Some methods to regulate low-bias negative differential resistance in σ barrier separating nanoscale molecular transport systems

NASA Astrophysics Data System (ADS)

Shen, Ji-Mei; Liu, Jing; Min, Yi; Zhou, Li-Ping

2016-12-01

Using the first-principles method which combines the nonequilibrium Green’s function (NEGF) with density functional theory (DFT), the role of defect, dopant, barrier length and geometric deformation for low-bias negative differential resistance (NDR) in two capped armchair carbon nanotubes (CNTs) sandwiching σ barrier are systematically analyzed. We found that this method can regulate the negative differential resistance (NDR) effects such as current peak and peak position. The adjusting mechanism may originate from orbital interaction and orbital reconstruction. Our calculations try to manipulate the transport characteristics in energy space by simply manipulating the structure in real space, which may promise the potential applications in nanomolecular-electronics in the future.

Modeling the Charge Transport in Graphene Nano Ribbon Interfaces for Nano Scale Electronic Devices

NASA Astrophysics Data System (ADS)

Kumar, Ravinder; Engles, Derick

2015-05-01

In this research work we have modeled, simulated and compared the electronic charge transport for Metal-Semiconductor-Metal interfaces of Graphene Nano Ribbons (GNR) with different geometries using First-Principle calculations and Non-Equilibrium Green's Function (NEGF) method. We modeled junctions of Armchair GNR strip sandwiched between two Zigzag strips with (Z-A-Z) and Zigzag GNR strip sandwiched between two Armchair strips with (A-Z-A) using semi-empirical Extended Huckle Theory (EHT) within the framework of Non-Equilibrium Green Function (NEGF). I-V characteristics of the interfaces were visualized for various transport parameters. The distinct changes in conductance and I-V curves reported as the Width across layers, Channel length (Central part) was varied at different bias voltages from -1V to 1 V with steps of 0.25 V. From the simulated results we observed that the conductance through A-Z-A graphene junction is in the range of 10-13 Siemens whereas the conductance through Z-A-Z graphene junction is in the range of 10-5 Siemens. These suggested conductance controlled mechanisms for the charge transport in the graphene interfaces with different geometries is important for the design of graphene based nano scale electronic devices like Graphene FETs, Sensors.

Comparative analysis of quantum cascade laser modeling based on density matrices and non-equilibrium Green's functions

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

Lindskog, M., E-mail: martin.lindskog@teorfys.lu.se; Wacker, A.; Wolf, J. M.

2014-09-08

We study the operation of an 8.5 μm quantum cascade laser based on GaInAs/AlInAs lattice matched to InP using three different simulation models based on density matrix (DM) and non-equilibrium Green's function (NEGF) formulations. The latter advanced scheme serves as a validation for the simpler DM schemes and, at the same time, provides additional insight, such as the temperatures of the sub-band carrier distributions. We find that for the particular quantum cascade laser studied here, the behavior is well described by simple quantum mechanical estimates based on Fermi's golden rule. As a consequence, the DM model, which includes second order currents,more » agrees well with the NEGF results. Both these simulations are in accordance with previously reported data and a second regrown device.« less

Compliant energy and momentum conservation in NEGF simulation of electron-phonon scattering in semiconductor nano-wire transistors

NASA Astrophysics Data System (ADS)

Barker, J. R.; Martinez, A.; Aldegunde, M.

2012-05-01

The modelling of spatially inhomogeneous silicon nanowire field-effect transistors has benefited from powerful simulation tools built around the Keldysh formulation of non-equilibrium Green function (NEGF) theory. The methodology is highly efficient for situations where the self-energies are diagonal (local) in space coordinates. It has thus been common practice to adopt diagonality (locality) approximations. We demonstrate here that the scattering kernel that controls the self-energies for electron-phonon interactions is generally non-local on the scale of at least a few lattice spacings (and thus within the spatial scale of features in extreme nano-transistors) and for polar optical phonon-electron interactions may be very much longer. It is shown that the diagonality approximation strongly under-estimates the scattering rates for scattering on polar optical phonons. This is an unexpected problem in silicon devices but occurs due to strong polar SO phonon-electron interactions extending into a narrow silicon channel surrounded by high kappa dielectric in wrap-round gate devices. Since dissipative inelastic scattering is already a serious problem for highly confined devices it is concluded that new algorithms need to be forthcoming to provide appropriate and efficient NEGF tools.

Effect of boundary treatments on quantum transport current in the Green's function and Wigner distribution methods for a nano-scale DG-MOSFET

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

Jiang Haiyan; Department of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC 28223-0001; Cai Wei

2010-06-20

In this paper, we conduct a study of quantum transport models for a two-dimensional nano-size double gate (DG) MOSFET using two approaches: non-equilibrium Green's function (NEGF) and Wigner distribution. Both methods are implemented in the framework of the mode space methodology where the electron confinements below the gates are pre-calculated to produce subbands along the vertical direction of the device while the transport along the horizontal channel direction is described by either approach. Each approach handles the open quantum system along the transport direction in a different manner. The NEGF treats the open boundaries with boundary self-energy defined by amore » Dirichlet to Neumann mapping, which ensures non-reflection at the device boundaries for electron waves leaving the quantum device active region. On the other hand, the Wigner equation method imposes an inflow boundary treatment for the Wigner distribution, which in contrast ensures non-reflection at the boundaries for free electron waves entering the device active region. In both cases the space-charge effect is accounted for by a self-consistent coupling with a Poisson equation. Our goals are to study how the device boundaries are treated in both transport models affects the current calculations, and to investigate the performance of both approaches in modeling the DG-MOSFET. Numerical results show mostly consistent quantum transport characteristics of the DG-MOSFET using both methods, though with higher transport current for the Wigner equation method, and also provide the current-voltage (I-V) curve dependence on various physical parameters such as the gate voltage and the oxide thickness.« less

DFT investigation on the adsorption behavior of dimethyl and trimethyl amine molecules on borophene nanotube

NASA Astrophysics Data System (ADS)

Bhuvaneswari, R.; Chandiramouli, R.

2018-06-01

The electronic properties of borophene nanotube (BNT) are witnessed and the adsorption properties of dimethyl amine (DMA) and trimethyl amine (TMA) molecules on borophene nanotube are explored through non-equilibrium Green's function (NEGF) and density functional theory (DFT) method. The device density of states spectrum interprets the change in peak maxima, thus indicating the electron transition between DMA, TMA molecules and BNT base material. I-V characteristics strengthen the adsorption property of DMA and TMA on BNT by pointing out the variation in the current. The present work assures that borophene nanotube (BNT) can be employed as DMA and TMA sensor.

Doping Effect of Graphene Nanoplatelets on Electrical Insulation Properties of Polyethylene: From Macroscopic to Molecular Scale

PubMed Central

Jing, Ziang; Li, Changming; Zhao, Hong; Zhang, Guiling; Han, Baozhong

2016-01-01

The doping effect of graphene nanoplatelets (GNPs) on electrical insulation properties of polyethylene (PE) was studied by combining experimental and theoretical methods. The electric conduction properties and trap characteristics were tested for pure PE and PE/GNPs composites by using a direct measurement method and a thermal stimulated current (TSC) method. It was found that doping smaller GNPs is more beneficial to decrease the conductivity of PE/GNPs. The PE/GNPs composite with smaller size GNPs mainly introduces deep energy traps, while with increasing GNPs size, besides deep energy traps, shallow energy traps are also introduced. These results were also confirmed by density functional theory (DFT) and the non-equilibrium Green’s function (NEGF) method calculations. Therefore, doping small size GNPs is favorable for trapping charge carriers and enhancing insulation ability, which is suggested as an effective strategy in exploring powerful insulation materials. PMID:28773802

Few-particle quantum dynamics-comparing nonequilibrium Green functions with the generalized Kadanoff-Baym ansatz to density operator theory

NASA Astrophysics Data System (ADS)

Hermanns, S.; Balzer, K.; Bonitz, M.

2013-03-01

The nonequilibrium description of quantum systems requires, for more than two or three particles, the use of a reduced description to be numerically tractable. Two possible approaches are based on either reduced density matrices or nonequilibrium Green functions (NEGF). Both concepts are formulated in terms of hierarchies of coupled equations—the Bogoliubov-Born-Green-Kirkwood-Yvon (BBGKY) hierarchy for the reduced density operators and the Martin-Schwinger-hierarchy (MS) for the Green functions, respectively. In both cases, similar approximations are introduced to decouple the hierarchy, yet still many questions regarding the correspondence of both approaches remain open. Here we analyze this correspondence by studying the generalized Kadanoff-Baym ansatz (GKBA) that reduces the NEGF to a single-time theory. Starting from the BBGKY-hierarchy we present the approximations that are necessary to recover the GKBA result both, with Hartree-Fock propagators (HF-GKBA) and propagators in second Born approximation. To test the quality of the HF-GKBA, we study the dynamics of a 4-electron Hubbard nanocluster starting from a strong nonequilibrium initial state and compare to exact results and the Wang-Cassing approximation to the BBGKY hierarchy presented recently by Akbari et al. [1].

When can time-dependent currents be reproduced by the Landauer steady-state approximation?

