courtney; Ninci, Jennifer; Garner, Jennifer; Moore, Melissa

2013-01-01

An analogue functional analysis identified attention as a function for a 5-year-old boy's bruxism (teeth grinding). Functional communication training resulted in a reduction of bruxism and an increase in alternative mands for attention. Results were maintained 3 weeks following the intervention. © Society for the Experimental Analysis of Behavior.

Multilevel sparse functional principal component analysis.

PubMed

Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

2014-01-29

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

Origin of Transitions between Metallic and Insulating States in Simple Metals

DOE PAGES

Naumov, Ivan I.; Hemley, Russell J.

2015-04-17

Unifying principles that underlie recently discovered transitions between metallic and insulating states in elemental solids under pressure are developed. Using group theory arguments and first principles calculations, we show that the electronic properties of the phases involved in these transitions are controlled by symmetry principles not previously recognized. The valence bands in these systems are described by simple and composite band representations constructed from localized Wannier functions centered on points unoccupied by atoms, and which are not necessarily all symmetrical. The character of the Wannier functions is closely related to the degree of s-p(-d) hybridization and reflects multi-center chemical bondingmore » in these insulating states. The conditions under which an insulating state is allowed for structures having an integer number of atoms per primitive unit cell as well as re-entrant (i.e., metal-insulator-metal) transition sequences are detailed, resulting in predictions of novel behavior such as phases having three-dimensional Dirac-like points. The general principles developed are tested and applied to the alkali and alkaline earth metals, including elements where high-pressure insulating phases have been identified or reported (e.g., Li, Na, and Ca).« less

An exploration of function analysis and function allocation in the commercial flight domain

NASA Technical Reports Server (NTRS)

Mcguire, James C.; Zich, John A.; Goins, Richard T.; Erickson, Jeffery B.; Dwyer, John P.; Cody, William J.; Rouse, William B.

1991-01-01

The applicability is explored of functional analysis methods to support cockpit design. Specifically, alternative techniques are studied for ensuring an effective division of responsibility between the flight crew and automation. A functional decomposition is performed of the commercial flight domain to provide the information necessary to support allocation decisions and demonstrate methodology for allocating functions to flight crew or to automation. The function analysis employed 'bottom up' and 'top down' analyses and demonstrated the comparability of identified functions, using the 'lift off' segment of the 'take off' phase as a test case. The normal flight mission and selected contingencies were addressed. Two alternative methods for using the functional description in the allocation of functions between man and machine were investigated. The two methods were compared in order to ascertain their relative strengths and weaknesses. Finally, conclusions were drawn regarding the practical utility of function analysis methods.

Functional Analysis in Virtual Environments

ERIC Educational Resources Information Center

Vasquez, Eleazar, III; Marino, Matthew T.; Donehower, Claire; Koch, Aaron

2017-01-01

Functional analysis (FA) is an assessment procedure involving the systematic manipulation of an individual's environment to determine why a target behavior is occurring. An analog FA provides practitioners the opportunity to manipulate variables in a controlled environment and formulate a hypothesis for the function of a behavior. In previous…

Functional Relationships and Regression Analysis.

ERIC Educational Resources Information Center

Preece, Peter F. W.

1978-01-01

Using a degenerate multivariate normal model for the distribution of organismic variables, the form of least-squares regression analysis required to estimate a linear functional relationship between variables is derived. It is suggested that the two conventional regression lines may be considered to describe functional, not merely statistical,…

Consumer Surplus, Demand Functions, and Policy Analysis,

DTIC Science & Technology

1983-06-01

ARD-AL758 865 CONSUMER SURPLUS DEMAND FUNCTIONS AND POLICY ANALYSIS 1/2 (U) RAND CORP SANTA MONICA CA F CANM JUN 83 RAND/R-3848-RC UNCLASSIFIED F/O 5...8217 - * 2, Consumer Surplus, Demand Functions, and Policy Analysis Frank Camm OCFILE COEYI b0 loo Thi! d Ci rr.i h,13 bea~n approvedS i i l ot p...ui.- r~aoz an~d sale; its (5 06 VP1 d’ *. . . * . ~ - V * * . R-3048-RC Consumer Surplus, Demand Functions, and Policy Analysis Frank Caomm June 1983

Large-Scale Hybrid Density Functional Theory Calculations in the Condensed-Phase: Ab Initio Molecular Dynamics in the Isobaric-Isothermal Ensemble

NASA Astrophysics Data System (ADS)

Ko, Hsin-Yu; Santra, Biswajit; Distasio, Robert A., Jr.; Wu, Xifan; Car, Roberto

Hybrid functionals are known to alleviate the self-interaction error in density functional theory (DFT) and provide a more accurate description of the electronic structure of molecules and materials. However, hybrid DFT in the condensed-phase has a prohibitively high associated computational cost which limits their applicability to large systems of interest. In this work, we present a general-purpose order(N) implementation of hybrid DFT in the condensed-phase using Maximally localized Wannier function; this implementation is optimized for massively parallel computing architectures. This algorithm is used to perform large-scale ab initio molecular dynamics simulations of liquid water, ice, and aqueous ionic solutions. We have performed simulations in the isothermal-isobaric ensemble to quantify the effects of exact exchange on the equilibrium density properties of water at different thermodynamic conditions. We find that the anomalous density difference between ice I h and liquid water at ambient conditions as well as the enthalpy differences between ice I h, II, and III phases at the experimental triple point (238 K and 20 Kbar) are significantly improved using hybrid DFT over previous estimates using the lower rungs of DFT This work has been supported by the Department of Energy under Grants No. DE-FG02-05ER46201 and DE-SC0008626.

Functional analysis screening for multiple topographies of problem behavior.

PubMed

Bell, Marlesha C; Fahmie, Tara A

2018-04-23

The current study evaluated a screening procedure for multiple topographies of problem behavior in the context of an ongoing functional analysis. Experimenters analyzed the function of a topography of primary concern while collecting data on topographies of secondary concern. We used visual analysis to predict the function of secondary topographies and a subsequent functional analysis to test those predictions. Results showed that a general function was accurately predicted for five of six (83%) secondary topographies. A specific function was predicted and supported for a subset of these topographies. The experimenters discuss the implication of these results for clinicians who have limited time for functional assessment. © 2018 Society for the Experimental Analysis of Behavior.

Dynamical mean-field theory on the real-frequency axis: p -d hybridization and atomic physics in SrMnO3

NASA Astrophysics Data System (ADS)

Bauernfeind, Daniel; Triebl, Robert; Zingl, Manuel; Aichhorn, Markus; Evertz, Hans Gerd

2018-03-01

We investigate the electronic structure of SrMnO3 with density functional theory plus dynamical mean-field theory (DMFT). Within this scheme the selection of the correlated subspace and the construction of the corresponding Wannier functions is a crucial step. Due to the crystal-field splitting of the Mn-3 d orbitals and their separation from the O -2 p bands, SrMnO3 is a material where on first sight a three-band d -only model should be sufficient. However, in the present work we demonstrate that the resulting spectrum is considerably influenced by the number of correlated orbitals and the number of bands included in the Wannier function construction. For example, in a d -d p model we observe a splitting of the t2 g lower Hubbard band into a more complex spectral structure, not observable in d -only models. To illustrate these high-frequency differences we employ the recently developed fork tensor product state (FTPS) impurity solver, as it provides the necessary spectral resolution on the real-frequency axis. We find that the spectral structure of a five-band d -d p model is in good agreement with PES and XAS experiments. Our results demonstrate that the FTPS solver is capable of performing full five-band DMFT calculations directly on the real-frequency axis.

Theoretical and computational studies of excitons in conjugated polymers

NASA Astrophysics Data System (ADS)

Barford, William; Bursill, Robert J.; Smith, Richard W.

2002-09-01

We present a theoretical and computational analysis of excitons in conjugated polymers. We use a tight-binding model of π-conjugated electrons, with 1/r interactions for large r. In both the weak-coupling limit (defined by W>>U) and the strong-coupling limit (defined by W<Wannier excitons, i.e., conduction-band electrons bound to valence-band holes. Singlet and triplet excitons whose relative wave functions are odd under a reflection of the relative coordinate are degenerate. Thus, the 2 1A+g and 1 3A-g states are degenerate in this limit. (2) In the strong-coupling limit the bound states are Mott-Hubbard excitons, i.e., particles in the upper Hubbard band bound to holes in the lower Hubbard band. These bound states occur in doublets of even and odd parity excitons. Triplet excitons are magnons bound to the singlet excitons, and hence are degenerate with their singlet counterparts. (3) In the intermediate-coupling regime Mott-Wannier excitons are the more appropriate description for large dimerization, while for the undimerized chain Mott-Hubbard excitons are the correct description. For dimerizations relevant to polyacetylene and polydiacetylene both Mott-Hubbard and Mott-Wannier excitons are present. (4) For all coupling strengths an infinite number of bound states exist for 1/r interactions for an infinite polymer. As a result of the discreteness of the lattice and the restrictions on the exciton wave functions in one dimension, the progression of states does not follow

Functional data analysis of sleeping energy expenditure.

PubMed

Lee, Jong Soo; Zakeri, Issa F; Butte, Nancy F

2017-01-01

Adequate sleep is crucial during childhood for metabolic health, and physical and cognitive development. Inadequate sleep can disrupt metabolic homeostasis and alter sleeping energy expenditure (SEE). Functional data analysis methods were applied to SEE data to elucidate the population structure of SEE and to discriminate SEE between obese and non-obese children. Minute-by-minute SEE in 109 children, ages 5-18, was measured in room respiration calorimeters. A smoothing spline method was applied to the calorimetric data to extract the true smoothing function for each subject. Functional principal component analysis was used to capture the important modes of variation of the functional data and to identify differences in SEE patterns. Combinations of functional principal component analysis and classifier algorithm were used to classify SEE. Smoothing effectively removed instrumentation noise inherent in the room calorimeter data, providing more accurate data for analysis of the dynamics of SEE. SEE exhibited declining but subtly undulating patterns throughout the night. Mean SEE was markedly higher in obese than non-obese children, as expected due to their greater body mass. SEE was higher among the obese than non-obese children (p<0.01); however, the weight-adjusted mean SEE was not statistically different (p>0.1, after post hoc testing). Functional principal component scores for the first two components explained 77.8% of the variance in SEE and also differed between groups (p = 0.037). Logistic regression, support vector machine or random forest classification methods were able to distinguish weight-adjusted SEE between obese and non-obese participants with good classification rates (62-64%). Our results implicate other factors, yet to be uncovered, that affect the weight-adjusted SEE of obese and non-obese children. Functional data analysis revealed differences in the structure of SEE between obese and non-obese children that may contribute to disruption of

Entropy for quantum pure states and quantum H theorem

NASA Astrophysics Data System (ADS)

Han, Xizhi; Wu, Biao

2015-06-01

We construct a complete set of Wannier functions that are localized at both given positions and momenta. This allows us to introduce the quantum phase space, onto which a quantum pure state can be mapped unitarily. Using its probability distribution in quantum phase space, we define an entropy for a quantum pure state. We prove an inequality regarding the long-time behavior of our entropy's fluctuation. For a typical initial state, this inequality indicates that our entropy can relax dynamically to a maximized value and stay there most of time with small fluctuations. This result echoes the quantum H theorem proved by von Neumann [Zeitschrift für Physik 57, 30 (1929), 10.1007/BF01339852]. Our entropy is different from the standard von Neumann entropy, which is always zero for quantum pure states. According to our definition, a system always has bigger entropy than its subsystem even when the system is described by a pure state. As the construction of the Wannier basis can be implemented numerically, the dynamical evolution of our entropy is illustrated with an example.

Relations among Functional Systems in Behavior Analysis

PubMed Central

Thompson, Travis

2007-01-01

This paper proposes that an organism's integrated repertoire of operant behavior has the status of a biological system, similar to other biological systems, like the nervous, cardiovascular, or immune systems. Evidence from a number of sources indicates that the distinctions between biological and behavioral events is often misleading, engendering counterproductive explanatory controversy. A good deal of what is viewed as biological (often thought to be inaccessible or hypothetical) can become publicly measurable variables using currently available and developing technologies. Moreover, such endogenous variables can serve as establishing operations, discriminative stimuli, conjoint mediating events, and maintaining consequences within a functional analysis of behavior and need not lead to reductionistic explanation. I suggest that explanatory misunderstandings often arise from conflating different levels of analysis and that behavior analysis can extend its reach by identifying variables operating within a functional analysis that also serve functions in other biological systems. PMID:17575907

Accelerated and Airy-Bloch oscillations

NASA Astrophysics Data System (ADS)

Longhi, Stefano

2016-09-01

A quantum particle subjected to a constant force undergoes an accelerated motion following a parabolic path, which differs from the classical motion just because of wave packet spreading (quantum diffusion). However, when a periodic potential is added (such as in a crystal) the particle undergoes Bragg scattering and an oscillatory (rather than accelerated) motion is found, corresponding to the famous Bloch oscillations (BOs). Here, we introduce an exactly-solvable quantum Hamiltonian model, corresponding to a generalized Wannier-Stark Hamiltonian Ĥ, in which a quantum particle shows an intermediate dynamical behavior, namely an oscillatory motion superimposed to an accelerated one. Such a novel dynamical behavior is referred to as accelerated BOs. Analytical expressions of the spectrum, improper eigenfunctions and propagator of the generalized Wannier-Stark Hamiltonian Ĥ are derived. Finally, it is shown that acceleration and quantum diffusion in the generalized Wannier-Stark Hamiltonian are prevented for Airy wave packets, which undergo a periodic breathing dynamics that can be referred to as Airy-Bloch oscillations.

Alterations to Functional Analysis Methodology to Clarify the Functions of Low Rate, High Intensity Problem Behavior

PubMed Central

Davis, Barbara J; Schmidt, Jonathan; Bowman, Lynn G; Boelter, Eric W

2012-01-01

Current research provides few suggestions for modifications to functional analysis procedures to accommodate low rate, high intensity problem behavior. This study examined the results of the extended duration functional analysis procedures of Kahng, Abt, and Schonbachler (2001) with six children admitted to an inpatient hospital for the treatment of severe problem behavior. Results of initial functional analyses (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) were inconclusive for all children because of low levels of responding. The altered functional analyses, which changed multiple variables including the duration of the functional analysis (i.e., 6 or 7 hrs), yielded clear behavioral functions for all six participants. These results add additional support for the utility of an altered analysis of low rate, high intensity problem behavior when standard functional analyses do not yield differentiated results. PMID:23326628

Alterations to functional analysis methodology to clarify the functions of low rate, high intensity problem behavior.

PubMed

Davis, Barbara J; Kahng, Sungwoo; Schmidt, Jonathan; Bowman, Lynn G; Boelter, Eric W

2012-01-01

Current research provides few suggestions for modifications to functional analysis procedures to accommodate low rate, high intensity problem behavior. This study examined the results of the extended duration functional analysis procedures of Kahng, Abt, and Schonbachler (2001) with six children admitted to an inpatient hospital for the treatment of severe problem behavior. Results of initial functional analyses (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) were inconclusive for all children because of low levels of responding. The altered functional analyses, which changed multiple variables including the duration of the functional analysis (i.e., 6 or 7 hrs), yielded clear behavioral functions for all six participants. These results add additional support for the utility of an altered analysis of low rate, high intensity problem behavior when standard functional analyses do not yield differentiated results.

Frequency-phase analysis of resting-state functional MRI

PubMed Central

Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert

2017-01-01

We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience. PMID:28272522

INFANT SIGN TRAINING AND FUNCTIONAL ANALYSIS

PubMed Central

Normand, Matthew P; Machado, Mychal A; Hustyi, Kristin M; Morley, Allison J

2011-01-01

We taught manual signs to typically developing infants using a reversal design and caregiver-nominated stimuli. We delivered the stimuli on a time-based schedule during baseline. During the intervention, we used progressive prompting and reinforcement, described by Thompson et al. (2004, 2007), to establish mands. Following sign training, we conducted functional analyses and verified that the signs functioned as mands. These results provide preliminary validation for the verbal behavior functional analysis methodology and further evidence of the functional independence of verbal operants. PMID:21709786

(LaTiO3)n/(LaVO3)n as a model system for unconventional charge transfer and polar metallicity

NASA Astrophysics Data System (ADS)

Weng, Yakui; Zhang, Jun-Jie; Gao, Bin; Dong, Shuai

At interfaces between oxide materials, lattice and electronic reconstructions always play important roles in exotic phenomena. In this study, the density-functional theory and maximally localized Wannier functions are employed to investigate the (LaTiO3)n/(LaVO3)n magnetic superlattices. By considering lattice distortion and dimensional effect, many interesting interfacial physics have been found in the n = 1 superlattice, e.g. magnetic phase transition, unconventional charge transfer, and metal-insulator transition. In addition, the compatibility among the polar structure, ferrimagnetism, and metallicity is predicted in the n = 2 superlattice.

Electromodulation spectroscopy of excitons in simple cubic TlCl and TlBr

DOE Office of Scientific and Technical Information (OSTI.GOV)

McClelland, J.F.; Lynch, D.W.

1979-03-15

Transmission and electromodulated transmission spectra have been measured in the direct Wannier exciton region for TlCl and TlBr. The spectra were obtained at a sample temperature between 5 and 6 K for a range of applied electric fields. The data have been reduced to obtain the electric-field-induced changes in the dielectric function and compared in detail to the calculations of Blossey. The experimental results support the trends predicted by the calculations.

[The structural functional analysis of functioning of day-hospitals of the Russian Federation].

PubMed

2012-01-01

The article deals with the results of structural functional analysis of functioning of day-hospitals in the Russian Federation. The dynamic analysis is presented concerning day-hospitals' network, capacity; financial support, beds stock structure, treated patients structure, volumes of diagnostic tests and curative procedures. The need in developing of population medical care in conditions of day-hospitals is demonstrated.

Trial-Based Functional Analysis and Functional Communication Training in an Early Childhood Setting

ERIC Educational Resources Information Center

Lambert, Joseph M.; Bloom, Sarah E.; Irvin, Jennifer

2012-01-01

Problem behavior is common in early childhood special education classrooms. Functional communication training (FCT; Carr & Durand, 1985) may reduce problem behavior but requires identification of its function. The trial-based functional analysis (FA) is a method that can be used to identify problem behavior function in schools. We conducted…

Left atrial function: evaluation by strain analysis

PubMed Central

Gan, Gary C. H.; Ferkh, Aaisha; Boyd, Anita

2018-01-01

The left atrium has an important role in modulating left ventricular filling and is an important biomarker of cardiovascular disease and adverse cardiovascular outcomes. While previously left atrial (LA) size was utilised, the role of LA function as a biomarker is increasingly being evaluated, both independently and also in combination with LA size. Strain analysis has been utilised for evaluation of LA function and can be measured throughout the cardiac cycle, thereby enabling the evaluation of LA reservoir, conduit and contractile function. Strain evaluates myocardial deformation while strain rate examines the rate of change in strain. This review will focus on the various types of strain analysis for evaluation of LA function, alterations in LA strain in physiological and pathologic states that alter LA function and finally evaluate its utility as a prognostic marker. PMID:29541609

Functional Analysis in Public Schools: A Summary of 90 Functional Analyses

ERIC Educational Resources Information Center

Mueller, Michael M.; Nkosi, Ajamu; Hine, Jeffrey F.

2011-01-01

Several review and epidemiological studies have been conducted over recent years to inform behavior analysts of functional analysis outcomes. None to date have closely examined demographic and clinical data for functional analyses conducted exclusively in public school settings. The current paper presents a data-based summary of 90 functional…

Correspondence between Traditional Models of Functional Analysis and a Functional Analysis of Manding Behavior

ERIC Educational Resources Information Center

LaRue, Robert H.; Sloman, Kimberly N.; Weiss, Mary Jane; Delmolino, Lara; Hansford, Amy; Szalony, Jill; Madigan, Ryan; Lambright, Nathan M.

2011-01-01

Functional analysis procedures have been effectively used to determine the maintaining variables for challenging behavior and subsequently develop effective interventions. However, fear of evoking dangerous topographies of maladaptive behavior and concerns for reinforcing infrequent maladaptive behavior present challenges for people working in…

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

Functional Analysis of Metabolomics Data.

PubMed

Chagoyen, Mónica; López-Ibáñez, Javier; Pazos, Florencio

2016-01-01

Metabolomics aims at characterizing the repertory of small chemical compounds in a biological sample. As it becomes more massive and larger sets of compounds are detected, a functional analysis is required to convert these raw lists of compounds into biological knowledge. The most common way of performing such analysis is "annotation enrichment analysis," also used in transcriptomics and proteomics. This approach extracts the annotations overrepresented in the set of chemical compounds arisen in a given experiment. Here, we describe the protocols for performing such analysis as well as for visualizing a set of compounds in different representations of the metabolic networks, in both cases using free accessible web tools.

Improving information retrieval in functional analysis.

PubMed

Rodriguez, Juan C; González, Germán A; Fresno, Cristóbal; Llera, Andrea S; Fernández, Elmer A

2016-12-01

Transcriptome analysis is essential to understand the mechanisms regulating key biological processes and functions. The first step usually consists of identifying candidate genes; to find out which pathways are affected by those genes, however, functional analysis (FA) is mandatory. The most frequently used strategies for this purpose are Gene Set and Singular Enrichment Analysis (GSEA and SEA) over Gene Ontology. Several statistical methods have been developed and compared in terms of computational efficiency and/or statistical appropriateness. However, whether their results are similar or complementary, the sensitivity to parameter settings, or possible bias in the analyzed terms has not been addressed so far. Here, two GSEA and four SEA methods and their parameter combinations were evaluated in six datasets by comparing two breast cancer subtypes with well-known differences in genetic background and patient outcomes. We show that GSEA and SEA lead to different results depending on the chosen statistic, model and/or parameters. Both approaches provide complementary results from a biological perspective. Hence, an Integrative Functional Analysis (IFA) tool is proposed to improve information retrieval in FA. It provides a common gene expression analytic framework that grants a comprehensive and coherent analysis. Only a minimal user parameter setting is required, since the best SEA/GSEA alternatives are integrated. IFA utility was demonstrated by evaluating four prostate cancer and the TCGA breast cancer microarray datasets, which showed its biological generalization capabilities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Space station functional relationships analysis

NASA Technical Reports Server (NTRS)

Tullis, Thomas S.; Bied, Barbra R.

1988-01-01

A systems engineering process is developed to assist Space Station designers to understand the underlying operational system of the facility so that it can be physically arranged and configured to support crew productivity. The study analyzes the operational system proposed for the Space Station in terms of mission functions, crew activities, and functional relationships in order to develop a quantitative model for evaluation of interior layouts, configuration, and traffic analysis for any Station configuration. Development of the model involved identification of crew functions, required support equipment, criteria of assessing functional relationships, and tools for analyzing functional relationship matrices, as well as analyses of crew transition frequency, sequential dependencies, support equipment requirements, potential for noise interference, need for privacy, and overall compatability of functions. The model can be used for analyzing crew functions for the Initial Operating Capability of the Station and for detecting relationships among these functions. Note: This process (FRA) was used during Phase B design studies to test optional layouts of the Space Station habitat module. The process is now being automated as a computer model for use in layout testing of the Space Station laboratory modules during Phase C.

Brief functional analysis and treatment of a vocal tic.

PubMed

Watson, T S; Sterling, H E

1998-01-01

This study sought to extend functional methodology to the assessment and treatment of habits. After a descriptive assessment indicated that coughing occurred while eating, a brief functional analysis suggested that social attention was the maintaining variable. Results demonstrated that treatment, derived from the assessment and analysis data, rapidly eliminated the cough. We discuss the appropriateness of using functional analysis procedures for deriving treatments for habits in a clinical setting.

Functional Analysis and Reduction of Inappropriate Spitting

ERIC Educational Resources Information Center

Carter, Stacy L.; Wheeler, John J.

2007-01-01

Functional analysis was used to determine the possible function of inappropriate spitting behavior of an adult woman who had been diagnosed with profound mental retardation. Results of an initial descriptive assessment indicated a possible attention function and led to an attention-based intervention, which was deemed ineffective at reducing the…

Functional Proteomic Analysis of Human NucleolusD⃞

PubMed Central

Scherl, Alexander; Couté, Yohann; Déon, Catherine; Callé, Aleth; Kindbeiter, Karine; Sanchez, Jean-Charles; Greco, Anna; Hochstrasser, Denis; Diaz, Jean-Jacques

2002-01-01

The notion of a “plurifunctional” nucleolus is now well established. However, molecular mechanisms underlying the biological processes occurring within this nuclear domain remain only partially understood. As a first step in elucidating these mechanisms we have carried out a proteomic analysis to draw up a list of proteins present within nucleoli of HeLa cells. This analysis allowed the identification of 213 different nucleolar proteins. This catalog complements that of the 271 proteins obtained recently by others, giving a total of ∼350 different nucleolar proteins. Functional classification of these proteins allowed outlining several biological processes taking place within nucleoli. Bioinformatic analyses permitted the assignment of hypothetical functions for 43 proteins for which no functional information is available. Notably, a role in ribosome biogenesis was proposed for 31 proteins. More generally, this functional classification reinforces the plurifunctional nature of nucleoli and provides convincing evidence that nucleoli may play a central role in the control of gene expression. Finally, this analysis supports the recent demonstration of a coupling of transcription and translation in higher eukaryotes. PMID:12429849

GOMA: functional enrichment analysis tool based on GO modules

PubMed Central

Huang, Qiang; Wu, Ling-Yun; Wang, Yong; Zhang, Xiang-Sun

2013-01-01

Analyzing the function of gene sets is a critical step in interpreting the results of high-throughput experiments in systems biology. A variety of enrichment analysis tools have been developed in recent years, but most output a long list of significantly enriched terms that are often redundant, making it difficult to extract the most meaningful functions. In this paper, we present GOMA, a novel enrichment analysis method based on the new concept of enriched functional Gene Ontology (GO) modules. With this method, we systematically revealed functional GO modules, i.e., groups of functionally similar GO terms, via an optimization model and then ranked them by enrichment scores. Our new method simplifies enrichment analysis results by reducing redundancy, thereby preventing inconsistent enrichment results among functionally similar terms and providing more biologically meaningful results. PMID:23237213

TWave: High-Order Analysis of Functional MRI

PubMed Central

Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.

2011-01-01

The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected

Analyzing coastal environments by means of functional data analysis

NASA Astrophysics Data System (ADS)

Sierra, Carlos; Flor-Blanco, Germán; Ordoñez, Celestino; Flor, Germán; Gallego, José R.

2017-07-01

Here we used Functional Data Analysis (FDA) to examine particle-size distributions (PSDs) in a beach/shallow marine sedimentary environment in Gijón Bay (NW Spain). The work involved both Functional Principal Components Analysis (FPCA) and Functional Cluster Analysis (FCA). The grainsize of the sand samples was characterized by means of laser dispersion spectroscopy. Within this framework, FPCA was used as a dimension reduction technique to explore and uncover patterns in grain-size frequency curves. This procedure proved useful to describe variability in the structure of the data set. Moreover, an alternative approach, FCA, was applied to identify clusters and to interpret their spatial distribution. Results obtained with this latter technique were compared with those obtained by means of two vector approaches that combine PCA with CA (Cluster Analysis). The first method, the point density function (PDF), was employed after adapting a log-normal distribution to each PSD and resuming each of the density functions by its mean, sorting, skewness and kurtosis. The second applied a centered-log-ratio (clr) to the original data. PCA was then applied to the transformed data, and finally CA to the retained principal component scores. The study revealed functional data analysis, specifically FPCA and FCA, as a suitable alternative with considerable advantages over traditional vector analysis techniques in sedimentary geology studies.

What can one learn about material structure given a single first-principles calculation?

NASA Astrophysics Data System (ADS)

Rajen, Nicholas; Coh, Sinisa

2018-05-01

We extract a variable X from electron orbitals Ψn k and energies En k in the parent high-symmetry structure of a wide range of complex oxides: perovskites, rutiles, pyrochlores, and cristobalites. Even though calculation was done only in the parent structure, with no distortions, we show that X dictates material's true ground-state structure. We propose using Wannier functions to extract concealed variables such as X both for material structure prediction and for high-throughput approaches.

Discrete-Trial Functional Analysis and Functional Communication Training with Three Adults with Intellectual Disabilities and Problem Behavior

ERIC Educational Resources Information Center

Chezan, Laura C.; Drasgow, Erik; Martin, Christian A.

2014-01-01

We conducted a sequence of two studies on the use of discrete-trial functional analysis and functional communication training. First, we used discrete-trial functional analysis (DTFA) to identify the function of problem behavior in three adults with intellectual disabilities and problem behavior. Results indicated clear patterns of problem…

False Positive Functional Analysis Results as a Contributor of Treatment Failure during Functional Communication Training

ERIC Educational Resources Information Center

Mann, Amanda J.; Mueller, Michael M.

2009-01-01

Research has shown that functional analysis results are beneficial for treatment selection because they identify reinforcers for severe behavior that can then be used to reinforce replacement behaviors either differentially or noncontingently. Theoretically then, if a reinforcer is identified in a functional analysis erroneously, a well researched…

Uncertainty importance analysis using parametric moment ratio functions.

PubMed

Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

2014-02-01

This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

On Special Functions in the Context of Clifford Analysis

NASA Astrophysics Data System (ADS)

Malonek, H. R.; Falcão, M. I.

2010-09-01

Considering the foundation of Quaternionic Analysis by R. Fueter and his collaborators in the beginning of the 1930s as starting point of Clifford Analysis, we can look back to 80 years of work in this field. However the interest in multivariate analysis using Clifford algebras only started to grow significantly in the 70s. Since then a great amount of papers on Clifford Analysis referring different classes of Special Functions have appeared. This situation may have been triggered by a more systematic treatment of monogenic functions by their multiple series development derived from Gegenbauer or associated Legendre polynomials (and not only by their integral representation). Also approaches to Special Functions by means of algebraic methods, either Lie algebras or through Lie groups and symmetric spaces gained by that time importance and influenced their treatment in Clifford Analysis. In our talk we will rely on the generalization of the classical approach to Special Functions through differential equations with respect to the hypercomplex derivative, which is a more recently developed tool in Clifford Analysis. In this context special attention will be payed to the role of Special Functions as intermediator between continuous and discrete mathematics. This corresponds to a more recent trend in combinatorics, since it has been revealed that many algebraic structures have hidden combinatorial underpinnings.

Polarization asymmetry in two-electron photodetachment - A cogent test of the ionization threshold law

NASA Technical Reports Server (NTRS)

Temkin, A.; Bhatia, A. K.

1988-01-01

A very sensitive test of the electron-atom ionization threshold law is suggested: for spin-aligned heavy negative ions it consists of measuring the polarization asymmetry A(PA) coming from double detachment by left- versus right-circularly polarized light. The respective yields are worked out for the Te(-) (5p)5 2P(3/2) ion. The Coulomb-dipole theory predicts A(PA) to be the ratio of two oscillating functions in sharp contrast to any power law (specifically that of Wannier, 1953) for which the ratio is expected to be a smooth function of energy.

Electronic and magnetic properties of magnetoelectric compound Ca2CoSi2O7: An ab initio study

NASA Astrophysics Data System (ADS)

Chakraborty, Jayita

2018-05-01

The detailed first principle density functional theory calculations are carried out to investigate the electronic and magnetic properties of magnetoelectric compound Ca2CoSi2O7. The magnetic properties of this system are analyzed by calculating various hopping integrals as well as exchange interactions and deriving the relevant spin Hamiltonian. The dominant exchange path is visualized with Wannier functions plotting. Only intra planer nearest neighbor exchange interaction is strong in this system. The magnetocrystalline anisotropy is calculated for this system, and the results of the calculation reveal that the spin quantization axis lies in the ab plane.

Magnon localization and Bloch oscillations in finite Heisenberg spin chains in an inhomogeneous magnetic field.

PubMed

Kosevich, Yuriy A; Gann, Vladimir V

2013-06-19

We study the localization of magnon states in finite defect-free Heisenberg spin-1/2 ferromagnetic chains placed in an inhomogeneous magnetic field with a constant spatial gradient. Continuous transformation from the extended magnon states to the localized Wannier-Zeeman states in a finite spin chain placed in an inhomogeneous field is described both analytically and numerically. We describe for the first time the non-monotonic dependence of the energy levels of magnons, both long and short wavelength, on the magnetic field gradient, which is a consequence of magnon localization in a finite spin chain. We show that, in contrast to the destruction of the magnon band and the establishment of the Wannier-Stark ladder in a vanishingly small field gradient in an infinite chain, the localization of magnon states at the chain ends preserves the memory of the magnon band. Essentially, the localization at the lower- or higher-field chain end resembles the localization of the positive- or negative-effective-mass band quasiparticles. We also show how the beat dynamics of coherent superposition of extended spin waves in a finite chain in a homogeneous or weakly inhomogeneous field transforms into magnon Bloch oscillations of the superposition of localized Wannier-Zeeman states in a strongly inhomogeneous field. We provide a semiclassical description of the magnon Bloch oscillations and show that the correspondence between the quantum and semiclassical descriptions is most accurate for Bloch oscillations of the magnon coherent states, which are built from a coherent superposition of a large number of the nearest-neighbour Wannier-Zeeman states.

Trial-Based Functional Analysis Informs Treatment for Vocal Scripting.

PubMed

Rispoli, Mandy; Brodhead, Matthew; Wolfe, Katie; Gregori, Emily

2018-05-01

Research on trial-based functional analysis has primarily focused on socially maintained challenging behaviors. However, procedural modifications may be necessary to clarify ambiguous assessment results. The purposes of this study were to evaluate the utility of iterative modifications to trial-based functional analysis on the identification of putative reinforcement and subsequent treatment for vocal scripting. For all participants, modifications to the trial-based functional analysis identified a primary function of automatic reinforcement. The structure of the trial-based format led to identification of social attention as an abolishing operation for vocal scripting. A noncontingent attention treatment was evaluated using withdrawal designs for each participant. This noncontingent attention treatment resulted in near zero levels of vocal scripting for all participants. Implications for research and practice are presented.

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

2017-06-01

Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

Function modeling: improved raster analysis through delayed reading and function raster datasets

Treesearch

John S. Hogland; Nathaniel M. Anderson; J .Greg Jones

2013-01-01

Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space, often limiting the types of analyses that can be performed. To address this issue, we have developed Function Modeling. Function Modeling is a new modeling framework that streamlines the...

[A functional analysis of healthcare auditors' skills in Venezuela, 2008].

PubMed

Chirinos-Muñoz, Mónica S

2010-10-01

Using functional analysis for identifying the basic, working, specific and generic skills and values which a health service auditor must have. Implementing the functional analysis technique with 10 experts, identifying specific, basic, generic skills and values by means of deductive logic. A functional map was obtained which started by establishing a key purpose based on improving healthcare and service quality from which three key functions emerged. The main functions and skills' units were then broken down into the competitive elements defining what a health service auditor is able to do. This functional map (following functional analysis methodology) shows in detail the simple and complex tasks which a healthcare auditor should apply in the workplace, adopting a forward management approach for improving healthcare and health service quality. This methodology, expressing logical-deductive awareness raising, provides expert consensual information validating each element regarding overall skills.

Towards tests of quark-hadron duality with functional analysis and spectral function data

NASA Astrophysics Data System (ADS)

Boito, Diogo; Caprini, Irinel

2017-04-01

The presence of terms that violate quark-hadron duality in the expansion of QCD Green's functions is a generally accepted fact. Recently, a new approach was proposed for the study of duality violations (DVs), which exploits the existence of a rigorous lower bound on the functional distance, measured in a certain norm, between a "true" correlator and its approximant calculated theoretically along a contour in the complex energy plane. In the present paper, we pursue the investigation of functional-analysis-based tests towards their application to real spectral function data. We derive a closed analytic expression for the minimal functional distance based on the general weighted L2 norm and discuss its relation with the distance measured in the L∞ norm. Using fake data sets obtained from a realistic toy model in which we allow for covariances inspired from the publicly available ALEPH spectral functions, we obtain, by Monte Carlo simulations, the statistical distribution of the strength parameter that measures the magnitude of the DV term added to the usual operator product expansion. The results show that, if the region with large errors near the end point of the spectrum in τ decays is excluded, the functional-analysis-based tests using either L2 or L∞ norms are able to detect, in a statistically significant way, the presence of DVs in realistic spectral function pseudodata.

Functional Analysis and Intervention for Breath Holding.

ERIC Educational Resources Information Center

Kern, Lee; And Others

1995-01-01

A functional analysis of breath-holding episodes in a 7-year-old girl with severe mental retardation and Cornelia-de-Lange syndrome indicated that breath holding served an operant function, primarily to gain access to attention. Use of extinction, scheduled attention, and a picture card communication system decreased breath holding. (Author/SW)

The Necessity of Functional Analysis for Space Exploration Programs

NASA Technical Reports Server (NTRS)

Morris, A. Terry; Breidenthal, Julian C.

2011-01-01

As NASA moves toward expanded commercial spaceflight within its human exploration capability, there is increased emphasis on how to allocate responsibilities between government and commercial organizations to achieve coordinated program objectives. The practice of program-level functional analysis offers an opportunity for improved understanding of collaborative functions among heterogeneous partners. Functional analysis is contrasted with the physical analysis more commonly done at the program level, and is shown to provide theoretical performance, risk, and safety advantages beneficial to a government-commercial partnership. Performance advantages include faster convergence to acceptable system solutions; discovery of superior solutions with higher commonality, greater simplicity and greater parallelism by substituting functional for physical redundancy to achieve robustness and safety goals; and greater organizational cohesion around program objectives. Risk advantages include avoidance of rework by revelation of some kinds of architectural and contractual mismatches before systems are specified, designed, constructed, or integrated; avoidance of cost and schedule growth by more complete and precise specifications of cost and schedule estimates; and higher likelihood of successful integration on the first try. Safety advantages include effective delineation of must-work and must-not-work functions for integrated hazard analysis, the ability to formally demonstrate completeness of safety analyses, and provably correct logic for certification of flight readiness. The key mechanism for realizing these benefits is the development of an inter-functional architecture at the program level, which reveals relationships between top-level system requirements that would otherwise be invisible using only a physical architecture. This paper describes the advantages and pitfalls of functional analysis as a means of coordinating the actions of large heterogeneous organizations

Models in palaeontological functional analysis

PubMed Central

Anderson, Philip S. L.; Bright, Jen A.; Gill, Pamela G.; Palmer, Colin; Rayfield, Emily J.

2012-01-01

Models are a principal tool of modern science. By definition, and in practice, models are not literal representations of reality but provide simplifications or substitutes of the events, scenarios or behaviours that are being studied or predicted. All models make assumptions, and palaeontological models in particular require additional assumptions to study unobservable events in deep time. In the case of functional analysis, the degree of missing data associated with reconstructing musculoskeletal anatomy and neuronal control in extinct organisms has, in the eyes of some scientists, rendered detailed functional analysis of fossils intractable. Such a prognosis may indeed be realized if palaeontologists attempt to recreate elaborate biomechanical models based on missing data and loosely justified assumptions. Yet multiple enabling methodologies and techniques now exist: tools for bracketing boundaries of reality; more rigorous consideration of soft tissues and missing data and methods drawing on physical principles that all organisms must adhere to. As with many aspects of science, the utility of such biomechanical models depends on the questions they seek to address, and the accuracy and validity of the models themselves. PMID:21865242

Use of Analog Functional Analysis in Assessing the Function of Mealtime Behavior Problems.

ERIC Educational Resources Information Center

Girolami, Peter A.; Scotti, Joseph R.

2001-01-01

This study applied the methodology of an analog experimental (functional) analysis of behavior to the specific interaction between parents and three children with mental retardation exhibiting food refusal and related mealtime problems. Analog results were highly consistent with other forms of functional assessment data, including interviews,…

Regional Morphology Analysis Package (RMAP): Empirical Orthogonal Function Analysis, Background and Examples

DTIC Science & Technology

2007-10-01

1984. Complex principal component analysis : Theory and examples. Journal of Climate and Applied Meteorology 23: 1660-1673. Hotelling, H. 1933...Sediments 99. ASCE: 2,566-2,581. Von Storch, H., and A. Navarra. 1995. Analysis of climate variability. Applications of statistical techniques. Berlin...ERDC TN-SWWRP-07-9 October 2007 Regional Morphology Empirical Analysis Package (RMAP): Orthogonal Function Analysis , Background and Examples by

Holographic maps of quasiparticle interference

NASA Astrophysics Data System (ADS)

Dalla Torre, Emanuele G.; He, Yang; Demler, Eugene

2016-11-01

The analysis of Fourier-transformed scanning tunnelling microscopy images with subatomic resolution is a common tool for studying the properties of quasiparticle excitations in strongly correlated materials. Although Fourier amplitudes are generally complex valued, earlier analysis primarily focused on their absolute values. Their complex phases were often deemed random, and thus irrelevant, due to the unknown positions of the impurities in the sample. Here we show how to factor out these random phases by analysing overlaps between Fourier amplitudes that differ by reciprocal lattice vectors. The resulting holographic maps provide important and previously unknown information about the electronic structures. When applied to superconducting cuprates, our method solves a long-standing puzzle of the dichotomy between equivalent wavevectors. We show that d-wave Wannier functions of the conduction band provide a natural explanation for experimental results that were interpreted as evidence for competing unconventional charge modulations. Our work opens a new pathway to identify the nature of electronic states in scanning tunnelling microscopy.

GPU accelerated dynamic functional connectivity analysis for functional MRI data.

PubMed

Akgün, Devrim; Sakoğlu, Ünal; Esquivel, Johnny; Adinoff, Bryon; Mete, Mutlu

2015-07-01

Recent advances in multi-core processors and graphics card based computational technologies have paved the way for an improved and dynamic utilization of parallel computing techniques. Numerous applications have been implemented for the acceleration of computationally-intensive problems in various computational science fields including bioinformatics, in which big data problems are prevalent. In neuroimaging, dynamic functional connectivity (DFC) analysis is a computationally demanding method used to investigate dynamic functional interactions among different brain regions or networks identified with functional magnetic resonance imaging (fMRI) data. In this study, we implemented and analyzed a parallel DFC algorithm based on thread-based and block-based approaches. The thread-based approach was designed to parallelize DFC computations and was implemented in both Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) programming platforms. Another approach developed in this study to better utilize CUDA architecture is the block-based approach, where parallelization involves smaller parts of fMRI time-courses obtained by sliding-windows. Experimental results showed that the proposed parallel design solutions enabled by the GPUs significantly reduce the computation time for DFC analysis. Multicore implementation using OpenMP on 8-core processor provides up to 7.7× speed-up. GPU implementation using CUDA yielded substantial accelerations ranging from 18.5× to 157× speed-up once thread-based and block-based approaches were combined in the analysis. Proposed parallel programming solutions showed that multi-core processor and CUDA-supported GPU implementations accelerated the DFC analyses significantly. Developed algorithms make the DFC analyses more practical for multi-subject studies with more dynamic analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Biosensors for functional food safety and analysis.

PubMed

Lavecchia, Teresa; Tibuzzi, Arianna; Giardi, Maria Teresa

2010-01-01

The importance of safety and functionality analysis of foodstuffs and raw materials is supported by national legislations and European Union (EU) directives concerning not only the amount of residues of pollutants and pathogens but also the activity and content of food additives and the health claims stated on their labels. In addition, consumers' awareness of the impact of functional foods' on their well-being and their desire for daily healthcare without the intake pharmaceuticals has immensely in recent years. Within this picture, the availability of fast, reliable, low cost control systems to measure the content and the quality of food additives and nutrients with health claims becomes mandatory, to be used by producers, consumers and the governmental bodies in charge of the legal supervision of such matters. This review aims at describing the most important methods and tools used for food analysis, starting with the classical methods (e.g., gas-chromatography GC, high performance liquid chromatography HPLC) and moving to the use of biosensors-novel biological material-based equipments. Four types of bio-sensors, among others, the novel photosynthetic proteins-based devices which are more promising and common in food analysis applications, are reviewed. A particular highlight on biosensors for the emerging market of functional foods is given and the most widely applied functional components are reviewed with a comprehensive analysis of papers published in the last three years; this report discusses recent trends for sensitive, fast, repeatable and cheap measurements, focused on the detection of vitamins, folate (folic acid), zinc (Zn), iron (Fe), calcium (Ca), fatty acids (in particular Omega 3), phytosterols and phytochemicals. A final market overview emphasizes some practical aspects ofbiosensor applications.

FUNCTIONAL ANALYSIS AND TREATMENT OF COPROPHAGIA

PubMed Central

Ing, Anna D; Roane, Henry S; Veenstra, Rebecca A

2011-01-01

In the current investigation, functional analysis results suggested that coprophagia, the ingestion of fecal matter, was maintained by automatic reinforcement. Providing noncontingent access to alternative stimuli decreased coprophagia, and the intervention was generalized to two settings. PMID:21541128

Functional Interaction Network Construction and Analysis for Disease Discovery.

PubMed

Wu, Guanming; Haw, Robin

2017-01-01

Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

Subcontract Report: Diffusion Mechanisms and Bond Dynamics in Solid Electrolyte Ion-Conductors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zevgolis, A.; Hall, A.; Alvez, T.

2017-10-03

We employ first-principles molecular dynamics simulations and Maximally Localized Wannier Function (MLWF) analysis to explore how halide substitution and nano-phase microstructures affect diffusivity, through the activation energy barrier - E a and D 0, in the solid electrolyte Li 3InBr 6-xCl x. We find that nano-phase microstructures with x=3 (50-50 Br-Cl) mixed composition have a higher diffusivity compared to x=2 and x=3 solid solutions. There is a positive linear relationship between ln(D 0.) and E a, which suggests that for superionic conductivity optimizing both the activation energy and the D 0 is important. Bond frustration due to mismatch in crystalmore » geometry and ideal coordination number leads to especially high diffusivity through a high D 0 in the x=3 composition.« less

Biosignals Analysis for Kidney Function Effect Analysis of Fennel Aromatherapy

PubMed Central

Kim, Bong-Hyun; Cho, Dong-Uk; Seo, Ssang-Hee

2015-01-01

Human effort in order to enjoy a healthy life is diverse. IT technology to these analyzes, the results of development efforts, it has been applied. Therefore, I use the care and maintenance diagnostic health management and prevention than treatment. In particular, the aromatherapy treatment easy to use without the side effects there is no irritation, are widely used in modern society. In this paper, we measured the aroma effect by applying a biosignal analysis techniques; an experiment was performed to analyze. In particular, we design methods and processes of research based on the theory aroma that affect renal function. Therefore, in this paper, measuring the biosignals and after fennel aromatherapy treatment prior to the enforcement of the mutual comparison, through the analysis, studies were carried out to analyze the effect of fennel aromatherapy therapy on kidney function. PMID:25977696

Mott transition and suppression of orbital fluctuations in orthorhombic 3d1 perovskites.

PubMed

Pavarini, E; Biermann, S; Poteryaev, A; Lichtenstein, A I; Georges, A; Andersen, O K

2004-04-30

Using t(2g) Wannier functions, a low-energy Hamiltonian is derived for orthorhombic 3d(1) transition-metal oxides. Electronic correlations are treated with a new implementation of dynamical mean-field theory for noncubic systems. Good agreement with photoemission data is obtained. The interplay of correlation effects and cation covalency (GdFeO3-type distortions) is found to suppress orbital fluctuations in LaTiO3 and even more in YTiO3, and to favor the transition to the insulating state.

A Quantitative Review of Functional Analysis Procedures in Public School Settings

ERIC Educational Resources Information Center

Solnick, Mark D.; Ardoin, Scott P.

2010-01-01

Functional behavioral assessments can consist of indirect, descriptive and experimental procedures, such as a functional analysis. Although the research contains numerous examples demonstrating the effectiveness of functional analysis procedures, experimental conditions are often difficult to implement in classroom settings and analog conditions…

Advances in the indirect, descriptive, and experimental approaches to the functional analysis of problem behavior.

PubMed

Wightman, Jade; Julio, Flávia; Virués-Ortega, Javier

2014-05-01

Experimental functional analysis is an assessment methodology to identify the environmental factors that maintain problem behavior in individuals with developmental disabilities and in other populations. Functional analysis provides the basis for the development of reinforcement-based approaches to treatment. This article reviews the procedures, validity, and clinical implementation of the methodological variations of functional analysis and function-based interventions. We present six variations of functional analysis methodology in addition to the typical functional analysis: brief functional analysis, single-function tests, latency-based functional analysis, functional analysis of precursors, and trial-based functional analysis. We also present the three general categories of function-based interventions: extinction, antecedent manipulation, and differential reinforcement. Functional analysis methodology is a valid and efficient approach to the assessment of problem behavior and the selection of treatment strategies.

A Comparison of Functional Behavioral Assessment and Functional Analysis Methodology among Students with Mild Disabilities

ERIC Educational Resources Information Center

Lewis, Timothy J.; Mitchell, Barbara S.; Harvey, Kristin; Green, Ambra; McKenzie, Jennifer

2015-01-01

Functional behavioral assessment (FBA) and functional analyses (FA) are grounded in the applied behavior analysis principle that posits problem behavior is functionally related to the environment in which it occurs and is maintained by either providing access to reinforcing outcomes or allowing the individual to avoid or escape that which they…

[Prematurity: longitudinal analysis of executive functions].

PubMed

Sastre-Riba, S

2009-02-27

Understanding cognitive development requires an interdisciplinary and neuropsychological approach. Executive functions facilitates cognitive activity and they are related to progressive cerebral configuration during pregnancy and infancy. One of the aims of the actual neuropsychology is the ontogeny of executive functions and their capacity to explain differential and normative developmental trends, specially because of its consequences on mental flexibility, monitoring, planning and cognitive control; they are also essential for good performance at school. The incidence of developmental risk factors as prematurity could affect long-term executive functioning expressed in learning difficulties or behavioral control. We studied, comparatively and longitudinally, the individual activity on objects displayed by typical babies (n = 25), and preterm babies (n = 10) from 1.5 to 2 years-old. Applying systematic observational methodology, spontaneous babies' activity is registered. Double intra and inter-group analysis compare the data from the resolution of a non-verbal task through a multifaceted design. Results obtained show us differential pattern of early executive functioning among the groups studied. The growth of executive functioning is showed, too, through the ages studied for every group.

Hand function evaluation: a factor analysis study.

PubMed

Jarus, T; Poremba, R

1993-05-01

The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

Linking Brief Functional Analysis to Intervention Design in General Education Settings

ERIC Educational Resources Information Center

Ishuin, Tifanie

2009-01-01

This study focused on the utility and applicability of brief functional analysis in general education settings. The purpose of the study was to first identify the environmental variables maintaining noncompliance through a brief functional analysis, and then to design and implement a functionally equivalent intervention. The participant exhibited…

Assessing the Social Acceptability of the Functional Analysis of Problem Behavior

ERIC Educational Resources Information Center

Langthorne, Paul; McGill, Peter

2011-01-01

Although the clinical utility of the functional analysis is well established, its social acceptability has received minimal attention. The current study assessed the social acceptability of functional analysis procedures among 10 parents and 3 teachers of children who had recently received functional analyses. Participants completed a 9-item…

Applying Cognitive Work Analysis to Time Critical Targeting Functionality

DTIC Science & Technology

2004-10-01

Cognitive Task Analysis , CTA, Cognitive Task Analysis , Human Factors, GUI, Graphical User Interface, Heuristic Evaluation... Cognitive Task Analysis MITRE Briefing January 2000 Dynamic Battle Management Functional Architecture 3-1 Section 3 Human Factors...clear distinction between Cognitive Work Analysis (CWA) and Cognitive Task Analysis (CTA), therefore this document will refer to these

First-Principles Framework to Compute Sum-Frequency Generation Vibrational Spectra of Semiconductors and Insulators.

PubMed

Wan, Quan; Galli, Giulia

2015-12-11

We present a first-principles framework to compute sum-frequency generation (SFG) vibrational spectra of semiconductors and insulators. The method is based on density functional theory and the use of maximally localized Wannier functions to compute the response to electric fields, and it includes the effect of electric field gradients at surfaces. In addition, it includes quadrupole contributions to SFG spectra, thus enabling the verification of the dipole approximation, whose validity determines the surface specificity of SFG spectroscopy. We compute the SFG spectra of ice I_{h} basal surfaces and identify which spectra components are affected by bulk contributions. Our results are in good agreement with experiments at low temperature.

Turkish Special Education Teachers' Implementation of Functional Analysis in Classroom Settings

ERIC Educational Resources Information Center

Erbas, Dilek; Yucesoy, Serife; Turan, Yasemin; Ostrosky, Michaelene M.

2006-01-01

Three Turkish special education teachers conducted a functional analysis to identify variables that might initiate or maintain the problem behaviors of three children with developmental disabilities. The analysis procedures were conducted in natural classroom settings. In Phase 1, following initial training in functional analysis procedures, the…

Functional analysis of tight junction organization.

PubMed

DiBona, D R

1985-01-01

The functional basis of tight junction design has been examined from the point of view that this rate-limiting barrier to paracellular transport is a multicompartment system. Review of the osmotic sensitivity of these structures points to the need for this sort of analysis for meaningful correlation of structure and function under a range of conditions. A similar conclusion is drawn with respect to results from voltage-clamping protocols where reversal of spontaneous transmural potential difference elicits parallel changes in both structure and function in much the same way as does reversal of naturally occurring osmotic gradients. In each case, it becomes necessary to regard the junction as a functionally polarized structure to account for observations of its rectifying properties. Lastly, the details of experimentally-induced junction deformation are examined in light of current theories of its organization; arguments are presented in favor of the view that the primary components of intramembranous organization (as viewed with freeze-fracture techniques) are lipidic rather than proteinaceous.

Functional Parallel Factor Analysis for Functions of One- and Two-dimensional Arguments.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Timmerman, Marieke E

2018-03-01

Parallel factor analysis (PARAFAC) is a useful multivariate method for decomposing three-way data that consist of three different types of entities simultaneously. This method estimates trilinear components, each of which is a low-dimensional representation of a set of entities, often called a mode, to explain the maximum variance of the data. Functional PARAFAC permits the entities in different modes to be smooth functions or curves, varying over a continuum, rather than a collection of unconnected responses. The existing functional PARAFAC methods handle functions of a one-dimensional argument (e.g., time) only. In this paper, we propose a new extension of functional PARAFAC for handling three-way data whose responses are sequenced along both a two-dimensional domain (e.g., a plane with x- and y-axis coordinates) and a one-dimensional argument. Technically, the proposed method combines PARAFAC with basis function expansion approximations, using a set of piecewise quadratic finite element basis functions for estimating two-dimensional smooth functions and a set of one-dimensional basis functions for estimating one-dimensional smooth functions. In a simulation study, the proposed method appeared to outperform the conventional PARAFAC. We apply the method to EEG data to demonstrate its empirical usefulness.

Classwide Functional Analysis and Treatment of Preschoolers' Disruptive Behavior

ERIC Educational Resources Information Center

Poole, Veena Y.; Dufrene, Brad A.; Sterling, Heather E.; Tingstrom, Daniel H.; Hardy, Christina M.

2012-01-01

Relatively few functional assessment and intervention studies have been conducted in preschool classrooms with children of typical development who engage in high incidence problem behaviors. Moreover, limited studies have used functional assessment procedures with the class as the unit of analysis. This study included functional analyses and a…

A Top Level Analysis of Training Management Functions.

ERIC Educational Resources Information Center

Ackerson, Jack

1995-01-01

Discusses how to conduct a top-level analysis of training management functions to identify problems within a training system resulting from rapid growth, the acquisition of new departments, or mergers. The data gathering process and analyses are explained, training management functions and activities are described, and root causes and solutions…

Industrial entrepreneurial network: Structural and functional analysis

NASA Astrophysics Data System (ADS)

Medvedeva, M. A.; Davletbaev, R. H.; Berg, D. B.; Nazarova, J. J.; Parusheva, S. S.

2016-12-01

Structure and functioning of two model industrial entrepreneurial networks are investigated in the present paper. One of these networks is forming when implementing an integrated project and consists of eight agents, which interact with each other and external environment. The other one is obtained from the municipal economy and is based on the set of the 12 real business entities. Analysis of the networks is carried out on the basis of the matrix of mutual payments aggregated over the certain time period. The matrix is created by the methods of experimental economics. Social Network Analysis (SNA) methods and instruments were used in the present research. The set of basic structural characteristics was investigated: set of quantitative parameters such as density, diameter, clustering coefficient, different kinds of centrality, and etc. They were compared with the random Bernoulli graphs of the corresponding size and density. Discovered variations of random and entrepreneurial networks structure are explained by the peculiarities of agents functioning in production network. Separately, were identified the closed exchange circuits (cyclically closed contours of graph) forming an autopoietic (self-replicating) network pattern. The purpose of the functional analysis was to identify the contribution of the autopoietic network pattern in its gross product. It was found that the magnitude of this contribution is more than 20%. Such value allows using of the complementary currency in order to stimulate economic activity of network agents.

Extrapolation of Functions of Many Variables by Means of Metric Analysis

NASA Astrophysics Data System (ADS)

Kryanev, Alexandr; Ivanov, Victor; Romanova, Anastasiya; Sevastianov, Leonid; Udumyan, David

2018-02-01

The paper considers a problem of extrapolating functions of several variables. It is assumed that the values of the function of m variables at a finite number of points in some domain D of the m-dimensional space are given. It is required to restore the value of the function at points outside the domain D. The paper proposes a fundamentally new method for functions of several variables extrapolation. In the presented paper, the method of extrapolating a function of many variables developed by us uses the interpolation scheme of metric analysis. To solve the extrapolation problem, a scheme based on metric analysis methods is proposed. This scheme consists of two stages. In the first stage, using the metric analysis, the function is interpolated to the points of the domain D belonging to the segment of the straight line connecting the center of the domain D with the point M, in which it is necessary to restore the value of the function. In the second stage, based on the auto regression model and metric analysis, the function values are predicted along the above straight-line segment beyond the domain D up to the point M. The presented numerical example demonstrates the efficiency of the method under consideration.

Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2017-11-01

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10 -6 , corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

Dipolar correlations and the dielectric permittivity of water.

PubMed

Sharma, Manu; Resta, Raffaele; Car, Roberto

2007-06-15

The static dielectric properties of liquid and solid water are investigated within linear response theory in the context of ab initio molecular dynamics. Using maximally localized Wannier functions to treat the macroscopic polarization we formulate a first-principles, parameter-free, generalization of Kirkwood's phenomenological theory. Our calculated static permittivity is in good agreement with experiment. Two effects of the hydrogen bonds, i.e., a significant increase of the average local moment and a local alignment of the molecular dipoles, contribute in almost equal measure to the unusually large dielectric constant of water.

Oscillator strengths of the optical transitions in a semiconductor superlattice under an electric field

NASA Astrophysics Data System (ADS)

Tronc, P.

1992-04-01

The oscillator strengths of the optical transitions in a semiconductor superlattice under an electric field parallel to the growth axis can be calculated using a perturbative model with Bloch envelope functions. The applied electric field and the electron-hole interaction inducing formation of indirect excitons both induce strength asymmetry between the oblique +p and -p transitions of the Wannier-Stark ladder. Features of the photocurrent spectra recorded at low temperature can be accounted for by the present model in a very simple manner. Les forces d'oscillateur des transitions optiques dans un superréseau semiconducteur soumis à un champ électrique parallèle à la direction de croissance, peuvent être calculées à l'aide d'un modèle de perturbation avec des fonctions enveloppes de Bloch. Le champ électrique appliqué ainsi que l'interaction électron-trou, qui induit la formation d'excitons indirects, entraînent une asymétrie entre les forces d'oscillateur des transitions +p et -p dans l'échelle de Wannier-Stark. Certaines caractéristiques des spectres de photocourant enregistrés à basse température peuvent être prévues d'une manière très simple.

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

FADTTS: functional analysis of diffusion tensor tract statistics.

PubMed

Zhu, Hongtu; Kong, Linglong; Li, Runze; Styner, Martin; Gerig, Guido; Lin, Weili; Gilmore, John H

2011-06-01

The aim of this paper is to present a functional analysis of a diffusion tensor tract statistics (FADTTS) pipeline for delineating the association between multiple diffusion properties along major white matter fiber bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these white matter tract properties in various diffusion tensor imaging studies. The FADTTS integrates five statistical tools: (i) a multivariate varying coefficient model for allowing the varying coefficient functions in terms of arc length to characterize the varying associations between fiber bundle diffusion properties and a set of covariates, (ii) a weighted least squares estimation of the varying coefficient functions, (iii) a functional principal component analysis to delineate the structure of the variability in fiber bundle diffusion properties, (iv) a global test statistic to test hypotheses of interest, and (v) a simultaneous confidence band to quantify the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FADTTS. We apply FADTTS to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment. FADTTS can be used to facilitate the understanding of normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. The advantages of FADTTS compared with the other existing approaches are that they are capable of modeling the structured inter-subject variability, testing the joint effects, and constructing their simultaneous confidence bands. However, FADTTS is not crucial for estimation and reduces to the functional analysis method for the single measure. Copyright © 2011 Elsevier Inc. All rights reserved.

Functional sequencing read annotation for high precision microbiome analysis

PubMed Central

Zhu, Chengsheng; Miller, Maximilian; Marpaka, Srinayani; Vaysberg, Pavel; Rühlemann, Malte C; Wu, Guojun; Heinsen, Femke-Anouska; Tempel, Marie; Zhao, Liping; Lieb, Wolfgang; Franke, Andre; Bromberg, Yana

2018-01-01

Abstract The vast majority of microorganisms on Earth reside in often-inseparable environment-specific communities—microbiomes. Meta-genomic/-transcriptomic sequencing could reveal the otherwise inaccessible functionality of microbiomes. However, existing analytical approaches focus on attributing sequencing reads to known genes/genomes, often failing to make maximal use of available data. We created faser (functional annotation of sequencing reads), an algorithm that is optimized to map reads to molecular functions encoded by the read-correspondent genes. The mi-faser microbiome analysis pipeline, combining faser with our manually curated reference database of protein functions, accurately annotates microbiome molecular functionality. mi-faser’s minutes-per-microbiome processing speed is significantly faster than that of other methods, allowing for large scale comparisons. Microbiome function vectors can be compared between different conditions to highlight environment-specific and/or time-dependent changes in functionality. Here, we identified previously unseen oil degradation-specific functions in BP oil-spill data, as well as functional signatures of individual-specific gut microbiome responses to a dietary intervention in children with Prader–Willi syndrome. Our method also revealed variability in Crohn's Disease patient microbiomes and clearly distinguished them from those of related healthy individuals. Our analysis highlighted the microbiome role in CD pathogenicity, demonstrating enrichment of patient microbiomes in functions that promote inflammation and that help bacteria survive it. PMID:29194524

Streamflow characterization using functional data analysis of the Potomac River

NASA Astrophysics Data System (ADS)

Zelmanow, A.; Maslova, I.; Ticlavilca, A. M.; McKee, M.

2013-12-01

Flooding and droughts are extreme hydrological events that affect the United States economically and socially. The severity and unpredictability of flooding has caused billions of dollars in damage and the loss of lives in the eastern United States. In this context, there is an urgent need to build a firm scientific basis for adaptation by developing and applying new modeling techniques for accurate streamflow characterization and reliable hydrological forecasting. The goal of this analysis is to use numerical streamflow characteristics in order to classify, model, and estimate the likelihood of extreme events in the eastern United States, mainly the Potomac River. Functional data analysis techniques are used to study yearly streamflow patterns, with the extreme streamflow events characterized via functional principal component analysis. These methods are merged with more classical techniques such as cluster analysis, classification analysis, and time series modeling. The developed functional data analysis approach is used to model continuous streamflow hydrographs. The forecasting potential of this technique is explored by incorporating climate factors to produce a yearly streamflow outlook.

Receiver function analysis applied to refraction survey data

NASA Astrophysics Data System (ADS)

Subaru, T.; Kyosuke, O.; Hitoshi, M.

2008-12-01

For the estimation of the thickness of oceanic crust or petrophysical investigation of subsurface material, refraction or reflection seismic exploration is one of the methods frequently practiced. These explorations use four-component (x,y,z component of acceleration and pressure) seismometer, but only compressional wave or vertical component of seismometers tends to be used in the analyses. Hence, it is needed to use shear wave or lateral component of seismograms for more precise investigation to estimate the thickness of oceanic crust. Receiver function is a function at a place that can be used to estimate the depth of velocity interfaces by receiving waves from teleseismic signal including shear wave. Receiver function analysis uses both vertical and horizontal components of seismograms and deconvolves the horizontal with the vertical to estimate the spectral difference of P-S converted waves arriving after the direct P wave. Once the phase information of the receiver function is obtained, then one can estimate the depth of the velocity interface. This analysis has advantage in the estimation of the depth of velocity interface including Mohorovicic discontinuity using two components of seismograms when P-to-S converted waves are generated at the interface. Our study presents results of the preliminary study using synthetic seismograms. First, we use three types of geological models that are composed of a single sediment layer, a crust layer, and a sloped Moho, respectively, for underground sources. The receiver function can estimate the depth and shape of Moho interface precisely for the three models. Second, We applied this method to synthetic refraction survey data generated not by earthquakes but by artificial sources on the ground or sea surface. Compressional seismic waves propagate under the velocity interface and radiate converted shear waves as well as at the other deep underground layer interfaces. However, the receiver function analysis applied to the

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

ProbFAST: Probabilistic functional analysis system tool.

PubMed

Silva, Israel T; Vêncio, Ricardo Z N; Oliveira, Thiago Y K; Molfetta, Greice A; Silva, Wilson A

2010-03-30

The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.

ProbFAST: Probabilistic Functional Analysis System Tool

PubMed Central

2010-01-01

Background The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. Results We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. Conclusions ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast. PMID:20353576

The most common technologies and tools for functional genome analysis.

PubMed

Gasperskaja, Evelina; Kučinskas, Vaidutis

2017-01-01

Since the sequence of the human genome is complete, the main issue is how to understand the information written in the DNA sequence. Despite numerous genome-wide studies that have already been performed, the challenge to determine the function of genes, gene products, and also their interaction is still open. As changes in the human genome are highly likely to cause pathological conditions, functional analysis is vitally important for human health. For many years there have been a variety of technologies and tools used in functional genome analysis. However, only in the past decade there has been rapid revolutionizing progress and improvement in high-throughput methods, which are ranging from traditional real-time polymerase chain reaction to more complex systems, such as next-generation sequencing or mass spectrometry. Furthermore, not only laboratory investigation, but also accurate bioinformatic analysis is required for reliable scientific results. These methods give an opportunity for accurate and comprehensive functional analysis that involves various fields of studies: genomics, epigenomics, proteomics, and interactomics. This is essential for filling the gaps in the knowledge about dynamic biological processes at both cellular and organismal level. However, each method has both advantages and limitations that should be taken into account before choosing the right method for particular research in order to ensure successful study. For this reason, the present review paper aims to describe the most frequent and widely-used methods for the comprehensive functional analysis.

Evaluation of the utility of a discrete-trial functional analysis in early intervention classrooms.

PubMed

Kodak, Tiffany; Fisher, Wayne W; Paden, Amber; Dickes, Nitasha

2013-01-01

We evaluated a discrete-trial functional analysis implemented by regular classroom staff in a classroom setting. The results suggest that the discrete-trial functional analysis identified a social function for each participant and may require fewer staff than standard functional analysis procedures. © Society for the Experimental Analysis of Behavior.

Partial correlation-based functional connectivity analysis for functional near-infrared spectroscopy signals

NASA Astrophysics Data System (ADS)

Akın, Ata

2017-12-01

A theoretical framework, a partial correlation-based functional connectivity (PC-FC) analysis to functional near-infrared spectroscopy (fNIRS) data, is proposed. This is based on generating a common background signal from a high passed version of fNIRS data averaged over all channels as the regressor in computing the PC between pairs of channels. This approach has been employed to real data collected during a Stroop task. The results show a strong significance in the global efficiency (GE) metric computed by the PC-FC analysis for neutral, congruent, and incongruent stimuli (NS, CS, IcS; GEN=0.10±0.009, GEC=0.11±0.01, GEIC=0.13±0.015, p=0.0073). A positive correlation (r=0.729 and p=0.0259) is observed between the interference of reaction times (incongruent-neutral) and interference of GE values (GEIC-GEN) computed from [HbO] signals.

Robust extraction of functional signals from gene set analysis using a generalized threshold free scoring function

PubMed Central

2009-01-01

Background A central task in contemporary biosciences is the identification of biological processes showing response in genome-wide differential gene expression experiments. Two types of analysis are common. Either, one generates an ordered list based on the differential expression values of the probed genes and examines the tail areas of the list for over-representation of various functional classes. Alternatively, one monitors the average differential expression level of genes belonging to a given functional class. So far these two types of method have not been combined. Results We introduce a scoring function, Gene Set Z-score (GSZ), for the analysis of functional class over-representation that combines two previous analysis methods. GSZ encompasses popular functions such as correlation, hypergeometric test, Max-Mean and Random Sets as limiting cases. GSZ is stable against changes in class size as well as across different positions of the analysed gene list in tests with randomized data. GSZ shows the best overall performance in a detailed comparison to popular functions using artificial data. Likewise, GSZ stands out in a cross-validation of methods using split real data. A comparison of empirical p-values further shows a strong difference in favour of GSZ, which clearly reports better p-values for top classes than the other methods. Furthermore, GSZ detects relevant biological themes that are missed by the other methods. These observations also hold when comparing GSZ with popular program packages. Conclusion GSZ and improved versions of earlier methods are a useful contribution to the analysis of differential gene expression. The methods and supplementary material are available from the website http://ekhidna.biocenter.helsinki.fi/users/petri/public/GSZ/GSZscore.html. PMID:19775443

Computational analysis of microRNA function in heart development.

PubMed

Liu, Ganqiang; Ding, Min; Chen, Jiajia; Huang, Jinyan; Wang, Haiyun; Jing, Qing; Shen, Bairong

2010-09-01

Emerging evidence suggests that specific spatio-temporal microRNA (miRNA) expression is required for heart development. In recent years, hundreds of miRNAs have been discovered. In contrast, functional annotations are available only for a very small fraction of these regulatory molecules. In order to provide a global perspective for the biologists who study the relationship between differentially expressed miRNAs and heart development, we employed computational analysis to uncover the specific cellular processes and biological pathways targeted by miRNAs in mouse heart development. Here, we utilized Gene Ontology (GO) categories, KEGG Pathway, and GeneGo Pathway Maps as a gene functional annotation system for miRNA target enrichment analysis. The target genes of miRNAs were found to be enriched in functional categories and pathway maps in which miRNAs could play important roles during heart development. Meanwhile, we developed miRHrt (http://sysbio.suda.edu.cn/mirhrt/), a database aiming to provide a comprehensive resource of miRNA function in regulating heart development. These computational analysis results effectively illustrated the correlation of differentially expressed miRNAs with cellular functions and heart development. We hope that the identified novel heart development-associated pathways and the database presented here would facilitate further understanding of the roles and mechanisms of miRNAs in heart development.

Functional data analysis of sleeping energy expenditure

USDA-ARS?s Scientific Manuscript database

Adequate sleep is crucial during childhood for metabolic health, and physical and cognitive development. Inadequate sleep can disrupt metabolic homeostasis and alter sleeping energy expenditure (SEE). Functional data analysis methods were applied to SEE data to elucidate the population structure of ...

Response functions for neutron skyshine analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gui, A.A.; Shultis, J.K.; Faw, R.E.

1997-02-01

Neutron and associated secondary photon line-beam response functions (LBRFs) for point monodirectional neutron sources are generated using the MCNP Monte Carlo code for use in neutron skyshine analysis employing the integral line-beam method. The LBRFs are evaluated at 14 neutron source energies ranging from 0.01 to 14 MeV and at 18 emission angles from 1 to 170 deg, as measured from the source-to-detector axis. The neutron and associated secondary photon conical-beam response functions (CBRFs) for azimuthally symmetric neutron sources are also evaluated at 13 neutron source energies in the same energy range and at 13 polar angles of source collimationmore » from 1 to 89 deg. The response functions are approximated by an empirical three-parameter function of the source-to-detector distance. These response function approximations are available for a source-to-detector distance up to 2,500 m and, for the first time, give dose equivalent responses that are required for modern radiological assessments. For the CBRFs, ground correction factors for neutrons and secondary photons are calculated and also approximated by empirical formulas for use in air-over-ground neutron skyshine problems with azimuthal symmetry. In addition, simple procedures are proposed for humidity and atmospheric density corrections.« less

Evaluation of the Utility of a Discrete-Trial Functional Analysis in Early Intervention Classrooms

ERIC Educational Resources Information Center

Kodak, Tiffany; Fisher, Wayne W.; Paden, Amber; Dickes, Nitasha

2013-01-01

We evaluated a discrete-trial functional analysis implemented by regular classroom staff in a classroom setting. The results suggest that the discrete-trial functional analysis identified a social function for each participant and may require fewer staff than standard functional analysis procedures.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

A Systematic Review of Brief Functional Analysis Methodology with Typically Developing Children

ERIC Educational Resources Information Center

Gardner, Andrew W.; Spencer, Trina D.; Boelter, Eric W.; DuBard, Melanie; Jennett, Heather K.

2012-01-01

Brief functional analysis (BFA) is an abbreviated assessment methodology derived from traditional extended functional analysis methods. BFAs are often conducted when time constraints in clinics, schools or homes are of concern. While BFAs have been used extensively to identify the function of problem behavior for children with disabilities, their…

Epistasis analysis for quantitative traits by functional regression model.

PubMed

Zhang, Futao; Boerwinkle, Eric; Xiong, Momiao

2014-06-01

The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study. © 2014 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.

Home health care cost-function analysis

PubMed Central

Hay, Joel W.; Mandes, George

1984-01-01

An exploratory home health care (HHC) cost-function model is estimated using State rate-setting data for the 74 traditional (nonprofit) Connecticut agencies. The analysis demonstrates U-shaped average costs curves for agencies' provision of skilled nursing visits, with substantial diseconomies of scale in the observable range. It is determined from the estimated cost function that the sample representative agency is providing fewer visits than optimal, and its marginal cost is significantly below average cost. The finding that an agency's costs are predominantly related to output levels, with little systematic variation due to other agency or patient characteristics, suggests that the economic inefficiency in a cost-based HHC reimbursement policy may be substantial. PMID:10310596

Discrete-Trial Functional Analysis and Functional Communication Training with Three Individuals with Autism and Severe Problem Behavior

ERIC Educational Resources Information Center

Schmidt, Jonathan D.; Drasgow, Erik; Halle, James W.; Martin, Christian A.; Bliss, Sacha A.

2014-01-01

Discrete-trial functional analysis (DTFA) is an experimental method for determining the variables maintaining problem behavior in the context of natural routines. Functional communication training (FCT) is an effective method for replacing problem behavior, once identified, with a functionally equivalent response. We implemented these procedures…

Functional Analysis and Treatment of Aggression Maintained by Preferred Conversational Topics

ERIC Educational Resources Information Center

Roscoe, Eileen M.; Kindle, Arianne E.; Pence, Sacha T.

2010-01-01

After an initial functional analysis of a participant's aggression showed unclear outcomes, we conducted preference and reinforcer assessments to identify preferred forms of attention that may maintain problem behavior. Next, we conducted an extended functional analysis that included a modified attention condition. Results showed that the…

Clarifying Inconclusive Functional Analysis Results: Assessment and Treatment of Automatically Reinforced Aggression

PubMed Central

Saini, Valdeep; Greer, Brian D.; Fisher, Wayne W.

2016-01-01

We conducted a series of studies in which multiple strategies were used to clarify the inconclusive results of one boy’s functional analysis of aggression. Specifically, we (a) evaluated individual response topographies to determine the composition of aggregated response rates, (b) conducted a separate functional analysis of aggression after high rates of disruption masked the consequences maintaining aggression during the initial functional analysis, (c) modified the experimental design used during the functional analysis of aggression to improve discrimination and decrease interaction effects between conditions, and (d) evaluated a treatment matched to the reinforcer hypothesized to maintain aggression. An effective yet practical intervention for aggression was developed based on the results of these analyses and from data collected during the matched-treatment evaluation. PMID:25891269

Analysis of Multiple Manding Topographies during Functional Communication Training

ERIC Educational Resources Information Center

Harding, Jay W.; Wacker, David P.; Berg, Wendy K.; Winborn-Kemmerer, Lisa; Lee, John F.; Ibrahimovic, Muska

2009-01-01

We evaluated the effects of reinforcing multiple manding topographies during functional communication training (FCT) to decrease problem behavior for three preschool-age children. During Phase 1, a functional analysis identified conditions that maintained problem behavior for each child. During Phase 2, the children's parents taught them to…

Fuzzy cluster analysis of high-field functional MRI data.

PubMed

Windischberger, Christian; Barth, Markus; Lamm, Claus; Schroeder, Lee; Bauer, Herbert; Gur, Ruben C; Moser, Ewald

2003-11-01

Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast today is an established brain research method and quickly gains acceptance for complementary clinical diagnosis. However, neither the basic mechanisms like coupling between neuronal activation and haemodynamic response are known exactly, nor can the various artifacts be predicted or controlled. Thus, modeling functional signal changes is non-trivial and exploratory data analysis (EDA) may be rather useful. In particular, identification and separation of artifacts as well as quantification of expected, i.e. stimulus correlated, and novel information on brain activity is important for both, new insights in neuroscience and future developments in functional MRI of the human brain. After an introduction on fuzzy clustering and very high-field fMRI we present several examples where fuzzy cluster analysis (FCA) of fMRI time series helps to identify and locally separate various artifacts. We also present and discuss applications and limitations of fuzzy cluster analysis in very high-field functional MRI: differentiate temporal patterns in MRI using (a) a test object with static and dynamic parts, (b) artifacts due to gross head motion artifacts. Using a synthetic fMRI data set we quantitatively examine the influences of relevant FCA parameters on clustering results in terms of receiver-operator characteristics (ROC) and compare them with a commonly used model-based correlation analysis (CA) approach. The application of FCA in analyzing in vivo fMRI data is shown for (a) a motor paradigm, (b) data from multi-echo imaging, and (c) a fMRI study using mental rotation of three-dimensional cubes. We found that differentiation of true "neural" from false "vascular" activation is possible based on echo time dependence and specific activation levels, as well as based on their signal time-course. Exploratory data analysis methods in general and fuzzy cluster analysis in particular may

An assessment of functioning and non-functioning distractors in multiple-choice questions: a descriptive analysis.

PubMed

Tarrant, Marie; Ware, James; Mohammed, Ahmed M

2009-07-07

Four- or five-option multiple choice questions (MCQs) are the standard in health-science disciplines, both on certification-level examinations and on in-house developed tests. Previous research has shown, however, that few MCQs have three or four functioning distractors. The purpose of this study was to investigate non-functioning distractors in teacher-developed tests in one nursing program in an English-language university in Hong Kong. Using item-analysis data, we assessed the proportion of non-functioning distractors on a sample of seven test papers administered to undergraduate nursing students. A total of 514 items were reviewed, including 2056 options (1542 distractors and 514 correct responses). Non-functioning options were defined as ones that were chosen by fewer than 5% of examinees and those with a positive option discrimination statistic. The proportion of items containing 0, 1, 2, and 3 functioning distractors was 12.3%, 34.8%, 39.1%, and 13.8% respectively. Overall, items contained an average of 1.54 (SD = 0.88) functioning distractors. Only 52.2% (n = 805) of all distractors were functioning effectively and 10.2% (n = 158) had a choice frequency of 0. Items with more functioning distractors were more difficult and more discriminating. The low frequency of items with three functioning distractors in the four-option items in this study suggests that teachers have difficulty developing plausible distractors for most MCQs. Test items should consist of as many options as is feasible given the item content and the number of plausible distractors; in most cases this would be three. Item analysis results can be used to identify and remove non-functioning distractors from MCQs that have been used in previous tests.