NASA Astrophysics Data System (ADS)

Carey, Rachel; Chen, Liping; Gu, Bing; Franco, Ignacio

2017-05-01

We establish well-defined limits in which the time-dependent electronic currents across a molecular junction subject to a fluctuating environment can be quantitatively captured via the Landauer steady-state approximation. For this, we calculate the exact time-dependent non-equilibrium Green's function (TD-NEGF) current along a model two-site molecular junction, in which the site energies are subject to correlated noise, and contrast it with that obtained from the Landauer approach. The ability of the steady-state approximation to capture the TD-NEGF behavior at each instant of time is quantified via the same-time correlation function of the currents obtained from the two methods, while their global agreement is quantified by examining differences in the average currents. The Landauer steady-state approach is found to be a useful approximation when (i) the fluctuations do not disrupt the degree of delocalization of the molecular eigenstates responsible for transport and (ii) the characteristic time for charge exchange between the molecule and leads is fast with respect to the molecular correlation time. For resonant transport, when these conditions are satisfied, the Landauer approach is found to accurately describe the current, both on average and at each instant of time. For non-resonant transport, we find that while the steady-state approach fails to capture the time-dependent transport at each instant of time, it still provides a good approximation to the average currents. These criteria can be employed to adopt effective modeling strategies for transport through molecular junctions in interaction with a fluctuating environment, as is necessary to describe experiments.

The spin-dependent electronic transport properties of M(dcdmp)2 (M = Cu, Au, Co, Ni) molecular devices based on zigzag graphene nanoribbon electrodes

NASA Astrophysics Data System (ADS)

Li, Dongde; Wu, Di; Zhang, Xiaojiao; Zeng, Bowen; Li, Mingjun; Duan, Haiming; Yang, Bingchu; Long, Mengqiu

2018-05-01

The spin-dependent electronic transport properties of M(dcdmp)2 (M = Cu, Au, Co, Ni; dcdmp = 2,3-dicyano-5,6-dimercaptopyrazyne) molecular devices based on zigzag graphene nanoribbon (ZGNR) electrodes were investigated by density functional theory combined nonequilibrium Green's function method (DFT-NEGF). Our results show that the spin-dependent transport properties of the M(dcdmp)2 molecular devices can be controlled by the spin configurations of the ZGNR electrodes, and the central 3d-transition metal atom can introduce a larger magnetism than that of the nonferrous metal one. Moreover, the perfect spin filtering effect, negative differential resistance, rectifying effect and magnetic resistance phenomena can be observed in our proposed M(dcdmp)2 molecular devices.

Numerical simulations of quantum devices

NASA Astrophysics Data System (ADS)

Sandu, Titus

This work has been motivated by the tremendous effort toward the next generation of electron devices that will replace the present CMOS (Complementary Metal Oxide Semiconductor). Non-equilibrium Green's function formalism (NEGF) and empirical tight-binding (ETB) methods have been utilized in this dissertation. We studied the transport properties of Si/SiO2 resonant tunneling diodes (RTDs) by employing NEGF. We analyzed the physics of electron transport in Si/SiO2 RTDs and provided some guidelines for the fabrication of such devices by considering the effect of interface roughness scattering. Atomic scale roughness is shown to be acceptable. As the island size of the roughness increases, the peak-to-valley ratio degrades to less than 5 for 1 nm roughness and less than 2 for 2 nm roughness. By the ETB method we calculated electronic and optical properties of the relatively new Si/BeSe0.41Te0.59 system, more precisely Si/BeSe0.41Te0.59 [001] superlattices (SLs). Two interface bands were found in the band gap of bulk silicon. They were related to the polar Si/BeSe0.41Te0.59 interface. In addition, numerical calculations showed that the optical gap is close to the fundamental gap of bulk Si and the transitions are optically allowed. Two more aspects have been studied with NEGF: intrinsic bistability and off-zone center current flow of electrons in the RTD. We showed that broadening of the quasi-bound state in the emitter by scattering reduces intrinsic bistability. So far in different theoretical papers dealing with intrinsic bistability, only the scattering in the well has been considered. Finally, we demonstrated that scattering induces off-zone center current flow of electrons in RTDs. In RTDs electrons usually have a zone-center current flow. This is due to the coherent transport for which Tsu-Esaki formula is valid. On the contrary, holes have off-zone-center current flow. We show that, generally, carrier current flow is off-center, which means that the hole behavior is extended to electrons and is related to the breakdown of the Tsu-Esaki formula. Oblique flow is due to incoherent scattering represented by interface roughness and acoustic phonons. This is a quite new result and has been recently seen experimentally for hole transport.

Tunable nano Peltier cooling device from geometric effects using a single graphene nanoribbon

NASA Astrophysics Data System (ADS)

Li, Wan-Ju; Yao, Dao-Xin; Carlson, E. W.

2014-08-01

Based on the phenomenon of curvature-induced doping in graphene we propose a class of Peltier cooling devices, produced by geometrical effects, without gating. We show how a graphene nanoribbon laid on an array of curved nano cylinders can be used to create a targeted and tunable cooling device. Using two different approaches, the Nonequilibrium Green's Function (NEGF) method and experimental inputs, we predict that the cooling power of such a device can approach the order of kW/cm2, on par with the best known techniques using standard superlattice structures. The structure proposed here helps pave the way toward designing graphene electronics which use geometry rather than gating to control devices.

A theoretical study for electronic and transport properties of covalent functionalized MoS2 monolayer

NASA Astrophysics Data System (ADS)

Gao, Lijuan; Yang, Zhao-Di; Zhang, Guiling

2017-06-01

The geometries, electronic and electron transport properties of a series of functionalized MoS2 monolayers were investigated using density-functional theory (DFT) and the non-equilibrium Green's function (NEGF) methods. n-Propyl, n-trisilicyl, phenyl, p-nitrophenyl and p-methoxyphenyl are chosen as electron-donating groups. The results show covalent functionalization with electron-donating groups could make a transformation from typical semiconducting to metallic properties for appearance of midgap level across the Fermi level (Ef). The calculations of transport properties for two-probe devices indicate that conductivities of functionalized systems are obviously enhanced relative to pristine MoS2 monolayer. Grafted groups contribute to the major transport path and play an important role in enhancing conductivity. The NDR effect is found. The influence of grafted density is also studied. Larger grafted density leads to wider bandwidth of midgap level, larger current response of I-V curves and larger current difference between peak and valley.

Computational modeling and analysis of thermoelectric properties of nanoporous silicon

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

Li, H.; Yu, Y.; Li, G., E-mail: gli@clemson.edu

2014-03-28

In this paper, thermoelectric properties of nanoporous silicon are modeled and studied by using a computational approach. The computational approach combines a quantum non-equilibrium Green's function (NEGF) coupled with the Poisson equation for electrical transport analysis, a phonon Boltzmann transport equation (BTE) for phonon thermal transport analysis and the Wiedemann-Franz law for calculating the electronic thermal conductivity. By solving the NEGF/Poisson equations self-consistently using a finite difference method, the electrical conductivity σ and Seebeck coefficient S of the material are numerically computed. The BTE is solved by using a finite volume method to obtain the phonon thermal conductivity k{sub p}more » and the Wiedemann-Franz law is used to obtain the electronic thermal conductivity k{sub e}. The figure of merit of nanoporous silicon is calculated by ZT=S{sup 2}σT/(k{sub p}+k{sub e}). The effects of doping density, porosity, temperature, and nanopore size on thermoelectric properties of nanoporous silicon are investigated. It is confirmed that nanoporous silicon has significantly higher thermoelectric energy conversion efficiency than its nonporous counterpart. Specifically, this study shows that, with a n-type doping density of 10{sup 20} cm{sup –3}, a porosity of 36% and nanopore size of 3 nm × 3 nm, the figure of merit ZT can reach 0.32 at 600 K. The results also show that the degradation of electrical conductivity of nanoporous Si due to the inclusion of nanopores is compensated by the large reduction in the phonon thermal conductivity and increase of absolute value of the Seebeck coefficient, resulting in a significantly improved ZT.« less

Partially coherent electron transport in terahertz quantum cascade lasers based on a Markovian master equation for the density matrix

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

Jonasson, O.; Karimi, F.; Knezevic, I.

2016-08-01

We derive a Markovian master equation for the single-electron density matrix, applicable to quantum cascade lasers (QCLs). The equation conserves the positivity of the density matrix, includes off-diagonal elements (coherences) as well as in-plane dynamics, and accounts for electron scattering with phonons and impurities. We use the model to simulate a terahertz-frequency QCL, and compare the results with both experiment and simulation via nonequilibrium Green's functions (NEGF). We obtain very good agreement with both experiment and NEGF when the QCL is biased for optimal lasing. For the considered device, we show that the magnitude of coherences can be a significantmore » fraction of the diagonal matrix elements, which demonstrates their importance when describing THz QCLs. We show that the in-plane energy distribution can deviate far from a heated Maxwellian distribution, which suggests that the assumption of thermalized subbands in simplified density-matrix models is inadequate. As a result, we also show that the current density and subband occupations relax towards their steady-state values on very different time scales.« less

Interplay of relativistic and nonrelativistic transport in atomically precise segmented graphene nanoribbons

DOE PAGES

Yannouleas, Constantine; Romanovsky, Igor; Landman, Uzi

2015-01-20

Graphene's isolation launched explorations of fundamental relativistic physics originating from the planar honeycomb lattice arrangement of the carbon atoms, and of potential technological applications in nanoscale electronics. Bottom-up fabricated atomically-precise segmented graphene nanoribbons, SGNRs, open avenues for studies of electrical transport, coherence, and interference effects in metallic, semiconducting, and mixed GNRs, with different edge terminations. Conceptual and practical understanding of electric transport through SGNRs is gained through nonequilibrium Green's function (NEGF) conductance calculations and a Dirac continuum model that absorbs the valence-to-conductance energy gaps as position-dependent masses, including topological-in-origin mass-barriers at the contacts between segments. The continuum model reproduces themore » NEGF results, including optical Dirac Fabry-Pérot (FP) equidistant oscillations for massless relativistic carriers in metallic armchair SGNRs, and an unequally-spaced FP pattern for mixed armchair-zigzag SGNRs where carriers transit from a relativistic (armchair) to a nonrelativistic (zigzag) regime. This provides a unifying framework for analysis of coherent transport phenomena and interpretation of forthcoming experiments in SGNRs.« less

Spin transport in oxygen adsorbed graphene nanoribbon

NASA Astrophysics Data System (ADS)

Kumar, Vipin

2018-04-01

The spin transport properties of pristine graphene nanoribbons (GNRs) have been most widely studied using theoretical and experimental tools. The possibilities of oxidation of fabricated graphene based nano electronic devices may change the device characteristics, which motivates to further explore the properties of graphene oxide nanoribbons (GONRs). Therefore, we present a systematic computational study on the spin polarized transport in surface oxidized GNR in antiferromagnetic (AFM) spin configuration using density functional theory combined with non-equilibrium Green's function (NEGF) method. It is found that the conductance in oxidized GNRs is significantly suppressed in the valance band and the conduction band. A further reduction in the conductance profile is seen in presence of two oxygen atoms on the ribbon plane. This change in the conductance may be attributed to change in the surface topology of the ribbon basal plane due to presence of the oxygen adatoms, where the charge transfer take place between the ribbon basal plane and the oxygen atoms.