Psychometric Properties on Lecturers' Beliefs on Teaching Function: Rasch Model Analysis

ERIC Educational Resources Information Center

Mofreh, Samah Ali Mohsen; Ghafar, Mohammed Najib Abdul; Omar, Abdul Hafiz Hj; Mosaku, Monsurat; Ma'ruf, Amar

2014-01-01

This paper focuses on the psychometric analysis of lecturers' beliefs on teaching function (LBTF) survey using Rasch Model analysis. The sample comprised 34 Community Colleges' lecturers. The Rasch Model is applied to produce specific measurements on the lecturers' beliefs on teaching function in order to generalize results and inferential…

Graph analysis of functional brain networks: practical issues in translational neuroscience

PubMed Central

De Vico Fallani, Fabrizio; Richiardi, Jonas; Chavez, Mario; Achard, Sophie

2014-01-01

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective, communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires the know-how of all the methodological steps of the pipeline that manipulate the input brain signals and extract the functional network properties. On the other hand, knowledge of the neural phenomenon under study is required to perform physiologically relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes. PMID:25180301

Visualization of atomic-scale phenomena in superconductors: application to FeSe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choubey, Peayush; Berlijn, Tom; Kreisel, Andreas

Here we propose a simple method of calculating inhomogeneous, atomic-scale phenomena in superconductors which makes use of the wave function information traditionally discarded in the construction of tight-binding models used in the Bogoliubov-de Gennes equations. The method uses symmetry- based first principles Wannier functions to visualize the effects of superconducting pairing on the distribution of electronic states over atoms within a crystal unit cell. Local symmetries lower than the global lattice symmetry can thus be exhibited as well, rendering theoretical comparisons with scanning tunneling spectroscopy data much more useful. As a simple example, we discuss the geometric dimer states observedmore » near defects in superconducting FeSe.« less

Visualization of atomic-scale phenomena in superconductors: application to FeSe

DOE PAGES

Choubey, Peayush; Berlijn, Tom; Kreisel, Andreas; ...

2014-10-31

Here we propose a simple method of calculating inhomogeneous, atomic-scale phenomena in superconductors which makes use of the wave function information traditionally discarded in the construction of tight-binding models used in the Bogoliubov-de Gennes equations. The method uses symmetry- based first principles Wannier functions to visualize the effects of superconducting pairing on the distribution of electronic states over atoms within a crystal unit cell. Local symmetries lower than the global lattice symmetry can thus be exhibited as well, rendering theoretical comparisons with scanning tunneling spectroscopy data much more useful. As a simple example, we discuss the geometric dimer states observedmore » near defects in superconducting FeSe.« less

Intratheater Airlift Functional Needs Analysis (FNA)

DTIC Science & Technology

2011-01-01

information on reprint and linking permissions, please see RAND Permissions. Skip all front matter: Jump to Page 16 The RAND Corporation is a nonprofit...facing the public and private sectors. All RAND mono- graphs undergo rigorous peer review to ensure high standards for research quality and...personnel. xii Intratheater Airlift Functional Needs Analysis all operating environments. The FNA assesses the ability of current assets to

Functional linear models for association analysis of quantitative traits.

PubMed

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY

Characterization of technical surfaces by structure function analysis

NASA Astrophysics Data System (ADS)

Kalms, Michael; Kreis, Thomas; Bergmann, Ralf B.

2018-03-01

The structure function is a tool for characterizing technical surfaces that exhibits a number of advantages over Fourierbased analysis methods. So it is optimally suited for analyzing the height distributions of surfaces measured by full-field non-contacting methods. The structure function is thus a useful method to extract global or local criteria like e. g. periodicities, waviness, lay, or roughness to analyze and evaluate technical surfaces. After the definition of line- and area-structure function and offering effective procedures for their calculation this paper presents examples using simulated and measured data of technical surfaces including aircraft parts.

Classification of functional interactions from multi-electrodes data using conditional modularity analysis

NASA Astrophysics Data System (ADS)

Makhtar, Siti Noormiza; Senik, Mohd Harizal

2018-02-01

The availability of massive amount of neuronal signals are attracting widespread interest in functional connectivity analysis. Functional interactions estimated by multivariate partial coherence analysis in the frequency domain represent the connectivity strength in this study. Modularity is a network measure for the detection of community structure in network analysis. The discovery of community structure for the functional neuronal network was implemented on multi-electrode array (MEA) signals recorded from hippocampal regions in isoflurane-anaesthetized Lister-hooded rats. The analysis is expected to show modularity changes before and after local unilateral kainic acid (KA)-induced epileptiform activity. The result is presented using color-coded graphic of conditional modularity measure for 19 MEA nodes. This network is separated into four sub-regions to show the community detection within each sub-region. The results show that classification of neuronal signals into the inter- and intra-modular nodes is feasible using conditional modularity analysis. Estimation of segregation properties using conditional modularity analysis may provide further information about functional connectivity from MEA data.

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Brief Functional Analysis and Intervention Evaluation for Treatment of Saliva-Play

ERIC Educational Resources Information Center

Luiselli, James K.; Ricciardi, Joseph N.; Schmidt, Sarah; Tarr, Melissa

2004-01-01

We conducted a brief (8 days) functional analysis to identify sources of control over persistent saliva-play displayed by a 6-year old child with autism in a school setting. The functional analysis suggested that saliva-play was maintained by automatic reinforcement, leading to an intervention evaluation (3 days) that compared two methods of…

Dynamic Blowout Risk Analysis Using Loss Functions.

PubMed

Abimbola, Majeed; Khan, Faisal

2018-02-01

Most risk analysis approaches are static; failing to capture evolving conditions. Blowout, the most feared accident during a drilling operation, is a complex and dynamic event. The traditional risk analysis methods are useful in the early design stage of drilling operation while falling short during evolving operational decision making. A new dynamic risk analysis approach is presented to capture evolving situations through dynamic probability and consequence models. The dynamic consequence models, the focus of this study, are developed in terms of loss functions. These models are subsequently integrated with the probability to estimate operational risk, providing a real-time risk analysis. The real-time evolving situation is considered dependent on the changing bottom-hole pressure as drilling progresses. The application of the methodology and models are demonstrated with a case study of an offshore drilling operation evolving to a blowout. © 2017 Society for Risk Analysis.

Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data.

PubMed

Salvatore, Stefania; Bramness, Jørgen G; Røislien, Jo

2016-07-12

Wastewater-based epidemiology (WBE) is a novel approach in drug use epidemiology which aims to monitor the extent of use of various drugs in a community. In this study, we investigate functional principal component analysis (FPCA) as a tool for analysing WBE data and compare it to traditional principal component analysis (PCA) and to wavelet principal component analysis (WPCA) which is more flexible temporally. We analysed temporal wastewater data from 42 European cities collected daily over one week in March 2013. The main temporal features of ecstasy (MDMA) were extracted using FPCA using both Fourier and B-spline basis functions with three different smoothing parameters, along with PCA and WPCA with different mother wavelets and shrinkage rules. The stability of FPCA was explored through bootstrapping and analysis of sensitivity to missing data. The first three principal components (PCs), functional principal components (FPCs) and wavelet principal components (WPCs) explained 87.5-99.6 % of the temporal variation between cities, depending on the choice of basis and smoothing. The extracted temporal features from PCA, FPCA and WPCA were consistent. FPCA using Fourier basis and common-optimal smoothing was the most stable and least sensitive to missing data. FPCA is a flexible and analytically tractable method for analysing temporal changes in wastewater data, and is robust to missing data. WPCA did not reveal any rapid temporal changes in the data not captured by FPCA. Overall the results suggest FPCA with Fourier basis functions and common-optimal smoothing parameter as the most accurate approach when analysing WBE data.

Mixed kernel function support vector regression for global sensitivity analysis

NASA Astrophysics Data System (ADS)

Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

2017-11-01

Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

A Factor Analysis of Peking Opera: Its Functions in Mass Communications.

ERIC Educational Resources Information Center

Cheng, Philip H.

The study reported in this paper examined the structure and function of Chinese opera (also known as Peking opera) as an effective communication medium of social control and change in China, a land populated by 800 million people and nourished by a 5,000-year-old civilization. The study followed structural-functional analysis, content analysis,…

Wave-function-based approach to quasiparticle bands: Insight into the electronic structure of c-ZnS

NASA Astrophysics Data System (ADS)

Stoyanova, A.; Hozoi, L.; Fulde, P.; Stoll, H.

2011-05-01

Ab initio wave-function-based methods are employed for the study of quasiparticle energy bands of zinc-blende ZnS, with focus on the Zn 3d “semicore” states. The relative energies of these states with respect to the top of the S 3p valence bands appear to be poorly described as compared to experimental values not only within the local density approximation (LDA), but also when many-body corrections within the GW approximation are applied to the LDA or LDA + U mean-field solutions [T. Miyake, P. Zhang, M. L. Cohen, and S. G. Louie, Phys. Rev. BPRBMDO1098-012110.1103/PhysRevB.74.245213 74, 245213 (2006)]. In the present study, we show that for the accurate description of the Zn 3d states a correlation treatment based on wave-function methods is needed. Our study rests on a local Hamiltonian approach which rigorously describes the short-range polarization and charge redistribution effects around an extra hole or electron placed into the valence respective conduction bands of semiconductors and insulators. The method also facilitates the computation of electron correlation effects beyond relaxation and polarization. The electron correlation treatment is performed on finite clusters cut off the infinite system. The formalism makes use of localized Wannier functions and embedding potentials derived explicitly from prior periodic Hartree-Fock calculations. The on-site and nearest-neighbor charge relaxation lead to corrections of several eV to the Hartree-Fock band energies and gap. Corrections due to long-range polarization are of the order of 1.0 eV. The dispersion of the Hartree-Fock bands is only slightly affected by electron correlations. We find the Zn 3d “semicore” states to lie ~9.0 eV below the top of the S 3p valence bands, in very good agreement with values from valence-band x-ray photoemission.

The energy level alignment at metal–molecule interfaces using Wannier–Koopmans method

DOE PAGES

Ma, Jie; Liu, Zhen-Fei; Neaton, Jeffrey B.; ...

2016-06-30

We apply a recently developed Wannier-Koopmans method (WKM), based on density functional theory (DFT), to calculate the electronic energy level alignment at an interface between a molecule and metal substrate. We consider two systems: benzenediamine on Au (111), and a bipyridine-Au molecular junction. The WKM calculated level alignment agrees well with the experimental measurements where available, as well as previous GW and DFT + Σ results. These results suggest that the WKM is a general approach that can be used to correct DFT eigenvalue errors, not only in bulk semiconductors and isolated molecules, but also in hybrid interfaces.

Does the physics of (Ga,Mn)N differ from (GaMn)As qualitatively or quantitatively? Is valance of Mn impurity 2+ or 3+?

NASA Astrophysics Data System (ADS)

Nelson, Ryky; Berlijn, Tom; Ku, Wei; Moreno, Juana; Jarrell, Mark

2013-03-01

(Ga,Mn)N is a promising material for spintronics due to its potential high currie temperature (Tc). However, unlike for (Ga,Mn)As, some of the experiments on (Ga,Mn)N are still controversial on the intrinsic nature of the magnetism. Furthermore, under debate are the spin and charge state of the disordered Mn impurities in (Ga,Mn)N and whether its local moments interact via the same exchange mechanism as in (Ga,Mn)As. To address these issues we will present ab-initio-based analyses of disorder and correlation via the recently developed Wannier function based methods.

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

PubMed Central

Seeley, Matthew K.; Francom, Devin; Reese, C. Shane; Hopkins, J. Ty

2017-01-01

Abstract In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. When using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function. PMID:29339984

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach.

PubMed

Park, Jihong; Seeley, Matthew K; Francom, Devin; Reese, C Shane; Hopkins, J Ty

2017-12-01

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. When using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Jihong; Seeley, Matthew K.; Francom, Devin

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle,more » knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. Thus when using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.« less

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

DOE PAGES

Park, Jihong; Seeley, Matthew K.; Francom, Devin; ...

2017-12-28

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle,more » knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. Thus when using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.« less

Software ion scan functions in analysis of glycomic and lipidomic MS/MS datasets.

PubMed

Haramija, Marko

2018-03-01

Hardware ion scan functions unique to tandem mass spectrometry (MS/MS) mode of data acquisition, such as precursor ion scan (PIS) and neutral loss scan (NLS), are important for selective extraction of key structural data from complex MS/MS spectra. However, their software counterparts, software ion scan (SIS) functions, are still not regularly available. Software ion scan functions can be easily coded for additional functionalities, such as software multiple precursor ion scan, software no ion scan, and software variable ion scan functions. These are often necessary, since they allow more efficient analysis of complex MS/MS datasets, often encountered in glycomics and lipidomics. Software ion scan functions can be easily coded by using modern script languages and can be independent of instrument manufacturer. Here we demonstrate the utility of SIS functions on a medium-size glycomic MS/MS dataset. Knowledge of sample properties, as well as of diagnostic and conditional diagnostic ions crucial for data analysis, was needed. Based on the tables constructed with the output data from the SIS functions performed, a detailed analysis of a complex MS/MS glycomic dataset could be carried out in a quick, accurate, and efficient manner. Glycomic research is progressing slowly, and with respect to the MS experiments, one of the key obstacles for moving forward is the lack of appropriate bioinformatic tools necessary for fast analysis of glycomic MS/MS datasets. Adding novel SIS functionalities to the glycomic MS/MS toolbox has a potential to significantly speed up the glycomic data analysis process. Similar tools are useful for analysis of lipidomic MS/MS datasets as well, as will be discussed briefly. Copyright © 2017 John Wiley & Sons, Ltd.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

FunShift: a database of function shift analysis on protein subfamilies

PubMed Central

Abhiman, Saraswathi; Sonnhammer, Erik L. L.

2005-01-01

Members of a protein family normally have a general biochemical function in common, but frequently one or more subgroups have evolved a slightly different function, such as different substrate specificity. It is important to detect such function shifts for a more accurate functional annotation. The FunShift database described here is a compilation of function shift analysis performed between subfamilies in protein families. It consists of two main components: (i) subfamilies derived from protein domain families and (ii) pairwise subfamily comparisons analyzed for function shift. The present release, FunShift 12, was derived from Pfam 12 and consists of 151 934 subfamilies derived from 7300 families. We carried out function shift analysis by two complementary methods on families with up to 500 members. From a total of 179 210 subfamily pairs, 62 384 were predicted to be functionally shifted in 2881 families. Each subfamily pair is provided with a markup of probable functional specificity-determining sites. Tools for searching and exploring the data are provided to make this database a valuable resource for protein function annotation. Knowledge of these functionally important sites will be useful for experimental biologists performing functional mutation studies. FunShift is available at http://FunShift.cgb.ki.se. PMID:15608176

Multidimensional Functional Behaviour Assessment within a Problem Analysis Framework.

ERIC Educational Resources Information Center

Ryba, Ken; Annan, Jean

This paper presents a new approach to contextualized problem analysis developed for use with multimodal Functional Behaviour Assessment (FBA) at Massey University in Auckland, New Zealand. The aim of problem analysis is to simplify complex problems that are difficult to understand. It accomplishes this by providing a high order framework that can…

Applications of functional data analysis: A systematic review.

PubMed

Ullah, Shahid; Finch, Caroline F

2013-03-19

Functional data analysis (FDA) is increasingly being used to better analyze, model and predict time series data. Key aspects of FDA include the choice of smoothing technique, data reduction, adjustment for clustering, functional linear modeling and forecasting methods. A systematic review using 11 electronic databases was conducted to identify FDA application studies published in the peer-review literature during 1995-2010. Papers reporting methodological considerations only were excluded, as were non-English articles. In total, 84 FDA application articles were identified; 75.0% of the reviewed articles have been published since 2005. Application of FDA has appeared in a large number of publications across various fields of sciences; the majority is related to biomedicine applications (21.4%). Overall, 72 studies (85.7%) provided information about the type of smoothing techniques used, with B-spline smoothing (29.8%) being the most popular. Functional principal component analysis (FPCA) for extracting information from functional data was reported in 51 (60.7%) studies. One-quarter (25.0%) of the published studies used functional linear models to describe relationships between explanatory and outcome variables and only 8.3% used FDA for forecasting time series data. Despite its clear benefits for analyzing time series data, full appreciation of the key features and value of FDA have been limited to date, though the applications show its relevance to many public health and biomedical problems. Wider application of FDA to all studies involving correlated measurements should allow better modeling of, and predictions from, such data in the future especially as FDA makes no a priori age and time effects assumptions.

Survival analysis with functional covariates for partial follow-up studies.

PubMed

Fang, Hong-Bin; Wu, Tong Tong; Rapoport, Aaron P; Tan, Ming

2016-12-01

Predictive or prognostic analysis plays an increasingly important role in the era of personalized medicine to identify subsets of patients whom the treatment may benefit the most. Although various time-dependent covariate models are available, such models require that covariates be followed in the whole follow-up period. This article studies a new class of functional survival models where the covariates are only monitored in a time interval that is shorter than the whole follow-up period. This paper is motivated by the analysis of a longitudinal study on advanced myeloma patients who received stem cell transplants and T cell infusions after the transplants. The absolute lymphocyte cell counts were collected serially during hospitalization. Those patients are still followed up if they are alive after hospitalization, while their absolute lymphocyte cell counts cannot be measured after that. Another complication is that absolute lymphocyte cell counts are sparsely and irregularly measured. The conventional method using Cox model with time-varying covariates is not applicable because of the different lengths of observation periods. Analysis based on each single observation obviously underutilizes available information and, more seriously, may yield misleading results. This so-called partial follow-up study design represents increasingly common predictive modeling problem where we have serial multiple biomarkers up to a certain time point, which is shorter than the total length of follow-up. We therefore propose a solution to the partial follow-up design. The new method combines functional principal components analysis and survival analysis with selection of those functional covariates. It also has the advantage of handling sparse and irregularly measured longitudinal observations of covariates and measurement errors. Our analysis based on functional principal components reveals that it is the patterns of the trajectories of absolute lymphocyte cell counts, instead of

An analysis of the functioning of mental healthcare in northwestern Poland.

PubMed

Bażydło, Marta; Karakiewicz, Beata

Modern psychiatry faces numerous challenges related with the change of the epidemiology of mental disorders and the development of knowledge in this area of science. An answer to this situation is to be the introduction of community psychiatry. The implementation of this model in Poland was the aim of the National Mental Health Protection Programme. The aim of the study was to analyse the functioning of mental healthcare using the example of the West Pomeranian Province in Poland. The analysis relied on a qualitative method. Three group interviews in an interdisciplinary advisory panel were conducted. People representing various areas acting for people with mental disorders participated in each meeting. Based on the conclusions that were drawn, PEST and SWOT analyses of functioning of mental healthcare were performed. Within the analysis of the macro-environment of mental healthcare, the influence of the following factors was evaluated through PEST analysis: political and legal, economic, socio-cultural, and technological. All of these factors were assessed as negative for the functioning of mental healthcare. Then, a SWOT analysis was performed to indicate the strengths, weaknesses, opportunities, and threats in the functioning of mental healthcare. 1. Mental healthcare is more influenced by external factors than by internal factors. 2. Macro-environmental factors influence the functioning of mental healthcare in a significantly negative manner. 3. The basic problem in the functioning of mental healthcare is insufficient funding. 4. In order to improve the functioning of mental healthcare, it is necessary to change the funding methods, regulations, the way society perceives mental disorders, and the system of monitoring mental healthcare services.

Aircraft/Air Traffic Management Functional Analysis Model: Technical Description. 2.0

NASA Technical Reports Server (NTRS)

Etheridge, Melvin; Plugge, Joana; Retina, Nusrat

1998-01-01

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) under a National Aeronautics and Space Administration (NASA) contract. This document provides a technical description of FAM 2.0 and its computer files to enable the modeler and programmer to make enhancements or modifications to the model. Those interested in a guide for using the model in analysis should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Users Manual.

Exciton dispersion in molecular solids

NASA Astrophysics Data System (ADS)

Cudazzo, Pierluigi; Sottile, Francesco; Rubio, Angel; Gatti, Matteo

2015-03-01

The investigation of the exciton dispersion (i.e. the exciton energy dependence as a function of the momentum carried by the electron-hole pair) is a powerful approach to identify the exciton character, ranging from the strongly localised Frenkel to the delocalised Wannier-Mott limiting cases. We illustrate this possibility at the example of four prototypical molecular solids (picene, pentacene, tetracene and coronene) on the basis of the parameter-free solution of the many-body Bethe-Salpeter equation. We discuss the mixing between Frenkel and charge-transfer excitons and the origin of their Davydov splitting in the framework of many-body perturbation theory and establish a link with model approaches based on molecular states. Finally, we show how the interplay between the electronic band dispersion and the exchange electron-hole interaction plays a fundamental role in setting the nature of the exciton. This analysis has a general validity holding also for other systems in which the electron wavefunctions are strongly localized, as in strongly correlated insulators.

What is the valence of Mn in Ga 1-xMn xN?

DOE PAGES

Berlijn, Tom; Jarrell, Mark; Nelson, Ryky; ...

2015-11-04

Motivated by the potential high Curie temperature of Ga 1-xMn xN, we investigate the controversial Mn valence in this diluted magnetic semiconductor. From a first-principles Wannier-function analysis of the high energy Hilbert space, we find unambiguously the Mn valence to be close to 2+(d 5), but in a mixed spin configuration with average magnetic moments of 4µ B. By integrating out high-energy degrees of freedom differently, we further demonstrate the feasibility of both effective d 4 and d 5 descriptions. These two descriptions offer simple pictures for local and extended properties of the system, and highlight the dual nature ofmore » its doped hole. Specifically, in the effective d 5 description, we demonstrate novel physical effects absent in previous studies. Thus, our derivation highlights the richness of low-energy sectors in interacting many-body systems and the generic need for multiple effective descriptions.« less

Efficient Bayesian hierarchical functional data analysis with basis function approximations using Gaussian-Wishart processes.

PubMed

Yang, Jingjing; Cox, Dennis D; Lee, Jong Soo; Ren, Peng; Choi, Taeryon

2017-12-01

Functional data are defined as realizations of random functions (mostly smooth functions) varying over a continuum, which are usually collected on discretized grids with measurement errors. In order to accurately smooth noisy functional observations and deal with the issue of high-dimensional observation grids, we propose a novel Bayesian method based on the Bayesian hierarchical model with a Gaussian-Wishart process prior and basis function representations. We first derive an induced model for the basis-function coefficients of the functional data, and then use this model to conduct posterior inference through Markov chain Monte Carlo methods. Compared to the standard Bayesian inference that suffers serious computational burden and instability in analyzing high-dimensional functional data, our method greatly improves the computational scalability and stability, while inheriting the advantage of simultaneously smoothing raw observations and estimating the mean-covariance functions in a nonparametric way. In addition, our method can naturally handle functional data observed on random or uncommon grids. Simulation and real studies demonstrate that our method produces similar results to those obtainable by the standard Bayesian inference with low-dimensional common grids, while efficiently smoothing and estimating functional data with random and high-dimensional observation grids when the standard Bayesian inference fails. In conclusion, our method can efficiently smooth and estimate high-dimensional functional data, providing one way to resolve the curse of dimensionality for Bayesian functional data analysis with Gaussian-Wishart processes. © 2017, The International Biometric Society.

Insight from first principles into the stability and magnetism of alkali-metal superoxide nanoclusters

NASA Astrophysics Data System (ADS)

Arcelus, Oier; Suaud, Nicolas; Katcho, Nebil A.; Carrasco, Javier

2017-05-01

Alkali-metal superoxides are gaining increasing interest as 2p magnetic materials for information and energy storage. Despite significant research efforts on bulk materials, gaps in our knowledge of the electronic and magnetic properties at the nanoscale still remain. Here, we focused on the role that structural details play in determining stability, electronic structure, and magnetic couplings of (MO2)n (M = Li, Na, and K, with n = 2-8) clusters. Using first-principles density functional theory based on the Perdew-Burke-Ernzerhof and Heyd-Scuseria-Ernzerhof functionals, we examined the effect of atomic structure on the relative stability of different polymorphs within each investigated cluster size. We found that small clusters prefer to form planar-ring structures, whereas non-planar geometries become more stable when increasing the cluster size. However, the crossover point depends on the nature of the alkali metal. Our analysis revealed that electrostatic interactions govern the highly ionic M-O2 bonding and ultimately control the relative stability between 2-D and 3-D geometries. In addition, we analyzed the weak magnetic couplings between superoxide molecules in (NaO2)4 clusters comparing model Hamiltonian methods based on Wannier function projections onto πg states with wave function-based multi-reference calculations.

Functional principal component analysis of glomerular filtration rate curves after kidney transplant.

PubMed

Dong, Jianghu J; Wang, Liangliang; Gill, Jagbir; Cao, Jiguo

2017-01-01

This article is motivated by some longitudinal clinical data of kidney transplant recipients, where kidney function progression is recorded as the estimated glomerular filtration rates at multiple time points post kidney transplantation. We propose to use the functional principal component analysis method to explore the major source of variations of glomerular filtration rate curves. We find that the estimated functional principal component scores can be used to cluster glomerular filtration rate curves. Ordering functional principal component scores can detect abnormal glomerular filtration rate curves. Finally, functional principal component analysis can effectively estimate missing glomerular filtration rate values and predict future glomerular filtration rate values.

Informing the Structure of Executive Function in Children: A Meta-Analysis of Functional Neuroimaging Data

PubMed Central

McKenna, Róisín; Rushe, T.; Woodcock, Kate A.

2017-01-01

The structure of executive function (EF) has been the focus of much debate for decades. What is more, the complexity and diversity provided by the developmental period only adds to this contention. The development of executive function plays an integral part in the expression of children's behavioral, cognitive, social, and emotional capabilities. Understanding how these processes are constructed during development allows for effective measurement of EF in this population. This meta-analysis aims to contribute to a better understanding of the structure of executive function in children. A coordinate-based meta-analysis was conducted (using BrainMap GingerALE 2.3), which incorporated studies administering functional magnetic resonance imaging (fMRI) during inhibition, switching, and working memory updating tasks in typical children (aged 6–18 years). The neural activation common across all executive tasks was compared to that shared by tasks pertaining only to inhibition, switching or updating, which are commonly considered to be fundamental executive processes. Results support the existence of partially separable but partially overlapping inhibition, switching, and updating executive processes at a neural level, in children over 6 years. Further, the shared neural activation across all tasks (associated with a proposed “unitary” component of executive function) overlapped to different degrees with the activation associated with each individual executive process. These findings provide evidence to support the suggestion that one of the most influential structural models of executive functioning in adults can also be applied to children of this age. However, the findings also call for careful consideration and measurement of both specific executive processes, and unitary executive function in this population. Furthermore, a need is highlighted for a new systematic developmental model, which captures the integrative nature of executive function in children. PMID

An analysis of maintenance following functional communication training.

PubMed Central

Durand, V M; Carr, E G

1992-01-01

The multiple and long-term effects of functional communication training relative to a common reductive procedure (time-out from positive reinforcement) were evaluated. Twelve children participated in a functional analysis of their challenging behaviors (Study 1), which implicated adult attention as a maintaining variable. The children were then matched for chronological age, mental age, and language age and assigned to two groups. One group received functional communication training as an intervention for their challenging behavior, and the second group received time-out as a contrast. Both interventions were initially successful (Study 2), but durable results were achieved only with the group that received functional communication training across different stimulus conditions (Study 3). Students whose challenging behaviors were previously reduced with time-out resumed these behaviors in the presence of naive teachers unaware of the children's intervention history. The value of teaching communicative responses to promote maintenance is discussed as it relates to the concept of functional equivalence. PMID:1478902

Integrating anatomy and function for zebrafish circuit analysis.

PubMed

Arrenberg, Aristides B; Driever, Wolfgang

2013-01-01

Due to its transparency, virtually every brain structure of the larval zebrafish is accessible to light-based interrogation of circuit function. Advanced stimulation techniques allow the activation of optogenetic actuators at different resolution levels, and genetically encoded calcium indicators report the activity of a large proportion of neurons in the CNS. Large datasets result and need to be analyzed to identify cells that have specific properties-e.g., activity correlation to sensory stimulation or behavior. Advances in three-dimensional (3D) functional mapping in zebrafish are promising; however, the mere coordinates of implicated neurons are not sufficient. To comprehensively understand circuit function, these functional maps need to be placed into the proper context of morphological features and projection patterns, neurotransmitter phenotypes, and key anatomical landmarks. We discuss the prospect of merging functional and anatomical data in an integrated atlas from the perspective of our work on long-range dopaminergic neuromodulation and the oculomotor system. We propose that such a resource would help researchers to surpass current hurdles in circuit analysis to achieve an integrated understanding of anatomy and function.

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

PubMed Central

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology

PubMed Central

Sun, Junfeng; Li, Zhijun; Tong, Shanbao

2012-01-01

Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals. PMID:22577470

Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

PubMed

Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

2016-09-01

In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control and disease groups through the average curves in each group. Such group differences, however, neglect the variability in the sample of connectivity curves. In this article, the use of functional principal component analysis (FPCA) is demonstrated to enrich functional connectivity studies by providing increased power and flexibility for statistical inference. Specifically, individual connectivity curves are related to individual characteristics such as age and measures of cognitive function, thus providing a tool to relate brain connectivity with these variables at the individual level. This individual level analysis opens a new perspective that goes beyond previous group level comparisons. Using a large data set of resting-state functional magnetic resonance imaging scans, relationships between connectivity and two measures of cognitive function-episodic memory and executive function-were investigated. The group-based approach was implemented by dichotomizing the continuous cognitive variable and testing for group differences, resulting in no statistically significant findings. To demonstrate the new approach, FPCA was implemented, followed by linear regression models with cognitive scores as responses, identifying significant associations of connectivity in the right middle temporal region with both cognitive scores.

Accurate evaluation and analysis of functional genomics data and methods

PubMed Central

Greene, Casey S.; Troyanskaya, Olga G.

2016-01-01

The development of technology capable of inexpensively performing large-scale measurements of biological systems has generated a wealth of data. Integrative analysis of these data holds the promise of uncovering gene function, regulation, and, in the longer run, understanding complex disease. However, their analysis has proved very challenging, as it is difficult to quickly and effectively assess the relevance and accuracy of these data for individual biological questions. Here, we identify biases that present challenges for the assessment of functional genomics data and methods. We then discuss evaluation methods that, taken together, begin to address these issues. We also argue that the funding of systematic data-driven experiments and of high-quality curation efforts will further improve evaluation metrics so that they more-accurately assess functional genomics data and methods. Such metrics will allow researchers in the field of functional genomics to continue to answer important biological questions in a data-driven manner. PMID:22268703

Applications of functional data analysis: A systematic review

PubMed Central

2013-01-01

Background Functional data analysis (FDA) is increasingly being used to better analyze, model and predict time series data. Key aspects of FDA include the choice of smoothing technique, data reduction, adjustment for clustering, functional linear modeling and forecasting methods. Methods A systematic review using 11 electronic databases was conducted to identify FDA application studies published in the peer-review literature during 1995–2010. Papers reporting methodological considerations only were excluded, as were non-English articles. Results In total, 84 FDA application articles were identified; 75.0% of the reviewed articles have been published since 2005. Application of FDA has appeared in a large number of publications across various fields of sciences; the majority is related to biomedicine applications (21.4%). Overall, 72 studies (85.7%) provided information about the type of smoothing techniques used, with B-spline smoothing (29.8%) being the most popular. Functional principal component analysis (FPCA) for extracting information from functional data was reported in 51 (60.7%) studies. One-quarter (25.0%) of the published studies used functional linear models to describe relationships between explanatory and outcome variables and only 8.3% used FDA for forecasting time series data. Conclusions Despite its clear benefits for analyzing time series data, full appreciation of the key features and value of FDA have been limited to date, though the applications show its relevance to many public health and biomedical problems. Wider application of FDA to all studies involving correlated measurements should allow better modeling of, and predictions from, such data in the future especially as FDA makes no a priori age and time effects assumptions. PMID:23510439

An advanced probabilistic structural analysis method for implicit performance functions

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

1989-01-01

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Aircraft/Air Traffic Management Functional Analysis Model. Version 2.0; User's Guide

NASA Technical Reports Server (NTRS)

Etheridge, Melvin; Plugge, Joana; Retina, Nusrat

1998-01-01

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) a National Aeronautics and Space Administration (NASA) contract. This document provides a guide for using the model in analysis. Those interested in making enhancements or modification to the model should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Technical Description.

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia.

PubMed

Damaraju, E; Allen, E A; Belger, A; Ford, J M; McEwen, S; Mathalon, D H; Mueller, B A; Pearlson, G D; Potkin, S G; Preda, A; Turner, J A; Vaidya, J G; van Erp, T G; Calhoun, V D

2014-01-01

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical-subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

PubMed Central

Damaraju, E.; Allen, E.A.; Belger, A.; Ford, J.M.; McEwen, S.; Mathalon, D.H.; Mueller, B.A.; Pearlson, G.D.; Potkin, S.G.; Preda, A.; Turner, J.A.; Vaidya, J.G.; van Erp, T.G.; Calhoun, V.D.

2014-01-01

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical–subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group

A Review of Functional Analysis Methods Conducted in Public School Classroom Settings

ERIC Educational Resources Information Center

Lloyd, Blair P.; Weaver, Emily S.; Staubitz, Johanna L.

2016-01-01

The use of functional behavior assessments (FBAs) to address problem behavior in classroom settings has increased as a result of education legislation and long-standing evidence supporting function-based interventions. Although functional analysis remains the standard for identifying behavior--environment functional relations, this component is…

(LaTiO3)n/(LaVO3)n as a model system for unconventional charge transfer and polar metallicity

NASA Astrophysics Data System (ADS)

Weng, Yakui; Zhang, Jun-Jie; Gao, Bin; Dong, Shuai

2017-04-01

At interfaces between oxide materials, lattice and electronic reconstructions always play important roles in exotic phenomena. In this study, the density functional theory and maximally localized Wannier functions are employed to investigate the (LaTiO3)n/(LaVO3)n magnetic superlattices. The electron transfer from Ti3 + to V3 + is predicted, which violates the intuitive band alignment based on the electronic structures of LaTiO3 and LaVO3. Such unconventional charge transfer quenches the magnetism of LaTiO3 layer mostly and leads to metal-insulator transition in the n =1 superlattice when the stacking orientation is altered. In addition, the compatibility among the polar structure, ferrimagnetism, and metallicity is predicted in the n =2 superlattice.

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.; ...

2016-05-09

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

A Multi-Dimensional Functional Principal Components Analysis of EEG Data

PubMed Central

Hasenstab, Kyle; Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine A.; Jeste, Shafali; DiStefano, Charlotte; Şentürk, Damla

2017-01-01

Summary The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations. PMID:28072468

Analysis of Social Variables when an Initial Functional Analysis Indicates Automatic Reinforcement as the Maintaining Variable for Self-Injurious Behavior

ERIC Educational Resources Information Center

Kuhn, Stephanie A. Contrucci; Triggs, Mandy

2009-01-01

Self-injurious behavior (SIB) that occurs at high rates across all conditions of a functional analysis can suggest automatic or multiple functions. In the current study, we conducted a functional analysis for 1 individual with SIB. Results indicated that SIB was, at least in part, maintained by automatic reinforcement. Further analyses using…

IMAGING OF BRAIN FUNCTION BASED ON THE ANALYSIS OF FUNCTIONAL CONNECTIVITY - IMAGING ANALYSIS OF BRAIN FUNCTION BY FMRI AFTER ACUPUNCTURE AT LR3 IN HEALTHY INDIVIDUALS.

PubMed

Zheng, Yu; Wang, Yuying; Lan, Yujun; Qu, Xiaodong; Lin, Kelin; Zhang, Jiping; Qu, Shanshan; Wang, Yanjie; Tang, Chunzhi; Huang, Yong

2016-01-01

This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint. A total of 45 healthy subjects were randomly divided into the Taichong (LR3) group, sham acupuncture group and sham acupoint group. Subjects received resting state fMRI before acupuncture, after true (sham) acupuncture in each group. Analysis of changes in connectivity among the brain areas was performed using the brain functional connectivity method. The right cerebrum temporal lobe was selected as the seed point to analyze the functional connectivity. It had a functional connectivity with right cerebrum superior frontal gyrus, limbic lobe cingulate gyrus and left cerebrum inferior temporal gyrus (BA 37), inferior parietal lobule compared by before vs. after acupuncture at LR3, and right cerebrum sub-lobar insula and left cerebrum middle frontal gyrus, medial frontal gyrus compared by true vs. sham acupuncture at LR3, and right cerebrum occipital lobe cuneus, occipital lobe sub-gyral, parietal lobe precuneus and left cerebellum anterior lobe culmen by acupuncture at LR3 vs. sham acupoint. Acupuncture at LR3 mainly specifically activated the brain functional network that participates in visual function, associative function, and emotion cognition, which are similar to the features on LR3 in tradition Chinese medicine. These brain areas constituted a neural network structure with specific functions that had specific reference values for the interpretation of the acupoint specificity of the Taichong acupoint.

Multiresolution Analysis by Infinitely Differentiable Compactly Supported Functions

DTIC Science & Technology

1992-09-01

Math. Surveys 45:1 (1990), 87-120. [I] (;. Strang and G. Fix, A Fourier analysis of the finite element variational method. C.I.M.F. I 1 Ciclo 1971, in Constructi’c Aspects of Functional Analyszs ed. G. Geymonat 1973, 793-840. 10

Interpretable functional principal component analysis.

PubMed

Lin, Zhenhua; Wang, Liangliang; Cao, Jiguo

2016-09-01

Functional principal component analysis (FPCA) is a popular approach to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional principal components (FPCs). The intervals where the values of FPCs are significant are interpreted as where sample curves have major variations. However, these intervals are often hard for naïve users to identify, because of the vague definition of "significant values". In this article, we develop a novel penalty-based method to derive FPCs that are only nonzero precisely in the intervals where the values of FPCs are significant, whence the derived FPCs possess better interpretability than the FPCs derived from existing methods. To compute the proposed FPCs, we devise an efficient algorithm based on projection deflation techniques. We show that the proposed interpretable FPCs are strongly consistent and asymptotically normal under mild conditions. Simulation studies confirm that with a competitive performance in explaining variations of sample curves, the proposed FPCs are more interpretable than the traditional counterparts. This advantage is demonstrated by analyzing two real datasets, namely, electroencephalography data and Canadian weather data. © 2015, The International Biometric Society.

Comparative analysis of taxonomic, functional, and metabolic patterns of microbiomes from 14 full-scale biogas reactors by metagenomic sequencing and radioisotopic analysis.

PubMed

Luo, Gang; Fotidis, Ioannis A; Angelidaki, Irini

2016-01-01

Biogas production is a very complex process due to the high complexity in diversity and interactions of the microorganisms mediating it, and only limited and diffuse knowledge exists about the variation of taxonomic and functional patterns of microbiomes across different biogas reactors, and their relationships with the metabolic patterns. The present study used metagenomic sequencing and radioisotopic analysis to assess the taxonomic, functional, and metabolic patterns of microbiomes from 14 full-scale biogas reactors operated under various conditions treating either sludge or manure. The results from metagenomic analysis showed that the dominant methanogenic pathway revealed by radioisotopic analysis was not always correlated with the taxonomic and functional compositions. It was found by radioisotopic experiments that the aceticlastic methanogenic pathway was dominant, while metagenomics analysis showed higher relative abundance of hydrogenotrophic methanogens. Principal coordinates analysis showed the sludge-based samples were clearly distinct from the manure-based samples for both taxonomic and functional patterns, and canonical correspondence analysis showed that the both temperature and free ammonia were crucial environmental variables shaping the taxonomic and functional patterns. The study further the overall patterns of functional genes were strongly correlated with overall patterns of taxonomic composition across different biogas reactors. The discrepancy between the metabolic patterns determined by metagenomic analysis and metabolic pathways determined by radioisotopic analysis was found. Besides, a clear correlation between taxonomic and functional patterns was demonstrated for biogas reactors, and also the environmental factors that shaping both taxonomic and functional genes patterns were identified.

Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

PubMed

Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

2015-10-01

With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

Combining Multiobjective Optimization and Cluster Analysis to Study Vocal Fold Functional Morphology

PubMed Central

Palaparthi, Anil; Riede, Tobias

2017-01-01

Morphological design and the relationship between form and function have great influence on the functionality of a biological organ. However, the simultaneous investigation of morphological diversity and function is difficult in complex natural systems. We have developed a multiobjective optimization (MOO) approach in association with cluster analysis to study the form-function relation in vocal folds. An evolutionary algorithm (NSGA-II) was used to integrate MOO with an existing finite element model of the laryngeal sound source. Vocal fold morphology parameters served as decision variables and acoustic requirements (fundamental frequency, sound pressure level) as objective functions. A two-layer and a three-layer vocal fold configuration were explored to produce the targeted acoustic requirements. The mutation and crossover parameters of the NSGA-II algorithm were chosen to maximize a hypervolume indicator. The results were expressed using cluster analysis and were validated against a brute force method. Results from the MOO and the brute force approaches were comparable. The MOO approach demonstrated greater resolution in the exploration of the morphological space. In association with cluster analysis, MOO can efficiently explore vocal fold functional morphology. PMID:24771563

Improvement of endothelial function by pitavastatin: a meta-analysis.

PubMed

Katsiki, Niki; Reiner, Željko; Tedeschi Reiner, Eugenia; Al-Rasadi, Khalid; Pirro, Matteo; Mikhailidis, Dimitri P; Sahebkar, Amirhossein

2018-02-01

Dyslipidemia is commonly associated with endothelial dysfunction and increased cardiovascular risk. Pitavastatin has been shown to reduce total and low-density lipoprotein cholesterol, to increase high-density lipoprotein (HDL)-cholesterol and improve HDL function. Furthermore, several trials explored its effects on flow-mediated dilation (FMD), as an index of endothelial function. The authors evaluated the effect of pitavastatin therapy on FMD. The authors performed a systematic review and meta-analysis of all clinical trials exploring the impact of pitavastatin on FMD. The search included PubMed-Medline, Scopus, ISI Web of Knowledge and Google Scholar databases. Quantitative data synthesis was performed using a random-effects model, with weighted mean difference (WMD) and 95% confidence interval (CI) as summary statistics. Six eligible studies comprising 7 treatment arms were selected for this meta-analysis. Overall, WMD was significant for the effect of pitavastatin on FMD (2.45%, 95% CI: 1.31, 3.60, p < 0.001) and the effect size was robust in the leave-one-out sensitivity analysis. This meta-analysis of all available clinical trials revealed a significant increase of FMD induced by pitavastatin.

Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

NASA Astrophysics Data System (ADS)

Curceac, S.; Ternynck, C.; Ouarda, T.

2015-12-01

Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed

Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

2016-03-29

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Data on the application of Functional Data Analysis in food fermentations.

PubMed

Ruiz-Bellido, M A; Romero-Gil, V; García-García, P; Rodríguez-Gómez, F; Arroyo-López, F N; Garrido-Fernández, A

2016-12-01

This article refers to the paper "Assessment of table olive fermentation by functional data analysis" (Ruiz-Bellido et al., 2016) [1]. The dataset include pH, titratable acidity, yeast count and area values obtained during fermentation process (380 days) of Aloreña de Málaga olives subjected to five different fermentation systems: i) control of acidified cured olives, ii) highly acidified cured olives, iii) intermediate acidified cured olives, iv) control of traditional cracked olives, and v) traditional olives cracked after 72 h of exposure to air. Many of the Tables and Figures shown in this paper were deduced after application of Functional Data Analysis to raw data using a routine executed under R software for comparison among treatments by the transformation of raw data into smooth curves and the application of a new battery of statistical tools (functional pointwise estimation of the averages and standard deviations, maximum, minimum, first and second derivatives, functional regression, and functional F and t-tests).

The impact of bariatric surgery on pulmonary function: a meta-analysis.

PubMed

Alsumali, Adnan; Al-Hawag, Ali; Bairdain, Sigrid; Eguale, Tewodros

2018-02-01

Morbid obesity may affect several body systems and cause ill effects to the cardiovascular, hepatobiliary, endocrine, and mental health systems. However, the impact on the pulmonary system and pulmonary function has been debated in the literature. A systematic review and meta-analysis for studies that have evaluated the impact of bariatric surgery on pulmonary function were pooled for this analysis. PubMed, Cochrane, and Embase databases were evaluated through September 31, 2016. They were used as the primary search engine for studies evaluating the impact pre- and post-bariatric surgery on pulmonary function. Pooled effect estimates were calculated using random-effects model. Twenty-three studies with 1013 participants were included in the final meta-analysis. Only 8 studies had intervention and control groups with different time points, but 15 studies had matched groups with different time points. Overall, pulmonary function score was significantly improved after bariatric surgery, with a pooled standardized mean difference of .59 (95% confidence interval: .46-.73). Heterogeneity test was performed by using Cochran's Q test (I 2 = 46%; P heterogeneity = .10). Subgroup analysis and univariate meta-regression based on study quality, age, presurgery body mass index, postsurgery body mass index, study design, female patients only, study continent, asthmatic patients in the study, and the type of bariatric surgery confirmed no statistically significant difference among these groups (P value>.05 for all). A multivariate meta-regression model, which adjusted simultaneously for these same covariates, did not change the results (P value > .05 overall). Assessment of publication bias was done visually and by Begg's rank correlation test and indicated the absence of publication bias (asymmetric shape was observed and P = .34). This meta-analysis shows that bariatric surgery significantly improved overall pulmonary functions score for morbid obesity. Copyright © 2018

Weighted functional linear regression models for gene-based association analysis.

PubMed

Belonogova, Nadezhda M; Svishcheva, Gulnara R; Wilson, James F; Campbell, Harry; Axenovich, Tatiana I

2018-01-01

Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P < 0.1 in at least one analysis had lower P values with weighted models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.

[Hazard function and life table: an introduction to the failure time analysis].

PubMed

Matsushita, K; Inaba, H

1987-04-01

Failure time analysis has become popular in demographic studies. It can be viewed as a part of regression analysis with limited dependent variables as well as a special case of event history analysis and multistate demography. The idea of hazard function and failure time analysis, however, has not been properly introduced to nor commonly discussed by demographers in Japan. The concept of hazard function in comparison with life tables is briefly described, where the force of mortality is interchangeable with the hazard rate. The basic idea of failure time analysis is summarized for the cases of exponential distribution, normal distribution, and proportional hazard models. The multiple decrement life table is also introduced as an example of lifetime data analysis with cause-specific hazard rates.

A knowledge base for Vitis vinifera functional analysis.

PubMed

Pulvirenti, Alfredo; Giugno, Rosalba; Distefano, Rosario; Pigola, Giuseppe; Mongiovi, Misael; Giudice, Girolamo; Vendramin, Vera; Lombardo, Alessandro; Cattonaro, Federica; Ferro, Alfredo

2015-01-01

Vitis vinifera (Grapevine) is the most important fruit species in the modern world. Wine and table grapes sales contribute significantly to the economy of major wine producing countries. The most relevant goals in wine production concern quality and safety. In order to significantly improve the achievement of these objectives and to gain biological knowledge about cultivars, a genomic approach is the most reliable strategy. The recent grapevine genome sequencing offers the opportunity to study the potential roles of genes and microRNAs in fruit maturation and other physiological and pathological processes. Although several systems allowing the analysis of plant genomes have been reported, none of them has been designed specifically for the functional analysis of grapevine genomes of cultivars under environmental stress in connection with microRNA data. Here we introduce a novel knowledge base, called BIOWINE, designed for the functional analysis of Vitis vinifera genomes of cultivars present in Sicily. The system allows the analysis of RNA-seq experiments of two different cultivars, namely Nero d'Avola and Nerello Mascalese. Samples were taken under different climatic conditions of phenological phases, diseases, and geographic locations. The BIOWINE web interface is equipped with data analysis modules for grapevine genomes. In particular users may analyze the current genome assembly together with the RNA-seq data through a customized version of GBrowse. The web interface allows users to perform gene set enrichment by exploiting third-party databases. BIOWINE is a knowledge base implementing a set of bioinformatics tools for the analysis of grapevine genomes. The system aims to increase our understanding of the grapevine varieties and species of Sicilian products focusing on adaptability to different climatic conditions, phenological phases, diseases, and geographic locations.

Functional Analysis of Arabidopsis Sucrose Transporters

DOE Office of Scientific and Technical Information (OSTI.GOV)

John M. Ward

2009-03-31

Sucrose is the main photosynthetic product that is transported in the vasculature of plants. The long-distance transport of carbohydrates is required to support the growth and development of net-importing (sink) tissues such as fruit, seeds and roots. This project is focused on understanding the transport mechanism sucrose transporters (SUTs). These are proton-coupled sucrose uptake transporters (membrane proteins) that are required for transport of sucrose in the vasculature and uptake into sink tissues. The accomplishments of this project included: 1) the first analysis of substrate specificity for any SUT. This was accomplished using electrophysiology to analyze AtSUC2, a sucrose transporter frommore » companion cells in Arabidopsis. 2) the first analysis of the transport activity for a monocot SUT. The transport kinetics and substrate specificity of HvSUT1 from barley were studied. 3) the first analysis of a sucrose transporter from sugarcane. and 4) the first analysis of transport activity of a sugar alcohol transporter homolog from plants, AtPLT5. During this period four primary research papers, funded directly by the project, were published in refereed journals. The characterization of several sucrose transporters was essential for the current effort in the analysis of structure/function for this gene family. In particular, the demonstration of strong differences in substrate specificity between type I and II SUTs was important to identify targets for site-directed mutagenesis.« less

A multi-dimensional functional principal components analysis of EEG data.

PubMed

Hasenstab, Kyle; Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine A; Jeste, Shafali; DiStefano, Charlotte; Şentürk, Damla

2017-09-01

The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal, and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations. © 2017, The International Biometric Society.

Production Functions for Water Delivery Systems: Analysis and Estimation Using Dual Cost Function and Implicit Price Specifications

NASA Astrophysics Data System (ADS)

Teeples, Ronald; Glyer, David

1987-05-01

Both policy and technical analysis of water delivery systems have been based on cost functions that are inconsistent with or are incomplete representations of the neoclassical production functions of economics. We present a full-featured production function model of water delivery which can be estimated from a multiproduct, dual cost function. The model features implicit prices for own-water inputs and is implemented as a jointly estimated system of input share equations and a translog cost function. Likelihood ratio tests are performed showing that a minimally constrained, full-featured production function is a necessary specification of the water delivery operations in our sample. This, plus the model's highly efficient and economically correct parameter estimates, confirms the usefulness of a production function approach to modeling the economic activities of water delivery systems.

Functional approach to high-throughput plant growth analysis

PubMed Central

2013-01-01

Method Taking advantage of the current rapid development in imaging systems and computer vision algorithms, we present HPGA, a high-throughput phenotyping platform for plant growth modeling and functional analysis, which produces better understanding of energy distribution in regards of the balance between growth and defense. HPGA has two components, PAE (Plant Area Estimation) and GMA (Growth Modeling and Analysis). In PAE, by taking the complex leaf overlap problem into consideration, the area of every plant is measured from top-view images in four steps. Given the abundant measurements obtained with PAE, in the second module GMA, a nonlinear growth model is applied to generate growth curves, followed by functional data analysis. Results Experimental results on model plant Arabidopsis thaliana show that, compared to an existing approach, HPGA reduces the error rate of measuring plant area by half. The application of HPGA on the cfq mutant plants under fluctuating light reveals the correlation between low photosynthetic rates and small plant area (compared to wild type), which raises a hypothesis that knocking out cfq changes the sensitivity of the energy distribution under fluctuating light conditions to repress leaf growth. Availability HPGA is available at http://www.msu.edu/~jinchen/HPGA. PMID:24565437

Using Operational Analysis to Improve Access to Pulmonary Function Testing.

PubMed

Ip, Ada; Asamoah-Barnieh, Raymond; Bischak, Diane P; Davidson, Warren J; Flemons, W Ward; Pendharkar, Sachin R

2016-01-01

Background. Timely pulmonary function testing is crucial to improving diagnosis and treatment of pulmonary diseases. Perceptions of poor access at an academic pulmonary function laboratory prompted analysis of system demand and capacity to identify factors contributing to poor access. Methods. Surveys and interviews identified stakeholder perspectives on operational processes and access challenges. Retrospective data on testing demand and resource capacity was analyzed to understand utilization of testing resources. Results. Qualitative analysis demonstrated that stakeholder groups had discrepant views on access and capacity in the laboratory. Mean daily resource utilization was 0.64 (SD 0.15), with monthly average utilization consistently less than 0.75. Reserved testing slots for subspecialty clinics were poorly utilized, leaving many testing slots unfilled. When subspecialty demand exceeded number of reserved slots, there was sufficient capacity in the pulmonary function schedule to accommodate added demand. Findings were shared with stakeholders and influenced scheduling process improvements. Conclusion. This study highlights the importance of operational data to identify causes of poor access, guide system decision-making, and determine effects of improvement initiatives in a variety of healthcare settings. Importantly, simple operational analysis can help to improve efficiency of health systems with little or no added financial investment.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

PubMed

Cao, Longlong; Guo, Shuixia; Xue, Zhimin; Hu, Yong; Liu, Haihong; Mwansisya, Tumbwene E; Pu, Weidan; Yang, Bo; Liu, Chang; Feng, Jianfeng; Chen, Eric Y H; Liu, Zhening

2014-02-01

Aberrant brain functional connectivity patterns have been reported in major depressive disorder (MDD). It is unknown whether they can be used in discriminant analysis for diagnosis of MDD. In the present study we examined the efficiency of discriminant analysis of MDD by individualized computer-assisted diagnosis. Based on resting-state functional magnetic resonance imaging data, a new approach was adopted to investigate functional connectivity changes in 39 MDD patients and 37 well-matched healthy controls. By using the proposed feature selection method, we identified significant altered functional connections in patients. They were subsequently applied to our analysis as discriminant features using a support vector machine classification method. Furthermore, the relative contribution of functional connectivity was estimated. After subset selection of high-dimension features, the support vector machine classifier reached up to approximately 84% with leave-one-out training during the discrimination process. Through summarizing the classification contribution of functional connectivities, we obtained four obvious contribution modules: inferior orbitofrontal module, supramarginal gyrus module, inferior parietal lobule-posterior cingulated gyrus module and middle temporal gyrus-inferior temporal gyrus module. The experimental results demonstrated that the proposed method is effective in discriminating MDD patients from healthy controls. Functional connectivities might be useful as new biomarkers to assist clinicians in computer auxiliary diagnosis of MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

Functional Job Analysis: An Annotated Bibliography. Methods for Manpower Analysis No. 10.

ERIC Educational Resources Information Center

Fine, Sidney A.; And Others

The bibliography provides a chronological survey of the development, growth, and application of the concept of Functional Job Analysis (FJA) which provides for the formulation of qualifications of workers and the requirements of jobs in the same terms so that the one can be equated with measures of the other. An introductory section discusses FJA,…

Exact Thermal Transport Properties of Gray-Arsenic using Electon-Phonon Coupling

NASA Astrophysics Data System (ADS)

Kang, Seoung-Hun; Kwon, Young-Kyun

Using various theoretical methods, we investigate the thermoelectric property of gray arsenic. Thermoelectric devices that utilize the Seebeck effect convert heat flow into electrical energy. The conversion efficiency of such a device is determined by its figure of merit or ZT value, which is related to various transport coefficients, such as Seebeck coefficient and the ratio of its electrical conductivity to its thermal counterpart for given temperature. To calculate various transport coefficients and thus the ZT values of gray arsenic, we apply the Boltzmann transport theory to its electronic and phononic structures obtained by density functional theory and density functional perturbation theory together with maximally locallized Wannier functions. During this procedure, we evaluate its relaxation time accurately by explicitly considering electron-phonon coupling. Our result reveals that gray arsenic may be used for a good p-type thermoelectric devices.

In-Home Parent Training of Functional Analysis Skills

ERIC Educational Resources Information Center

Stokes, John V.; Luiselli, James K.

2008-01-01

We taught two sets of parents to conduct a functional analysis (FA) under simulated conditions in their homes. Relative to a baseline (pre-training) phase, the accuracy of FA implementation by parents improved when they were given verbal, written, and video performance feedback. When training concluded, parents were able to implement FA accurately…

Functional analysis of regulatory single-nucleotide polymorphisms.

PubMed

Pampín, Sandra; Rodríguez-Rey, José C

2007-04-01

The identification of regulatory polymorphisms has become a key problem in human genetics. In the past few years there has been a conceptual change in the way in which regulatory single-nucleotide polymorphisms are studied. We revise the new approaches and discuss how gene expression studies can contribute to a better knowledge of the genetics of common diseases. New techniques for the association of single-nucleotide polymorphisms with changes in gene expression have been recently developed. This, together with a more comprehensive use of the old in-vitro methods, has produced a great amount of genetic information. When added to current databases, it will help to design better tools for the detection of regulatory single-nucleotide polymorphisms. The identification of functional regulatory single-nucleotide polymorphisms cannot be done by the simple inspection of DNA sequence. In-vivo techniques, based on primer-extension, and the more recently developed 'haploChIP' allow the association of gene variants to changes in gene expression. Gene expression analysis by conventional in-vitro techniques is the only way to identify the functional consequences of regulatory single-nucleotide polymorphisms. The amount of information produced in the last few years will help to refine the tools for the future analysis of regulatory gene variants.

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family.

PubMed

Danisman, Selahattin; van Dijk, Aalt D J; Bimbo, Andrea; van der Wal, Froukje; Hennig, Lars; de Folter, Stefan; Angenent, Gerco C; Immink, Richard G H

2013-12-01

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein-protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein-protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family.

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family

PubMed Central

Danisman, Selahattin; de Folter, Stefan; Immink, Richard G. H.

2013-01-01

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein–protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein–protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family. PMID:24129704

Efficient "on-the-fly" calculation of Raman spectra from ab-initio molecular dynamics: Application to hydrophobic/hydrophilic solutes in bulk water.

PubMed

Partovi-Azar, Pouya; Kühne, Thomas D

2015-11-05

We present a novel computational method to accurately calculate Raman spectra from first principles. Together with an extension of the second-generation Car-Parrinello method of Kühne et al. (Phys. Rev. Lett. 2007, 98, 066401) to propagate maximally localized Wannier functions together with the nuclei, a speed-up of one order of magnitude can be observed. This scheme thus allows to routinely calculate finite-temperature Raman spectra "on-the-fly" by means of ab-initio molecular dynamics simulations. To demonstrate the predictive power of this approach we investigate the effect of hydrophobic and hydrophilic solutes in water solution on the infrared and Raman spectra. © 2015 Wiley Periodicals, Inc.

Cocaine dependence and thalamic functional connectivity: a multivariate pattern analysis.

PubMed

Zhang, Sheng; Hu, Sien; Sinha, Rajita; Potenza, Marc N; Malison, Robert T; Li, Chiang-Shan R

2016-01-01

Cocaine dependence is associated with deficits in cognitive control. Previous studies demonstrated that chronic cocaine use affects the activity and functional connectivity of the thalamus, a subcortical structure critical for cognitive functioning. However, the thalamus contains nuclei heterogeneous in functions, and it is not known how thalamic subregions contribute to cognitive dysfunctions in cocaine dependence. To address this issue, we used multivariate pattern analysis (MVPA) to examine how functional connectivity of the thalamus distinguishes 100 cocaine-dependent participants (CD) from 100 demographically matched healthy control individuals (HC). We characterized six task-related networks with independent component analysis of fMRI data of a stop signal task and employed MVPA to distinguish CD from HC on the basis of voxel-wise thalamic connectivity to the six independent components. In an unbiased model of distinct training and testing data, the analysis correctly classified 72% of subjects with leave-one-out cross-validation (p < 0.001), superior to comparison brain regions with similar voxel counts (p < 0.004, two-sample t test). Thalamic voxels that form the basis of classification aggregate in distinct subclusters, suggesting that connectivities of thalamic subnuclei distinguish CD from HC. Further, linear regressions provided suggestive evidence for a correlation of the thalamic connectivities with clinical variables and performance measures on the stop signal task. Together, these findings support thalamic circuit dysfunction in cognitive control as an important neural marker of cocaine dependence.

Identification and Functional Analysis of Healing Regulators in Drosophila

PubMed Central

Álvarez-Fernández, Carmen; Tamirisa, Srividya; Prada, Federico; Chernomoretz, Ariel; Podhajcer, Osvaldo; Blanco, Enrique; Martín-Blanco, Enrique

2015-01-01

Wound healing is an essential homeostatic mechanism that maintains the epithelial barrier integrity after tissue damage. Although we know the overall steps in wound healing, many of the underlying molecular mechanisms remain unclear. Genetically amenable systems, such as wound healing in Drosophila imaginal discs, do not model all aspects of the repair process. However, they do allow the less understood aspects of the healing response to be explored, e.g., which signal(s) are responsible for initiating tissue remodeling? How is sealing of the epithelia achieved? Or, what inhibitory cues cancel the healing machinery upon completion? Answering these and other questions first requires the identification and functional analysis of wound specific genes. A variety of different microarray analyses of murine and humans have identified characteristic profiles of gene expression at the wound site, however, very few functional studies in healing regulation have been carried out. We developed an experimentally controlled method that is healing-permissive and that allows live imaging and biochemical analysis of cultured imaginal discs. We performed comparative genome-wide profiling between Drosophila imaginal cells actively involved in healing versus their non-engaged siblings. Sets of potential wound-specific genes were subsequently identified. Importantly, besides identifying and categorizing new genes, we functionally tested many of their gene products by genetic interference and overexpression in healing assays. This non-saturated analysis defines a relevant set of genes whose changes in expression level are functionally significant for proper tissue repair. Amongst these we identified the TCP1 chaperonin complex as a key regulator of the actin cytoskeleton essential for the wound healing response. There is promise that our newly identified wound-healing genes will guide future work in the more complex mammalian wound healing response. PMID:25647511

Emotional functioning of adolescents and adults with congenital heart disease: a meta-analysis.

PubMed

Jackson, Jamie L; Misiti, Brian; Bridge, Jeffrey A; Daniels, Curt J; Vannatta, Kathryn

2015-01-01

This study aimed to quantitatively compare findings of emotional functioning across studies of adolescents and adults with congenital heart disease (CHD) through meta-analysis. The current meta-analysis included 22 studies of adolescent and adult survivors of CHD who completed measures of emotional functioning. Effect sizes were represented by Hedge's g. Heterogeneity was calculated and possible moderators (i.e., lesion severity, age, study location, study quality) were examined. Overall, adolescent and adult survivors of CHD did not differ in emotional functioning from healthy controls or normative data. However, significant heterogeneity was found, and there was a trend for degree of lesion severity to moderate emotional functioning. Further analysis of lesion severity indicated that individuals with moderate lesions reported better emotional functioning than controls/normative data. Limitations in existing literature precluded examination of patient age as a moderator. Study location and quality did not explain a significant portion of the variance in effects. Findings suggest that differences in emotional functioning may exist across lesion severities, and individuals with moderately severe lesions are emotionally thriving. Given the diversity within CHD lesion classifications, future studies should include other indicators of disease severity, such as measures of morbidity, to determine how disease may affect emotional functioning among survivors of CHD. Furthermore, authors and journals need to ensure that research is reported in enough detail to facilitate meta-analysis, a critically important tool in answering discrepancies in the literature. © 2014 Wiley Periodicals, Inc.

Meta-analysis of executive functioning in ecstasy/polydrug users.

PubMed

Roberts, C A; Jones, A; Montgomery, C

2016-06-01

Ecstasy/3,4-methylenedioxymethamphetamine (MDMA) use is proposed to cause damage to serotonergic (5-HT) axons in humans. Therefore, users should show deficits in cognitive processes that rely on serotonin-rich, prefrontal areas of the brain. However, there is inconsistency in findings to support this hypothesis. The aim of the current study was to examine deficits in executive functioning in ecstasy users compared with controls using meta-analysis. We identified k = 39 studies, contributing 89 effect sizes, investigating executive functioning in ecstasy users and polydrug-using controls. We compared function-specific task performance in 1221 current ecstasy users and 1242 drug-using controls, from tasks tapping the executive functions - updating, switching, inhibition and access to long-term memory. The significant main effect demonstrated overall executive dysfunction in ecstasy users [standardized mean difference (SMD) = -0.18, 95% confidence interval (CI) -0.26 to -0.11, Z = 5.05, p < 0.001, I 2 = 82%], with a significant subgroup effect (χ 2 = 22.06, degrees of freedom = 3, p < 0.001, I 2 = 86.4%) demonstrating differential effects across executive functions. Ecstasy users showed significant performance deficits in access (SMD = -0.33, 95% CI -0.46 to -0.19, Z = 4.72, p < 0.001, I 2 = 74%), switching (SMD = -0.19, 95% CI -0.36 to -0.02, Z = 2.16, p < 0.05, I 2 = 85%) and updating (SMD = -0.26, 95% CI -0.37 to -0.15, Z = 4.49, p < 0.001, I 2 = 82%). No differences were observed in inhibitory control. We conclude that this is the most comprehensive analysis of executive function in ecstasy users to date and provides a behavioural correlate of potential serotonergic neurotoxicity.

Functional analysis-based interventions for challenging behaviour in dementia.

PubMed

Moniz Cook, Esme D; Swift, Katie; James, Ian; Malouf, Reem; De Vugt, Marjolein; Verhey, Frans

2012-02-15

Functional analysis (FA) for the management of challenging behaviour is a promising behavioural intervention that involves exploring the meaning or purpose of an individual's behaviour. It extends the 'ABC' approach of behavioural analysis, to overcome the restriction of having to derive a single explanatory hypothesis for the person's behaviour. It is seen as a first line alternative to traditional pharmacological management for agitation and aggression. FA typically requires the therapist to develop and evaluate hypotheses-driven strategies that aid family and staff caregivers to reduce or resolve a person's distress and its associated behavioural manifestations. To assess the effects of functional analysis-based interventions for people with dementia (and their caregivers) living in their own home or in other settings. We searched ALOIS: the Cochrane Dementia and Cognitive Improvement Group's Specialized Register on 3 March 2011 using the terms: FA, behaviour (intervention, management, modification), BPSD, psychosocial and Dementia. Randomised controlled trials (RCTs) with reported behavioural outcomes that could be associated with functional analysis for the management of challenging behaviour in dementia. Four reviewers selected trials for inclusion. Two reviewers worked independently to extract data and assess trial quality, including bias. Meta-analyses for reported incidence, frequency, severity of care recipient challenging behaviour and mood (primary outcomes) and caregiver reaction, burden and mood were performed. Details of adverse effects were noted. Eighteen trials are included in the review. The majority were in family care settings. For fourteen studies, FA was just one aspect of a broad multi-component programme of care. Assessing the effect of FA was compromised by ill-defined protocols for the duration of component parts of these programmes (i.e. frequency of the intervention or actual time spent). Therefore, establishing the real effect of the

Motor function and incident dementia: a systematic review and meta-analysis.

PubMed

Kueper, Jacqueline Kathleen; Speechley, Mark; Lingum, Navena Rebecca; Montero-Odasso, Manuel

2017-09-01

cognitive and mobility decline are interrelated processes, whereby mobility decline coincides or precedes the onset of cognitive decline. to assess whether there is an association between performance on motor function tests and incident dementia. electronic database, grey literature and hand searching identified studies testing for associations between baseline motor function and incident dementia in older adults. of 2,540 potentially relevant documents, 37 met the final inclusion criteria and were reviewed qualitatively. Three meta-analyses were conducted using data from 10 studies. Three main motor domains-upper limb motor function, parkinsonism and lower limb motor function-emerged as associated with increased risk of incident dementia. Studies including older adults without neurological overt disease found a higher risk of incident dementia associated with poorer performance on composite motor function scores, balance and gait velocity (meta-analysis pooled HR = 1.94, 95% CI: 1.41, 2.65). Mixed results were found across different study samples for upper limb motor function, overall parkinsonism (meta-analysis pooled OR = 3.05, 95% CI: 1.31, 7.08), bradykinesia and rigidity. Studies restricted to older adults with Parkinson's Disease found weak or no association with incident dementia even for motor domains highly associated in less restrictive samples. Tremor was not associated with an increased risk of dementia in any population (meta-analysis pooled HR = 0.80, 95% CI 0.31, 2.03). lower limb motor function was associated with increased risk of developing dementia, while tremor and hand grip strength were not. Our results support future research investigating the inclusion of quantitative motor assessment, specifically gait velocity tests, for clinical dementia risk evaluation. © The Author 2017. Published by Oxford University Press on behalf of the British Geriatrics Society.All rights reserved. For permissions, please email: journals.permissions@oup.com

The aquatic animals' transcriptome resource for comparative functional analysis.

PubMed

Chou, Chih-Hung; Huang, Hsi-Yuan; Huang, Wei-Chih; Hsu, Sheng-Da; Hsiao, Chung-Der; Liu, Chia-Yu; Chen, Yu-Hung; Liu, Yu-Chen; Huang, Wei-Yun; Lee, Meng-Lin; Chen, Yi-Chang; Huang, Hsien-Da

2018-05-09

Aquatic animals have great economic and ecological importance. Among them, non-model organisms have been studied regarding eco-toxicity, stress biology, and environmental adaptation. Due to recent advances in next-generation sequencing techniques, large amounts of RNA-seq data for aquatic animals are publicly available. However, currently there is no comprehensive resource exist for the analysis, unification, and integration of these datasets. This study utilizes computational approaches to build a new resource of transcriptomic maps for aquatic animals. This aquatic animal transcriptome map database dbATM provides de novo assembly of transcriptome, gene annotation and comparative analysis of more than twenty aquatic organisms without draft genome. To improve the assembly quality, three computational tools (Trinity, Oases and SOAPdenovo-Trans) were employed to enhance individual transcriptome assembly, and CAP3 and CD-HIT-EST software were then used to merge these three assembled transcriptomes. In addition, functional annotation analysis provides valuable clues to gene characteristics, including full-length transcript coding regions, conserved domains, gene ontology and KEGG pathways. Furthermore, all aquatic animal genes are essential for comparative genomics tasks such as constructing homologous gene groups and blast databases and phylogenetic analysis. In conclusion, we establish a resource for non model organism aquatic animals, which is great economic and ecological importance and provide transcriptomic information including functional annotation and comparative transcriptome analysis. The database is now publically accessible through the URL http://dbATM.mbc.nctu.edu.tw/ .

A density difference based analysis of orbital-dependent exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Grabowski, Ireneusz; Teale, Andrew M.; Fabiano, Eduardo; Śmiga, Szymon; Buksztel, Adam; Della Sala, Fabio

2014-03-01

We present a density difference based analysis for a range of orbital-dependent Kohn-Sham functionals. Results for atoms, some members of the neon isoelectronic series and small molecules are reported and compared with ab initio wave function calculations. Particular attention is paid to the quality of approximations to the exchange-only optimised effective potential (OEP) approach: we consider both the localised Hartree-Fock as well as the Krieger-Li-Iafrate methods. Analysis of density differences at the exchange-only level reveals the impact of the approximations on the resulting electronic densities. These differences are further quantified in terms of the ground state energies, frontier orbital energy differences and highest occupied orbital energies obtained. At the correlated level, an OEP approach based on a perturbative second-order correlation energy expression is shown to deliver results comparable with those from traditional wave function approaches, making it suitable for use as a benchmark against which to compare standard density functional approximations.

Bayesian hierarchical functional data analysis via contaminated informative priors.

PubMed

Scarpa, Bruno; Dunson, David B

2009-09-01

A variety of flexible approaches have been proposed for functional data analysis, allowing both the mean curve and the distribution about the mean to be unknown. Such methods are most useful when there is limited prior information. Motivated by applications to modeling of temperature curves in the menstrual cycle, this article proposes a flexible approach for incorporating prior information in semiparametric Bayesian analyses of hierarchical functional data. The proposed approach is based on specifying the distribution of functions as a mixture of a parametric hierarchical model and a nonparametric contamination. The parametric component is chosen based on prior knowledge, while the contamination is characterized as a functional Dirichlet process. In the motivating application, the contamination component allows unanticipated curve shapes in unhealthy menstrual cycles. Methods are developed for posterior computation, and the approach is applied to data from a European fecundability study.

Mendelian randomization analysis of a time-varying exposure for binary disease outcomes using functional data analysis methods.

PubMed

Cao, Ying; Rajan, Suja S; Wei, Peng

2016-12-01

A Mendelian randomization (MR) analysis is performed to analyze the causal effect of an exposure variable on a disease outcome in observational studies, by using genetic variants that affect the disease outcome only through the exposure variable. This method has recently gained popularity among epidemiologists given the success of genetic association studies. Many exposure variables of interest in epidemiological studies are time varying, for example, body mass index (BMI). Although longitudinal data have been collected in many cohort studies, current MR studies only use one measurement of a time-varying exposure variable, which cannot adequately capture the long-term time-varying information. We propose using the functional principal component analysis method to recover the underlying individual trajectory of the time-varying exposure from the sparsely and irregularly observed longitudinal data, and then conduct MR analysis using the recovered curves. We further propose two MR analysis methods. The first assumes a cumulative effect of the time-varying exposure variable on the disease risk, while the second assumes a time-varying genetic effect and employs functional regression models. We focus on statistical testing for a causal effect. Our simulation studies mimicking the real data show that the proposed functional data analysis based methods incorporating longitudinal data have substantial power gains compared to standard MR analysis using only one measurement. We used the Framingham Heart Study data to demonstrate the promising performance of the new methods as well as inconsistent results produced by the standard MR analysis that relies on a single measurement of the exposure at some arbitrary time point. © 2016 WILEY PERIODICALS, INC.

An analysis of functional shoulder movements during task performance using Dartfish movement analysis software.

PubMed

Khadilkar, Leenesh; MacDermid, Joy C; Sinden, Kathryn E; Jenkyn, Thomas R; Birmingham, Trevor B; Athwal, George S

2014-01-01

Video-based movement analysis software (Dartfish) has potential for clinical applications for understanding shoulder motion if functional measures can be reliably obtained. The primary purpose of this study was to describe the functional range of motion (ROM) of the shoulder used to perform a subset of functional tasks. A second purpose was to assess the reliability of functional ROM measurements obtained by different raters using Dartfish software. Ten healthy participants, mean age 29 ± 5 years, were videotaped while performing five tasks selected from the Disabilities of the Arm, Shoulder and Hand (DASH). Video cameras and markers were used to obtain video images suitable for analysis in Dartfish software. Three repetitions of each task were performed. Shoulder movements from all three repetitions were analyzed using Dartfish software. The tracking tool of the Dartfish software was used to obtain shoulder joint angles and arcs of motion. Test-retest and inter-rater reliability of the measurements were evaluated using intraclass correlation coefficients (ICC). Maximum (coronal plane) abduction (118° ± 16°) and (sagittal plane) flexion (111° ± 15°) was observed during 'washing one's hair;' maximum extension (-68° ± 9°) was identified during 'washing one's own back.' Minimum shoulder ROM was observed during 'opening a tight jar' (33° ± 13° abduction and 13° ± 19° flexion). Test-retest reliability (ICC = 0.45 to 0.94) suggests high inter-individual task variability, and inter-rater reliability (ICC = 0.68 to 1.00) showed moderate to excellent agreement. KEY FINDINGS INCLUDE: 1) functional shoulder ROM identified in this study compared to similar studies; 2) healthy individuals require less than full ROM when performing five common ADL tasks 3) high participant variability was observed during performance of the five ADL tasks; and 4) Dartfish software provides a clinically relevant tool to analyze shoulder function.

Threshold law for positron-atom impact ionisation

NASA Technical Reports Server (NTRS)

Temkin, A.

1982-01-01

The threshold law for ionisation of atoms by positron impact is adduced in analogy with our approach to the electron-atom ionization. It is concluded the Coulomb-dipole region of the potential gives the essential part of the interaction in both cases and leads to the same kind of result: a modulated linear law. An additional process which enters positron ionization is positronium formation in the continuum, but that will not dominate the threshold yield. The result is in sharp contrast to the positron threshold law as recently derived by Klar on the basis of a Wannier-type analysis.

Resting-state functional magnetic resonance imaging: the impact of regression analysis.

PubMed

Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

2015-01-01

To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

Big Bang Bifurcation Analysis and Allee Effect in Generic Growth Functions

NASA Astrophysics Data System (ADS)

Leonel Rocha, J.; Taha, Abdel-Kaddous; Fournier-Prunaret, D.

2016-06-01

The main purpose of this work is to study the dynamics and bifurcation properties of generic growth functions, which are defined by the population size functions of the generic growth equation. This family of unimodal maps naturally incorporates a principal focus of ecological and biological research: the Allee effect. The analysis of this kind of extinction phenomenon allows to identify a class of Allee’s functions and characterize the corresponding Allee’s effect region and Allee’s bifurcation curve. The bifurcation analysis is founded on the performance of fold and flip bifurcations. The dynamical behavior is rich with abundant complex bifurcation structures, the big bang bifurcations of the so-called “box-within-a-box” fractal type being the most outstanding. Moreover, these bifurcation cascades converge to different big bang bifurcation curves with distinct kinds of boxes, where for the corresponding parameter values several attractors are associated. To the best of our knowledge, these results represent an original contribution to clarify the big bang bifurcation analysis of continuous 1D maps.

Using Trial-Based Functional Analysis to Design Effective Interventions for Students Diagnosed with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Larkin, Wallace; Hawkins, Renee O.; Collins, Tai

2016-01-01

Functional behavior assessments and function-based interventions are effective methods for addressing the challenging behaviors of children; however, traditional functional analysis has limitations that impact usability in applied settings. Trial-based functional analysis addresses concerns relating to the length of time, level of expertise…

A complementation assay for in vivo protein structure/function analysis in Physcomitrella patens (Funariaceae)

DOE PAGES

Scavuzzo-Duggan, Tess R.; Chaves, Arielle M.; Roberts, Alison W.

2015-07-14

Here, a method for rapid in vivo functional analysis of engineered proteins was developed using Physcomitrella patens. A complementation assay was designed for testing structure/function relationships in cellulose synthase (CESA) proteins. The components of the assay include (1) construction of test vectors that drive expression of epitope-tagged PpCESA5 carrying engineered mutations, (2) transformation of a ppcesa5 knockout line that fails to produce gametophores with test and control vectors, (3) scoring the stable transformants for gametophore production, (4) statistical analysis comparing complementation rates for test vectors to positive and negative control vectors, and (5) analysis of transgenic protein expression by Westernmore » blotting. The assay distinguished mutations that generate fully functional, nonfunctional, and partially functional proteins. In conclusion, compared with existing methods for in vivo testing of protein function, this complementation assay provides a rapid method for investigating protein structure/function relationships in plants.« less

Human factors evaluation of teletherapy: Function and task analysis. Volume 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaye, R.D.; Henriksen, K.; Jones, R.

1995-07-01

As a treatment methodology, teletherapy selectively destroys cancerous and other tissue by exposure to an external beam of ionizing radiation. Sources of radiation are either a radioactive isotope, typically Cobalt-60 (Co-60), or a linear accelerator. Records maintained by the NRC have identified instances of teletherapy misadministration where the delivered radiation dose has differed from the radiation prescription (e.g., instances where fractions were delivered to the wrong patient, to the wrong body part, or were too great or too little with respect to the defined treatment volume). Both human error and machine malfunction have led to misadministrations. Effective and safe treatmentmore » requires a concern for precision and consistency of human-human and human-machine interactions throughout the course of therapy. The present study is the first part of a series of human factors evaluations for identifying the root causes that lead to human error in the teletherapy environment. The human factors evaluations included: (1) a function and task analysis of teletherapy activities, (2) an evaluation of the human-system interfaces, (3) an evaluation of procedures used by teletherapy staff, (4) an evaluation of the training and qualifications of treatment staff (excluding the oncologists), (5) an evaluation of organizational practices and policies, and (6) an identification of problems and alternative approaches for NRC and industry attention. The present report addresses the function and task analysis of teletherapy activities and provides the foundation for the conduct of the subsequent evaluations. The report includes sections on background, methodology, a description of the function and task analysis, and use of the task analysis findings for the subsequent tasks. The function and task analysis data base also is included.« less

Comparisons of synthesized and individual reinforcement contingencies during functional analysis.