Field effect transistors based on phosphorene nanoribbon with selective edge-adsorption: A first-principles study

NASA Astrophysics Data System (ADS)

Hu, Mengli; Yang, Zhixiong; Zhou, Wenzhe; Li, Aolin; Pan, Jiangling; Ouyang, Fangping

2018-04-01

By using density functional theory (DFT) and nonequilibrium Green's function (NEGF), field effect transistor (FET) based on zigzag shaped phosphorene nanoribbons (ZPNR) are investigated. The FETs are constructed with bare-edged ZPNRs as electrodes and H, Cl or OH adsorbed ZPNRs as channel. It is found FETs with the three kinds of channel show similar transport properties. The FET is p-type with a maximum current on/off ratio of 104 and a minimum off-current of 1 nA. The working mode of FETs is dependent on the parity of channel length. It can be either enhancement mode or depletion mode and the off-state current shows an even-odd oscillation. The current oscillations are interpreted with density of states (DOS) analysis and methods of evolution operator and tight-binding Hamiltonian. Operating mechanism of the designed FETs is also presented with projected local density of states and band diagrams.

Electron transport in polycyclic aromatic hydrocarbons/boron nitride hybrid structures: density functional theory combined with the nonequilibrium Green's function.

PubMed

Panahi, S F K S; Namiranian, Afshin; Soleimani, Maryam; Jamaati, Maryam

2018-02-07

We investigate the electronic transport properties of two types of junction based on single polyaromatic hydrocarbons (PAHs) and PAHs embedded in boron nitride (h-BN) nanoribbons, using nonequilibrium Green's functions (NEGF) and density functional theory (DFT). In the PAH junctions, a Fano resonance line shape at the Fermi energy in the transport feature can be clearly seen. In hybrid junctions, structural asymmetries enable interactions between the electronic states, leading to observation of interface-based transport. Our findings reveal that the interface of PAH/h-BN strongly affects the transport properties of the structures.

Application of a self-consistent NEGF procedure to study the coherent transport with phase breaking scattering in low dimensional systems

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

Pratap, Surender, E-mail: surender.pratap@pilani.bits-pilani.ac.in; Sarkar, Niladri, E-mail: niladri@pilani.bits-pilani.ac.in

2016-04-13

We have studied Quantum Transport with dephasing in Low Dimensional systems. Here, we apply a self-consistent NEGF procedure to study the transport mechanism in low-dimensional systems with phase breaking scatterers. Under this we have determined the transmission coefficient of a very small Multi-Moded Nanowire which is under a small bias potential of few meV. We have calculated the transmission of this device first with no scatterers. Then we have introduced scatterers in the device and calculated the transmission for the device.

Performance of Topological Insulator Interconnects

NASA Astrophysics Data System (ADS)

Philip, Timothy M.; Hirsbrunner, Mark R.; Park, Moon Jip; Gilbert, Matthew J.

2017-01-01

The poor performance of copper interconnects at the nanometer scale calls for new material solutions for continued scaling of integrated circuits. We propose the use of three dimensional time-reversal-invariant topological insulators (TIs), which host backscattering-protected surface states, for this purpose. Using semiclassical methods, we demonstrate that nanoscale TI interconnects have a resistance 1-3 orders of magnitude lower than copper interconnects and graphene nanoribbons at the nanometer scale. We use the nonequilibrium Green function (NEGF) formalism to measure the change in conductance of nanoscale TI and metal interconnects caused by the presence of impurity disorder. We show that metal interconnects suffer a resistance increase, relative to the clean limit, in excess of 500% due to disorder while the TI's surface states increase less than 35% in the same regime.

Shuttlecock-Shaped Molecular Rectifier: Asymmetric Electron Transport Coupled with Controlled Molecular Motion.

PubMed

Ryu, Taekhee; Lansac, Yves; Jang, Yun Hee

2017-07-12

A fullerene derivative with five hydroxyphenyl groups attached around a pentagon, (4-HOC 6 H 4 ) 5 HC 60 (1), has shown an asymmetric current-voltage (I-V) curve in a conducting atomic force microscopy experiment on gold. Such molecular rectification has been ascribed to the asymmetric distribution of frontier molecular orbitals over its shuttlecock-shaped structure. Our nonequilibrium Green's function (NEGF) calculations based on density functional theory (DFT) indeed exhibit an asymmetric I-V curve for 1 standing up between two Au(111) electrodes, but the resulting rectification ratio (RR ∼ 3) is insufficient to explain the wide range of RR observed in experiments performed under a high bias voltage. Therefore, we formulate a hypothesis that high RR (>10) may come from molecular orientation switching induced by a strong electric field applied between two electrodes. Indeed, molecular dynamics simulations of a self-assembled monolayer of 1 on Au(111) show that the orientation of 1 can be switched between standing-up and lying-on-the-side configurations in a manner to align its molecular dipole moment with the direction of the applied electric field. The DFT-NEGF calculations taking into account such field-induced reorientation between up and side configurations indeed yield RR of ∼13, which agrees well with the experimental value obtained under a high bias voltage.

Flexural resonance mechanism of thermal transport across graphene-SiO2 interfaces

NASA Astrophysics Data System (ADS)

Ong, Zhun-Yong; Qiu, Bo; Xu, Shanglong; Ruan, Xiulin; Pop, Eric

2018-03-01

Understanding the microscopic mechanism of heat dissipation at the dimensionally mismatched interface between a two-dimensional (2D) crystal and its substrate is crucial for the thermal management of devices based on 2D materials. Here, we study the lattice contribution to thermal (Kapitza) transport at graphene-SiO2 interfaces using molecular dynamics (MD) simulations and non-equilibrium Green's functions (NEGF). We find that 78 percent of the Kapitza conductance is due to sub-20 THz flexural acoustic modes, and that a resonance mechanism dominates the interfacial phonon transport. MD and NEGF estimate the classical Kapitza conductance to be hK ≈ 10 to 16 MW K-1 m-2 at 300 K, respectively, consistent with existing experimental observations. Taking into account quantum mechanical corrections, this value is approximately 28% lower at 300 K. Our calculations also suggest that hK scales as T2 at low temperatures (T < 100 K) due to the linear frequency dependence of phonon transmission across the graphene-SiO2 interface at low frequencies. Our study sheds light on the role of flexural acoustic phonons in heat dissipation from graphene to its substrate.

High-Temperature Spintronic Devices and Circuits in Absence of Magnetic Field

DTIC Science & Technology

2012-04-23

non-equilibrium Green’s function (NEGF) formalism. • Molecular beam epitaxy (MBE) growth of ferromagnetic metals (Fe, MnAs) and...measured for two diode injection currents in the Faraday geometry. The quantum dot microcavity device was grown by molecular beam epitaxy with a low...channel (10 nm, lxlOl9j Mn-doped) / undoped-AlAs (1 nm) tunnel barrier / undoped-GaAs (0.5 nm) / MnAs (25 nm) were grown by molecular beam epitaxy (MBE

Organic field effect transistor composed by fullerene C60 and heterojunctions

NASA Astrophysics Data System (ADS)

Vasconcelos, Railson C.; Aleixo, Vicente F. P.; Del Nero, Jordan

2017-02-01

We present a study of the complex electronic behavior of a fullerene (C60) molecule attached to six leads (heterojunctions), which works as a three-dimension rectifier. In addition, we confirmed that the fullerene works not only as an electron donor, but also as barrier and transport channel to electrons through the molecule. Moreover, when the phenylpropanodinilla (PPP) lead is orthogonally subjected to bias voltage, the charge distribution and the current displays regions of saturation and resonance similar to semiconductor devices. In order to understand the electronic transport in the molecule, we applied non-equilibrium green function (NEGF) method and performed Fowler-Nordheim (FN) and Millikan-Lauritsen (ML) analyses. The ML curves proved to be sufficient to describe the FN characteristics. In this work, we report the theoretical design for electronic transport of a 3D device (6-terminal).

First principles molecular dynamics of metal/water interfaces under bias potential

NASA Astrophysics Data System (ADS)

Pedroza, Luana; Brandimarte, Pedro; Rocha, Alexandre; Fernandez-Serra, Marivi

2014-03-01

Understanding the interaction of the water-metal system at an atomic level is extremely important in electrocatalysts for fuel cells, photocatalysis among other systems. The question of the interface energetics involves a detailed study of the nature of the interactions between water-water and water-substrate. A first principles description of all components of the system is the most appropriate methodology in order to advance understanding of electrochemically processes. In this work we describe, using first principles molecular dynamics simulations, the dynamics of a combined surface(Au and Pd)/water system both in the presence and absence of an external bias potential applied to the electrodes, as one would come across in electrochemistry. This is accomplished using a combination of density functional theory (DFT) and non-equilibrium Green's functions methods (NEGF), thus accounting for the fact that one is dealing with an out-of-equilibrium open system, with and without van der Waals interactions. DOE Early Career Award No. DE-SC0003871.