PubMed

Fisher, Wayne W; Greer, Brian D; Romani, Patrick W; Zangrillo, Amanda N; Owen, Todd M

2016-09-01

Researchers typically modify individual functional analysis (FA) conditions after results are inconclusive (Hanley, Iwata, & McCord, 2003). Hanley, Jin, Vanselow, and Hanratty (2014) introduced a marked departure from this practice, using an interview-informed synthesized contingency analysis (IISCA). In the test condition, they delivered multiple contingencies simultaneously (e.g., attention and escape) after each occurrence of problem behavior; in the control condition, they delivered those same reinforcers noncontingently and continuously. In the current investigation, we compared the results of the IISCA with a more traditional FA in which we evaluated each putative reinforcer individually. Four of 5 participants displayed destructive behavior that was sensitive to the individual contingencies evaluated in the traditional FA. By contrast, none of the participants showed a response pattern consistent with the assumption of the IISCA. We discuss the implications of these findings on the development of accurate and efficient functional analyses. © 2016 Society for the Experimental Analysis of Behavior.

A functional U-statistic method for association analysis of sequencing data.

PubMed

Jadhav, Sneha; Tong, Xiaoran; Lu, Qing

2017-11-01

Although sequencing studies hold great promise for uncovering novel variants predisposing to human diseases, the high dimensionality of the sequencing data brings tremendous challenges to data analysis. Moreover, for many complex diseases (e.g., psychiatric disorders) multiple related phenotypes are collected. These phenotypes can be different measurements of an underlying disease, or measurements characterizing multiple related diseases for studying common genetic mechanism. Although jointly analyzing these phenotypes could potentially increase the power of identifying disease-associated genes, the different types of phenotypes pose challenges for association analysis. To address these challenges, we propose a nonparametric method, functional U-statistic method (FU), for multivariate analysis of sequencing data. It first constructs smooth functions from individuals' sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic. The method provides a general framework for analyzing various types of phenotypes (e.g., binary and continuous phenotypes) with unknown distributions. Fitting the genetic variants within a gene using a smoothing function also allows us to capture complexities of gene structure (e.g., linkage disequilibrium, LD), which could potentially increase the power of association analysis. Through simulations, we compared our method to the multivariate outcome score test (MOST), and found that our test attained better performance than MOST. In a real data application, we apply our method to the sequencing data from Minnesota Twin Study (MTS) and found potential associations of several nicotine receptor subunit (CHRN) genes, including CHRNB3, associated with nicotine dependence and/or alcohol dependence. © 2017 WILEY PERIODICALS, INC.

Discriminant analysis of functional optical topography for schizophrenia diagnosis

NASA Astrophysics Data System (ADS)

Chuang, Ching-Cheng; Nakagome, Kazuyuki; Pu, Shenghong; Lan, Tsuo-Hung; Lee, Chia-Yen; Sun, Chia-Wei

2014-01-01

Abnormal prefrontal function plays a central role in the cognition deficits of schizophrenic patients; however, the character of the relationship between discriminant analysis and prefrontal activation remains undetermined. Recently, evidence of low prefrontal cortex (PFC) activation in individuals with schizophrenia has also been found during verbal fluency tests (VFT) and other cognitive tests with several neuroimaging methods. The purpose of this study is to assess the hemodynamic changes of the PFC and discriminant analysis between schizophrenia patients and healthy controls during VFT task by utilizing functional optical topography. A total of 99 subjects including 53 schizophrenic patients and 46 age- and gender-matched healthy controls were studied. The results showed that the healthy group had larger activation in the right and left PFC than in the middle PFC. Besides, the schizophrenic group showed weaker task performance and lower activation in the whole PFC than the healthy group. The result of the discriminant analysis showed a significant difference with P value <0.001 in six channels (CH 23, 29, 31, 40, 42, 52) between the schizophrenic and healthy groups. Finally, 68.69% and 71.72% of subjects are correctly classified as being schizophrenic or healthy with all 52 channels and six significantly different channels, respectively. Our findings suggest that the left PFC can be a feature region for discriminant analysis of schizophrenic diagnosis.

Dynamic analysis of patterns of renal sympathetic nerve activity: implications for renal function.

PubMed

DiBona, Gerald F

2005-03-01

Methods of dynamic analysis are used to provide additional understanding of the renal sympathetic neural control of renal function. The concept of functionally specific subgroups of renal sympathetic nerve fibres conveying information encoded in the frequency domain is presented. Analog pulse modulation and pseudorandom binary sequence stimulation patterns are used for the determination of renal vascular frequency response. Transfer function analysis is used to determine the effects of non-renal vasoconstrictor and vasoconstrictor intensities of renal sympathetic nerve activity on dynamic autoregulation of renal blood flow.

Function Point Analysis Depot

NASA Technical Reports Server (NTRS)

Muniz, R.; Martinez, El; Szafran, J.; Dalton, A.

2011-01-01

The Function Point Analysis (FPA) Depot is a web application originally designed by one of the NE-C3 branch's engineers, Jamie Szafran, and created specifically for the Software Development team of the Launch Control Systems (LCS) project. The application consists of evaluating the work of each developer to be able to get a real estimate of the hours that is going to be assigned to a specific task of development. The Architect Team had made design change requests for the depot to change the schema of the application's information; that information, changed in the database, needed to be changed in the graphical user interface (GUI) (written in Ruby on Rails (RoR and the web service/server side in Java to match the database changes. These changes were made by two interns from NE-C, Ricardo Muniz from NE-C3, who made all the schema changes for the GUI in RoR and Edwin Martinez, from NE-C2, who made all the changes in the Java side.

Functional neuroanatomy of auditory scene analysis in Alzheimer's disease

PubMed Central

Golden, Hannah L.; Agustus, Jennifer L.; Goll, Johanna C.; Downey, Laura E.; Mummery, Catherine J.; Schott, Jonathan M.; Crutch, Sebastian J.; Warren, Jason D.

2015-01-01

Auditory scene analysis is a demanding computational process that is performed automatically and efficiently by the healthy brain but vulnerable to the neurodegenerative pathology of Alzheimer's disease. Here we assessed the functional neuroanatomy of auditory scene analysis in Alzheimer's disease using the well-known ‘cocktail party effect’ as a model paradigm whereby stored templates for auditory objects (e.g., hearing one's spoken name) are used to segregate auditory ‘foreground’ and ‘background’. Patients with typical amnestic Alzheimer's disease (n = 13) and age-matched healthy individuals (n = 17) underwent functional 3T-MRI using a sparse acquisition protocol with passive listening to auditory stimulus conditions comprising the participant's own name interleaved with or superimposed on multi-talker babble, and spectrally rotated (unrecognisable) analogues of these conditions. Name identification (conditions containing the participant's own name contrasted with spectrally rotated analogues) produced extensive bilateral activation involving superior temporal cortex in both the AD and healthy control groups, with no significant differences between groups. Auditory object segregation (conditions with interleaved name sounds contrasted with superimposed name sounds) produced activation of right posterior superior temporal cortex in both groups, again with no differences between groups. However, the cocktail party effect (interaction of own name identification with auditory object segregation processing) produced activation of right supramarginal gyrus in the AD group that was significantly enhanced compared with the healthy control group. The findings delineate an altered functional neuroanatomical profile of auditory scene analysis in Alzheimer's disease that may constitute a novel computational signature of this neurodegenerative pathology. PMID:26029629

Project FAST: [Functional Analysis Systems Training]: Adopter/Facilitator Information.

ERIC Educational Resources Information Center

Essexville-Hampton Public Schools, MI.

Presented is adopter/facilitator information of Project FAST (Functional Analysis Systems Training) to provide educational and support services to learning disordered children and their regular elementary teachers. Briefly described are the three schools in the Essexville-Hampton (Michigan) school district; objectives of the program; program…

Functional Analysis of Episodic Self-Injury Correlated with Recurrent Otitis Media.

ERIC Educational Resources Information Center

O'Reilly, Mark F.

1997-01-01

A functional analysis examined the consequences that maintained episodic self-injury and the relationship between those consequences and otitis media for a 26-month-old child with developmental disabilities. Results indicated that self-injury occurred only during periods of otitis media and may have served as a sensory escape function. (Author/CR)

Training Public School Special Educators to Implement Two Functional Analysis Models

ERIC Educational Resources Information Center

Rispoli, Mandy; Neely, Leslie; Healy, Olive; Gregori, Emily

2016-01-01

The purpose of this study was to investigate the efficacy and efficiency of a training package to teach public school special educators to conduct functional analyses of challenging behavior. Six public school educators were divided into two cohorts of three and were taught two models of functional analysis of challenging behavior: traditional and…

Transfer function analysis of thermospheric perturbations

NASA Technical Reports Server (NTRS)

Mayr, H. G.; Harris, I.; Varosi, F.; Herrero, F. A.; Spencer, N. W.

1986-01-01

Applying perturbation theory, a spectral model in terms of vectors spherical harmonics (Legendre polynomials) is used to describe the short term thermospheric perturbations originating in the auroral regions. The source may be Joule heating, particle precipitation or ExB ion drift-momentum coupling. A multiconstituent atmosphere is considered, allowing for the collisional momentum exchange between species including Ar, O2, N2, O, He and H. The coupled equations of energy, mass and momentum conservation are solved simultaneously for the major species N2 and O. Applying homogeneous boundary conditions, the integration is carred out from the Earth's surface up to 700 km. In the analysis, the spherical harmonics are treated as eigenfunctions, assuming that the Earth's rotation (and prevailing circulation) do not significantly affect perturbations with periods which are typically much less than one day. Under these simplifying assumptions, and given a particular source distribution in the vertical, a two dimensional transfer function is constructed to describe the three dimensional response of the atmosphere. In the order of increasing horizontal wave numbers (order of polynomials), this transfer function reveals five components. To compile the transfer function, the numerical computations are very time consuming (about 100 hours on a VAX for one particular vertical source distribution). However, given the transfer function, the atmospheric response in space and time (using Fourier integral representation) can be constructed with a few seconds of a central processing unit. This model is applied in a case study of wind and temperature measurements on the Dynamics Explorer B, which show features characteristic of a ringlike excitation source in the auroral oval. The data can be interpreted as gravity waves which are focused (and amplified) in the polar region and then are reflected to propagate toward lower latitudes.

Transfer function analysis of thermospheric perturbations

NASA Astrophysics Data System (ADS)

Mayr, H. G.; Harris, I.; Varosi, F.; Herrero, F. A.; Spencer, N. W.

1986-06-01

Applying perturbation theory, a spectral model in terms of vectors spherical harmonics (Legendre polynomials) is used to describe the short term thermospheric perturbations originating in the auroral regions. The source may be Joule heating, particle precipitation or ExB ion drift-momentum coupling. A multiconstituent atmosphere is considered, allowing for the collisional momentum exchange between species including Ar, O2, N2, O, He and H. The coupled equations of energy, mass and momentum conservation are solved simultaneously for the major species N2 and O. Applying homogeneous boundary conditions, the integration is carred out from the Earth's surface up to 700 km. In the analysis, the spherical harmonics are treated as eigenfunctions, assuming that the Earth's rotation (and prevailing circulation) do not significantly affect perturbations with periods which are typically much less than one day. Under these simplifying assumptions, and given a particular source distribution in the vertical, a two dimensional transfer function is constructed to describe the three dimensional response of the atmosphere. In the order of increasing horizontal wave numbers (order of polynomials), this transfer function reveals five components. To compile the transfer function, the numerical computations are very time consuming (about 100 hours on a VAX for one particular vertical source distribution). However, given the transfer function, the atmospheric response in space and time (using Fourier integral representation) can be constructed with a few seconds of a central processing unit. This model is applied in a case study of wind and temperature measurements on the Dynamics Explorer B, which show features characteristic of a ringlike excitation source in the auroral oval. The data can be interpreted as gravity waves which are focused (and amplified) in the polar region and then are reflected to propagate toward lower latitudes.

Molar Functional Relations and Clinical Behavior Analysis: Implications for Assessment and Treatment

ERIC Educational Resources Information Center

Waltz, Thomas J.; Follette, William C.

2009-01-01

The experimental analysis of behavior has identified several molar functional relations that are highly relevant to clinical behavior analysis. These include matching, discounting, momentum, and variability. Matching provides a broader analysis of how multiple sources of reinforcement influence how individuals choose to allocate their time and…

Functional Analysis and Treatment of Noncompliance by Preschool Children

ERIC Educational Resources Information Center

Wilder, David A.; Harris, Carelle; Reagan, Renee; Rasey, Amy

2007-01-01

A functional analysis showed that noncompliance occurred most often for 2 preschoolers when it resulted in termination of a preferred activity, suggesting that noncompliance was maintained by positive reinforcement. A differential reinforcement procedure, which involved contingent access to coupons that could be exchanged for uninterrupted access…

The Limits of Functional Analysis in the Study of Mass Communication.

ERIC Educational Resources Information Center

Anderson, James A.; Meyer, Timothy P.

The fundamental limits of the functional approach to the study of mass communication are embodied in two of its criticisms. The first weakness is in its logical structure and the second involves the limits that are set by known methods. Functional analysis has difficulties as a meaningful research perspective because the process of mass…

Exploratory factor analysis of the functional movement screen in elite athletes.

PubMed

Li, Yongming; Wang, Xiong; Chen, Xiaoping; Dai, Boyi

2015-01-01

The functional movement screen is developed to examine individuals' movement patterns through 7 functional tasks. The purpose of this study was to identify the internal consistency and factor structure of the 7 tasks of the functional movement screen in elite athletes; 290 elite athletes from a variety of Chinese national teams were assessed using the functional movement screen. Cronbach's alpha was calculated for the scores of the 7 tasks. Exploratory factor analysis was performed to explore the factor structure of the functional movement screen. The mean and standard deviation of the sum score were 15.2 ± 3.0. A low Cronbach's alpha (0.58) was found for the scores of the 7 tasks. Exploratory factor analysis extracted 2 factors with eigenvalues greater than 1, and these 2 factors explained 47.3% of the total variance. The first factor had a high loading on the rotatory stability (loading = 0.99) and low loadings on the other 6 tasks (loading range: 0.04-0.34). The second factor had high loadings on the deep squat, hurdle step and inline lunge (loading range: 0.46-0.61) and low loadings on the other 3 tasks (loading range: 0.12-0.32). The 7 tasks of the functional movement screen had low internal consistency and were not indicators of a single factor. Evidence for unidimensionality was not found for the functional movement screen in elite athletes. More attention should be paid to the score of each task rather than the sum score when we interpret the functional movement screen scores.

Analysis of space vehicle structures using the transfer-function concept

NASA Technical Reports Server (NTRS)

Heer, E.; Trubert, M. R.

1969-01-01

Analysis of large complex systems is accomplished by dividing it into suitable subsystems and determining the individual dynamical and vibrational responses. Frequency transfer functions then determine the vibrational response of the whole system.

Parametric Cost Analysis: A Design Function

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1989-01-01

Parametric cost analysis uses equations to map measurable system attributes into cost. The measures of the system attributes are called metrics. The equations are called cost estimating relationships (CER's), and are obtained by the analysis of cost and technical metric data of products analogous to those to be estimated. Examples of system metrics include mass, power, failure_rate, mean_time_to_repair, energy _consumed, payload_to_orbit, pointing_accuracy, manufacturing_complexity, number_of_fasteners, and percent_of_electronics_weight. The basic assumption is that a measurable relationship exists between system attributes and the cost of the system. If a function exists, the attributes are cost drivers. Candidates for metrics include system requirement metrics and engineering process metrics. Requirements are constraints on the engineering process. From optimization theory we know that any active constraint generates cost by not permitting full optimization of the objective. Thus, requirements are cost drivers. Engineering processes reflect a projection of the requirements onto the corporate culture, engineering technology, and system technology. Engineering processes are an indirect measure of the requirements and, hence, are cost drivers.

Image-derived input function with factor analysis and a-priori information.

PubMed

Simončič, Urban; Zanotti-Fregonara, Paolo

2015-02-01

Quantitative PET studies often require the cumbersome and invasive procedure of arterial cannulation to measure the input function. This study sought to minimize the number of necessary blood samples by developing a factor-analysis-based image-derived input function (IDIF) methodology for dynamic PET brain studies. IDIF estimation was performed as follows: (a) carotid and background regions were segmented manually on an early PET time frame; (b) blood-weighted and tissue-weighted time-activity curves (TACs) were extracted with factor analysis; (c) factor analysis results were denoised and scaled using the voxels with the highest blood signal; (d) using population data and one blood sample at 40 min, whole-blood TAC was estimated from postprocessed factor analysis results; and (e) the parent concentration was finally estimated by correcting the whole-blood curve with measured radiometabolite concentrations. The methodology was tested using data from 10 healthy individuals imaged with [(11)C](R)-rolipram. The accuracy of IDIFs was assessed against full arterial sampling by comparing the area under the curve of the input functions and by calculating the total distribution volume (VT). The shape of the image-derived whole-blood TAC matched the reference arterial curves well, and the whole-blood area under the curves were accurately estimated (mean error 1.0±4.3%). The relative Logan-V(T) error was -4.1±6.4%. Compartmental modeling and spectral analysis gave less accurate V(T) results compared with Logan. A factor-analysis-based IDIF for [(11)C](R)-rolipram brain PET studies that relies on a single blood sample and population data can be used for accurate quantification of Logan-V(T) values.

Analysis/forecast experiments with a flow-dependent correlation function using FGGE data

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Carus, H.; Nestler, M. S.

1986-01-01

The use of a flow-dependent correlation function to improve the accuracy of an optimum interpolation (OI) scheme is examined. The development of the correlation function for the OI analysis scheme used for numerical weather prediction is described. The scheme uses a multivariate surface analysis over the oceans to model the pressure-wind error cross-correlation and it has the ability to use an error correlation function that is flow- and geographically-dependent. A series of four-day data assimilation experiments, conducted from January 5-9, 1979, were used to investigate the effect of the different features of the OI scheme (error correlation) on forecast skill for the barotropic lows and highs. The skill of the OI was compared with that of a successive correlation method (SCM) of analysis. It is observed that the largest difference in the correlation statistics occurred in barotropic and baroclinic lows and highs. The comparison reveals that the OI forecasts were more accurate than the SCM forecasts.

Density functional plus dynamical mean-field theory of the metal-insulator transition in early transition-metal oxides

NASA Astrophysics Data System (ADS)

Dang, Hung T.; Ai, Xinyuan; Millis, Andrew J.; Marianetti, Chris A.

2014-09-01

The combination of density functional theory and single-site dynamical mean-field theory, using both Hartree and full continuous-time quantum Monte Carlo impurity solvers, is used to study the metal-insulator phase diagram of perovskite transition-metal oxides of the form ABO3 with a rare-earth ion A =Sr, La, Y and transition metal B =Ti, V, Cr. The correlated subspace is constructed from atomiclike d orbitals defined using maximally localized Wannier functions derived from the full p-d manifold; for comparison, results obtained using a projector method are also given. Paramagnetic DFT + DMFT computations using full charge self-consistency along with the standard "fully localized limit" (FLL) double counting are shown to incorrectly predict that LaTiO3, YTiO3, LaVO3, and SrMnO3 are metals. A more general examination of the dependence of physical properties on the mean p-d energy splitting, the occupancy of the correlated d states, the double-counting correction, and the lattice structure demonstrates the importance of charge-transfer physics even in the early transition-metal oxides and elucidates the factors underlying the failure of the standard approximations. If the double counting is chosen to produce a p-d splitting consistent with experimental spectra, single-site dynamical mean-field theory provides a reasonable account of the materials properties. The relation of the results to those obtained from "d-only" models in which the correlation problem is based on the frontier orbital p-d antibonding bands is determined. It is found that if an effective interaction U is properly chosen the d-only model provides a good account of the physics of the d1 and d2 materials.

Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

PubMed Central

Wild, Philipp S.; Felix, Janine F.; Schillert, Arne; Chen, Ming-Huei; Leening, Maarten J.G.; Völker, Uwe; Großmann, Vera; Brody, Jennifer A.; Irvin, Marguerite R.; Shah, Sanjiv J.; Pramana, Setia; Lieb, Wolfgang; Schmidt, Reinhold; Stanton, Alice V.; Malzahn, Dörthe; Lyytikäinen, Leo-Pekka; Tiller, Daniel; Smith, J. Gustav; Di Tullio, Marco R.; Musani, Solomon K.; Morrison, Alanna C.; Pers, Tune H.; Morley, Michael; Kleber, Marcus E.; Aragam, Jayashri; Bis, Joshua C.; Bisping, Egbert; Broeckel, Ulrich; Cheng, Susan; Deckers, Jaap W.; Del Greco M, Fabiola; Edelmann, Frank; Fornage, Myriam; Franke, Lude; Friedrich, Nele; Harris, Tamara B.; Hofer, Edith; Hofman, Albert; Huang, Jie; Hughes, Alun D.; Kähönen, Mika; investigators, KNHI; Kruppa, Jochen; Lackner, Karl J.; Lannfelt, Lars; Laskowski, Rafael; Launer, Lenore J.; Lindgren, Cecilia M.; Loley, Christina; Mayet, Jamil; Medenwald, Daniel; Morris, Andrew P.; Müller, Christian; Müller-Nurasyid, Martina; Nappo, Stefania; Nilsson, Peter M.; Nuding, Sebastian; Nutile, Teresa; Peters, Annette; Pfeufer, Arne; Pietzner, Diana; Pramstaller, Peter P.; Raitakari, Olli T.; Rice, Kenneth M.; Rotter, Jerome I.; Ruohonen, Saku T.; Sacco, Ralph L.; Samdarshi, Tandaw E.; Sharp, Andrew S.P.; Shields, Denis C.; Sorice, Rossella; Sotoodehnia, Nona; Stricker, Bruno H.; Surendran, Praveen; Töglhofer, Anna M.; Uitterlinden, André G.; Völzke, Henry; Ziegler, Andreas; Münzel, Thomas; März, Winfried; Cappola, Thomas P.; Hirschhorn, Joel N.; Mitchell, Gary F.; Smith, Nicholas L.; Fox, Ervin R.; Dueker, Nicole D.; Jaddoe, Vincent W.V.; Melander, Olle; Lehtimäki, Terho; Ciullo, Marina; Hicks, Andrew A.; Lind, Lars; Gudnason, Vilmundur; Pieske, Burkert; Barron, Anthony J.; Zweiker, Robert; Schunkert, Heribert; Ingelsson, Erik; Liu, Kiang; Arnett, Donna K.; Psaty, Bruce M.; Blankenberg, Stefan; Larson, Martin G.; Felix, Stephan B.; Franco, Oscar H.; Zeller, Tanja; Vasan, Ramachandran S.; Dörr, Marcus

2017-01-01

BACKGROUND. Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS. A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS. The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION. The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING. For detailed information per study, see Acknowledgments. PMID:28394258

Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data

PubMed Central

Wang, Yinxue; Shi, Guilai; Miller, David J.; Wang, Yizhi; Wang, Congchao; Broussard, Gerard; Wang, Yue; Tian, Lin; Yu, Guoqiang

2017-01-01

Recent discoveries that astrocytes exert proactive regulatory effects on neural information processing and that they are deeply involved in normal brain development and disease pathology have stimulated broad interest in understanding astrocyte functional roles in brain circuit. Measuring astrocyte functional status is now technically feasible, due to recent advances in modern microscopy and ultrasensitive cell-type specific genetically encoded Ca2+ indicators for chronic imaging. However, there is a big gap between the capability of generating large dataset via calcium imaging and the availability of sophisticated analytical tools for decoding the astrocyte function. Current practice is essentially manual, which not only limits analysis throughput but also risks introducing bias and missing important information latent in complex, dynamic big data. Here, we report a suite of computational tools, called Functional AStrocyte Phenotyping (FASP), for automatically quantifying the functional status of astrocytes. Considering the complex nature of Ca2+ signaling in astrocytes and low signal to noise ratio, FASP is designed with data-driven and probabilistic principles, to flexibly account for various patterns and to perform robustly with noisy data. In particular, FASP explicitly models signal propagation, which rules out the applicability of tools designed for other types of data. We demonstrate the effectiveness of FASP using extensive synthetic and real data sets. The findings by FASP were verified by manual inspection. FASP also detected signals that were missed by purely manual analysis but could be confirmed by more careful manual examination under the guidance of automatic analysis. All algorithms and the analysis pipeline are packaged into a plugin for Fiji (ImageJ), with the source code freely available online at https://github.com/VTcbil/FASP. PMID:28769780

Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data.

PubMed

Wang, Yinxue; Shi, Guilai; Miller, David J; Wang, Yizhi; Wang, Congchao; Broussard, Gerard; Wang, Yue; Tian, Lin; Yu, Guoqiang

2017-01-01

Recent discoveries that astrocytes exert proactive regulatory effects on neural information processing and that they are deeply involved in normal brain development and disease pathology have stimulated broad interest in understanding astrocyte functional roles in brain circuit. Measuring astrocyte functional status is now technically feasible, due to recent advances in modern microscopy and ultrasensitive cell-type specific genetically encoded Ca 2+ indicators for chronic imaging. However, there is a big gap between the capability of generating large dataset via calcium imaging and the availability of sophisticated analytical tools for decoding the astrocyte function. Current practice is essentially manual, which not only limits analysis throughput but also risks introducing bias and missing important information latent in complex, dynamic big data. Here, we report a suite of computational tools, called Functional AStrocyte Phenotyping (FASP), for automatically quantifying the functional status of astrocytes. Considering the complex nature of Ca 2+ signaling in astrocytes and low signal to noise ratio, FASP is designed with data-driven and probabilistic principles, to flexibly account for various patterns and to perform robustly with noisy data. In particular, FASP explicitly models signal propagation, which rules out the applicability of tools designed for other types of data. We demonstrate the effectiveness of FASP using extensive synthetic and real data sets. The findings by FASP were verified by manual inspection. FASP also detected signals that were missed by purely manual analysis but could be confirmed by more careful manual examination under the guidance of automatic analysis. All algorithms and the analysis pipeline are packaged into a plugin for Fiji (ImageJ), with the source code freely available online at https://github.com/VTcbil/FASP.

A Factor Analysis of Functional Independence and Functional Assessment Measure Scores Among Focal and Diffuse Brain Injury Patients: The Importance of Bifactor Models.

PubMed

Gunn, Sarah; Burgess, Gerald H; Maltby, John

2018-04-30

To explore the factor structure of the UK Functional Independence Measure and Functional Assessment Measure (FIM+FAM) among focal and diffuse acquired brain injury patients. Criterion standard. A National Health Service acute acquired brain injury inpatient rehabilitation hospital. Referred sample of N=447 adults admitted for inpatient treatment following an acquired brain injury significant enough to justify intensive inpatient neurorehabilitation INTERVENTION: Not applicable. Functional Independence Measure and Functional Assessment Measure. Exploratory factor analysis suggested a 2-factor structure to FIM+FAM scores, among both focal-proximate and diffuse-proximate acquired brain injury aetiologies. Confirmatory factor analysis suggested a 3-factor bifactor structure presented the best fit of the FIM+FAM score data across both aetiologies. However, across both analyses, a convergence was found towards a general factor, demonstrated by high correlations between factors in the exploratory factor analysis, and by a general factor explaining the majority of the variance in scores on confirmatory factor analysis. Our findings suggested that although factors describing specific functional domains can be derived from FIM+FAM item scores, there is a convergence towards a single factor describing overall functioning. This single factor informs the specific group factors (eg, motor, psychosocial, and communication function) after brain injury. Further research into the comparative value of the general and group factors as evaluative/prognostic measures is indicated. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

A Cognitive Engineering Analysis of the Vertical Navigation (VNAV) Function

NASA Technical Reports Server (NTRS)

Sherry, Lance; Feary, Michael; Polson, Peter; Mumaw, Randall; Palmer, Everett

2001-01-01

A cognitive engineering analysis of the Flight Management System (FMS) Vertical Navigation (VNAV) function has identified overloading of the VNAV button and overloading of the Flight Mode Annunciator (FMA) used by the VNAV function. These two types of overloading, resulting in modal input devices and ambiguous feedback, are well known sources of operator confusion, and explain, in part, the operational issues experienced by airline pilots using VNAV in descent and approach. A proposal to modify the existing VNAV design to eliminate the overloading is discussed. The proposed design improves pilot's situational awareness of the VNAV function, and potentially reduces the cost of software development and improves safety.

Effects of Language of Implementation on Functional Analysis Outcomes

ERIC Educational Resources Information Center

Rispoli, Mandy; O'Reilly, Mark; Lang, Russell; Sigafoos, Jeff; Mulloy, Austin; Aguilar, Jeannie; Singer, George

2011-01-01

This study evaluated the influence of language of implementation on functional analysis outcomes for a child with a severe intellectual disability from a Spanish-speaking home. Challenging behavior was assessed during 5-min sessions under 4 conditions; attention, play-verbal, play-nonverbal, and demand and across 2 phases; implementation in…

Nationwide analysis of adrenocortical carcinoma reveals higher perioperative morbidity in functional tumors.

PubMed

Parikh, Punam P; Rubio, Gustavo A; Farra, Josefina C; Lew, John I

2017-08-25

Current adrenalectomy outcomes for functional adrenocortical carcinoma (ACC) remain unclear. This study examines nationwide in-hospital post-adrenalectomy outcomes for ACC. A retrospective analysis of the Nationwide Inpatient Sample database (2006-2011) to identify unilateral adrenalectomy patients for functional or nonfunctional ACC was performed. Patient demographics, comorbidities and postoperative outcomes were evaluated by t-test, Chi-square and multivariate regression. Of 2199 patients who underwent adrenalectomy, 87% had nonfunctional and 13% had functional ACC (86% hypercortisolism, 16% hyperaldosteronism, 4% hyperandrogenism). Functional ACC patients had significantly more comorbidities, and experienced certain postoperative complications more frequently including wound issues, adrenocortical insufficiency and acute kidney injury with longer hospital stay compared to nonfunctional ACC (P < 0.01). On multivariate analysis, functional ACC was an independent prognosticator for wound complications (28.1, 95%CI 4.59-176.6). Patients with functional ACC manifest significant comorbidities with certain in-hospital complications. Such high-risk patients require appropriate preoperative medical optimization prior to adrenalectomy. Patients with functional adrenocortical carcinoma (ACC) have significant preoperative comorbidities and experience higher rates of certain postoperative complications including wound complications, hematoma formation, adrenal insufficiency, pulmonary embolism and acute kidney injury. Functional ACC patients also necessitate longer hospitalizations. These patients should undergo appropriate preoperative counseling in preparation for adrenalectomy. Copyright © 2017 Elsevier Inc. All rights reserved.

A Comparison of Experimental Functional Analysis and the Questions about Behavioral Function (QABF) in the Assessment of Challenging Behavior of Individuals with Autism

ERIC Educational Resources Information Center

Healy, Olive; Brett, Denise; Leader, Geraldine

2013-01-01

We compared two functional behavioral assessment methods: the Questions About Behavioral Function (QABF; a standardized test) and experimental functional analysis (EFA) to identify behavioral functions of aggressive/destructive behavior, self-injurious behavior and stereotypy in 32 people diagnosed with autism. Both assessments found that self…

Data preparation for functional data analysis of PM10 in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Shaadan, Norshahida; Jemain, Abdul Aziz; Deni, Sayang Mohd

2014-07-01

The use of curves or functional data in the study analysis is increasingly gaining momentum in the various fields of research. The statistical method to analyze such data is known as functional data analysis (FDA). The first step in FDA is to convert the observed data points which are repeatedly recorded over a period of time or space into either a rough (raw) or smooth curve. In the case of the smooth curve, basis functions expansion is one of the methods used for the data conversion. The data can be converted into a smooth curve either by using the regression smoothing or roughness penalty smoothing approach. By using the regression smoothing approach, the degree of curve's smoothness is very dependent on k number of basis functions; meanwhile for the roughness penalty approach, the smoothness is dependent on a roughness coefficient given by parameter λ Based on previous studies, researchers often used the rather time-consuming trial and error or cross validation method to estimate the appropriate number of basis functions. Thus, this paper proposes a statistical procedure to construct functional data or curves for the hourly and daily recorded data. The Bayesian Information Criteria is used to determine the number of basis functions while the Generalized Cross Validation criteria is used to identify the parameter λ The proposed procedure is then applied on a ten year (2001-2010) period of PM10 data from 30 air quality monitoring stations that are located in Peninsular Malaysia. It was found that the number of basis functions required for the construction of the PM10 daily curve in Peninsular Malaysia was in the interval of between 14 and 20 with an average value of 17; the first percentile is 15 and the third percentile is 19. Meanwhile the initial value of the roughness coefficient was in the interval of between 10-5 and 10-7 and the mode was 10-6. An example of the functional descriptive analysis is also shown.

Functional Analysis of the Aspergillus nidulans Kinome

PubMed Central

De Souza, Colin P.; Hashmi, Shahr B.; Osmani, Aysha H.; Andrews, Peter; Ringelberg, Carol S.; Dunlap, Jay C.; Osmani, Stephen A.

2013-01-01

The filamentous fungi are an ecologically important group of organisms which also have important industrial applications but devastating effects as pathogens and agents of food spoilage. Protein kinases have been implicated in the regulation of virtually all biological processes but how they regulate filamentous fungal specific processes is not understood. The filamentous fungus Aspergillus nidulans has long been utilized as a powerful molecular genetic system and recent technical advances have made systematic approaches to study large gene sets possible. To enhance A. nidulans functional genomics we have created gene deletion constructs for 9851 genes representing 93.3% of the encoding genome. To illustrate the utility of these constructs, and advance the understanding of fungal kinases, we have systematically generated deletion strains for 128 A. nidulans kinases including expanded groups of 15 histidine kinases, 7 SRPK (serine-arginine protein kinases) kinases and an interesting group of 11 filamentous fungal specific kinases. We defined the terminal phenotype of 23 of the 25 essential kinases by heterokaryon rescue and identified phenotypes for 43 of the 103 non-essential kinases. Uncovered phenotypes ranged from almost no growth for a small number of essential kinases implicated in processes such as ribosomal biosynthesis, to conditional defects in response to cellular stresses. The data provide experimental evidence that previously uncharacterized kinases function in the septation initiation network, the cell wall integrity and the morphogenesis Orb6 kinase signaling pathways, as well as in pathways regulating vesicular trafficking, sexual development and secondary metabolism. Finally, we identify ChkC as a third effector kinase functioning in the cellular response to genotoxic stress. The identification of many previously unknown functions for kinases through the functional analysis of the A. nidulans kinome illustrates the utility of the A. nidulans gene

What is the Valence of Mn in Ga(1-x)Mn(x)N?

PubMed

Nelson, Ryky; Berlijn, Tom; Moreno, Juana; Jarrell, Mark; Ku, Wei

2015-11-06

We investigate the current debate on the Mn valence in Ga(1-x)Mn(x)N, a diluted magnetic semiconductor (DMS) with a potentially high Curie temperature. From a first-principles Wannier-function analysis, we unambiguously find the Mn valence to be close to 2+ (d(5)), but in a mixed spin configuration with average magnetic moments of 4μ(B). By integrating out high-energy degrees of freedom differently, we further derive for the first time from first-principles two low-energy pictures that reflect the intrinsic dual nature of the doped holes in the DMS: (1) an effective d(4) picture ideal for local physics, and (2) an effective d(5) picture suitable for extended properties. In the latter, our results further reveal a few novel physical effects, and pave the way for future realistic studies of magnetism. Our study not only resolves one of the outstanding key controversies of the field, but also exemplifies the general need for multiple effective descriptions to account for the rich low-energy physics in many-body systems in general.

Assessing prescription drug abuse using functional principal component analysis (FPCA) of wastewater data.

PubMed

Salvatore, Stefania; Røislien, Jo; Baz-Lomba, Jose A; Bramness, Jørgen G

2017-03-01

Wastewater-based epidemiology is an alternative method for estimating the collective drug use in a community. We applied functional data analysis, a statistical framework developed for analysing curve data, to investigate weekly temporal patterns in wastewater measurements of three prescription drugs with known abuse potential: methadone, oxazepam and methylphenidate, comparing them to positive and negative control drugs. Sewage samples were collected in February 2014 from a wastewater treatment plant in Oslo, Norway. The weekly pattern of each drug was extracted by fitting of generalized additive models, using trigonometric functions to model the cyclic behaviour. From the weekly component, the main temporal features were then extracted using functional principal component analysis. Results are presented through the functional principal components (FPCs) and corresponding FPC scores. Clinically, the most important weekly feature of the wastewater-based epidemiology data was the second FPC, representing the difference between average midweek level and a peak during the weekend, representing possible recreational use of a drug in the weekend. Estimated scores on this FPC indicated recreational use of methylphenidate, with a high weekend peak, but not for methadone and oxazepam. The functional principal component analysis uncovered clinically important temporal features of the weekly patterns of the use of prescription drugs detected from wastewater analysis. This may be used as a post-marketing surveillance method to monitor prescription drugs with abuse potential. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function.

PubMed

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D

2008-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings.

Electrochemical reactions in fluoride-ion batteries: mechanistic insights from pair distribution function analysis

DOE PAGES

Grenier, Antonin; Porras-Gutierrez, Ana-Gabriela; Groult, Henri; ...

2017-07-05

Detailed analysis of electrochemical reactions occurring in rechargeable Fluoride-Ion Batteries (FIBs) is provided by means of synchrotron X-ray diffraction (XRD) and Pair Distribution Function (PDF) analysis.

An exploratory data analysis of electroencephalograms using the functional boxplots approach

PubMed Central

Ngo, Duy; Sun, Ying; Genton, Marc G.; Wu, Jennifer; Srinivasan, Ramesh; Cramer, Steven C.; Ombao, Hernando

2015-01-01

Many model-based methods have been developed over the last several decades for analysis of electroencephalograms (EEGs) in order to understand electrical neural data. In this work, we propose to use the functional boxplot (FBP) to analyze log periodograms of EEG time series data in the spectral domain. The functional bloxplot approach produces a median curve—which is not equivalent to connecting medians obtained from frequency-specific boxplots. In addition, this approach identifies a functional median, summarizes variability, and detects potential outliers. By extending FBPs analysis from one-dimensional curves to surfaces, surface boxplots are also used to explore the variation of the spectral power for the alpha (8–12 Hz) and beta (16–32 Hz) frequency bands across the brain cortical surface. By using rank-based nonparametric tests, we also investigate the stationarity of EEG traces across an exam acquired during resting-state by comparing the spectrum during the early vs. late phases of a single resting-state EEG exam. PMID:26347598

Proteomic Analysis of the Arabidopsis Nucleolus Suggests Novel Nucleolar FunctionsD⃞

PubMed Central

Pendle, Alison F.; Clark, Gillian P.; Boon, Reinier; Lewandowska, Dominika; Lam, Yun Wah; Andersen, Jens; Mann, Matthias; Lamond, Angus I.; Brown, John W. S.; Shaw, Peter J.