Physics and performances of III-V nanowire broken-gap heterojunction TFETs using an efficient tight-binding mode-space NEGF model enabling million-atom nanowire simulations.

PubMed

Afzalian, A; Vasen, T; Ramvall, P; Shen, T-M; Wu, J; Passlack, M

2018-06-27

We report the capability to simulate in a quantum-mechanical atomistic fashion record-large nanowire devices, featuring several hundred to millions of atoms and a diameter up to 18.2 nm. We have employed a tight-binding mode-space NEGF technique demonstrating by far the fastest (up to 10 000  ×  faster) but accurate (error  <  1%) atomistic simulations to date. Such technique and capability opens new avenues to explore and understand the physics of nanoscale and mesoscopic devices dominated by quantum effects. In particular, our method addresses in an unprecedented way the technologically-relevant case of band-to-band tunneling (BTBT) in III-V nanowire broken-gap heterojunction tunnel-FETs (HTFETs). We demonstrate an accurate match of simulated BTBT currents to experimental measurements in a 12 nm diameter InAs NW and in an InAs/GaSb Esaki tunneling diode. We apply our TB MS simulations and report the first in-depth atomistic study of the scaling potential of III-V GAA nanowire HTFETs including the effect of electron-phonon scattering and discrete dopant impurity band tails, quantifying the benefits of this technology for low-power low-voltage CMOS applications.

Physics and performances of III–V nanowire broken-gap heterojunction TFETs using an efficient tight-binding mode-space NEGF model enabling million-atom nanowire simulations

NASA Astrophysics Data System (ADS)

Afzalian, A.; Vasen, T.; Ramvall, P.; Shen, T.-M.; Wu, J.; Passlack, M.

2018-06-01

We report the capability to simulate in a quantum-mechanical atomistic fashion record-large nanowire devices, featuring several hundred to millions of atoms and a diameter up to 18.2 nm. We have employed a tight-binding mode-space NEGF technique demonstrating by far the fastest (up to 10 000  ×  faster) but accurate (error  <  1%) atomistic simulations to date. Such technique and capability opens new avenues to explore and understand the physics of nanoscale and mesoscopic devices dominated by quantum effects. In particular, our method addresses in an unprecedented way the technologically-relevant case of band-to-band tunneling (BTBT) in III–V nanowire broken-gap heterojunction tunnel-FETs (HTFETs). We demonstrate an accurate match of simulated BTBT currents to experimental measurements in a 12 nm diameter InAs NW and in an InAs/GaSb Esaki tunneling diode. We apply our TB MS simulations and report the first in-depth atomistic study of the scaling potential of III–V GAA nanowire HTFETs including the effect of electron–phonon scattering and discrete dopant impurity band tails, quantifying the benefits of this technology for low-power low-voltage CMOS applications.

Electron transport in doped fullerene molecular junctions

NASA Astrophysics Data System (ADS)

Kaur, Milanpreet; Sawhney, Ravinder Singh; Engles, Derick

The effect of doping on the electron transport of molecular junctions is analyzed in this paper. The doped fullerene molecules are stringed to two semi-infinite gold electrodes and analyzed at equilibrium and nonequilibrium conditions of these device configurations. The contemplation is done using nonequilibrium Green’s function (NEGF)-density functional theory (DFT) to evaluate its density of states (DOS), transmission coefficient, molecular orbitals, electron density, charge transfer, current, and conductance. We conclude from the elucidated results that Au-C16Li4-Au and Au-C16Ne4-Au devices behave as an ordinary p-n junction diode and a Zener diode, respectively. Moreover, these doped fullerene molecules do not lose their metallic nature when sandwiched between the pair of gold electrodes.

Electronic structure, transport, and collective effects in molecular layered systems.

PubMed

Hahn, Torsten; Ludwig, Tim; Timm, Carsten; Kortus, Jens

2017-01-01

The great potential of organic heterostructures for organic device applications is exemplified by the targeted engineering of the electronic properties of phthalocyanine-based systems. The transport properties of two different phthalocyanine systems, a pure copper phthalocyanine (CoPc) and a flourinated copper phthalocyanine-manganese phthalocyanine (F 16 CoPc/MnPc) heterostructure, are investigated by means of density functional theory (DFT) and the non-equilibrium Green's function (NEGF) approach. Furthermore, a master-equation-based approach is used to include electronic correlations beyond the mean-field-type approximation of DFT. We describe the essential theoretical tools to obtain the parameters needed for the master equation from DFT results. Finally, an interacting molecular monolayer is considered within a master-equation approach.

Dissipative NEGF methodology to treat short range Coulomb interaction: Current through a 1D nanostructure.

PubMed

Martinez, Antonio; Barker, John R; Di Prieto, Riccardo

2018-06-13

A methodology describing Coulomb blockade in the Non-equilibrium Green Function formalism is presented. We carried out ballistic and dissipative simulations through a 1D quantum dot using an Einstein phonon model. Inelastic phonons with different energies have been considered. The methodology incorporates the short-range Coulomb interaction between two electrons through the use of a two-particle Green's function. Unlike previous work, the quantum dot has spatial resolution i.e. it is not just parameterized by the energy level and coupling constants of the dot. Our method intends to describe the effect of electron localization while maintaining an open boundary or extended wave function. The formalism conserves the current through the nanostructure. A simple 1D model is used to explain the increase of mobility in semi-crystalline polymers as a function of the electron concentration. The mechanism suggested is based on the lifting of energy levels into the transmission window as a result of the local electron-electron repulsion inside a crystalline domain. The results are aligned with recent experimental findings. Finally, as a proof of concept, we present a simulation of a low temperature resonant structure showing the stability diagram in the Coulomb blockade regime. . © 2018 IOP Publishing Ltd.

Fano effect dominance over Coulomb blockade in transport properties of parallel coupled quantum dot system

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

Brogi, Bharat Bhushan, E-mail: brogi-221179@yahoo.in; Ahluwalia, P. K.; Chand, Shyam

2015-06-24

Theoretical study of the Coulomb blockade effect on transport properties (Transmission Probability and I-V characteristics) for varied configuration of coupled quantum dot system has been studied by using Non Equilibrium Green Function(NEGF) formalism and Equation of Motion(EOM) method in the presence of magnetic flux. The self consistent approach and intra-dot Coulomb interaction is being taken into account. As the key parameters of the coupled quantum dot system such as dot-lead coupling, inter-dot tunneling and magnetic flux threading through the system can be tuned, the effect of asymmetry parameter and magnetic flux on this tuning is being explored in Coulomb blockademore » regime. The presence of the Coulomb blockade due to on-dot Coulomb interaction decreases the width of transmission peak at energy level ε + U and by adjusting the magnetic flux the swapping effect in the Fano peaks in asymmetric and symmetric parallel configuration sustains despite strong Coulomb blockade effect.« less

Designing lateral spintronic devices with giant tunnel magnetoresistance and perfect spin injection efficiency based on transition metal dichalcogenides.

PubMed

Zhao, Pei; Li, Jianwei; Jin, Hao; Yu, Lin; Huang, Baibiao; Ying, Dai

2018-04-18

Giant tunnel magnetoresistance (TMR) and perfect spin-injection efficiency (SIE) are extremely significant for modern spintronic devices. Quantum transport properties in a two-dimensional (2D) VS2/MoS2/VS2 magnetic tunneling junction (MTJ) are investigated theoretically within the framework of density functional theory combining with the non-equilibrium Green's functions (DFT-NEGF) method. Our results indicate that the designed MTJ exhibits a TMR with a value up to 4 × 103, which can be used as a switch of spin-electron devices. And due to the huge barrier for spin-down transport, the spin-down electrons could hardly cross the central scattering region, thus achieving a perfect SIE. Furthermore, we also explore for the effect of bias voltage on the TMR and SIE. We find that the TMR increases with the increasing bias voltage, and the SIE is robust against either bias or gate voltage in MTJs, which can serve as effective spin filter devices. Our results can not only give fresh impetus to the research community to build MTJs but also provide potential materials for spintronic devices.

Bias-dependent local structure of water molecules at an electrochemical interface

NASA Astrophysics Data System (ADS)

Pedroza, Luana; Brandimarte, Pedro; Rocha, Alexandre R.; Fernandez-Serra, Marivi

2015-03-01

Following the need for new - and renewable - sources of energy worldwide, fuel cells using electrocatalysts can be thought of as a viable option. Understanding the local structure of water molecules at the interfaces of the metallic electrodes is a key problem. Notably the system is under an external potential bias, which makes the task of simulating this setup difficult. A first principle description of all components of the system is the most appropriate methodology in order to advance understanding of electrochemical processes. There, the metal is usually charged. To correctly compute the effect of an external bias potential applied to electrodes, we combine density functional theory (DFT) and non-equilibrium Green's functions methods (NEGF), with and without van der Waals interactions. In this work, we apply this methodology to study the electronic properties and forces of one water molecule and water monolayer at the interface of gold electrodes. We find that the water molecule has a different torque direction depending on the sign of the bias applied. We also show that it changes the position of the most stable configuration indicating that the external bias plays an important role in the structural properties of the interface. We acknowledge financial support from FAPESP.