2005-01-01

The eukaryotic nucleolus is involved in ribosome biogenesis and a wide range of other RNA metabolism and cellular functions. An important step in the functional analysis of the nucleolus is to determine the complement of proteins of this nuclear compartment. Here, we describe the first proteomic analysis of plant (Arabidopsis thaliana) nucleoli, in which we have identified 217 proteins. This allows a direct comparison of the proteomes of an important nuclear structure between two widely divergent species: human and Arabidopsis. The comparison identified many common proteins, plant-specific proteins, proteins of unknown function found in both proteomes, and proteins that were nucleolar in plants but nonnucleolar in human. Seventy-two proteins were expressed as GFP fusions and 87% showed nucleolar or nucleolar-associated localization. In a striking and unexpected finding, we have identified six components of the postsplicing exon-junction complex (EJC) involved in mRNA export and nonsense-mediated decay (NMD)/mRNA surveillance. This association was confirmed by GFP-fusion protein localization. These results raise the possibility that in plants, nucleoli may have additional functions in mRNA export or surveillance. PMID:15496452

Uncertainty analysis of signal deconvolution using a measured instrument response function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartouni, E. P.; Beeman, B.; Caggiano, J. A.

2016-10-05

A common analysis procedure minimizes the ln-likelihood that a set of experimental observables matches a parameterized model of the observation. The model includes a description of the underlying physical process as well as the instrument response function (IRF). Here, we investigate the National Ignition Facility (NIF) neutron time-of-flight (nTOF) spectrometers, the IRF is constructed from measurements and models. IRF measurements have a finite precision that can make significant contributions to the uncertainty estimate of the physical model’s parameters. Finally, we apply a Bayesian analysis to properly account for IRF uncertainties in calculating the ln-likelihood function used to find the optimummore » physical parameters.« less

Whole-genome sequence-based analysis of thyroid function.

PubMed

Taylor, Peter N; Porcu, Eleonora; Chew, Shelby; Campbell, Purdey J; Traglia, Michela; Brown, Suzanne J; Mullin, Benjamin H; Shihab, Hashem A; Min, Josine; Walter, Klaudia; Memari, Yasin; Huang, Jie; Barnes, Michael R; Beilby, John P; Charoen, Pimphen; Danecek, Petr; Dudbridge, Frank; Forgetta, Vincenzo; Greenwood, Celia; Grundberg, Elin; Johnson, Andrew D; Hui, Jennie; Lim, Ee M; McCarthy, Shane; Muddyman, Dawn; Panicker, Vijay; Perry, John R B; Bell, Jordana T; Yuan, Wei; Relton, Caroline; Gaunt, Tom; Schlessinger, David; Abecasis, Goncalo; Cucca, Francesco; Surdulescu, Gabriela L; Woltersdorf, Wolfram; Zeggini, Eleftheria; Zheng, Hou-Feng; Toniolo, Daniela; Dayan, Colin M; Naitza, Silvia; Walsh, John P; Spector, Tim; Davey Smith, George; Durbin, Richard; Richards, J Brent; Sanna, Serena; Soranzo, Nicole; Timpson, Nicholas J; Wilson, Scott G

2015-03-06

Normal thyroid function is essential for health, but its genetic architecture remains poorly understood. Here, for the heritable thyroid traits thyrotropin (TSH) and free thyroxine (FT4), we analyse whole-genome sequence data from the UK10K project (N=2,287). Using additional whole-genome sequence and deeply imputed data sets, we report meta-analysis results for common variants (MAF≥1%) associated with TSH and FT4 (N=16,335). For TSH, we identify a novel variant in SYN2 (MAF=23.5%, P=6.15 × 10(-9)) and a new independent variant in PDE8B (MAF=10.4%, P=5.94 × 10(-14)). For FT4, we report a low-frequency variant near B4GALT6/SLC25A52 (MAF=3.2%, P=1.27 × 10(-9)) tagging a rare TTR variant (MAF=0.4%, P=2.14 × 10(-11)). All common variants explain ≥20% of the variance in TSH and FT4. Analysis of rare variants (MAF<1%) using sequence kernel association testing reveals a novel association with FT4 in NRG1. Our results demonstrate that increased coverage in whole-genome sequence association studies identifies novel variants associated with thyroid function.

Hazard function analysis for flood planning under nonstationarity

NASA Astrophysics Data System (ADS)

Read, Laura K.; Vogel, Richard M.

2016-05-01

The field of hazard function analysis (HFA) involves a probabilistic assessment of the "time to failure" or "return period," T, of an event of interest. HFA is used in epidemiology, manufacturing, medicine, actuarial statistics, reliability engineering, economics, and elsewhere. For a stationary process, the probability distribution function (pdf) of the return period always follows an exponential distribution, the same is not true for nonstationary processes. When the process of interest, X, exhibits nonstationary behavior, HFA can provide a complementary approach to risk analysis with analytical tools particularly useful for hydrological applications. After a general introduction to HFA, we describe a new mathematical linkage between the magnitude of the flood event, X, and its return period, T, for nonstationary processes. We derive the probabilistic properties of T for a nonstationary one-parameter exponential model of X, and then use both Monte-Carlo simulation and HFA to generalize the behavior of T when X arises from a nonstationary two-parameter lognormal distribution. For this case, our findings suggest that a two-parameter Weibull distribution provides a reasonable approximation for the pdf of T. We document how HFA can provide an alternative approach to characterize the probabilistic properties of both nonstationary flood series and the resulting pdf of T.

An effective 2-band eg model of sulfur hydride H3S for high-Tc superconductivity

NASA Astrophysics Data System (ADS)

Nishiguchi, Kazutaka; Teranishi, Shingo; Miyao, Satoaki; Matsushita, Goh; Kusakabe, Koichi

To understand high transition temperature (Tc) superconductivity in sulfur hydride H3S, we propose an effective 2-band model having the eg symmetry as the minimal model for H3S. Two eg orbitals centered on a sulfur S atom are chosen for the smallest representation of relevant bands with the van-Hove singularity around the Fermi levels except for the Γ-centered small hole pockets by the sulfur 3 p orbitals. By using the maximally localized Wannier functions, we derive the minimal effective model preserving the body-centered cubic (bcc) crystal symmetry of the H3S phase having the highest Tc ( 203 K under pressures) among the other polymorphs of H3S.

Functional analysis and treatment of elopement for a child with attention deficit hyperactivity disorder.

PubMed

Kodak, Tiffany; Grow, Laura; Northup, John

2004-01-01

We conducted a functional analysis of elopement in an outdoor setting for a child with a diagnosis of attention deficit hyperactivity disorder. A subsequent treatment consisting of noncontingent attention and time-out was demonstrated to be effective in eliminating elopement. Modifications of functional analysis procedures associated with the occurrence of elopement in a natural setting are demonstrated.

Functional analysis and treatment of elopement for a child with attention deficit hyperactivity disorder.

PubMed Central

Kodak, Tiffany; Grow, Laura; Northup, John

2004-01-01

We conducted a functional analysis of elopement in an outdoor setting for a child with a diagnosis of attention deficit hyperactivity disorder. A subsequent treatment consisting of noncontingent attention and time-out was demonstrated to be effective in eliminating elopement. Modifications of functional analysis procedures associated with the occurrence of elopement in a natural setting are demonstrated. PMID:15293643

Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

PubMed

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction

Comparison of Penalty Functions for Sparse Canonical Correlation Analysis

PubMed Central

Chalise, Prabhakar; Fridley, Brooke L.

2011-01-01

Canonical correlation analysis (CCA) is a widely used multivariate method for assessing the association between two sets of variables. However, when the number of variables far exceeds the number of subjects, such in the case of large-scale genomic studies, the traditional CCA method is not appropriate. In addition, when the variables are highly correlated the sample covariance matrices become unstable or undefined. To overcome these two issues, sparse canonical correlation analysis (SCCA) for multiple data sets has been proposed using a Lasso type of penalty. However, these methods do not have direct control over sparsity of solution. An additional step that uses Bayesian Information Criterion (BIC) has also been suggested to further filter out unimportant features. In this paper, a comparison of four penalty functions (Lasso, Elastic-net, SCAD and Hard-threshold) for SCCA with and without the BIC filtering step have been carried out using both real and simulated genotypic and mRNA expression data. This study indicates that the SCAD penalty with BIC filter would be a preferable penalty function for application of SCCA to genomic data. PMID:21984855

Rice proteome analysis: a step toward functional analysis of the rice genome.

PubMed

Komatsu, Setsuko; Tanaka, Naoki

2005-03-01

The technique of proteome analysis using 2-DE has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this review, we describe construction of the rice proteome database, the cataloging of rice proteins, and the functional characterization of some of the proteins identified. Initially, proteins extracted from various tissues and organelles were separated by 2-DE and an image analyzer was used to construct a display or reference map of the proteins. The rice proteome database currently contains 23 reference maps based on 2-DE of proteins from different rice tissues and subcellular compartments. These reference maps comprise 13 129 rice proteins, and the amino acid sequences of 5092 of these proteins are entered in the database. Major proteins involved in growth or stress responses have been identified by using a proteomics approach and some of these proteins have unique functions. Furthermore, initial work has also begun on analyzing the phosphoproteome and protein-protein interactions in rice. The information obtained from the rice proteome database will aid in the molecular cloning of rice genes and in predicting the function of unknown proteins.

Confirmatory factor analysis of the female sexual function index.

PubMed

Opperman, Emily A; Benson, Lindsay E; Milhausen, Robin R

2013-01-01

The Female Sexual Functioning Index (Rosen et al., 2000 ) was designed to assess the key dimensions of female sexual functioning using six domains: desire, arousal, lubrication, orgasm, satisfaction, and pain. A full-scale score was proposed to represent women's overall sexual function. The fifth revision to the Diagnostic and Statistical Manual (DSM) is currently underway and includes a proposal to combine desire and arousal problems. The objective of this article was to evaluate and compare four models of the Female Sexual Functioning Index: (a) single-factor model, (b) six-factor model, (c) second-order factor model, and (4) five-factor model combining the desire and arousal subscales. Cross-sectional and observational data from 85 women were used to conduct a confirmatory factor analysis on the Female Sexual Functioning Index. Local and global goodness-of-fit measures, the chi-square test of differences, squared multiple correlations, and regression weights were used. The single-factor model fit was not acceptable. The original six-factor model was confirmed, and good model fit was found for the second-order and five-factor models. Delta chi-square tests of differences supported best fit for the six-factor model validating usage of the six domains. However, when revisions are made to the DSM-5, the Female Sexual Functioning Index can adapt to reflect these changes and remain a valid assessment tool for women's sexual functioning, as the five-factor structure was also supported.

Local structure studies of materials using pair distribution function analysis

NASA Astrophysics Data System (ADS)

Peterson, Joseph W.

A collection of pair distribution function studies on various materials is presented in this dissertation. In each case, local structure information of interest pushes the current limits of what these studies can accomplish. The goal is to provide insight into the individual material behaviors as well as to investigate ways to expand the current limits of PDF analysis. Where possible, I provide a framework for how PDF analysis might be applied to a wider set of material phenomena. Throughout the dissertation, I discuss 0 the capabilities of the PDF method to provide information pertaining to a material's structure and properties, ii) current limitations in the conventional approach to PDF analysis, iii) possible solutions to overcome certain limitations in PDF analysis, and iv) suggestions for future work to expand and improve the capabilities PDF analysis.

Functional Group Analysis for Diesel-like Mixing-Controlled Compression Ignition Combustion Blendstocks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaspar, Daniel J.; McCormick, Robert L.; Polikarpov, Evgueni

This report addresses the suitability of hydrocarbon and oxygenate functional groups for use as a diesel-like fuel blending component in an advanced, mixing-controlled, compression ignition combustion engine. The functional groups are chosen from those that could be derived from a biomass feedstock, and represent a full range of chemistries. This first systematic analysis of functional groups will be of value to all who are pursuing new bio-blendstocks for diesel-like fuels.

Accurate modeling of defects in graphene transport calculations

NASA Astrophysics Data System (ADS)

Linhart, Lukas; Burgdörfer, Joachim; Libisch, Florian

2018-01-01

We present an approach for embedding defect structures modeled by density functional theory into large-scale tight-binding simulations. We extract local tight-binding parameters for the vicinity of the defect site using Wannier functions. In the transition region between the bulk lattice and the defect the tight-binding parameters are continuously adjusted to approach the bulk limit far away from the defect. This embedding approach allows for an accurate high-level treatment of the defect orbitals using as many as ten nearest neighbors while keeping a small number of nearest neighbors in the bulk to render the overall computational cost reasonable. As an example of our approach, we consider an extended graphene lattice decorated with Stone-Wales defects, flower defects, double vacancies, or silicon substitutes. We predict distinct scattering patterns mirroring the defect symmetries and magnitude that should be experimentally accessible.

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function

PubMed Central

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D.

2009-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings. PMID:19834575

Electrically tunable organic–inorganic hybrid polaritons with monolayer WS2

PubMed Central

Flatten, Lucas C.; Coles, David M.; He, Zhengyu; Lidzey, David G.; Taylor, Robert A.; Warner, Jamie H.; Smith, Jason M.

2017-01-01

Exciton-polaritons are quasiparticles consisting of a linear superposition of photonic and excitonic states, offering potential for nonlinear optical devices. The excitonic component of the polariton provides a finite Coulomb scattering cross section, such that the different types of exciton found in organic materials (Frenkel) and inorganic materials (Wannier-Mott) produce polaritons with different interparticle interaction strength. A hybrid polariton state with distinct excitons provides a potential technological route towards in situ control of nonlinear behaviour. Here we demonstrate a device in which hybrid polaritons are displayed at ambient temperatures, the excitonic component of which is part Frenkel and part Wannier-Mott, and in which the dominant exciton type can be switched with an applied voltage. The device consists of an open microcavity containing both organic dye and a monolayer of the transition metal dichalcogenide WS2. Our findings offer a perspective for electrically controlled nonlinear polariton devices at room temperature. PMID:28094281

An Example of an Elementary School Paraprofessional-Implemented Functional Analysis and Intervention

ERIC Educational Resources Information Center

Bessette, Kimberly K.; Wills, Howard P.

2007-01-01

The Individuals With Disabilities Education Act mandates the performance of functional assessment for students with severe behavior problems. A functional analysis can be one part of this process but its use has been minimal. This study evaluates whether a paraprofessional could (a) be trained to correctly perform 3 conditions of a functional…

Linearised and non-linearised isotherm models optimization analysis by error functions and statistical means

PubMed Central

2014-01-01

In adsorption study, to describe sorption process and evaluation of best-fitting isotherm model is a key analysis to investigate the theoretical hypothesis. Hence, numerous statistically analysis have been extensively used to estimate validity of the experimental equilibrium adsorption values with the predicted equilibrium values. Several statistical error analysis were carried out. In the present study, the following statistical analysis were carried out to evaluate the adsorption isotherm model fitness, like the Pearson correlation, the coefficient of determination and the Chi-square test, have been used. The ANOVA test was carried out for evaluating significance of various error functions and also coefficient of dispersion were evaluated for linearised and non-linearised models. The adsorption of phenol onto natural soil (Local name Kalathur soil) was carried out, in batch mode at 30 ± 20 C. For estimating the isotherm parameters, to get a holistic view of the analysis the models were compared between linear and non-linear isotherm models. The result reveled that, among above mentioned error functions and statistical functions were designed to determine the best fitting isotherm. PMID:25018878

Genome-wide identification, functional and evolutionary analysis of terpene synthases in pineapple.

PubMed

Chen, Xiaoe; Yang, Wei; Zhang, Liqin; Wu, Xianmiao; Cheng, Tian; Li, Guanglin

2017-10-01

Terpene synthases (TPSs) are vital for the biosynthesis of active terpenoids, which have important physiological, ecological and medicinal value. Although terpenoids have been reported in pineapple (Ananas comosus), genome-wide investigations of the TPS genes responsible for pineapple terpenoid synthesis are still lacking. By integrating pineapple genome and proteome data, twenty-one putative terpene synthase genes were found in pineapple and divided into five subfamilies. Tandem duplication is the cause of TPS gene family duplication. Furthermore, functional differentiation between each TPS subfamily may have occurred for several reasons. Sixty-two key amino acid sites were identified as being type-II functionally divergence between TPS-a and TPS-c subfamily. Finally, coevolution analysis indicated that multiple amino acid residues are involved in coevolutionary processes. In addition, the enzyme activity of two TPSs were tested. This genome-wide identification, functional and evolutionary analysis of pineapple TPS genes provide a new insight into understanding the roles of TPS family and lay the basis for further characterizing the function and evolution of TPS gene family. Copyright © 2017 Elsevier Ltd. All rights reserved.

The neuronal correlates of intranasal trigeminal function – An ALE meta-analysis of human functional brain imaging data

PubMed Central

Albrecht, Jessica; Kopietz, Rainer; Frasnelli, Johannes; Wiesmann, Martin; Hummel, Thomas; Lundström, Johan N.

2009-01-01

Almost every odor we encounter in daily life has the capacity to produce a trigeminal sensation. Surprisingly, few functional imaging studies exploring human neuronal correlates of intranasal trigeminal function exist, and results are to some degree inconsistent. We utilized activation likelihood estimation (ALE), a quantitative voxel-based meta-analysis tool, to analyze functional imaging data (fMRI/PET) following intranasal trigeminal stimulation with carbon dioxide (CO2), a stimulus known to exclusively activate the trigeminal system. Meta-analysis tools are able to identify activations common across studies, thereby enabling activation mapping with higher certainty. Activation foci of nine studies utilizing trigeminal stimulation were included in the meta-analysis. We found significant ALE scores, thus indicating consistent activation across studies, in the brainstem, ventrolateral posterior thalamic nucleus, anterior cingulate cortex, insula, precentral gyrus, as well as in primary and secondary somatosensory cortices – a network known for the processing of intranasal nociceptive stimuli. Significant ALE values were also observed in the piriform cortex, insula, and the orbitofrontal cortex, areas known to process chemosensory stimuli, and in association cortices. Additionally, the trigeminal ALE statistics were directly compared with ALE statistics originating from olfactory stimulation, demonstrating considerable overlap in activation. In conclusion, the results of this meta-analysis map the human neuronal correlates of intranasal trigeminal stimulation with high statistical certainty and demonstrate that the cortical areas recruited during the processing of intranasal CO2 stimuli include those outside traditional trigeminal areas. Moreover, through illustrations of the considerable overlap between brain areas that process trigeminal and olfactory information; these results demonstrate the interconnectivity of flavor processing. PMID:19913573

Progressing from Identification and Functional Analysis of Precursor Behavior to Treatment of Self-Injurious Behavior

ERIC Educational Resources Information Center

Dracobly, Joseph D.; Smith, Richard G.

2012-01-01

This multiple-study experiment evaluated the utility of assessing and treating severe self-injurious behavior (SIB) based on the outcomes of a functional analysis of precursor behavior. In Study 1, a precursor to SIB was identified using descriptive assessment and conditional probability analyses. In Study 2, a functional analysis of precursor…

Analyzing Distributed Functions in an Integrated Hazard Analysis

NASA Technical Reports Server (NTRS)

Morris, A. Terry; Massie, Michael J.

2010-01-01

Large scale integration of today's aerospace systems is achievable through the use of distributed systems. Validating the safety of distributed systems is significantly more difficult as compared to centralized systems because of the complexity of the interactions between simultaneously active components. Integrated hazard analysis (IHA), a process used to identify unacceptable risks and to provide a means of controlling them, can be applied to either centralized or distributed systems. IHA, though, must be tailored to fit the particular system being analyzed. Distributed systems, for instance, must be analyzed for hazards in terms of the functions that rely on them. This paper will describe systems-oriented IHA techniques (as opposed to traditional failure-event or reliability techniques) that should be employed for distributed systems in aerospace environments. Special considerations will be addressed when dealing with specific distributed systems such as active thermal control, electrical power, command and data handling, and software systems (including the interaction with fault management systems). Because of the significance of second-order effects in large scale distributed systems, the paper will also describe how to analyze secondary functions to secondary functions through the use of channelization.

Coupled-cluster Green's function: Analysis of properties originating in the exponential parametrization of the ground-state wave function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peng, Bo; Kowalski, Karol

In this paper we derive basic properties of the Green’s function matrix elements stemming from the exponential coupled cluster (CC) parametrization of the ground-state wave function. We demon- strate that all intermediates used to express retarded (or equivalently, ionized) part of the Green’s function in the ω-representation can be expressed through connected diagrams only. Similar proper- ties are also shared by the first order ω-derivatives of the retarded part of the CC Green’s function. This property can be extended to any order ω-derivatives of the Green’s function. Through the Dyson equation of CC Green’s function, the derivatives of corresponding CCmore » self-energy can be evaluated analytically. In analogy to the CC Green’s function, the corresponding CC self-energy is expressed in terms of connected diagrams only. Moreover, the ionized part of the CC Green’s func- tion satisfies the non-homogeneous linear system of ordinary differential equations, whose solution may be represented in the exponential form. Our analysis can be easily generalized to the advanced part of the CC Green’s function.« less

Functional analysis and treatment of problem behavior in early education classrooms.

PubMed

Greer, Brian D; Neidert, Pamela L; Dozier, Claudia L; Payne, Steven W; Zonneveld, Kimberley L M; Harper, Amy M

2013-01-01

We conducted functional analyses (FA) with 4 typically developing preschool children during ongoing classroom activities and evaluated treatments that were based on FA results. Results of each child's FA suggested social-positive reinforcement functions, and differential reinforcement of alternative behavior plus time-out was effective in decreasing problem behavior and increasing appropriate behavior. We discuss the utility of classroom-based FAs and potential compromises to experimental control. © Society for the Experimental Analysis of Behavior.

Analysis and selection of optimal function implementations in massively parallel computer

DOEpatents

Archer, Charles Jens [Rochester, MN; Peters, Amanda [Rochester, MN; Ratterman, Joseph D [Rochester, MN

2011-05-31

An apparatus, program product and method optimize the operation of a parallel computer system by, in part, collecting performance data for a set of implementations of a function capable of being executed on the parallel computer system based upon the execution of the set of implementations under varying input parameters in a plurality of input dimensions. The collected performance data may be used to generate selection program code that is configured to call selected implementations of the function in response to a call to the function under varying input parameters. The collected performance data may be used to perform more detailed analysis to ascertain the comparative performance of the set of implementations of the function under the varying input parameters.

An Analysis of Risk and Function Information in Early Stage Design

NASA Technical Reports Server (NTRS)

Barrientos, Francesca; Tumer, Irem; Grantham, Katie; VanWie, Michael; Stone, Robert

2005-01-01

The concept of function offers a high potential for thinking and reasoning about designs as well as providing a common thread for relating together other design information. This paper focuses specifically on the relation between function and risk by examining how this information is addressed for a design team conducting early stage design for space missions. Risk information is decomposed into a set of key attributes which are then used to scrutinize the risk information using three approaches from the pragmatics sub-field of linguistics: i) Gricean, ii) Relevance Theory, and Functional Analysis. Results of this linguistics-based approach descriptively account for the context of designer communication with respect to function and risk, and offer prescriptive guidelines for improving designer communication.

Abnormal functional specialization within medial prefrontal cortex in high-functioning autism: a multi-voxel similarity analysis

PubMed Central

Meuwese, Julia D.I.; Towgood, Karren J.; Frith, Christopher D.; Burgess, Paul W.

2009-01-01

Multi-voxel pattern analyses have proved successful in ‘decoding’ mental states from fMRI data, but have not been used to examine brain differences associated with atypical populations. We investigated a group of 16 (14 males) high-functioning participants with autism spectrum disorder (ASD) and 16 non-autistic control participants (12 males) performing two tasks (spatial/verbal) previously shown to activate medial rostral prefrontal cortex (mrPFC). Each task manipulated: (i) attention towards perceptual versus self-generated information and (ii) reflection on another person's mental state (‘mentalizing'versus ‘non-mentalizing’) in a 2 × 2 design. Behavioral performance and group-level fMRI results were similar between groups. However, multi-voxel similarity analyses revealed strong differences. In control participants, the spatial distribution of activity generalized significantly between task contexts (spatial/verbal) when examining the same function (attention/mentalizing) but not when comparing different functions. This pattern was disrupted in the ASD group, indicating abnormal functional specialization within mrPFC, and demonstrating the applicability of multi-voxel pattern analysis to investigations of atypical populations. PMID:19174370

Differential Item Functioning Analysis of the Mental, Emotional, and Bodily Toughness Inventory

ERIC Educational Resources Information Center

Gao, Yong; Mack, Mick G.; Ragan, Moira A.; Ragan, Brian

2012-01-01

In this study the authors used differential item functioning analysis to examine if there were items in the Mental, Emotional, and Bodily Toughness Inventory functioning differently across gender and athletic membership. A total of 444 male (56.3%) and female (43.7%) participants (30.9% athletes and 69.1% non-athletes) responded to the Mental,…

Classroom-Based Functional Analysis and Intervention for Disruptive and Off-Task Behaviors

ERIC Educational Resources Information Center

Shumate, Emily D.; Wills, Howard P.

2010-01-01

Although there is a growing body of literature on the use of functional analysis in schools, there is a need for more demonstrations of this technology being used during the course of typical instruction. In this study, we conducted functional analyses of disruptive and off-task behavior in a reading classroom setting for 3 participants of typical…

Advances in structural and functional analysis of membrane proteins by electron crystallography

PubMed Central

Wisedchaisri, Goragot; Reichow, Steve L.; Gonen, Tamir

2011-01-01

Summary Electron crystallography is a powerful technique for the study of membrane protein structure and function in the lipid environment. When well-ordered two-dimensional crystals are obtained the structure of both protein and lipid can be determined and lipid-protein interactions analyzed. Protons and ionic charges can be visualized by electron crystallography and the protein of interest can be captured for structural analysis in a variety of physiologically distinct states. This review highlights the strengths of electron crystallography and the momentum that is building up in automation and the development of high throughput tools and methods for structural and functional analysis of membrane proteins by electron crystallography. PMID:22000511

[Effect factors analysis of knee function recovery after distal femoral fracture operation].

PubMed

Bei, Chaoyong; Wang, Ruiying; Tang, Jicun; Li, Qiang

2009-09-01

To investigate the effect factors of knee function recovery after operation in distal femoral fractures. From January 2001 to May 2007, 92 cases of distal femoral fracture were treated. There were 50 males and 42 females, aged 20-77 years old (average 46.7 years old). Fracture was caused by traffic accident in 48 cases, by falling from height in 26 cases, by bruise in 12 cases and by tumble in 6 cases. According to Müller's Fracture classification, there were 29 cases of type A, 12 cases of type B and 51 cases of type C. According to American Society of Anesthesiologists (ASA) classification, there were 21 cases of grade I, 39 cases of grade II, 24 cases of grade III, and 8 cases of grade IV. The time from injury to operation was 4 hours to 24 days with an average of 7 days. Anatomical plate was used in 43 cases, retrograde interlocking intramedullary nail in 37 cases, and bone screws, bolts and internal fixation with Kirschner pins in 12 cases. After operation, the HSS knee function score was used to evaluate efficacy. Ten related factors were applied for statistical analysis, to knee function recovery after operation in distal femoral fractures, such as age, sex, preoperative ASA classification, injury to surgery time, fracture type, treatment, reduction quality, functional exercise after operation, whether or not CPM functional training and postoperative complications. Wound healed by first intention in 88 cases, infection occurred in 4 cases. All patients followed up 16-32 months with an average of 23.1 months. Clinical union of fracture was achieved within 3-7 months after operation. Extensor device adhesions and the scope of activities of <80 degrees occurred in 29 cases, traumatic arthritis in 25 cases, postoperative fracture displacement in 6 cases, mild knee varus or valgus in 7 cases and implant loosening in 6 cases. According to HSS knee function score, the results were excellent in 52 cases, good in 15 cases, fair in 10 cases and poor in 15 cases with

A Mobile Computing Solution for Collecting Functional Analysis Data on a Pocket PC

ERIC Educational Resources Information Center

Jackson, James; Dixon, Mark R.

2007-01-01

The present paper provides a task analysis for creating a computerized data system using a Pocket PC and Microsoft Visual Basic. With Visual Basic software and any handheld device running the Windows MOBLE operating system, this task analysis will allow behavior analysts to program and customize their own functional analysis data-collection…

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, J.; Wei, T.Y.C.

1993-11-23

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures.

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, Jaques; Wei, Thomas Y. C.

1993-01-01

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system.

Association Between Blood Glucose and Functional Outcome in Intracerebral Hemorrhage: A Systematic Review and Meta-Analysis.

PubMed

Zheng, Jun; Yu, Zhiyuan; Ma, Lu; Guo, Rui; Lin, Sen; You, Chao; Li, Hao

2018-03-16

Intracerebral hemorrhage (ICH) is a devastating subtype of stroke. Patients with ICH have poor functional outcomes. The association between blood glucose level and functional outcome in ICH remains unclear. This systematic review and meta-analysis aimed to investigate the association between blood glucose level and functional outcomes in patients with ICH. Literature was searched systemically in PubMed, EMBASE, Web of Science, and Cochrane Library. Published cohort studies evaluating the association between blood glucose and functional outcome in patients with ICH were included. This meta-analysis was performed using odds ratios (ORs) and 95% confidence intervals (CIs). A total of 16 studies were included in our meta-analysis. Our data show that hyperglycemia defined by cutoff values was significantly associated with unfavorable functional outcome (OR, 1.80; 95% CI, 1.36-2.39; P < 0.001). Our analysis also suggested a significant association between increased blood glucose levels and functional outcomes (OR, 1.05; 95% CI, 1.03-1.07; P < 0.001). High blood glucose level is significantly associated with poor functional outcome in ICH. Further studies with larger sample sizes, more time points, and longer follow-up times are necessary to confirm this association. Copyright © 2018 Elsevier Inc. All rights reserved.

Grey Matter Alterations Co-Localize with Functional Abnormalities in Developmental Dyslexia: An ALE Meta-Analysis

PubMed Central

Linkersdörfer, Janosch; Lonnemann, Jan; Lindberg, Sven; Hasselhorn, Marcus; Fiebach, Christian J.

2012-01-01

The neural correlates of developmental dyslexia have been investigated intensively over the last two decades and reliable evidence for a dysfunction of left-hemispheric reading systems in dyslexic readers has been found in functional neuroimaging studies. In addition, structural imaging studies using voxel-based morphometry (VBM) demonstrated grey matter reductions in dyslexics in several brain regions. To objectively assess the consistency of these findings, we performed activation likelihood estimation (ALE) meta-analysis on nine published VBM studies reporting 62 foci of grey matter reduction in dyslexic readers. We found six significant clusters of convergence in bilateral temporo-parietal and left occipito-temporal cortical regions and in the cerebellum bilaterally. To identify possible overlaps between structural and functional deviations in dyslexic readers, we conducted additional ALE meta-analyses of imaging studies reporting functional underactivations (125 foci from 24 studies) or overactivations (95 foci from 11 studies ) in dyslexics. Subsequent conjunction analyses revealed overlaps between the results of the VBM meta-analysis and the meta-analysis of functional underactivations in the fusiform and supramarginal gyri of the left hemisphere. An overlap between VBM results and the meta-analysis of functional overactivations was found in the left cerebellum. The results of our study provide evidence for consistent grey matter variations bilaterally in the dyslexic brain and substantial overlap of these structural variations with functional abnormalities in left hemispheric regions. PMID:22916214

Charge Transport Properties of Durene Crystals from First-Principles.

PubMed

Motta, Carlo; Sanvito, Stefano

2014-10-14

We establish a rigorous computational scheme for constructing an effective Hamiltonian to be used for the determination of the charge carrier mobility of pure organic crystals at finite temperature, which accounts for van der Waals interactions, and it includes vibrational contributions from the entire phonon spectrum of the crystal. Such an approach is based on the ab initio framework provided by density functional theory and the construction of a tight-binding effective model via Wannier transformation. The final Hamiltonian includes coupling of the electrons to the crystals phonons, which are also calculated from density functional theory. We apply this methodology to the case of durene, a small π-conjugated molecule, which forms a high-mobility herringbone-stacked crystal. We show that accounting correctly for dispersive forces is fundamental for obtaining a high-quality phonon spectrum, in agreement with experiments. Then, the mobility as a function of temperature is calculated along different crystallographic directions and the phonons most responsible for the scattering are identified.

Meta-analysis of neuropsychological measures of executive functioning in children and adolescents with high-functioning autism spectrum disorder.

PubMed

Lai, Chun Lun Eric; Lau, Zoe; Lui, Simon S Y; Lok, Eugenia; Tam, Venus; Chan, Quinney; Cheng, Koi Man; Lam, Siu Man; Cheung, Eric F C

2017-05-01

Existing literature on the profile of executive dysfunction in autism spectrum disorder showed inconsistent results. Age, comorbid attention-deficit/hyperactivity disorder (ADHD) and cognitive abilities appeared to play a role in confounding the picture. Previous meta-analyses have focused on a few components of executive functions. This meta-analysis attempted to delineate the profile of deficit in several components of executive functioning in children and adolescents with high-functioning autism spectrum disorder (HFASD). Ninety-eight English published case-control studies comparing children and adolescents with HFASD with typically developing controls using well-known neuropsychological measures to assess executive functions were included. Results showed that children and adolescents with HFASD were moderately impaired in verbal working memory (g = 0.67), spatial working memory (g = 0.58), flexibility (g = 0.59), planning (g = 0.62), and generativity (g = 0.60) except for inhibition (g = 0.41). Subgroup analysis showed that impairments were still significant for flexibility (g = 0.57-0.61), generativity (g = 0.52-0.68), and working memory (g = 0.49-0.56) in a sample of autism spectrum disorder (ASD) subjects without comorbid ADHD or when the cognitive abilities of the ASD group and the control group were comparable. This meta-analysis confirmed the presence of executive dysfunction in children and adolescents with HFASD. These deficits are not solely accounted for by the effect of comorbid ADHD and the general cognitive abilities. Our results support the executive dysfunction hypothesis and contribute to the clinical understanding and possible development of interventions to alleviate these deficits in children and adolescents with HFASD. Autism Res 2017, 10: 911-939. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Man-Machine Integrated Design and Analysis System (MIDAS): Functional Overview

NASA Technical Reports Server (NTRS)

Corker, Kevin; Neukom, Christian

1998-01-01

Included in the series of screen print-outs illustrates the structure and function of the Man-Machine Integrated Design and Analysis System (MIDAS). Views into the use of the system and editors are featured. The use-case in this set of graphs includes the development of a simulation scenario.

DNA mimic proteins: functions, structures, and bioinformatic analysis.

PubMed

Wang, Hao-Ching; Ho, Chun-Han; Hsu, Kai-Cheng; Yang, Jinn-Moon; Wang, Andrew H-J

2014-05-13

DNA mimic proteins have DNA-like negative surface charge distributions, and they function by occupying the DNA binding sites of DNA binding proteins to prevent these sites from being accessed by DNA. DNA mimic proteins control the activities of a variety of DNA binding proteins and are involved in a wide range of cellular mechanisms such as chromatin assembly, DNA repair, transcription regulation, and gene recombination. However, the sequences and structures of DNA mimic proteins are diverse, making them difficult to predict by bioinformatic search. To date, only a few DNA mimic proteins have been reported. These DNA mimics were not found by searching for functional motifs in their sequences but were revealed only by structural analysis of their charge distribution. This review highlights the biological roles and structures of 16 reported DNA mimic proteins. We also discuss approaches that might be used to discover new DNA mimic proteins.

Memory-Efficient Analysis of Dense Functional Connectomes.

PubMed

Loewe, Kristian; Donohue, Sarah E; Schoenfeld, Mircea A; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to

Memory-Efficient Analysis of Dense Functional Connectomes

PubMed Central

Loewe, Kristian; Donohue, Sarah E.; Schoenfeld, Mircea A.; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to

Family Functioning and Adolescent Alcohol Use: A Moderated Mediation Analysis

PubMed Central

Ohannessian, Christine McCauley; Flannery, Kaitlin M.; Simpson, Emily; Russell, Beth S.

2016-01-01

The primary goals of this longitudinal study were to examine the relationship between family functioning and adolescent alcohol use and to examine whether depressed mood mediates this relationship. An additional goal was to explore whether these relations were moderated by gender. The sample included 1,031 high school students from the Mid-Atlantic United States. Participants completed surveys in school during the spring of 2007, 2008, and 2009. Path analysis results indicated that family functioning predicted alcohol use for girls. Moreover, depressed mood mediated this relationship. None of the direct paths between family functioning and adolescent alcohol use were significant for boys. However, similar to girls, depressed mood negatively predicted alcohol use for boys. Taken together, the findings highlight the need for prevention programs targeting adolescent substance use to consider gender-specific trajectories. PMID:26994346

Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites

PubMed Central

Cuperlovic-Culf, Miroslava; Rajagopalan, NandhaKishore; Tulpan, Dan; Loewen, Michele C.

2016-01-01

Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum, such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions. PMID:27706030

Construction and Analysis of Functional Networks in the Gut Microbiome of Type 2 Diabetes Patients.

PubMed

Li, Lianshuo; Wang, Zicheng; He, Peng; Ma, Shining; Du, Jie; Jiang, Rui

2016-10-01

Although networks of microbial species have been widely used in the analysis of 16S rRNA sequencing data of a microbiome, the construction and analysis of a complete microbial gene network are in general problematic because of the large number of microbial genes in metagenomics studies. To overcome this limitation, we propose to map microbial genes to functional units, including KEGG orthologous groups and the evolutionary genealogy of genes: Non-supervised Orthologous Groups (eggNOG) orthologous groups, to enable the construction and analysis of a microbial functional network. We devised two statistical methods to infer pairwise relationships between microbial functional units based on a deep sequencing dataset of gut microbiome from type 2 diabetes (T2D) patients as well as healthy controls. Networks containing such functional units and their significant interactions were constructed subsequently. We conducted a variety of analyses of global properties, local properties, and functional modules in the resulting functional networks. Our data indicate that besides the observations consistent with the current knowledge, this study provides novel biological insights into the gut microbiome associated with T2D. Copyright © 2016. Production and hosting by Elsevier Ltd.

Forecast Vienna Mapping Functions 1 for real-time analysis of space geodetic observations

NASA Astrophysics Data System (ADS)

Boehm, J.; Kouba, J.; Schuh, H.

2009-05-01

The Vienna Mapping Functions 1 (VMF1) as provided by the Institute of Geodesy and Geophysics (IGG) at the Vienna University of Technology are the most accurate mapping functions for the troposphere delays that are available globally and for the entire history of space geodetic observations. So far, the VMF1 coefficients have been released with a time delay of almost two days; however, many scientific applications require their availability in near real-time, e.g. the Ultra Rapid solutions of the International GNSS Service (IGS) or the analysis of the Intensive sessions of the International VLBI Service (IVS). Here we present coefficients of the VMF1 as well as the hydrostatic and wet zenith delays that have been determined from forecasting data of the European Centre for Medium-Range Weather Forecasts (ECMWF) and provided on global grids. The comparison with parameters derived from ECMWF analysis data shows that the agreement is at the 1 mm level in terms of station height, and that the differences are larger for the wet mapping functions than for the hydrostatic mapping functions and the hydrostatic zenith delays. These new products (VMF1-FC and hydrostatic zenith delays from forecast data) can be used in real-time analysis of geodetic data without significant loss of accuracy.

Functional materials analysis using in situ and in operando X-ray and neutron scattering

PubMed Central

Peterson, Vanessa K.; Papadakis, Christine M.

2015-01-01

In situ and in operando studies are commonplace and necessary in functional materials research. This review highlights recent developments in the analysis of functional materials using state-of-the-art in situ and in operando X-ray and neutron scattering and analysis. Examples are given covering a number of important materials areas, alongside a description of the types of information that can be obtained and the experimental setups used to acquire them. PMID:25866665

Assessing the Utility of a Demand Assessment for Functional Analysis

ERIC Educational Resources Information Center

Roscoe, Eileen M.; Rooker, Griffin W.; Pence, Sacha T.; Longworth, Lynlea J.

2009-01-01

We evaluated the utility of an assessment for identifying tasks for the functional analysis demand condition with 4 individuals who had been diagnosed with autism. During the demand assessment, a therapist presented a variety of tasks, and observers measured problem behavior and compliance to identify demands associated with low levels of…

Generalization of the subsonic kernel function in the s-plane, with applications to flutter analysis

NASA Technical Reports Server (NTRS)

Cunningham, H. J.; Desmarais, R. N.