Spin-dependent electronic transport properties of transition metal atoms doped α-armchair graphyne nanoribbons

NASA Astrophysics Data System (ADS)

Fotoohi, Somayeh; Haji-Nasiri, Saeed

2018-04-01

Spin-dependent electronic transport properties of single 3d transition metal (TM) atoms doped α-armchair graphyne nanoribbons (α-AGyNR) are investigated by non-equilibrium Green's function (NEGF) method combined with density functional theory (DFT). It is found that all of the impurity atoms considered in this study (Fe, Co, Ni) prefer to occupy the sp-hybridized C atom site in α-AGyNR, and the obtained structures remain planar. The results show that highly localized impurity states are appeared around the Fermi level which correspond to the 3d orbitals of TM atoms, as can be derived from the projected density of states (PDOS). Moreover, Fe, Co, and Ni doped α-AGyNRs exhibit magnetic properties due to the strong spin splitting property of the energy levels. Also for each case, the calculated current-voltage characteristic per super-cell shows that the spin degeneracy in the system is obviously broken and the current becomes strongly spin dependent. Furthermore, a high spin-filtering effect around 90% is found under the certain bias voltages in Ni doped α-AGyNR. Additionally, the structure with Ni impurity reveals transfer characteristic that is suitable for designing a spin current switch. Our findings provide a high possibility to design the next generation spin nanodevices with novel functionalities.

Random dopant fluctuations and statistical variability in n-channel junctionless FETs

NASA Astrophysics Data System (ADS)

Akhavan, N. D.; Umana-Membreno, G. A.; Gu, R.; Antoszewski, J.; Faraone, L.

2018-01-01

The influence of random dopant fluctuations on the statistical variability of the electrical characteristics of n-channel silicon junctionless nanowire transistor (JNT) has been studied using three dimensional quantum simulations based on the non-equilibrium Green’s function (NEGF) formalism. Average randomly distributed body doping densities of 2 × 1019, 6 × 1019 and 1 × 1020 cm-3 have been considered employing an atomistic model for JNTs with gate lengths of 5, 10 and 15 nm. We demonstrate that by properly adjusting the doping density in the JNT, a near ideal statistical variability and electrical performance can be achieved, which can pave the way for the continuation of scaling in silicon CMOS technology.

Stacking dependence of carrier transport properties in multilayered black phosphorous

NASA Astrophysics Data System (ADS)

Sengupta, A.; Audiffred, M.; Heine, T.; Niehaus, T. A.

2016-02-01

We present the effect of different stacking orders on carrier transport properties of multi-layer black phosphorous. We consider three different stacking orders AAA, ABA and ACA, with increasing number of layers (from 2 to 6 layers). We employ a hierarchical approach in density functional theory (DFT), with structural simulations performed with generalized gradient approximation (GGA) and the bandstructure, carrier effective masses and optical properties evaluated with the meta-generalized gradient approximation (MGGA). The carrier transmission in the various black phosphorous sheets was carried out with the non-equilibrium green’s function (NEGF) approach. The results show that ACA stacking has the highest electron and hole transmission probabilities. The results show tunability for a wide range of band-gaps, carrier effective masses and transmission with a great promise for lattice engineering (stacking order and layers) in black phosphorous.

Study of electron transport in the functionalized nanotubes and their impact on the electron transfer in the active site of horseradish peroxidase

NASA Astrophysics Data System (ADS)

Feizabadi, Mina; Ajloo, Davood; Soleymanpour, Ahmad; Faridnouri, Hassan

2018-05-01

Electrochemical characterization of functionalized carbon nanotubes (f-CNT) including carboxyl (CNT-COOH), amine (CNT-NH2) and hydroxyl (CNT-OH) functional groups were studied using differential pulse voltammetry (DPV). The current-voltage (I-V) curves were obtained from each system and the effect of f-CNT on redox interaction of horseradish peroxidase (HRP) immobilized on the electrode surface was investigated. The non-equilibrium Green's function (NEGF) combined with density functional theory (DFT) were used to study the transport properties of f-CNT. Additionally, the effect of the number of functional groups on transport properties of CNT, I-V characteristics, electronic transmission coefficients and spatial distribution of f-CNTs have been calculated and analyzed. The results showed that the carboxyl derivative has larger transmission coefficients and current value than other f-CNTs. Then, the effect of functional groups on the electron transport in heme group of HRP is discussed. Finally, the effect of a covalent bond between active site amino acids and amine functional group of CNT was investigated and discussed.

Nonlinear and Nonequilibrium Spin Injection in Magnetic Tunneling Junctions

NASA Astrophysics Data System (ADS)

Guo, Hong

2007-03-01

Quantitative analysis of charge and spin quantum transport in spintronic devices requires an atomistic first principles approach that can handle nonlinear and nonequilibrium transport conditions. We have developed an approach for this purpose based on real space density functional theory (DFT) carried out within the Keldysh nonequilibrium Green's function formalism (NEGF). We report theoretical analysis of nonlinear and nonequilibrium spin injection and quantum transport in Fe/MgO/Fe trilayer structures as a function of external bias voltage. Devices with well relaxed atomic structures and with FeO oxidization layers are investigated as a function of external bias voltage. We also report calculations of nonequilibrium spin injection into molecular layers and graphene. Comparisons to experimental data will be presented. Work in collaborations with: Derek Waldron, Vladimir Timochevski (McGill University); Ke Xia (Institute of Physics, Chinese Academy of Science, Beijing, China); Eric Zhu, Jian Wang (University of Hong Kong); Paul Haney, and Allan MacDonald (University of Texas at Austin).

Improving performance of armchair graphene nanoribbon field effect transistors via boron nitride doping

NASA Astrophysics Data System (ADS)

Goharrizi, A. Yazdanpanah; Sanaeepur, M.; Sharifi, M. J.

2015-09-01

Device performance of 10 nm length armchair graphene nanoribbon field effect transistors with 1.5 nm and 4 nm width (13 and 33 atoms in width respectively) are compared in terms of Ion /Ioff , trans-conductance, and sub-threshold swing. While narrow devices suffer from edge roughness wider devices are subject to more substrate surface roughness and reduced bandgap. Boron Nitride doping is employed to compensate reduced bandgap in wider devices. Simultaneous effects of edge and substrate surface roughness are considered. Results show that in the presence of both the edge and substrate surface roughness the 4 nm wide device with boron nitride doping shows improved performance with respect to the 1.5 nm one (both of which incorporate the same bandgap AGNR as channel material). Electronic simulations are performed via NEGF method along with tight-binding Hamiltonian. Edge and surface roughness are created by means of one and two dimensional auto correlation functions respectively. Electronic characteristics are averaged over a large number of devices due to statistic nature of both the edge and surface roughness.

Double gate graphene nanoribbon field effect transistor with single halo pocket in channel region

NASA Astrophysics Data System (ADS)

Naderi, Ali

2016-01-01

A new structure for graphene nanoribbon field-effect transistors (GNRFETs) is proposed and investigated using quantum simulation with a nonequilibrium Green's function (NEGF) method. Tunneling leakage current and ambipolar conduction are known effects for MOSFET-like GNRFETs. To minimize these issues a novel structure with a simple change of the GNRFETs by using single halo pocket in the intrinsic channel region, "Single Halo GNRFET (SH-GNRFET)", is proposed. An appropriate halo pocket at source side of channel is used to modify potential distribution of the gate region and weaken band to band tunneling (BTBT). In devices with materials like Si in channel region, doping type of halo and source/drain regions are different. But, here, due to the smaller bandgap of graphene, the mentioned doping types should be the same to reduce BTBT. Simulations have shown that in comparison with conventional GNRFET (C-GNRFET), an SH-GNRFET with appropriately halo doping results in a larger ON current (Ion), smaller OFF current (Ioff), a larger ON-OFF current ratio (Ion/Ioff), superior ambipolar characteristics, a reduced power-delay product and lower delay time.

Phonon transport in single-layer boron nanoribbons

NASA Astrophysics Data System (ADS)

Zhang, Zhongwei; Xie, Yuee; Peng, Qing; Chen, Yuanping

2016-11-01

Inspired by the successful synthesis of three two-dimensional (2D) allotropes, the boron sheet has recently been one of the hottest 2D materials around. However, to date, phonon transport properties of these new materials are still unknown. By using the non-equilibrium Green’s function (NEGF) combined with the first principles method, we study ballistic phonon transport in three types of boron sheets; two of them correspond to the structures reported in the experiments, while the third one is a stable structure that has not been synthesized yet. At room temperature, the highest thermal conductance of the boron nanoribbons is comparable with that of graphene, while the lowest thermal conductance is less than half of graphene’s. Compared with graphene, the three boron sheets exhibit diverse anisotropic transport characteristics. With an analysis of phonon dispersion, bonding charge density, and simplified models of atomic chains, the mechanisms of the diverse phonon properties are discussed. Moreover, we find that many hybrid patterns based on the boron allotropes can be constructed naturally without doping, adsorption, and defects. This provides abundant nanostructures for thermal management and thermoelectric applications.

Aspects of electron transport in zigzag graphene nanoribbons

NASA Astrophysics Data System (ADS)

Bhalla, Pankaj; Pratap, Surender

2018-05-01

In this paper, we investigate the aspects of electron transport in the zigzag graphene nanoribbons (ZGNRs) using the nonequilibrium Green’s function (NEGF) formalism. The latter is an esoteric tool in mesoscopic physics. It is used to perform an analysis of ZGNRs by considering potential well. Within this potential, the dependence of transmission coefficient, local density of states (LDOS) and electron transport properties on number of atoms per unit cell is discussed. It is observed that there is an increment in electron and thermal conductance with increasing number of atoms. In addition to these properties, the dependence of same is also studied in figure of merit. The results infer that the contribution of electrons to enhance the figure of merit is important above the crossover temperature.