1984-01-01

A generalized subsonic unsteady aerodynamic kernel function, valid for both growing and decaying oscillatory motions, is developed and applied in a modified flutter analysis computer program to solve the boundaries of constant damping ratio as well as the flutter boundary. Rates of change of damping ratios with respect to dynamic pressure near flutter are substantially lower from the generalized-kernel-function calculations than from the conventional velocity-damping (V-g) calculation. A rational function approximation for aerodynamic forces used in control theory for s-plane analysis gave rather good agreement with kernel-function results, except for strongly damped motion at combinations of high (subsonic) Mach number and reduced frequency.

Structural and functional analysis of 5S rRNA in Saccharomyces cerevisiae

PubMed Central

Kiparisov, S.; Sergiev, P. V.; Dontsova, O. A.; Petrov, A.; Meskauskas, A.; Dinman, J. D.

2005-01-01

5S rRNA extends from the central protuberance of the large ribosomal subunit, through the A-site finger, and down to the GTPase-associated center. Here, we present a structure-function analysis of seven 5S rRNA alleles which are sufficient for viability in the yeast Saccharomyces cerevisiae when expressed in the absence of wild-type 5S rRNAs, and extend this analysis using a large bank of mutant alleles that show semidominant phenotypes in the presence of wild-type 5S rRNA. This analysis supports the hypothesis that 5S rRNA serves to link together several different functional centers of the ribosome. Data are also presented which suggest that in eukaryotic genomes selection has favored the maintenance of multiple alleles of 5S rRNA, and that these may provide cells with a mechanism to post-transcriptionally regulate gene expression. PMID:16047201

An Examination of the Effects of a Video-Based Training Package on Professional Staff's Implementation of a Brief Functional Analysis and Data Analysis

ERIC Educational Resources Information Center

Fleming, Courtney V.

2011-01-01

Minimal research has investigated training packages used to teach professional staff how to implement functional analysis procedures and to interpret data gathered during functional analysis. The current investigation used video-based training with role-play and feedback to teach six professionals in a clinical setting to implement procedures of a…

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

PubMed

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal

Methods to evaluate functional nerve recovery in adult rats: walking track analysis, video analysis and the withdrawal reflex.

PubMed

Dijkstra, J R; Meek, M F; Robinson, P H; Gramsbergen, A

2000-03-15

The aim of this study was to compare different methods for the evaluation of functional nerve recovery. Three groups of adult male Wistar rats were studied. In group A, a 12-mm gap between nerve ends was bridged by an autologous nerve graft; in rats of group B we performed a crush lesion of the sciatic nerve and group C consisted of non-operated control rats. The withdrawal reflex, elicited by an electric stimulus, was used to evaluate the recovery of sensory nerve function. To investigate motor nerve recovery we analyzed the walking pattern. Three different methods were used to obtain data for footprint analysis: photographic paper with thickened film developer on the paws, normal white paper with finger paint, and video recordings. The footprints were used to calculate the sciatic function index (SFI). From the video recordings, we also analyzed stepcycles. The withdrawal reflex is a convenient and reproducible test for the evaluation of global sensory nerve recovery. Recording walking movements on video and the analysis of footplacing is a perfect although time-consuming method for the evaluation of functional aspects of motor nerve recovery.

Local linear regression for function learning: an analysis based on sample discrepancy.

PubMed

Cervellera, Cristiano; Macciò, Danilo

2014-11-01

Local linear regression models, a kind of nonparametric structures that locally perform a linear estimation of the target function, are analyzed in the context of empirical risk minimization (ERM) for function learning. The analysis is carried out with emphasis on geometric properties of the available data. In particular, the discrepancy of the observation points used both to build the local regression models and compute the empirical risk is considered. This allows to treat indifferently the case in which the samples come from a random external source and the one in which the input space can be freely explored. Both consistency of the ERM procedure and approximating capabilities of the estimator are analyzed, proving conditions to ensure convergence. Since the theoretical analysis shows that the estimation improves as the discrepancy of the observation points becomes smaller, low-discrepancy sequences, a family of sampling methods commonly employed for efficient numerical integration, are also analyzed. Simulation results involving two different examples of function learning are provided.

Advances in structural and functional analysis of membrane proteins by electron crystallography.

PubMed

Wisedchaisri, Goragot; Reichow, Steve L; Gonen, Tamir

2011-10-12

Electron crystallography is a powerful technique for the study of membrane protein structure and function in the lipid environment. When well-ordered two-dimensional crystals are obtained the structure of both protein and lipid can be determined and lipid-protein interactions analyzed. Protons and ionic charges can be visualized by electron crystallography and the protein of interest can be captured for structural analysis in a variety of physiologically distinct states. This review highlights the strengths of electron crystallography and the momentum that is building up in automation and the development of high throughput tools and methods for structural and functional analysis of membrane proteins by electron crystallography. Copyright © 2011 Elsevier Ltd. All rights reserved.

Advances in the quantification of mitochondrial function in primary human immune cells through extracellular flux analysis.

PubMed

Nicholas, Dequina; Proctor, Elizabeth A; Raval, Forum M; Ip, Blanche C; Habib, Chloe; Ritou, Eleni; Grammatopoulos, Tom N; Steenkamp, Devin; Dooms, Hans; Apovian, Caroline M; Lauffenburger, Douglas A; Nikolajczyk, Barbara S

2017-01-01

Numerous studies show that mitochondrial energy generation determines the effectiveness of immune responses. Furthermore, changes in mitochondrial function may regulate lymphocyte function in inflammatory diseases like type 2 diabetes. Analysis of lymphocyte mitochondrial function has been facilitated by introduction of 96-well format extracellular flux (XF96) analyzers, but the technology remains imperfect for analysis of human lymphocytes. Limitations in XF technology include the lack of practical protocols for analysis of archived human cells, and inadequate data analysis tools that require manual quality checks. Current analysis tools for XF outcomes are also unable to automatically assess data quality and delete untenable data from the relatively high number of biological replicates needed to power complex human cell studies. The objectives of work presented herein are to test the impact of common cellular manipulations on XF outcomes, and to develop and validate a new automated tool that objectively analyzes a virtually unlimited number of samples to quantitate mitochondrial function in immune cells. We present significant improvements on previous XF analyses of primary human cells that will be absolutely essential to test the prediction that changes in immune cell mitochondrial function and fuel sources support immune dysfunction in chronic inflammatory diseases like type 2 diabetes.

Human factors evaluation of remote afterloading brachytherapy. Volume 2, Function and task analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Callan, J.R.; Gwynne, J.W. III; Kelly, T.T.

1995-05-01

A human factors project on the use of nuclear by-product material to treat cancer using remotely operated afterloaders was undertaken by the Nuclear Regulatory Commission. The purpose of the project was to identify factors that contribute to human error in the system for remote afterloading brachytherapy (RAB). This report documents the findings from the first phase of the project, which involved an extensive function and task analysis of RAB. This analysis identified the functions and tasks in RAB, made preliminary estimates of the likelihood of human error in each task, and determined the skills needed to perform each RAB task.more » The findings of the function and task analysis served as the foundation for the remainder of the project, which evaluated four major aspects of the RAB system linked to human error: human-system interfaces; procedures and practices; training and qualifications of RAB staff; and organizational practices and policies. At its completion, the project identified and prioritized areas for recommended NRC and industry attention based on all of the evaluations and analyses.« less

Functional analysis of PGRP-LA in Drosophila immunity.

PubMed

Gendrin, Mathilde; Zaidman-Rémy, Anna; Broderick, Nichole A; Paredes, Juan; Poidevin, Mickaël; Roussel, Alain; Lemaitre, Bruno

2013-01-01

PeptidoGlycan Recognition Proteins (PGRPs) are key regulators of the insect innate antibacterial response. Even if they have been intensively studied, some of them have yet unknown functions. Here, we present a functional analysis of PGRP-LA, an as yet uncharacterized Drosophila PGRP. The PGRP-LA gene is located in cluster with PGRP-LC and PGRP-LF, which encode a receptor and a negative regulator of the Imd pathway, respectively. Structure predictions indicate that PGRP-LA would not bind to peptidoglycan, pointing to a regulatory role of this PGRP. PGRP-LA expression was enriched in barrier epithelia, but low in the fat body. Use of a newly generated PGRP-LA deficient mutant indicates that PGRP-LA is not required for the production of antimicrobial peptides by the fat body in response to a systemic infection. Focusing on the respiratory tract, where PGRP-LA is strongly expressed, we conducted a genome-wide microarray analysis of the tracheal immune response of wild-type, Relish, and PGRP-LA mutant larvae. Comparing our data to previous microarray studies, we report that a majority of genes regulated in the trachea upon infection differ from those induced in the gut or the fat body. Importantly, antimicrobial peptide gene expression was reduced in the tracheae of larvae and in the adult gut of PGRP-LA-deficient Drosophila upon oral bacterial infection. Together, our results suggest that PGRP-LA positively regulates the Imd pathway in barrier epithelia.

Functional and Structural Analysis of the Conserved EFhd2 Protein

PubMed Central

Acosta, Yancy Ferrer; Rodríguez Cruz, Eva N.; Vaquer, Ana del C.; Vega, Irving E.

2013-01-01

EFhd2 is a novel protein conserved from C. elegans to H. sapiens. This novel protein was originally identified in cells of the immune and central nervous systems. However, it is most abundant in the central nervous system, where it has been found associated with pathological forms of the microtubule-associated protein tau. The physiological or pathological roles of EFhd2 are poorly understood. In this study, a functional and structural analysis was carried to characterize the molecular requirements for EFhd2’s calcium binding activity. The results showed that mutations of a conserved aspartate on either EF-hand motif disrupted the calcium binding activity, indicating that these motifs work in pair as a functional calcium binding domain. Furthermore, characterization of an identified single-nucleotide polymorphisms (SNP) that introduced a missense mutation indicates the importance of a conserved phenylalanine on EFhd2 calcium binding activity. Structural analysis revealed that EFhd2 is predominantly composed of alpha helix and random coil structures and that this novel protein is thermostable. EFhd2’s thermo stability depends on its N-terminus. In the absence of the N-terminus, calcium binding restored EFhd2’s thermal stability. Overall, these studies contribute to our understanding on EFhd2 functional and structural properties, and introduce it into the family of canonical EF-hand domain containing proteins. PMID:22973849

Exponential Family Functional data analysis via a low-rank model.

PubMed

Li, Gen; Huang, Jianhua Z; Shen, Haipeng

2018-05-08

In many applications, non-Gaussian data such as binary or count are observed over a continuous domain and there exists a smooth underlying structure for describing such data. We develop a new functional data method to deal with this kind of data when the data are regularly spaced on the continuous domain. Our method, referred to as Exponential Family Functional Principal Component Analysis (EFPCA), assumes the data are generated from an exponential family distribution, and the matrix of the canonical parameters has a low-rank structure. The proposed method flexibly accommodates not only the standard one-way functional data, but also two-way (or bivariate) functional data. In addition, we introduce a new cross validation method for estimating the latent rank of a generalized data matrix. We demonstrate the efficacy of the proposed methods using a comprehensive simulation study. The proposed method is also applied to a real application of the UK mortality study, where data are binomially distributed and two-way functional across age groups and calendar years. The results offer novel insights into the underlying mortality pattern. © 2018, The International Biometric Society.

Brain-Wide Analysis of Functional Connectivity in First-Episode and Chronic Stages of Schizophrenia.

PubMed

Li, Tao; Wang, Qiang; Zhang, Jie; Rolls, Edmund T; Yang, Wei; Palaniyappan, Lena; Zhang, Lu; Cheng, Wei; Yao, Ye; Liu, Zhaowen; Gong, Xiaohong; Luo, Qiang; Tang, Yanqing; Crow, Timothy J; Broome, Matthew R; Xu, Ke; Li, Chunbo; Wang, Jijun; Liu, Zhening; Lu, Guangming; Wang, Fei; Feng, Jianfeng

2017-03-01

Published reports of functional abnormalities in schizophrenia remain divergent due to lack of staging point-of-view and whole-brain analysis. To identify key functional-connectivity differences of first-episode (FE) and chronic patients from controls using resting-state functional MRI, and determine changes that are specifically associated with disease onset, a clinical staging model is adopted. We analyze functional-connectivity differences in prodromal, FE (mostly drug naïve), and chronic patients from their matched controls from 6 independent datasets involving a total of 789 participants (343 patients). Brain-wide functional-connectivity analysis was performed in different datasets and the results from the datasets of the same stage were then integrated by meta-analysis, with Bonferroni correction for multiple comparisons. Prodromal patients differed from controls in their pattern of functional-connectivity involving the inferior frontal gyri (Broca's area). In FE patients, 90% of the functional-connectivity changes involved the frontal lobes, mostly the inferior frontal gyrus including Broca's area, and these changes were correlated with delusions/blunted affect. For chronic patients, functional-connectivity differences extended to wider areas of the brain, including reduced thalamo-frontal connectivity, and increased thalamo-temporal and thalamo-sensorimoter connectivity that were correlated with the positive, negative, and general symptoms, respectively. Thalamic changes became prominent at the chronic stage. These results provide evidence for distinct patterns of functional-dysconnectivity across FE and chronic stages of schizophrenia. Importantly, abnormalities in the frontal language networks appear early, at the time of disease onset. The identification of stage-specific pathological processes may help to understand the disease course of schizophrenia and identify neurobiological markers crucial for early diagnosis. © The Author 2016. Published by

Estimation of Psychophysical Thresholds Based on Neural Network Analysis of DPOAE Input/Output Functions

NASA Astrophysics Data System (ADS)

Naghibolhosseini, Maryam; Long, Glenis

2011-11-01

The distortion product otoacoustic emission (DPOAE) input/output (I/O) function may provide a potential tool for evaluating cochlear compression. Hearing loss causes an increase in the level of the sound that is just audible for the person, which affects the cochlea compression and thus the dynamic range of hearing. Although the slope of the I/O function is highly variable when the total DPOAE is used, separating the nonlinear-generator component from the reflection component reduces this variability. We separated the two components using least squares fit (LSF) analysis of logarithmic sweeping tones, and confirmed that the separated generator component provides more consistent I/O functions than the total DPOAE. In this paper we estimated the slope of the I/O functions of the generator components at different sound levels using LSF analysis. An artificial neural network (ANN) was used to estimate psychophysical thresholds using the estimated slopes of the I/O functions. DPOAE I/O functions determined in this way may help to estimate hearing thresholds and cochlear health.

Dynamic biochemical tissue analysis detects functional L-selectin ligands on colon cancer tissues

PubMed Central

Carlson, Grady E.; Martin, Eric W.; Shirure, Venktesh S.; Malgor, Ramiro; Resto, Vicente A.; Goetz, Douglas J.; Burdick, Monica M.

2017-01-01

A growing body of evidence suggests that L-selectin ligands presented on circulating tumor cells facilitate metastasis by binding L-selectin presented on leukocytes. Commonly used methods for detecting L-selectin ligands on tissues, e.g., immunostaining, are performed under static, no-flow conditions. However, such analysis does not assay for functional L-selectin ligands, specifically those ligands that promote adhesion under shear flow conditions. Recently our lab developed a method, termed dynamic biochemical tissue analysis (DBTA), to detect functional selectin ligands in situ by probing tissues with L-selectin-coated microspheres under hemodynamic flow conditions. In this investigation, DBTA was used to probe human colon tissues for L-selectin ligand activity. The detection of L-selectin ligands using DBTA was highly specific. Furthermore, DBTA reproducibly detected functional L-selectin ligands on diseased, e.g., cancerous or inflamed, tissues but not on noncancerous tissues. In addition, DBTA revealed a heterogeneous distribution of functional L-selectin ligands on colon cancer tissues. Most notably, detection of L-selectin ligands by immunostaining using HECA-452 antibody only partially correlated with functional L-selectin ligands detected by DBTA. In summation, the results of this study demonstrate that DBTA detects functional selectin ligands to provide a unique characterization of pathological tissue. PMID:28282455

Dynamic biochemical tissue analysis detects functional L-selectin ligands on colon cancer tissues.

PubMed

Carlson, Grady E; Martin, Eric W; Shirure, Venktesh S; Malgor, Ramiro; Resto, Vicente A; Goetz, Douglas J; Burdick, Monica M

2017-01-01

A growing body of evidence suggests that L-selectin ligands presented on circulating tumor cells facilitate metastasis by binding L-selectin presented on leukocytes. Commonly used methods for detecting L-selectin ligands on tissues, e.g., immunostaining, are performed under static, no-flow conditions. However, such analysis does not assay for functional L-selectin ligands, specifically those ligands that promote adhesion under shear flow conditions. Recently our lab developed a method, termed dynamic biochemical tissue analysis (DBTA), to detect functional selectin ligands in situ by probing tissues with L-selectin-coated microspheres under hemodynamic flow conditions. In this investigation, DBTA was used to probe human colon tissues for L-selectin ligand activity. The detection of L-selectin ligands using DBTA was highly specific. Furthermore, DBTA reproducibly detected functional L-selectin ligands on diseased, e.g., cancerous or inflamed, tissues but not on noncancerous tissues. In addition, DBTA revealed a heterogeneous distribution of functional L-selectin ligands on colon cancer tissues. Most notably, detection of L-selectin ligands by immunostaining using HECA-452 antibody only partially correlated with functional L-selectin ligands detected by DBTA. In summation, the results of this study demonstrate that DBTA detects functional selectin ligands to provide a unique characterization of pathological tissue.

Functional analysis of the zebrafish ortholog of HMGCS1 reveals independent functions for cholesterol and isoprenoids in craniofacial development

PubMed Central

Hernandez, Jose A.; Gonzalez, Cesar G.

2017-01-01

There are 8 different human syndromes caused by mutations in the cholesterol synthesis pathway. A subset of these disorders such as Smith-Lemli-Opitz disorder, are associated with facial dysmorphia. However, the molecular and cellular mechanisms underlying such facial deficits are not fully understood, primarily because of the diverse functions associated with the cholesterol synthesis pathway. Recent evidence has demonstrated that mutation of the zebrafish ortholog of HMGCR results in orofacial clefts. Here we sought to expand upon these data, by deciphering the cholesterol dependent functions of the cholesterol synthesis pathway from the cholesterol independent functions. Moreover, we utilized loss of function analysis and pharmacological inhibition to determine the extent of sonic hedgehog (Shh) signaling in animals with aberrant cholesterol and/or isoprenoid synthesis. Our analysis confirmed that mutation of hmgcs1, which encodes the first enzyme in the cholesterol synthesis pathway, results in craniofacial abnormalities via defects in cranial neural crest cell differentiation. Furthermore targeted pharmacological inhibition of the cholesterol synthesis pathway revealed a novel function for isoprenoid synthesis during vertebrate craniofacial development. Mutation of hmgcs1 had no effect on Shh signaling at 2 and 3 days post fertilization (dpf), but did result in a decrease in the expression of gli1, a known Shh target gene, at 4 dpf, after morphological deficits in craniofacial development and chondrocyte differentiation were observed in hmgcs1 mutants. These data raise the possibility that deficiencies in cholesterol modulate chondrocyte differentiation by a combination of Shh independent and Shh dependent mechanisms. Moreover, our results describe a novel function for isoprenoids in facial development and collectively suggest that cholesterol regulates craniofacial development through versatile mechanisms. PMID:28686747

The use of copula functions for predictive analysis of correlations between extreme storm tides

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

A functional approach to movement analysis and error identification in sports and physical education

PubMed Central

Hossner, Ernst-Joachim; Schiebl, Frank; Göhner, Ulrich

2015-01-01

In a hypothesis-and-theory paper, a functional approach to movement analysis in sports is introduced. In this approach, contrary to classical concepts, it is not anymore the “ideal” movement of elite athletes that is taken as a template for the movements produced by learners. Instead, movements are understood as the means to solve given tasks that in turn, are defined by to-be-achieved task goals. A functional analysis comprises the steps of (1) recognizing constraints that define the functional structure, (2) identifying sub-actions that subserve the achievement of structure-dependent goals, (3) explicating modalities as specifics of the movement execution, and (4) assigning functions to actions, sub-actions and modalities. Regarding motor-control theory, a functional approach can be linked to a dynamical-system framework of behavioral shaping, to cognitive models of modular effect-related motor control as well as to explicit concepts of goal setting and goal achievement. Finally, it is shown that a functional approach is of particular help for sports practice in the context of structuring part practice, recognizing functionally equivalent task solutions, finding innovative technique alternatives, distinguishing errors from style, and identifying root causes of movement errors. PMID:26441717

Combined first-principles and model Hamiltonian study of the perovskite series R MnO 3 (R =La ,Pr ,Nd ,Sm ,Eu , and Gd )

NASA Astrophysics Data System (ADS)

Kováčik, Roman; Murthy, Sowmya Sathyanarayana; Quiroga, Carmen E.; Ederer, Claude; Franchini, Cesare

2016-02-01

We merge advanced ab initio schemes (standard density functional theory, hybrid functionals, and the G W approximation) with model Hamiltonian approaches (tight-binding and Heisenberg Hamiltonian) to study the evolution of the electronic, magnetic, and dielectric properties of the manganite family R MnO3 (R =La,Pr,Nd,Sm,Eu, and Gd) . The link between first principles and tight binding is established by downfolding the physically relevant subset of 3 d bands with eg character by means of maximally localized Wannier functions (MLWFs) using the VASP2WANNIER90 interface. The MLWFs are then used to construct a general tight-binding Hamiltonian written as a sum of the kinetic term, the Hund's rule coupling, the JT coupling, and the electron-electron interaction. The dispersion of the tight-binding (TB) eg bands at all levels are found to match closely the MLWFs. We provide a complete set of TB parameters which can serve as guidance for the interpretation of future studies based on many-body Hamiltonian approaches. In particular, we find that the Hund's rule coupling strength, the Jahn-Teller coupling strength, and the Hubbard interaction parameter U remain nearly constant for all the members of the R MnO3 series, whereas the nearest-neighbor hopping amplitudes show a monotonic attenuation as expected from the trend of the tolerance factor. Magnetic exchange interactions, computed by mapping a large set of hybrid functional total energies onto an Heisenberg Hamiltonian, clarify the origin of the A-type magnetic ordering observed in the early rare-earth manganite series as arising from a net negative out-of-plane interaction energy. The obtained exchange parameters are used to estimate the Néel temperature by means of Monte Carlo simulations. The resulting data capture well the monotonic decrease of the ordering temperature down the series from R =La to Gd, in agreement with experiments. This trend correlates well with the modulation of structural properties, in

Training Head Start Teachers to Conduct Trial-Based Functional Analysis of Challenging Behavior

ERIC Educational Resources Information Center

Rispoli, Mandy; Burke, Mack D.; Hatton, Heather; Ninci, Jennifer; Zaini, Samar; Sanchez, Lisa

2015-01-01

Trial-based functional analysis (TBFA) is a procedure for experimentally identifying the function of challenging behavior within applied settings. The purpose of this study was to examine the effects of a TBFA teacher-training package in the context of two Head Start centers implementing programwide positive behavior support (PWPBS). Four Head…

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

Free vibrations and buckling analysis of laminated plates by oscillatory radial basis functions

NASA Astrophysics Data System (ADS)

Neves, A. M. A.; Ferreira, A. J. M.

2015-12-01

In this paper the free vibrations and buckling analysis of laminated plates is performed using a global meshless method. A refined version of Kant's theorie which accounts for transverse normal stress and through-the-thickness deformation is used. The innovation is the use of oscillatory radial basis functions. Numerical examples are performed and results are presented and compared to available references. Such functions proved to be an alternative to the tradicional nonoscillatory radial basis functions.

Computational Functional Analysis of Lipid Metabolic Enzymes.

PubMed

Bagnato, Carolina; Have, Arjen Ten; Prados, María B; Beligni, María V

2017-01-01

The computational analysis of enzymes that participate in lipid metabolism has both common and unique challenges when compared to the whole protein universe. Some of the hurdles that interfere with the functional annotation of lipid metabolic enzymes that are common to other pathways include the definition of proper starting datasets, the construction of reliable multiple sequence alignments, the definition of appropriate evolutionary models, and the reconstruction of phylogenetic trees with high statistical support, particularly for large datasets. Most enzymes that take part in lipid metabolism belong to complex superfamilies with many members that are not involved in lipid metabolism. In addition, some enzymes that do not have sequence similarity catalyze similar or even identical reactions. Some of the challenges that, albeit not unique, are more specific to lipid metabolism refer to the high compartmentalization of the routes, the catalysis in hydrophobic environments and, related to this, the function near or in biological membranes.In this work, we provide guidelines intended to assist in the proper functional annotation of lipid metabolic enzymes, based on previous experiences related to the phospholipase D superfamily and the annotation of the triglyceride synthesis pathway in algae. We describe a pipeline that starts with the definition of an initial set of sequences to be used in similarity-based searches and ends in the reconstruction of phylogenies. We also mention the main issues that have to be taken into consideration when using tools to analyze subcellular localization, hydrophobicity patterns, or presence of transmembrane domains in lipid metabolic enzymes.

Influence of Type of Frequency Weighting Function On VDV Analysis

NASA Astrophysics Data System (ADS)

Kowalska-Koczwara, Alicja; Stypuła, Krzysztof

2017-10-01

Transport vibrations are the subject of many research, mostly their influence on structural elements of the building is investigated. However, nowadays, especially in the centres of large cities were apartments, residential buildings are closer to the transport vibration sources, an increasing attention is given to providing vibrational comfort to humans in buildings. Currently, in most countries, two main methods of evaluation are used: root mean squared method (RMS) and vibration dose value (VDV). In this article, VDV method is presented and the analysis of the weighting functions selection on value of VDV is made. Measurements required for the analysis were made in Krakow, on masonry, residential, two storey building located in the city centre. The building is subjected into two transport vibration sources: tram passages and vehicle passages on very close located road. Measurement points were located on the basement wall at ground level to control the excitation and in the middle of the floor on the highest storey (in the place where people percept vibration). The room chosen for measurements is located closest to the transport excitation sources. During the measurements, 25 vibration events were recorded and analysed. VDV values were calculated for three different weighting functions according to standard: ISO 2631-1, ISO 2631-2 and BS-6841. Differences in VDV values are shown, but also influence of the weighting function selection on result of evaluation is also presented. VDV analysis was performed not only for the individual vibration event but also all day and night vibration exposure were calculated using formulas contained in the annex to the standard BS-6841. It is demonstrated that, although there are differences in the values of VDV, an influence on all day and night exposure is no longer so significant.

Experimental functional analysis of severe skin-picking behavior in Prader-Willi syndrome.

PubMed

Hall, Scott S; Hustyi, Kristin M; Chui, Clara; Hammond, Jennifer L

2014-10-01

Skin picking is an extremely distressing and treatment resistant behavior commonly shown by individuals with Prader-Willi syndrome (PWS). However, with the exception of a limited number of published single-case and survey studies, little is known about the environmental determinants of skin picking in this population. In this study, functional analyses were conducted with thirteen individuals with PWS, aged 6-23 years, who engaged in severe skin-picking behavior. In addition to the conditions typically employed in a functional analysis (i.e., alone, attention, play, demand), we included an ignore condition to examine potential effects of stimulus control by the presence of an adult. Twelve participants engaged in skin picking during the functional analysis, with the highest levels occurring in the alone and ignore conditions for eight participants, suggesting that skin picking in these participants was maintained by automatic reinforcement. For the remaining four participants, an undifferentiated pattern of low-rate skin picking was observed across conditions. These data confirm previous studies indicating that skin picking in PWS may be maintained most often by automatically produced sensory consequences. There were no associations between demographic characteristics of the participants (e.g., sex, age, IQ or BMI) and levels of skin picking observed in the functional analysis. Additional investigations are needed to identify the nature of the sensory consequences produced during episodes of skin picking in PWS. Behavioral interventions designed to extinguish or compete with the potential sensory consequences arising from skin picking in PWS are also warranted. Copyright © 2014 Elsevier Ltd. All rights reserved.

Functional Morphometric Analysis of the Furcula in Mesozoic Birds

PubMed Central

Close, Roger A.; Rayfield, Emily J.

2012-01-01

The furcula displays enormous morphological and structural diversity. Acting as an important origin for flight muscles involved in the downstroke, the form of this element has been shown to vary with flight mode. This study seeks to clarify the strength of this form-function relationship through the use of eigenshape morphometric analysis coupled with recently developed phylogenetic comparative methods (PCMs), including phylogenetic Flexible Discriminant Analysis (pFDA). Additionally, the morphospace derived from the furculae of extant birds is used to shed light on possible flight adaptations of Mesozoic fossil taxa. While broad conclusions of earlier work are supported (U-shaped furculae are associated with soaring, strong anteroposterior curvature with wing-propelled diving), correlations between form and function do not appear to be so clear-cut, likely due to the significantly larger dataset and wider spectrum of flight modes sampled here. Interclavicular angle is an even more powerful discriminator of flight mode than curvature, and is positively correlated with body size. With the exception of the close relatives of modern birds, the ornithuromorphs, Mesozoic taxa tend to occupy unique regions of morphospace, and thus may have either evolved unfamiliar flight styles or have arrived at similar styles through divergent musculoskeletal configurations. PMID:22666324

Structural, Functional, and Genetic Analysis of Sorangicin Inhibition of Bacterial RNA Polymerase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell,E.; Pavlova, O.; Zenkin, N.

2005-01-01

A combined structural, functional, and genetic approach was used to investigate inhibition of bacterial RNA polymerase (RNAP) by sorangicin (Sor), a macrolide polyether antibiotic. Sor lacks chemical and structural similarity to the ansamycin rifampicin (Rif), an RNAP inhibitor widely used to treat tuberculosis. Nevertheless, structural analysis revealed Sor binds in the same RNAP {beta} subunit pocket as Rif, with almost complete overlap of RNAP binding determinants, and functional analysis revealed that both antibiotics inhibit transcription by directly blocking the path of the elongating transcript at a length of 2-3 nucleotides. Genetic analysis indicates that Rif binding is extremely sensitive tomore » mutations expected to change the shape of the antibiotic binding pocket, while Sor is not. We suggest that conformational flexibility of Sor, in contrast to the rigid conformation of Rif, allows Sor to adapt to changes in the binding pocket. This has important implications for drug design against rapidly mutating targets.« less

Functional Group Analysis.

ERIC Educational Resources Information Center

Smith, Walter T., Jr.; Patterson, John M.

1984-01-01

Literature on analytical methods related to the functional groups of 17 chemical compounds is reviewed. These compounds include acids, acid azides, alcohols, aldehydes, ketones, amino acids, aromatic hydrocarbons, carbodiimides, carbohydrates, ethers, nitro compounds, nitrosamines, organometallic compounds, peroxides, phenols, silicon compounds,…

Spherical Harmonic Analysis of Particle Velocity Distribution Function: Comparison of Moments and Anisotropies using Cluster Data

NASA Technical Reports Server (NTRS)

Gurgiolo, Chris; Vinas, Adolfo F.

2009-01-01

This paper presents a spherical harmonic analysis of the plasma velocity distribution function using high-angular, energy, and time resolution Cluster data obtained from the PEACE spectrometer instrument to demonstrate how this analysis models the particle distribution function and its moments and anisotropies. The results show that spherical harmonic analysis produced a robust physical representation model of the velocity distribution function, resolving the main features of the measured distributions. From the spherical harmonic analysis, a minimum set of nine spectral coefficients was obtained from which the moment (up to the heat flux), anisotropy, and asymmetry calculations of the velocity distribution function were obtained. The spherical harmonic method provides a potentially effective "compression" technique that can be easily carried out onboard a spacecraft to determine the moments and anisotropies of the particle velocity distribution function for any species. These calculations were implemented using three different approaches, namely, the standard traditional integration, the spherical harmonic (SPH) spectral coefficients integration, and the singular value decomposition (SVD) on the spherical harmonic methods. A comparison among the various methods shows that both SPH and SVD approaches provide remarkable agreement with the standard moment integration method.

Nutritional intervention as part of functional rehabilitation in older people with reduced functional ability: a systematic review and meta-analysis of randomised controlled studies.

PubMed

Beck, A M; Dent, E; Baldwin, C

2016-12-01

Nutritional intervention is increasingly recognised as having an important role in functional rehabilitation for older people. Nonetheless, a greater understanding of the functional benefit of nutritional interventions is needed. A systematic review and meta-analysis examined randomised controlled trials (RCTs) published between 2007 and 2014 with the aim of determining whether nutritional intervention combined with rehabilitation benefited older people with reduced functional ability. Six electronic databases were searched. RCTs including people aged 65 years and older with reduced physical, social and/or cognitive function were included. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed, and gradepro computer software (http://gradepro.org) was used for the quality assessment of critical and important outcomes. Included studies considered to be clinical homogenous were combined in a meta-analysis. Of the 788 studies screened, five were identified for inclusion. Nutritional intervention given with functional rehabilitation improved energy and protein intake, although it failed to provide any improvement in final body weight, hand-grip strength or muscle strength. There was no difference between groups in the critical outcomes; balance, cognition, activities of daily living and mortality at long-term follow-up. Nutritional intervention given with functional rehabilitation was associated with an increased likelihood of both mortality (odds ratio = 1.77; 95% confidence interval = 1.13-2.76) and hospitalisation (odds ratio = 2.29; 95% confidence interval = 1.10-4.79) during the intervention. Meta-analysis of the baseline data showed that, overall, the intervention cohort had a lower body weight and cognition. This meta-analysis highlights concerns regarding the quality of the randomisation of participants at baseline. Future high-quality research is essential to establish whether older people with loss of functional

Quantitative Analysis of the Effective Functional Structure in Yeast Glycolysis

PubMed Central

De la Fuente, Ildefonso M.; Cortes, Jesus M.

2012-01-01

The understanding of the effective functionality that governs the enzymatic self-organized processes in cellular conditions is a crucial topic in the post-genomic era. In recent studies, Transfer Entropy has been proposed as a rigorous, robust and self-consistent method for the causal quantification of the functional information flow among nonlinear processes. Here, in order to quantify the functional connectivity for the glycolytic enzymes in dissipative conditions we have analyzed different catalytic patterns using the technique of Transfer Entropy. The data were obtained by means of a yeast glycolytic model formed by three delay differential equations where the enzymatic rate equations of the irreversible stages have been explicitly considered. These enzymatic activity functions were previously modeled and tested experimentally by other different groups. The results show the emergence of a new kind of dynamical functional structure, characterized by changing connectivity flows and a metabolic invariant that constrains the activity of the irreversible enzymes. In addition to the classical topological structure characterized by the specific location of enzymes, substrates, products and feedback-regulatory metabolites, an effective functional structure emerges in the modeled glycolytic system, which is dynamical and characterized by notable variations of the functional interactions. The dynamical structure also exhibits a metabolic invariant which constrains the functional attributes of the enzymes. Finally, in accordance with the classical biochemical studies, our numerical analysis reveals in a quantitative manner that the enzyme phosphofructokinase is the key-core of the metabolic system, behaving for all conditions as the main source of the effective causal flows in yeast glycolysis. PMID:22393350

Study of space shuttle orbiter system management computer function. Volume 1: Analysis, baseline design

NASA Technical Reports Server (NTRS)

1975-01-01

A system analysis of the shuttle orbiter baseline system management (SM) computer function is performed. This analysis results in an alternative SM design which is also described. The alternative design exhibits several improvements over the baseline, some of which are increased crew usability, improved flexibility, and improved growth potential. The analysis consists of two parts: an application assessment and an implementation assessment. The former is concerned with the SM user needs and design functional aspects. The latter is concerned with design flexibility, reliability, growth potential, and technical risk. The system analysis is supported by several topical investigations. These include: treatment of false alarms, treatment of off-line items, significant interface parameters, and a design evaluation checklist. An in-depth formulation of techniques, concepts, and guidelines for design of automated performance verification is discussed.

Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations

PubMed Central

Beleva Guthrie, Violeta; Masica, David L; Fraser, Andrew; Federico, Joseph; Fan, Yunfan; Camps, Manel; Karchin, Rachel

2018-01-01

Abstract The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure. PMID:29522102

Nonparametric Bayesian inference for mean residual life functions in survival analysis.

PubMed

Poynor, Valerie; Kottas, Athanasios

2018-01-19

Modeling and inference for survival analysis problems typically revolves around different functions related to the survival distribution. Here, we focus on the mean residual life (MRL) function, which provides the expected remaining lifetime given that a subject has survived (i.e. is event-free) up to a particular time. This function is of direct interest in reliability, medical, and actuarial fields. In addition to its practical interpretation, the MRL function characterizes the survival distribution. We develop general Bayesian nonparametric inference for MRL functions built from a Dirichlet process mixture model for the associated survival distribution. The resulting model for the MRL function admits a representation as a mixture of the kernel MRL functions with time-dependent mixture weights. This model structure allows for a wide range of shapes for the MRL function. Particular emphasis is placed on the selection of the mixture kernel, taken to be a gamma distribution, to obtain desirable properties for the MRL function arising from the mixture model. The inference method is illustrated with a data set of two experimental groups and a data set involving right censoring. The supplementary material available at Biostatistics online provides further results on empirical performance of the model, using simulated data examples. © The Author 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benadjaoud, Mohamed Amine, E-mail: mohamedamine.benadjaoud@gustaveroussy.fr; Université Paris sud, Le Kremlin-Bicêtre; Institut Gustave Roussy, Villejuif

2014-11-01

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principalmore » components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion

Functional data analysis on ground reaction force of military load carriage increment

NASA Astrophysics Data System (ADS)

Din, Wan Rozita Wan; Rambely, Azmin Sham

2014-06-01

Analysis of ground reaction force on military load carriage is done through functional data analysis (FDA) statistical technique. The main objective of the research is to investigate the effect of 10% load increment and to find the maximum suitable load for the Malaysian military. Ten military soldiers age 31 ± 6.2 years, weigh 71.6 ± 10.4 kg and height of 166.3 ± 5.9 cm carrying different military load range from 0% body weight (BW) up to 40% BW participated in an experiment to gather the GRF and kinematic data using Vicon Motion Analysis System, Kirstler force plates and thirty nine body markers. The analysis is conducted in sagittal, medial lateral and anterior posterior planes. The results show that 10% BW load increment has an effect when heel strike and toe-off for all the three planes analyzed with P-value less than 0.001 at 0.05 significant levels. FDA proves to be one of the best statistical techniques in analyzing the functional data. It has the ability to handle filtering, smoothing and curve aligning according to curve features and points of interest.

Meta-analysis of Results of Testosterone Therapy on Sexual Function Based on International Index of Erectile Function Scores.

PubMed

Corona, Giovanni; Rastrelli, Giulia; Morgentaler, Abraham; Sforza, Alessandra; Mannucci, Edoardo; Maggi, Mario

2017-12-01

The interpretation of available clinical evidence related to the effect of testosterone (T) treatment (TTh) on sexual function has been inconsistent, in part due to the use of different and self-reported measures to assess outcomes. The International Index of Erectile Function (IIEF) is the most frequently used validated tool to assess male sexual function. To perform a meta-analysis of available data evaluating the effect of TTh on male sexual function using IIEF as the primary outcome. An extensive Medline, Embase, and Cochrane search was performed including all placebo-controlled randomized clinical trials enrolling men comparing the effect of TTh on sexual function. Out of 137 retrieved articles, 14 were included in the study enrolling 2298 participants, with a mean follow-up of 40.1 wk and mean age of 60.2±6.5 yr. Using IIEF-erectile function domain (IIEF-EFD) as the outcome, we found that TTh significantly improved erectile function compared with placebo (mean difference=2.31 [1.41;3.22] IIEF-EFD score, p<0.0001). Patients with more severe hypogonadism (total T<8 nmol/l) reported greater changes in final IIEF-EFD score when compared with those with a milder T deficiency (total T<12 nmol/l; 1.47 [0.90;2.03] and 2.95 [1.86;4.03] for total T<12 nmol/l and <8 nmol/l, respectively, Q=5.61, p=0.02). The magnitude of the effect was lower in the presence of metabolic derangements, such as diabetes and obesity. Other aspects of sexual function, as evaluated by IIEF subdomains, were also improved with TTh including libido, intercourse satisfaction, orgasm, and overall sexual satisfaction. TTh significantly improves erectile function and other sexual parameters as measured by IIEF in hypogonadal men. These results argue that sexual dysfunction should be considered a hallmark manifestation of T deficiency, since those symptoms can be significantly improved with normalization of serum T. In addition, these results suggest that TTh alone may be considered a reasonable

INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).