A Klein-tunneling transistor with ballistic graphene

NASA Astrophysics Data System (ADS)

Wilmart, Quentin; Berrada, Salim; Torrin, David; Nguyen, V. Hung; Fève, Gwendal; Berroir, Jean-Marc; Dollfus, Philippe; Plaçais, Bernard

2014-06-01

Today, the availability of high mobility graphene up to room temperature makes ballistic transport in nanodevices achievable. In particular, p-n-p transistors in the ballistic regime give access to Klein tunneling physics and allow the realization of devices exploiting the optics-like behavior of Dirac Fermions (DFs) as in the Veselago lens or the Fabry-Pérot cavity. Here we propose a Klein tunneling transistor based on the geometrical optics of DFs. We consider the case of a prismatic active region delimited by a triangular gate, where total internal reflection may occur, which leads to the tunable suppression of transistor transmission. We calculate the transmission and the current by means of scattering theory and the finite bias properties using non-equilibrium Green's function (NEGF) simulation.

Atomically thin heterostructures based on single-layer tungsten diselenide and graphene.

PubMed

Lin, Yu-Chuan; Chang, Chih-Yuan S; Ghosh, Ram Krishna; Li, Jie; Zhu, Hui; Addou, Rafik; Diaconescu, Bogdan; Ohta, Taisuke; Peng, Xin; Lu, Ning; Kim, Moon J; Robinson, Jeremy T; Wallace, Robert M; Mayer, Theresa S; Datta, Suman; Li, Lain-Jong; Robinson, Joshua A

2014-12-10

Heterogeneous engineering of two-dimensional layered materials, including metallic graphene and semiconducting transition metal dichalcogenides, presents an exciting opportunity to produce highly tunable electronic and optoelectronic systems. In order to engineer pristine layers and their interfaces, epitaxial growth of such heterostructures is required. We report the direct growth of crystalline, monolayer tungsten diselenide (WSe2) on epitaxial graphene (EG) grown from silicon carbide. Raman spectroscopy, photoluminescence, and scanning tunneling microscopy confirm high-quality WSe2 monolayers, whereas transmission electron microscopy shows an atomically sharp interface, and low energy electron diffraction confirms near perfect orientation between WSe2 and EG. Vertical transport measurements across the WSe2/EG heterostructure provides evidence that an additional barrier to carrier transport beyond the expected WSe2/EG band offset exists due to the interlayer gap, which is supported by theoretical local density of states (LDOS) calculations using self-consistent density functional theory (DFT) and nonequilibrium Green's function (NEGF).

Electronic structure and transport properties of zigzag MoS2 nanoribbons

NASA Astrophysics Data System (ADS)

Sharma, Uma Shankar; Shah, Rashmi; Mishra, Pankaj Kumar

2018-05-01

In present study, electronic and transport properties of the 8zigzag MoS2 nanoribbons (8ZMoS2NRs) are investigated using ab-initio density functional theory [DFT]. The calculations were performed using nonequilibrium Green's function (NEGF) formalism based on DFT as implemented in the TranSiesta code. Results show that the defect can introduces few extra states into the energy gap, which lead nanoribbons to reveal a metallic characteristic. The voltage-current (VI) graph of 8ZMoS2NRs show a threshold current increases after introducing Mo defect in the devices. when introducing a Mo vacancy under low biases, the current will be suppressed—whereas under high biases, the current through the defected 8ZMoS2NRs will increases rapidly, due to the other channel being opened, that make possibility of 8ZMoS2NRs application in electronic devices such as voltage regulation.

Electron transport in NH3/NO2 sensed buckled antimonene

NASA Astrophysics Data System (ADS)

Srivastava, Anurag; Khan, Md. Shahzad; Ahuja, Rajeev

2018-04-01

The structural and electronic properties of buckled antimonene have been analysed using density functional theory based ab-initio approach. Geometrical parameters in terms of bond length and bond angle are found close to the single ruffle mono-layer of rhombohedral antimony. Inter-frontier orbital analyses suggest localization of lone pair electrons at each atomic centre. Phonon dispersion along with high symmetry point of Brillouin zone does not signify any soft mode. With an electronic band gap of 1.8eV, the quasi-2D nano-surface has been further explored for NH3/NO2 molecules sensing and qualities of interaction between NH3/NO2 gas and antimonene scrutinized in terms of electronic charges transfer. A current-voltage characteristic has also been analysed, using Non Equilibrium Green's function (NEGF), for antimonene, in presence of incoming NH3/NO2 molecules.

BN-C Hybrid Nanoribbons as Gas Sensors

NASA Astrophysics Data System (ADS)

Darvishi Gilan, Mahdi; Chegel, Raad

2018-02-01

The effects of carbon monoxide (CO) and ammonia (NH3) molecules adsorption on the various composites of boron nitride and graphene BN-C hybrid nanoribbons are investigated using the non-equilibrium Green's function (NEGF) technique based on density functional theory (DFT). The effects of adsorption with possible random configurations on the average of the density of states (DOS), transmission coefficient, and the current-voltage ( I- V) characteristics are calculated. The results indicate that, by embedding armchair graphene nanoribbon (AGNR) with boron nitride nanoribbon (BNNR), the various electronic properties can be observed after gas molecule adsorption. The electronic structure and gap of hybrids system is modified due to gas adsorption, and the systems act like the n-type semiconductor by NH3 molecule adsorption. The hybrid structures due to their tunable band gap are better candidates for gas detecting compared to the pristine BNNRs and AGNRs.

Anisotropic thermoelectric behavior in armchair and zigzag mono- and fewlayer MoS2 in thermoelectric generator applications

PubMed Central

Arab, Abbas; Li, Qiliang

2015-01-01

In this work, we have studied thermoelectric properties of monolayer and fewlayer MoS2 in both armchair and zigzag orientations. Density functional theory (DFT) using non-equilibrium Green’s function (NEGF) method has been implemented to calculate the transmission spectra of mono- and fewlayer MoS2 in armchair and zigzag directions. Phonon transmission spectra are calculated based on parameterization of Stillinger-Weber potential. Thermoelectric figure of merit, ZT, is calculated using these electronic and phonon transmission spectra. In general, a thermoelectric generator is composed of thermocouples made of both n-type and p-type legs. Based on our calculations, monolayer MoS2 in armchair orientation is found to have the highest ZT value for both p-type and n-type legs compared to all other armchair and zigzag structures. We have proposed a thermoelectric generator based on monolayer MoS2 in armchair orientation. Moreover, we have studied the effect of various dopant species on thermoelectric current of our proposed generator. Further, we have compared output current of our proposed generator with those of Silicon thin films. Results indicate that thermoelectric current of MoS2 armchair monolayer is several orders of magnitude higher than that of Silicon thin films. PMID:26333948

Anisotropic thermoelectric behavior in armchair and zigzag mono- and fewlayer MoS2 in thermoelectric generator applications.

PubMed

Arab, Abbas; Li, Qiliang

2015-09-03

In this work, we have studied thermoelectric properties of monolayer and fewlayer MoS2 in both armchair and zigzag orientations. Density functional theory (DFT) using non-equilibrium Green's function (NEGF) method has been implemented to calculate the transmission spectra of mono- and fewlayer MoS2 in armchair and zigzag directions. Phonon transmission spectra are calculated based on parameterization of Stillinger-Weber potential. Thermoelectric figure of merit, ZT, is calculated using these electronic and phonon transmission spectra. In general, a thermoelectric generator is composed of thermocouples made of both n-type and p-type legs. Based on our calculations, monolayer MoS2 in armchair orientation is found to have the highest ZT value for both p-type and n-type legs compared to all other armchair and zigzag structures. We have proposed a thermoelectric generator based on monolayer MoS2 in armchair orientation. Moreover, we have studied the effect of various dopant species on thermoelectric current of our proposed generator. Further, we have compared output current of our proposed generator with those of Silicon thin films. Results indicate that thermoelectric current of MoS2 armchair monolayer is several orders of magnitude higher than that of Silicon thin films.

Electronic and transport properties of Cobalt-based valence tautomeric molecules and polymers

NASA Astrophysics Data System (ADS)

Chen, Yifeng; Calzolari, Arrigo; Buongiorno Nardelli, Marco

2011-03-01

The advancement of molecular spintronics requires further understandings of the fundamental electronic structures and transport properties of prototypical spintronics molecules and polymers. Here we present a density functional based theoretical study of the electronic structures of Cobalt-based valence tautomeric molecules Co III (SQ)(Cat)L Co II (SQ)2 L and their polymers, where SQ refers to the semiquinone ligand, and Cat the catecholate ligand, while L is a redox innocent backbone ligand. The conversion from low-spin Co III ground state to high-spin Co II excited state is realized by imposing an on-site potential U on the Co atom and elongating the Co-N bond. Transport properties are subsequently calculated by extracting electronic Wannier functions from these systems and computing the charge transport in the ballistic regime using a Non-Equilibrium Green's Function (NEGF) approach. Our transport results show distinct charge transport properties between low-spin ground state and high-spin excited state, hence suggesting potential spintronics devices from these molecules and polymers such as spin valves.

Spin-orbit torque-driven magnetization switching in 2D-topological insulator heterostructure

NASA Astrophysics Data System (ADS)

Soleimani, Maryam; Jalili, Seifollah; Mahfouzi, Farzad; Kioussis, Nicholas

2017-02-01

Charge pumping and spin-orbit torque (SOT) are two reciprocal phenomena widely studied in ferromagnet (FM)/topological insulator (TI) heterostructures. However, the SOT and its corresponding switching phase diagram for a FM island in proximity to a two-dimensional topological insulator (2DTI) has not been explored yet. We have addressed these features, using the recently developed adiabatic expansion of time-dependent nonequilibrium Green's function (NEGF) in the presence of both precessing magnetization and bias voltage. We have calculated the angular and spatial dependence of different components of the SOT on the FM island. We determined the switching phase diagram of the FM for different orientations of the easy axis. The results can be used as a guideline for the future experiments on such systems.

A computational study of a novel graphene nanoribbon field effect transistor

NASA Astrophysics Data System (ADS)

Ghoreishi, Seyed Saleh; Yousefi, Reza

2017-04-01

In this paper, using gate structure engineering and modification of channel dopant profile, we propose a new double gate graphene nanoribbon field effect transistor (DG-GNRFET) mainly to suppress the band-to-band tunneling (BTBT) of carriers. In the new device, the intrinsic part of the channel is replaced by an intrinsic-lightly doped-intrinsic (I -N--I) configuration in a way that only the intrinsic parts are covered by the gate contact. Transport characteristics of the device are investigated theoretically using the nonequilibrium Green’s function (NEGF) formalism. Numerical simulations show that off-current, ambipolar behavior, on/off-current ratio and the switching characteristics such as intrinsic delay and power-delay product are improved. In addition, the new device demonstrates better sub-threshold swing and less drain-induced barrier lowering (DIBL).

Large-scale quantum transport calculations for electronic devices with over ten thousand atoms

NASA Astrophysics Data System (ADS)

Lu, Wenchang; Lu, Yan; Xiao, Zhongcan; Hodak, Miro; Briggs, Emil; Bernholc, Jerry

The non-equilibrium Green's function method (NEGF) has been implemented in our massively parallel DFT software, the real space multigrid (RMG) code suite. Our implementation employs multi-level parallelization strategies and fully utilizes both multi-core CPUs and GPU accelerators. Since the cost of the calculations increases dramatically with the number of orbitals, an optimal basis set is crucial for including a large number of atoms in the ``active device'' part of the simulations. In our implementation, the localized orbitals are separately optimized for each principal layer of the device region, in order to obtain an accurate and optimal basis set. As a large example, we calculated the transmission characteristics of a Si nanowire p-n junction. The nanowire is along (110) direction in order to minimize the number dangling bonds that are saturated by H atoms. Its diameter is 3 nm. The length of 24 nm is necessary because of the long-range screening length in Si. Our calculations clearly show the I-V characteristics of a diode, i.e., the current increases exponentially with forward bias and is near zero with backward bias. Other examples will also be presented, including three-terminal transistors and large sensor structures.

Study of transmission function and electronic transport in one dimensional silver nanowire: Ab-initio method using density functional theory (DFT)

NASA Astrophysics Data System (ADS)

Thakur, Anil; Kashyap, Rajinder

2018-05-01

Single nanowire electrode devices have their application in variety of fields which vary from information technology to solar energy. Silver nanowires, made in an aqueous chemical reduction process, can be reacted with gold salt to create bimetallic nanowires. Silver nanowire can be used as electrodes in batteries and have many other applications. In this paper we investigated structural and electronic transport properties of Ag nanowire using density functional theory (DFT) with SIESTA code. Electronic transport properties of Ag nanowire have been studied theoretically. First of all an optimized geometry for Ag nanowire is obtained using DFT calculations, and then the transport relations are obtained using NEGF approach. SIESTA and TranSIESTA simulation codes are used in the calculations respectively. The electrodes are chosen to be the same as the central region where transport is studied, eliminating current quantization effects due to contacts and focusing the electronic transport study to the intrinsic structure of the material. By varying chemical potential in the electrode regions, an I-V curve is traced which is in agreement with the predicted behavior. Bulk properties of Ag are in agreement with experimental values which make the study of electronic and transport properties in silver nanowires interesting because they are promising materials as bridging pieces in nanoelectronics. Transmission coefficient and V-I characteristic of Ag nano wire reveals that silver nanowire can be used as an electrode device.

Ballistic heat conduction and mass disorder in one dimension.

PubMed

Ong, Zhun-Yong; Zhang, Gang

2014-08-20

It is well-known that in the disordered harmonic chain, heat conduction is subballistic and the thermal conductivity (κ) scales asymptotically as lim(L--> ∞) κ ∝ L(0.5) where L is the chain length. However, using the nonequilibrium Green's function (NEGF) method and analytical modelling, we show that there exists a critical crossover length scale (LC) below which ballistic heat conduction (κ ∝ L) can coexist with mass disorder. This ballistic-to-subballistic heat conduction crossover is connected to the exponential attenuation of the phonon transmittance function Ξ i.e. Ξ(ω, L) = exp[-L/λ(ω)], where λ is the frequency-dependent attenuation length. The crossover length can be determined from the minimum attenuation length, which depends on the maximum transmitted frequency. We numerically determine the dependence of the transmittance on frequency and mass composition as well as derive a closed form estimate, which agrees closely with the numerical results. For the length-dependent thermal conductance, we also derive a closed form expression which agrees closely with numerical results and reproduces the ballistic to subballistic thermal conduction crossover. This allows us to characterize the crossover in terms of changes in the length, mass composition and temperature dependence, and also to determine the conditions under which heat conduction enters the ballistic regime. We describe how the mass composition can be modified to increase ballistic heat conduction.

Adsorption of NO2 molecules on armchair phosphorene nanosheet for nano sensor applications - A first-principles study.

PubMed

Nagarajan, V; Chandiramouli, R

2017-08-01

The electronic and NO 2 adsorption properties of hydrogenated armchair phosphorene nanosheet device is investigated through density functional theory (DFT) and non-equilibrium Green's function method (NEGF). The armchair phosphorene nanosheet is used for the detection of NO 2 gas in phosphorene molecular device. The DOS spectrum demonstrates the change in peak maxima due to transfer of electrons between NO 2 gas and phosphorene base material. The change in the peak amplitude is observed along the valance band as well as in the conduction band in the transmission spectrum of phosphorene device. I-V characteristics support the change in the current upon adsorption of NO 2 gas molecule on phosphorene molecular device. Using formation energy, structural stability of phosphorene nanosheet has been studied. The adsorption properties of NO 2 on phosphorene nanosheet have also been investigated with the help of adsorption energy, Mulliken charge and Bader charge analysis. In order to ascertain the selectivity of NO 2 gas along phosphorene molecular device in the ambient condition, the adsorption behavior of O 2 and CO 2 is also studied. The findings of the present work confirm that phosphorene molecular device can be used as a NO 2 gas sensor and also the influence of Al substitution in phosphorene nanosheet device is explored and reported. Copyright © 2017 Elsevier Inc. All rights reserved.

Thermoelectric and thermospintronic transport in Dirac material-based nanostructures

NASA Astrophysics Data System (ADS)

Chang, Po-Hao

The growing need for power due to the rapid developments of the technologies has urged both engineers and scientists to study more sustainable types of energy. On the other hand, the improvement of our abilities although enable us, for example, to double the number of transistors in a dense integrated circuit approximately every two years (Moore's law), comes with side effect due to overheating. Taking advantage of thermoelectric effect has thus become one of the obvious solutions for the problems. But due to the poor efficiency of electricity-heat conversion, there are still challenges to be overcome in order to fully utilize the idea. In the past few years, the realization of graphene along with the discoveries of topological insulators (TI) which are both considered as Dirac material (DM) have offer alternative routs for improving the energy conversion efficiency through different approaches as well as novel quantum effects of materials themselves for investigation. The aim of this thesis is to present contributions to improving the efficiency of thermoelectric conversion as well as analyzing spin transport phenomena that occur in nano-devices. This thesis spans the areas of thermoelectric (TE) effect, spin-Seebeck effect (SSE) and the spin transport on the 3D topological insulator (TI). The different methods have been applied ranging from tight-binding (TB) approximation to density function theory (DFT) combined with non-equilibrium function (NEGF) techniques.

Performance and Design Considerations of a Novel Dual-Material Gate Carbon Nanotube Field-Effect Transistors: Nonequilibrium Green's Function Approach

NASA Astrophysics Data System (ADS)

Arefinia, Zahra; Orouji, Ali A.

2009-02-01

The concept of dual-material gate (DMG) is applied to the carbon nanotube field-effect transistor (CNTFET) with doped source and drain extensions, and the features exhibited by the resulting new structure, i.e., the DMG-CNTFET structure, have been examined for the first time by developing a two-dimensional (2D) full quantum simulation. The simulations have been done by the self-consistent solution of 2D Poisson-Schrödinger equations, within the nonequilibrium Green's function (NEGF) formalism. The results show DMG-CNTFET decreases significantly leakage current and drain conductance and increases on-off current ratio and voltage gain as compared to the single material gate counterparts CNTFET. It is seen that short channel effects in this structure are suppressed because of the perceivable step in the surface potential profile, which screens the drain potential. Moreover, these unique features can be controlled by engineering the workfunction and length of the gate metals. Therefore, this work provides an incentive for further experimental exploration.

Spin-Filtering Rectifying and Negative Differential Resistance Behaviors in Co(dmit)2 Molecular Devices with Monatomic (C, Fe, Au) Electrodes

NASA Astrophysics Data System (ADS)

Yan, Shenlang; Long, Mengqiu; Zhang, Xiaojiao; He, Jun; Xu, Hui; Gao, Yongli

2014-09-01

Using nonequilibrium Green's functions (NEGFs) combined with the density functional theory (DFT), we study the electronic transport properties of a single molecule magnet Co(dmit)2, which is sandwiched between two monatomic chain electrodes, and the different electrode materials carbon, iron and gold, have been considered. The results show that the electrodes play a crucial role in the spin-dependent transport of the Co(dmit)2 molecular device, and some interesting phenomenon, such as perfect spin-filtering effect, rectifying and negative differential resistance (NDR) can be observed. We demonstrated that the magnetic Fe electrode can lead to high spin-flittering effect, and the different hybridization and alignment of energy levels between the molecule and the electrodes may be responsible for the rectification performance, and the distributions (delocalization or localization) of the frontier molecular orbitals under different bias result in the NDR behaviors. These characteristics could be used in the study of spin physics and the realization of nanospintronic devices.