Identifying Predictors of Social Functioning in College Students: A Meta-Analysis

ERIC Educational Resources Information Center

Beard, Jennifer Blair

2011-01-01

This meta-analysis draws studies from the literature on college student persistence, need theories, and positive psychology in investigating the strongest predictors of social functioning in college students in the United States and Canada. The predictor categories included background characteristics, measures of personality, mental health…

Functional Analysis and Treatment of Human-Directed Undesirable Behavior Exhibited by a Captive Chimpanzee

ERIC Educational Resources Information Center

Martin, Allison L.; Bloomsmith, Mollie A.; Kelley, Michael E.; Marr, M. Jackson; Maple, Terry L.

2011-01-01

A functional analysis identified the reinforcer maintaining feces throwing and spitting exhibited by a captive adult chimpanzee ("Pan troglodytes"). The implementation of a function-based treatment combining extinction with differential reinforcement of an alternate behavior decreased levels of inappropriate behavior. These findings further…

Functional changes of neural circuits in stroke patients with dysphagia: A meta-analysis.

PubMed

Liu, Lu; Xiao, Yuan; Zhang, Wenjing; Yao, Li; Gao, Xin; Chandan, Shah; Lui, Su

2017-08-01

Dysphagia is a common problem in stroke patients with unclear pathogenesis. Several recent functional magnetic resonance imaging (fMRI) studies had been carried out to explore the cerebral functional changes in dysphagic stroke patients. The aim of this study was to analysis these imaging findings using a meta-analysis. We used seed-based d mapping (SDM) to conduct a meta-analysis for dysphagic stroke patients prior to any kind of special treatment for dysphagia. A systematic search was conducted for the relevant studies. SDM meta-analysis method was used to examine regions of increased and decreased functional activation between dysphagic stroke patients and healthy controls. Finally, six studies including 81 stroke patients with dysphagia and 78 healthy controls met the inclusion standards. When compared with healthy controls, stroke patients with dysphagia showed hyperactivation in left cingulate gyrus, left precentral gyrus and right posterior cingulate gyrus, and hypoactivation in right cuneus and left middle frontal gyrus. The hyperactivity of precentral gyrus is crucial in stroke patients with dysphagia and may be associated with the severity of stroke. Besides the motor areas, the default-mode network regions (DMN) and affective network regions (AN) circuits are also involved in dysphagia after stroke. © 2017 Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.

The Secrets of Scheherazade: Toward a Functional Analysis of Imaginative Literature

PubMed Central

Grant, Lyle K

2005-01-01

A functional analysis of selected aspects of imaginative literature is presented. Reading imaginative literature is described as a process in which the reader makes indirect contact with the contingencies operating on the behavior of story characters. A functional story grammar is proposed in which the reader's experience with a story is interpreted in terms of escape contingencies in which the author initially introduces an establishing operation consisting of a source of tension, which is resolved in some way by the outcome of the story. Although escape contingencies represent the functional basis for the structure of stories, they are to be understood in a context of many other reinforcers for reading fiction. Other contingencies that maintain reading are discussed. Functional analyses of imaginative literature have much to offer, both in improving literary education and in understanding the behavioral processes that occur on the part of the reader. PMID:22477324

Large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

2016-03-01

We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

Finite element analysis of functionally graded bone plate at femur bone fracture site

NASA Astrophysics Data System (ADS)

Satapathy, Pravat Kumar; Sahoo, Bamadev; Panda, L. N.; Das, S.

2018-03-01

This paper focuses on the analysis of fractured Femur bone with functionally graded bone plate. The Femur bone is modeled by using the data from the CT (Computerized Tomography) scan and the material properties are assigned using Mimics software. The fracture fixation plate used here is composed of Functionally Graded Material (FGM). The functionally graded bone plate is considered to be composed of different layers of homogeneous materials. Finite element method approach is adopted for analysis. The volume fraction of the material is calculated by considering its variation along the thickness direction (z) according to a power law and the effective properties of the homogeneous layers are estimated. The model developed is validated by comparing numerical results available in the literature. Static analysis has been performed for the bone plate system by considering both axial compressive load and torsional load. The investigation shows that by introducing FG bone plate instead of titanium, the stress at the fracture site increases by 63 percentage and the deformation decreases by 15 percentage, especially when torsional load is taken into consideration. The present model yields better results in comparison with the commercially available bone plates.

Functional phylogenomics analysis of bacteria and archaea using consistent genome annotation with UniFam

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chai, Juanjuan; Kora, Guruprasad; Ahn, Tae-Hyuk

2014-10-09

To supply some background, phylogenetic studies have provided detailed knowledge on the evolutionary mechanisms of genes and species in Bacteria and Archaea. However, the evolution of cellular functions, represented by metabolic pathways and biological processes, has not been systematically characterized. Many clades in the prokaryotic tree of life have now been covered by sequenced genomes in GenBank. This enables a large-scale functional phylogenomics study of many computationally inferred cellular functions across all sequenced prokaryotes. Our results show a total of 14,727 GenBank prokaryotic genomes were re-annotated using a new protein family database, UniFam, to obtain consistent functional annotations for accuratemore » comparison. The functional profile of a genome was represented by the biological process Gene Ontology (GO) terms in its annotation. The GO term enrichment analysis differentiated the functional profiles between selected archaeal taxa. 706 prokaryotic metabolic pathways were inferred from these genomes using Pathway Tools and MetaCyc. The consistency between the distribution of metabolic pathways in the genomes and the phylogenetic tree of the genomes was measured using parsimony scores and retention indices. The ancestral functional profiles at the internal nodes of the phylogenetic tree were reconstructed to track the gains and losses of metabolic pathways in evolutionary history. In conclusion, our functional phylogenomics analysis shows divergent functional profiles of taxa and clades. Such function-phylogeny correlation stems from a set of clade-specific cellular functions with low parsimony scores. On the other hand, many cellular functions are sparsely dispersed across many clades with high parsimony scores. These different types of cellular functions have distinct evolutionary patterns reconstructed from the prokaryotic tree.« less

EELS Analysis of Nylon 6 Nanofibers Reinforced with Nitroxide-Functionalized Graphene Oxide.

PubMed

Leyva-Porras, César; Ornelas-Gutiérrez, C; Miki-Yoshida, M; Avila-Vega, Yazmín I; Macossay, Javier; Bonilla-Cruz, José

2014-01-01

A detailed analysis by transmission electron microscopy (TEM) and electron energy loss spectroscopy (EELS) of nitroxide-functionalized graphene oxide layers (GOFT) dispersed in Nylon 6 nanofibers is reported herein. The functionalization and exfoliation process of graphite oxide to GOFT was confirmed by TEM using electron diffraction patterns (EDP), wherein 1 to 4 graphene layers of GOFT were observed. The distribution and alignment of GOFT layers within a sample of Nylon 6 nanofiber reveals that GOFT platelets are mainly within the fiber, but some were partially protruding from it. Furthermore, Nylon 6 nanofibers exhibit an average diameter of 225 nm with several microns in length. GOFT platelets embedded into the fiber, the pristine fiber, and amorphous carbon were analyzed by EELS where each spectra [corresponding to the carbon edge (C-K)] exhibited changes in the fine structure, allowing a clear distinction between: i) GOFT single-layers, ii) Nylon-6 nanofibers, and iii) the carbon substrate. EELS analysis is presented here for the first time as a powerful tool to identify functionalized graphene single-layers (< 4 layers of GOFT) into a Nylon 6 nanofiber composite.

Protein arginine methylation: Cellular functions and methods of analysis.

PubMed

Pahlich, Steffen; Zakaryan, Rouzanna P; Gehring, Heinz

2006-12-01

During the last few years, new members of the growing family of protein arginine methyltransferases (PRMTs) have been identified and the role of arginine methylation in manifold cellular processes like signaling, RNA processing, transcription, and subcellular transport has been extensively investigated. In this review, we describe recent methods and findings that have yielded new insights into the cellular functions of arginine-methylated proteins, and we evaluate the currently used procedures for the detection and analysis of arginine methylation.

A human functional protein interaction network and its application to cancer data analysis

PubMed Central

2010-01-01

Background One challenge facing biologists is to tease out useful information from massive data sets for further analysis. A pathway-based analysis may shed light by projecting candidate genes onto protein functional relationship networks. We are building such a pathway-based analysis system. Results We have constructed a protein functional interaction network by extending curated pathways with non-curated sources of information, including protein-protein interactions, gene coexpression, protein domain interaction, Gene Ontology (GO) annotations and text-mined protein interactions, which cover close to 50% of the human proteome. By applying this network to two glioblastoma multiforme (GBM) data sets and projecting cancer candidate genes onto the network, we found that the majority of GBM candidate genes form a cluster and are closer than expected by chance, and the majority of GBM samples have sequence-altered genes in two network modules, one mainly comprising genes whose products are localized in the cytoplasm and plasma membrane, and another comprising gene products in the nucleus. Both modules are highly enriched in known oncogenes, tumor suppressors and genes involved in signal transduction. Similar network patterns were also found in breast, colorectal and pancreatic cancers. Conclusions We have built a highly reliable functional interaction network upon expert-curated pathways and applied this network to the analysis of two genome-wide GBM and several other cancer data sets. The network patterns revealed from our results suggest common mechanisms in the cancer biology. Our system should provide a foundation for a network or pathway-based analysis platform for cancer and other diseases. PMID:20482850

Extending bicluster analysis to annotate unclassified ORFs and predict novel functional modules using expression data

PubMed Central

Bryan, Kenneth; Cunningham, Pádraig

2008-01-01

Background Microarrays have the capacity to measure the expressions of thousands of genes in parallel over many experimental samples. The unsupervised classification technique of bicluster analysis has been employed previously to uncover gene expression correlations over subsets of samples with the aim of providing a more accurate model of the natural gene functional classes. This approach also has the potential to aid functional annotation of unclassified open reading frames (ORFs). Until now this aspect of biclustering has been under-explored. In this work we illustrate how bicluster analysis may be extended into a 'semi-supervised' ORF annotation approach referred to as BALBOA. Results The efficacy of the BALBOA ORF classification technique is first assessed via cross validation and compared to a multi-class k-Nearest Neighbour (kNN) benchmark across three independent gene expression datasets. BALBOA is then used to assign putative functional annotations to unclassified yeast ORFs. These predictions are evaluated using existing experimental and protein sequence information. Lastly, we employ a related semi-supervised method to predict the presence of novel functional modules within yeast. Conclusion In this paper we demonstrate how unsupervised classification methods, such as bicluster analysis, may be extended using of available annotations to form semi-supervised approaches within the gene expression analysis domain. We show that such methods have the potential to improve upon supervised approaches and shed new light on the functions of unclassified ORFs and their co-regulation. PMID:18831786

Development of pair distribution function analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vondreele, R.; Billinge, S.; Kwei, G.

1996-09-01

This is the final report of a 3-year LDRD project at LANL. It has become more and more evident that structural coherence in the CuO{sub 2} planes of high-{Tc} superconducting materials over some intermediate length scale (nm range) is important to superconductivity. In recent years, the pair distribution function (PDF) analysis of powder diffraction data has been developed for extracting structural information on these length scales. This project sought to expand and develop this technique, use it to analyze neutron powder diffraction data, and apply it to problems. In particular, interest is in the area of high-{Tc} superconductors, although wemore » planned to extend the study to the closely related perovskite ferroelectric materials andother materials where the local structure affects the properties where detailed knowledge of the local and intermediate range structure is important. In addition, we planned to carry out single crystal experiments to look for diffuse scattering. This information augments the information from the PDF.« less

First Monte Carlo analysis of fragmentation functions from single-inclusive e + e - annihilation

DOE PAGES

Sato, Nobuo; Ethier, J. J.; Melnitchouk, W.; ...

2016-12-02

Here, we perform the first iterative Monte Carlo (IMC) analysis of fragmentation functions constrained by all available data from single-inclusive $e^+ e^-$ annihilation into pions and kaons. The IMC method eliminates potential bias in traditional analyses based on single fits introduced by fixing parameters not well contrained by the data, and provides a statistically rigorous determination of uncertainties. Our analysis reveals specific features of fragmentation functions using the new IMC methodology and those obtained from previous analyses, especially for light quarks and for strange quark fragmentation to kaons.

FADTTSter: accelerating hypothesis testing with functional analysis of diffusion tensor tract statistics

NASA Astrophysics Data System (ADS)

Noel, Jean; Prieto, Juan C.; Styner, Martin

2017-03-01

Functional Analysis of Diffusion Tensor Tract Statistics (FADTTS) is a toolbox for analysis of white matter (WM) fiber tracts. It allows associating diffusion properties along major WM bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these WM tract properties. However, to use this toolbox, a user must have an intermediate knowledge in scripting languages (MATLAB). FADTTSter was created to overcome this issue and make the statistical analysis accessible to any non-technical researcher. FADTTSter is actively being used by researchers at the University of North Carolina. FADTTSter guides non-technical users through a series of steps including quality control of subjects and fibers in order to setup the necessary parameters to run FADTTS. Additionally, FADTTSter implements interactive charts for FADTTS' outputs. This interactive chart enhances the researcher experience and facilitates the analysis of the results. FADTTSter's motivation is to improve usability and provide a new analysis tool to the community that complements FADTTS. Ultimately, by enabling FADTTS to a broader audience, FADTTSter seeks to accelerate hypothesis testing in neuroimaging studies involving heterogeneous clinical data and diffusion tensor imaging. This work is submitted to the Biomedical Applications in Molecular, Structural, and Functional Imaging conference. The source code of this application is available in NITRC.

Extracting intrinsic functional networks with feature-based group independent component analysis.

PubMed

Calhoun, Vince D; Allen, Elena

2013-04-01

There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in functional MRI data. While networks are typically estimated based on the temporal similarity between regions (based on temporal correlation, clustering methods, or independent component analysis [ICA]), some recent work has suggested that these intrinsic networks can be extracted from the inter-subject covariation among highly distilled features, such as amplitude maps reflecting regions modulated by a task or even coordinates extracted from large meta analytic studies. In this paper our goal was to explicitly compare the networks obtained from a first-level ICA (ICA on the spatio-temporal functional magnetic resonance imaging (fMRI) data) to those from a second-level ICA (i.e., ICA on computed features rather than on the first-level fMRI data). Convergent results from simulations, task-fMRI data, and rest-fMRI data show that the second-level analysis is slightly noisier than the first-level analysis but yields strikingly similar patterns of intrinsic networks (spatial correlations as high as 0.85 for task data and 0.65 for rest data, well above the empirical null) and also preserves the relationship of these networks with other variables such as age (for example, default mode network regions tended to show decreased low frequency power for first-level analyses and decreased loading parameters for second-level analyses). In addition, the best-estimated second-level results are those which are the most strongly reflected in the input feature. In summary, the use of feature-based ICA appears to be a valid tool for extracting intrinsic networks. We believe it will become a useful and important approach in the study of the macro

Revisiting 2D Lattice Based Spin Flip-Flop Ising Model: Magnetic Properties of a Thin Film and Its Temperature Dependence

ERIC Educational Resources Information Center

Singh, Satya Pal

2014-01-01

This paper presents a brief review of Ising's work done in 1925 for one dimensional spin chain with periodic boundary condition. Ising observed that no phase transition occurred at finite temperature in one dimension. He erroneously generalized his views in higher dimensions but that was not true. In 1941 Kramer and Wannier obtained…

Functional mixed effects spectral analysis

PubMed Central

KRAFTY, ROBERT T.; HALL, MARTICA; GUO, WENSHENG

2011-01-01

SUMMARY In many experiments, time series data can be collected from multiple units and multiple time series segments can be collected from the same unit. This article introduces a mixed effects Cramér spectral representation which can be used to model the effects of design covariates on the second-order power spectrum while accounting for potential correlations among the time series segments collected from the same unit. The transfer function is composed of a deterministic component to account for the population-average effects and a random component to account for the unit-specific deviations. The resulting log-spectrum has a functional mixed effects representation where both the fixed effects and random effects are functions in the frequency domain. It is shown that, when the replicate-specific spectra are smooth, the log-periodograms converge to a functional mixed effects model. A data-driven iterative estimation procedure is offered for the periodic smoothing spline estimation of the fixed effects, penalized estimation of the functional covariance of the random effects, and unit-specific random effects prediction via the best linear unbiased predictor. PMID:26855437

Graph Theoretical Analysis of Functional Brain Networks: Test-Retest Evaluation on Short- and Long-Term Resting-State Functional MRI Data

PubMed Central

Wang, Jin-Hui; Zuo, Xi-Nian; Gohel, Suril; Milham, Michael P.; Biswal, Bharat B.; He, Yong

2011-01-01

Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic resonance imaging data. Specifically, we evaluated both short-term (<1 hour apart) and long-term (>5 months apart) TRT reliability for 12 global and 6 local nodal network metrics. We found that reliability of global network metrics was overall low, threshold-sensitive and dependent on several factors of scanning time interval (TI, long-term>short-term), network membership (NM, networks excluding negative correlations>networks including negative correlations) and network type (NT, binarized networks>weighted networks). The dependence was modulated by another factor of node definition (ND) strategy. The local nodal reliability exhibited large variability across nodal metrics and a spatially heterogeneous distribution. Nodal degree was the most reliable metric and varied the least across the factors above. Hub regions in association and limbic/paralimbic cortices showed moderate TRT reliability. Importantly, nodal reliability was robust to above-mentioned four factors. Simulation analysis revealed that global network metrics were extremely sensitive (but varying degrees) to noise in functional connectivity and weighted networks generated numerically more reliable results in compared with binarized networks. For nodal network metrics, they showed high resistance to noise in functional connectivity and no NT related differences were found in the resistance. These findings provide important implications on how to choose reliable analytical schemes and network metrics of interest. PMID:21818285

Analysis of the functional aspects and seminal plasma proteomic profile of sperm from smokers.

PubMed

Antoniassi, Mariana Pereira; Intasqui, Paula; Camargo, Mariana; Zylbersztejn, Daniel Suslik; Carvalho, Valdemir Melechco; Cardozo, Karina H M; Bertolla, Ricardo Pimenta

2016-11-01

To evaluate the effect of smoking on sperm functional quality and seminal plasma proteomic profile. Sperm functional tests were performed in 20 non-smoking men with normal semen quality, according to the World Health Organization (2010) and in 20 smoking patients. These included: evaluation of DNA fragmentation by alkaline Comet assay; analysis of mitochondrial activity using DAB staining; and acrosomal integrity evaluation by PNA binding. The remaining semen was centrifuged and seminal plasma was used for proteomic analysis (liquid chromatography-tandem mass spectrometry). The quantified proteins were used for Venn diagram construction in Cytoscape 3.2.1 software, using the PINA4MS plug-in. Then, differentially expressed proteins were used for functional enrichment analysis of Gene Ontology categories, Kyoto Encyclopedia of Genes and Genomes and Reactome, using Cytoscape software and the ClueGO 2.2.0 plug-in. Smokers had a higher percentage of sperm DNA damage (Comet classes III and IV; P < 0.01), partially and fully inactive mitochondria (DAB classes III and IV; P = 0.001 and P = 0.006, respectively) and non-intact acrosomes (P < 0.01) when compared with the control group. With respect to proteomic analysis, 422 proteins were identified and quantified, of which one protein was absent, 27 proteins were under-represented and six proteins were over-represented in smokers. Functional enrichment analysis showed the enrichment of antigen processing and presentation, positive regulation of prostaglandin secretion involved in immune response, protein kinase A signalling and arachidonic acid secretion, complement activation, regulation of the cytokine-mediated signalling pathway and regulation of acute inflammatory response in the study group (smokers). In conclusion, cigarette smoking was associated with an inflammatory state in the accessory glands and in the testis, as shown by enriched proteomic pathways. This state causes an alteration in sperm functional quality

Brief Functional Analysis and Supplemental Feeding for Postmeal Rumination in Children with Developmental Disabilities

ERIC Educational Resources Information Center

Lyons, Elizabeth A.; Rue, Hanna C.; Luiselli, James K.; DiGennaro, Florence D.

2007-01-01

Rumination is a serious problem demonstrated by some people with developmental disabilities, but previous research has not included a functional analysis and has rarely compared intervention methods during the assessment process. We conducted functional analyses with 2 children who displayed postmeal rumination and subsequently evaluated a…

A Functional Analysis of Gestural Behaviors Emitted by Young Children with Severe Developmental Disabilities

ERIC Educational Resources Information Center

Ferreri, Summer J.; Plavnick, Joshua B.

2011-01-01

Many children with severe developmental disabilities emit idiosyncratic gestures that may function as verbal operants (Sigafoos et al., 2000). This study examined the effectiveness of a functional analysis methodology to identify the variables responsible for gestures emitted by 2 young children with severe developmental disabilities. Potential…

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

PubMed Central

Du, Yushen; Wu, Nicholas C.; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting

2016-01-01

ABSTRACT Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. PMID:27803181

Regeneration in the era of functional genomics and gene network analysis.

PubMed

Smith, Joel; Morgan, Jennifer R; Zottoli, Steven J; Smith, Peter J; Buxbaum, Joseph D; Bloom, Ona E

2011-08-01

What gives an organism the ability to regrow tissues and to recover function where another organism fails is the central problem of regenerative biology. The challenge is to describe the mechanisms of regeneration at the molecular level, delivering detailed insights into the many components that are cross-regulated. In other words, a broad, yet deep dissection of the system-wide network of molecular interactions is needed. Functional genomics has been used to elucidate gene regulatory networks (GRNs) in developing tissues, which, like regeneration, are complex systems. Therefore, we reason that the GRN approach, aided by next generation technologies, can also be applied to study the molecular mechanisms underlying the complex functions of regeneration. We ask what characteristics a model system must have to support a GRN analysis. Our discussion focuses on regeneration in the central nervous system, where loss of function has particularly devastating consequences for an organism. We examine a cohort of cells conserved across all vertebrates, the reticulospinal (RS) neurons, which lend themselves well to experimental manipulations. In the lamprey, a jawless vertebrate, there are giant RS neurons whose large size and ability to regenerate make them particularly suited for a GRN analysis. Adding to their value, a distinct subset of lamprey RS neurons reproducibly fail to regenerate, presenting an opportunity for side-by-side comparison of gene networks that promote or inhibit regeneration. Thus, determining the GRN for regeneration in RS neurons will provide a mechanistic understanding of the fundamental cues that lead to success or failure to regenerate.

Functional Genomics Assistant (FUGA): a toolbox for the analysis of complex biological networks

PubMed Central

2011-01-01

Background Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context. Findings We present Functional Genomics Assistant (FUGA) - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology. Conclusion FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga. PMID:22035155

Crustal Properties Across the Mid-Continent Rift via Transfer Function Analysis

NASA Astrophysics Data System (ADS)

Frederiksen, A. W.; Tyomkin, Y.; Campbell, R.; van der Lee, S.; Zhang, H.

2015-12-01

The Mid-Continent Rift (MCR), a failed Proterozoic rift structure in central North America, is a dominant feature of North American gravity maps. The rift underwent a combination of extension, magmatism, and later compression, and it is difficult to predict how these events affected the overall crustal thickness and bulk composition in the vicinity of the rift axis, though the associated gravity high indicates that large-volume mafic magmatism took place. The Superior Province Rifting Earthscope Experiment (SPREE) project instrumented the MCR with Flexible Array broadband seismographs from 2011 through 2013 in Minnesota and Wisconsin, along two lines crossing the rift axis as well as a line following the axis. We examine teleseismic P-coda data from SPREE and nearby Transportable Array instruments using a new technique: transfer-function analysis. In this approach, possible models of crustal structure are used to generate a predicted transfer function relating the radial and vertical components of the P coda at a particular site. The transfer function then allows generation of a misfit (between the true radial component and a synthetic radial component predicted from the vertical trace) without the need to perform receiver-function deconvolution, thus avoiding the deconvolution problems encountered with receiver functions in sedimentary basins. We use the transfer-function approach to perform a grid search over three crustal properties: crustal thickness, crustal P/S velocity ratio, and the thickness of an overlying sedimentary basin. Results for our SPREE/TA data set indicate that the crust is significantly thickened along the rift axis, with maximum thicknesses approaching 50 km; the crust is thinner (ca. 40 km) outside of the rift zone. The crustal thickness structure is particularly complex beneath southeastern Minnesota, where very strong Moho topography is present, as well as up to 2 km of sediment; further north, the Moho is smoother and the basin is not

Differential item functioning analysis of the Vanderbilt Expertise Test for cars

PubMed Central

Lee, Woo-Yeol; Cho, Sun-Joo; McGugin, Rankin W.; Van Gulick, Ana Beth; Gauthier, Isabel

2015-01-01

The Vanderbilt Expertise Test for cars (VETcar) is a test of visual learning for contemporary car models. We used item response theory to assess the VETcar and in particular used differential item functioning (DIF) analysis to ask if the test functions the same way in laboratory versus online settings and for different groups based on age and gender. An exploratory factor analysis found evidence of multidimensionality in the VETcar, although a single dimension was deemed sufficient to capture the recognition ability measured by the test. We selected a unidimensional three-parameter logistic item response model to examine item characteristics and subject abilities. The VETcar had satisfactory internal consistency. A substantial number of items showed DIF at a medium effect size for test setting and for age group, whereas gender DIF was negligible. Because online subjects were on average older than those tested in the lab, we focused on the age groups to conduct a multigroup item response theory analysis. This revealed that most items on the test favored the younger group. DIF could be more the rule than the exception when measuring performance with familiar object categories, therefore posing a challenge for the measurement of either domain-general visual abilities or category-specific knowledge. PMID:26418499

Differential item functioning analysis of the Vanderbilt Expertise Test for cars.

PubMed

Lee, Woo-Yeol; Cho, Sun-Joo; McGugin, Rankin W; Van Gulick, Ana Beth; Gauthier, Isabel

2015-01-01

The Vanderbilt Expertise Test for cars (VETcar) is a test of visual learning for contemporary car models. We used item response theory to assess the VETcar and in particular used differential item functioning (DIF) analysis to ask if the test functions the same way in laboratory versus online settings and for different groups based on age and gender. An exploratory factor analysis found evidence of multidimensionality in the VETcar, although a single dimension was deemed sufficient to capture the recognition ability measured by the test. We selected a unidimensional three-parameter logistic item response model to examine item characteristics and subject abilities. The VETcar had satisfactory internal consistency. A substantial number of items showed DIF at a medium effect size for test setting and for age group, whereas gender DIF was negligible. Because online subjects were on average older than those tested in the lab, we focused on the age groups to conduct a multigroup item response theory analysis. This revealed that most items on the test favored the younger group. DIF could be more the rule than the exception when measuring performance with familiar object categories, therefore posing a challenge for the measurement of either domain-general visual abilities or category-specific knowledge.

Republication of "Functional Analysis of Classroom Variables for Students with Emotional and Behavioral Disorders"

ERIC Educational Resources Information Center

Dunlap, Glen; Kern, Lee; dePerczel, Maria; Clarke, Shelley; Wilson, Diane; Childs, Karen E.; White, Ronnie; Falk, George D.

2018-01-01

Functional assessment and functional analysis are processes that have been applied successfully in work with people who have developmental disabilities, but they have been used rarely with students who experience emotional or behavioral disorders. In the present study, five students in elementary school programs for severe emotional disturbance…

Ion-selective electrodes in organic elemental and functional group analysis: a review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Selig, W.

1977-11-08

The literature on the use of ion-selective electrodes in organic elemental and functional group analysis is surveyed in some detail. The survey is complete through Chemical Abstracts, Vol. 83 (1975). 40 figures, 52 tables, 236 references.

Wavelet coherence analysis: A new approach to distinguish organic and functional tremor types.

PubMed

Kramer, G; Van der Stouwe, A M M; Maurits, N M; Tijssen, M A J; Elting, J W J

2018-01-01

To distinguish tremor subtypes using wavelet coherence analysis (WCA). WCA enables to detect variations in coherence and phase difference between two signals over time and might be especially useful in distinguishing functional from organic tremor. In this pilot study, polymyography recordings were studied retrospectively of 26 Parkinsonian (PT), 26 functional (FT), 26 essential (ET), and 20 enhanced physiological (EPT) tremor patients. Per patient one segment of 20 s in duration, in which tremor was present continuously in the same posture, was selected. We studied several coherence and phase related parameters, and analysed all possible muscle combinations of the flexor and extensor muscles of the upper and fore arm. The area under the receiver operating characteristic curve (AUC-ROC) was applied to compare WCA and standard coherence analysis to distinguish tremor subtypes. The percentage of time with significant coherence (PTSC) and the number of periods without significant coherence (NOV) proved the most discriminative parameters. FT could be discriminated from organic (PT, ET, EPT) tremor by high NOV (31.88 vs 21.58, 23.12 and 10.20 respectively) with an AUC-ROC of 0.809, while standard coherence analysis resulted in an AUC-ROC of 0.552. EMG-EMG WCA analysis might provide additional variables to distinguish functional from organic tremor. WCA might prove to be of additional value to discriminate between tremor types. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Structure-Functional Prediction and Analysis of Cancer Mutation Effects in Protein Kinases

PubMed Central

Dixit, Anshuman; Verkhivker, Gennady M.

2014-01-01

A central goal of cancer research is to discover and characterize the functional effects of mutated genes that contribute to tumorigenesis. In this study, we provide a detailed structural classification and analysis of functional dynamics for members of protein kinase families that are known to harbor cancer mutations. We also present a systematic computational analysis that combines sequence and structure-based prediction models to characterize the effect of cancer mutations in protein kinases. We focus on the differential effects of activating point mutations that increase protein kinase activity and kinase-inactivating mutations that decrease activity. Mapping of cancer mutations onto the conformational mobility profiles of known crystal structures demonstrated that activating mutations could reduce a steric barrier for the movement from the basal “low” activity state to the “active” state. According to our analysis, the mechanism of activating mutations reflects a combined effect of partial destabilization of the kinase in its inactive state and a concomitant stabilization of its active-like form, which is likely to drive tumorigenesis at some level. Ultimately, the analysis of the evolutionary and structural features of the major cancer-causing mutational hotspot in kinases can also aid in the correlation of kinase mutation effects with clinical outcomes. PMID:24817905

Structure-functional prediction and analysis of cancer mutation effects in protein kinases.

PubMed

Dixit, Anshuman; Verkhivker, Gennady M

2014-01-01

A central goal of cancer research is to discover and characterize the functional effects of mutated genes that contribute to tumorigenesis. In this study, we provide a detailed structural classification and analysis of functional dynamics for members of protein kinase families that are known to harbor cancer mutations. We also present a systematic computational analysis that combines sequence and structure-based prediction models to characterize the effect of cancer mutations in protein kinases. We focus on the differential effects of activating point mutations that increase protein kinase activity and kinase-inactivating mutations that decrease activity. Mapping of cancer mutations onto the conformational mobility profiles of known crystal structures demonstrated that activating mutations could reduce a steric barrier for the movement from the basal "low" activity state to the "active" state. According to our analysis, the mechanism of activating mutations reflects a combined effect of partial destabilization of the kinase in its inactive state and a concomitant stabilization of its active-like form, which is likely to drive tumorigenesis at some level. Ultimately, the analysis of the evolutionary and structural features of the major cancer-causing mutational hotspot in kinases can also aid in the correlation of kinase mutation effects with clinical outcomes.

Application and Mechanics Analysis of Multi-Function Construction Platforms in Prefabricated-Concrete Construction

NASA Astrophysics Data System (ADS)

Wang, Meihua; Li, Rongshuai; Zhang, Wenze

2017-11-01

Multi-function construction platforms (MCPs) as an “old construction technology, new application” of the building facade construction equipment, its efforts to reduce labour intensity, improve labour productivity, ensure construction safety, shorten the duration of construction and other aspects of the effect are significant. In this study, the functional analysis of the multi-function construction platforms is carried out in the construction of the assembly building. Based on the general finite element software ANSYS, the static calculation and dynamic characteristics analysis of the MCPs structure are analysed, the simplified finite element model is constructed, and the selection of the unit, the processing and solution of boundary are under discussion and research. The maximum deformation value, the maximum stress value and the structural dynamic characteristic model are obtained. The dangerous parts of the platform structure are analysed, too. Multiple types of MCPs under engineering construction conditions are calculated, so as to put forward the rationalization suggestions for engineering application of the MCPs.

A phylogenetic analysis of normal modes evolution in enzymes and its relationship to enzyme function

PubMed Central

Lai, Jason; Jin, Jing; Kubelka, Jan; Liberles, David A.

2012-01-01

Since the dynamic nature of protein structures is essential for enzymatic function, it is expected that the functional evolution can be inferred from the changes in the protein dynamics. However, dynamics can also diverge neutrally with sequence substitution between enzymes without changes of function. In this study, a phylogenetic approach is implemented to explore the relationship between enzyme dynamics and function through evolutionary history. Protein dynamics are described by normal mode analysis based on a simplified harmonic potential force field applied to the reduced Cα representation of the protein structure while enzymatic function is described by Enzyme Commission (EC) numbers. Similarity of the binding pocket dynamics at each branch of the protein family’s phylogeny was analyzed in two ways: 1) explicitly by quantifying the normal mode overlap calculated for the reconstructed ancestral proteins at each end and 2) implicitly using a diffusion model to obtain the reconstructed lineage-specific changes in the normal modes. Both explicit and implicit ancestral reconstruction identified generally faster rates of change in dynamics compared with the expected change from neutral evolution at the branches of potential functional divergences for the alpha-amylase, D-isomer specific 2-hydroxyacid dehydrogenase, and copper-containing amine oxidase protein families. Normal modes analysis added additional information over just comparing the RMSD of static structures. However, the branch-specific changes were not statistically significant compared to background function-independent neutral rates of change of dynamic properties and blind application of the analysis would not enable prediction of changes in enzyme specificity. PMID:22651983

A phylogenetic analysis of normal modes evolution in enzymes and its relationship to enzyme function.

PubMed

Lai, Jason; Jin, Jing; Kubelka, Jan; Liberles, David A

2012-09-21

Since the dynamic nature of protein structures is essential for enzymatic function, it is expected that functional evolution can be inferred from the changes in protein dynamics. However, dynamics can also diverge neutrally with sequence substitution between enzymes without changes of function. In this study, a phylogenetic approach is implemented to explore the relationship between enzyme dynamics and function through evolutionary history. Protein dynamics are described by normal mode analysis based on a simplified harmonic potential force field applied to the reduced C(α) representation of the protein structure while enzymatic function is described by Enzyme Commission numbers. Similarity of the binding pocket dynamics at each branch of the protein family's phylogeny was analyzed in two ways: (1) explicitly by quantifying the normal mode overlap calculated for the reconstructed ancestral proteins at each end and (2) implicitly using a diffusion model to obtain the reconstructed lineage-specific changes in the normal modes. Both explicit and implicit ancestral reconstruction identified generally faster rates of change in dynamics compared with the expected change from neutral evolution at the branches of potential functional divergences for the α-amylase, D-isomer-specific 2-hydroxyacid dehydrogenase, and copper-containing amine oxidase protein families. Normal mode analysis added additional information over just comparing the RMSD of static structures. However, the branch-specific changes were not statistically significant compared to background function-independent neutral rates of change of dynamic properties and blind application of the analysis would not enable prediction of changes in enzyme specificity. Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparing rainfall patterns between regions in Peninsular Malaysia via a functional data analysis technique

NASA Astrophysics Data System (ADS)

Suhaila, Jamaludin; Jemain, Abdul Aziz; Hamdan, Muhammad Fauzee; Wan Zin, Wan Zawiah

2011-12-01

SummaryNormally, rainfall data is collected on a daily, monthly or annual basis in the form of discrete observations. The aim of this study is to convert these rainfall values into a smooth curve or function which could be used to represent the continuous rainfall process at each region via a technique known as functional data analysis. Since rainfall data shows a periodic pattern in each region, the Fourier basis is introduced to capture these variations. Eleven basis functions with five harmonics are used to describe the unimodal rainfall pattern for stations in the East while five basis functions which represent two harmonics are needed to describe the rainfall pattern in the West. Based on the fitted smooth curve, the wet and dry periods as well as the maximum and minimum rainfall values could be determined. Different rainfall patterns are observed among the studied regions based on the smooth curve. Using the functional analysis of variance, the test results indicated that there exist significant differences in the functional means between each region. The largest differences in the functional means are found between the East and Northwest regions and these differences may probably be due to the effect of topography and, geographical location and are mostly influenced by the monsoons. Therefore, the same inputs or approaches might not be useful in modeling the hydrological process for different regions.

Impact of Plant Functional Types on Coherence Between Precipitation and Soil Moisture: A Wavelet Analysis

NASA Astrophysics Data System (ADS)

Liu, Qi; Hao, Yonghong; Stebler, Elaine; Tanaka, Nobuaki; Zou, Chris B.

2017-12-01

Mapping the spatiotemporal patterns of soil moisture within heterogeneous landscapes is important for resource management and for the understanding of hydrological processes. A critical challenge in this mapping is comparing remotely sensed or in situ observations from areas with different vegetation cover but subject to the same precipitation regime. We address this challenge by wavelet analysis of multiyear observations of soil moisture profiles from adjacent areas with contrasting plant functional types (grassland, woodland, and encroached) and precipitation. The analysis reveals the differing soil moisture patterns and dynamics between plant functional types. The coherence at high-frequency periodicities between precipitation and soil moisture generally decreases with depth but this is much more pronounced under woodland compared to grassland. Wavelet analysis provides new insights on soil moisture dynamics across plant functional types and is useful for assessing differences and similarities in landscapes with heterogeneous vegetation cover.

Uncertainty Analysis via Failure Domain Characterization: Unrestricted Requirement Functions

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2011-01-01

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. The methods developed herein, which are based on nonlinear constrained optimization, are applicable to requirement functions whose functional dependency on the uncertainty is arbitrary and whose explicit form may even be unknown. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the assumed uncertainty model (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

Epidemiology of pediatric functional abdominal pain disorders: a meta-analysis.

PubMed

Korterink, Judith J; Diederen, Kay; Benninga, Marc A; Tabbers, Merit M

2015-01-01

We aimed to review the literature regarding epidemiology of functional abdominal pain disorders in children and to assess its geographic, gender and age distribution including associated risk factors of developing functional abdominal pain. The Cochrane Library, MEDLINE, EMBASE, CINAHL and PsychInfo databases were systematically searched up to February 2014. Study selection criteria included: (1) studies of birth cohort, school based or general population samples (2) containing data concerning epidemiology, prevalence or incidence (3) of children aged 4-18 years (4) suffering from functional abdominal pain. Quality of studies was rated by a self-made assessment tool. A random-effect meta-analysis model was used to estimate the prevalence of functional abdominal pain in childhood. A total of 58 articles, including 196,472 children were included. Worldwide pooled prevalence for functional abdominal pain disorders was 13.5% (95% CI 11.8-15.3), of which irritable bowel syndrome was reported most frequently (8.8%, 95% CI 6.2-11.9). The prevalence across studies ranged widely from 1.6% to 41.2%. Higher pooled prevalence rates were reported in South America (16.8%) and Asia (16.5%) compared to Europe (10.5%). And a higher pooled prevalence was reported when using the Rome III criteria (16.4%, 95% CI 13.5-19.4). Functional abdominal pain disorders are shown to occur significantly more in girls (15.9% vs. 11.5%, pooled OR 1.5) and is associated with the presence of anxiety and depressive disorders, stress and traumatic life events. Functional abdominal pain disorders are a common problem worldwide with irritable bowel syndrome as most encountered abdominal pain-related functional gastrointestinal disorder. Female gender, psychological disorders, stress and traumatic life events affect prevalence.