Strain-enhanced tunneling magnetoresistance in MgO magnetic tunnel junctions

PubMed Central

Loong, Li Ming; Qiu, Xuepeng; Neo, Zhi Peng; Deorani, Praveen; Wu, Yang; Bhatia, Charanjit S.; Saeys, Mark; Yang, Hyunsoo

2014-01-01

While the effects of lattice mismatch-induced strain, mechanical strain, as well as the intrinsic strain of thin films are sometimes detrimental, resulting in mechanical deformation and failure, strain can also be usefully harnessed for applications such as data storage, transistors, solar cells, and strain gauges, among other things. Here, we demonstrate that quantum transport across magnetic tunnel junctions (MTJs) can be significantly affected by the introduction of controllable mechanical strain, achieving an enhancement factor of ~2 in the experimental tunneling magnetoresistance (TMR) ratio. We further correlate this strain-enhanced TMR with coherent spin tunneling through the MgO barrier. Moreover, the strain-enhanced TMR is analyzed using non-equilibrium Green's function (NEGF) quantum transport calculations. Our results help elucidate the TMR mechanism at the atomic level and can provide a new way to enhance, as well as tune, the quantum properties in nanoscale materials and devices. PMID:25266219

Resonant tunneling diode based on band gap engineered graphene antidot structures

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

Palla, Penchalaiah, E-mail: penchalaiah.palla@vit.ac.in; Ethiraj, Anita S.; Raina, J. P.

The present work demonstrates the operation and performance of double barrier Graphene Antidot Resonant Tunnel Diode (DBGA-RTD). Non-Equilibrium Green’s Function (NEGF) frame work with tight-binding Hamiltonian and 2-D Poisson equations were solved self-consistently for device study. The interesting feature in this device is that it is an all graphene RTD with band gap engineered graphene antidot tunnel barriers. Another interesting new finding is that it shows negative differential resistance (NDR), which involves the resonant tunneling in the graphene quantum well through both the electron and hole bound states. The Graphene Antidot Lattice (GAL) barriers in this device efficiently improved themore » Peak to Valley Ratio to approximately 20 even at room temperature. A new fitting model is developed for the number of antidots and their corresponding effective barrier width, which will help in determining effective barrier width of any size of actual antidot geometry.« less

Graphene for amino acid biosensing: Theoretical study of the electronic transport

NASA Astrophysics Data System (ADS)

Rodríguez, S. J.; Makinistian, L.; Albanesi, E. A.

2017-10-01

The study of biosensors based on graphene has increased in the last years, the combination of excellent electrical properties and low noise makes graphene a material for next generation electronic devices. This work discusses the application of a graphene-based biosensor for the detection of amino acids histidine (His), alanine (Ala), aspartic acid (Asp), and tyrosine (Tyr). First, we present the results of modeling from first principles the adsorption of the four amino acids on a graphene sheet, we calculate adsorption energy, substrate-adsorbate distance, equilibrium geometrical configurations (upon relaxation) and densities of states (DOS) for each biomolecule adsorbed. Furthermore, in order to evaluate the effects of amino acid adsorption on the electronic transport of graphene, we modeled a device using first-principles calculations with a combination of Density Functional Theory (DFT) and Nonequilibrium Greens Functions (NEGF). We provide with a detailed discussion in terms of transmission, current-voltage curves, and charge transfer. We found evidence of differences in the electronic transport through the graphene sheet due to amino acid adsorption, reinforcing the possibility of graphene-based sensors for amino acid sequencing of proteins.

Contemplating Transport Characteristics by Augmenting the Length of Molecule

NASA Astrophysics Data System (ADS)

Kaur, Milanpreet; Sawhney, Ravinder Singh; Engles, Derick

2013-11-01

In this paper, we contemplated the transport characteristics of a single molecular device junction by augmenting the length of the molecule in the scattering region. The molecules considered here belongs to class of alkanedithiols (CnH2n+2S2). Specifically, we used a tight binding semi-empirical model to compute the transport characteristics of butanedithiol, pentanedithiol, hexanedithiol and heptanedithiol connected to semi-infinite gold electrodes through thiol anchoring elements. The exploration of transport properties of considered alkanes was completed for different bias voltages within the sphere of Keldysh's Non Equilibrium Green's Function (NEGF) and Extended Hückel Theory (EHT), for studying the self-consistent steady-state solution, analyzing the out-of-equilibrium electron distribution, and the behavior of the self-consistent potential. We perceived that the current and conductance retrenches with aggravation with the increase in length of the molecule with exhibition of single electron tunneling. We observed that the coupling regime shifts from strong coupling to weak for higher order alkanedithiols and the transmission is function of evenness or oddness of the carbon atoms forming an alkane.

Non-equilibrium Transport in Carbon based Adsorbate Systems

NASA Astrophysics Data System (ADS)

Fürst, Joachim; Brandbyge, Mads; Stokbro, Kurt; Jauho, Antti-Pekka

2007-03-01

We have used the Atomistix Tool Kit(ATK) and TranSIESTA[1] packages to investigate adsorption of iron atoms on a graphene sheet. The technique of both codes is based on density functional theory using local basis sets[2], and non-equilibrium Green's functions (NEGF) to calculate the charge distribution under external bias. Spin dependent electronic structure calculations are performed for different iron coverages. These reveal adsorption site dependent charge transfer from iron to graphene leading to screening effects. Transport calculations show spin dependent scattering of the transmission which is analysed obtaining the transmission eigenchannels for each spin type. The phenomena of electromigration of iron in these systems at finite bias will be discussed, estimating the so-called wind force from the reflection[3]. [1] M. Brandbyge, J.-L. Mozos, P. Ordejon, J. Taylor, and K. Stokbro. Physical Review B (Condensed Matter and Materials Physics), 65(16):165401/11-7, 2002. [2] Jose M. Soler, Emilio Artacho, Julian D. Gale, Alberto Garcia, Javier Junquera, Pablo Ordejon, and Daniel Sanchez-Portal. Journal of Physics Condensed Matter, 14(11):2745-2779, 2002. [3] Sorbello. Theory of electromigration. Solid State Physics, 1997.

Topological Hall Effect in Skyrmions: A Nonequilibrium Coherent Transport Approach

NASA Astrophysics Data System (ADS)

Yin, Gen; Zang, Jiadong; Lake, Roger

2014-03-01

Skyrmion is a topological spin texture recently observed in many materials with broken inversion symmetry. In experiments, one effective method to detect the skyrmion crystal phase is the topological Hall measurement. At adiabatic approximation, previous theoretical studies show that the Hall signal is provided by an emergent magnetic field, which explains the topological Hall effect in the classical level. Motivated by the potential device application of skyrmions as digital bits, it is important to understand the topological Hall effect in the mesoscopic level, where the electron coherence should be considered. In this talk, we will discuss the quantum aspects of the topological Hall effect on a tight binding setup solved by nonequilibrium Green's function (NEGF). The charge distribution, Hall potential distribution, thermal broadening effect and the Hall resistivity are investigated in detail. The relation between the Hall resistance and the DM interaction is investigated. Driven by the spin transferred torque (SST), Skyrmion dynamics is previously studied within the adiabatic approximation. At the quantum transport level, this talk will also discuss the non-adiabatic effect in the skyrmion motion with the presence of the topological Hall effect. This material is based upon work supported by the National Science Foundation under Grant Nos. NSF 1128304 and NSF 1124733. It was also supported in part by FAME, one of six centers of STARnet, an SRC program sponsored by MARCO and DARPA.

Effect of B, N, Ge, Sn, K doping on electronic-transport properties of (5, 0) zigzag carbon nanotube

NASA Astrophysics Data System (ADS)

Kamalian, Monir; Seyed Jalili, Yousef; Abbasi, Afshin

2018-04-01

In this paper the effect of impurity on the electronic properties and quantum conductance of zigzag (5, 0) carbon nanotube have been studied by using the Density Functional Theory (DFT) combined with Non-Equilibrium Green’s Function (NEGF) formalism with TranSIESTA software. The effect of Boron (B), Nitrogen (N), Germanium (Ge), Tin (Sn) and Potassium (K) impurities on the CNT conduction behavior and physical characteristics, like density of states (DOS), band structure, transmission coefficients and quantum conductance was considered and discussed simultaneously. The current‑voltage (I‑V) curves of all the proposed models were studied for comparative study under low-bias conditions. The distinct changes in conductance reported as the positions, number and type of dopants was varied in central region of the CNT between two electrodes at different bias voltages. This suggested conductance enhancement mechanism for the charge transport in the doped CNT at different positions is important for the design of CNT based nanoelectronic devices. The results show that Germanium, Tin and Potassium dopant atoms has increased the conductance of the model manifold than other doping atoms furthermore 10 Boron and 10 Nitrogen dopant atoms showed the amazing property of Negative Differential Resistance (NDR).

Predictive Models for Semiconductor Device Design and Processing

NASA Technical Reports Server (NTRS)

Meyyappan, Meyya; Arnold, James O. (Technical Monitor)

1998-01-01

The device feature size continues to be on a downward trend with a simultaneous upward trend in wafer size to 300 mm. Predictive models are needed more than ever before for this reason. At NASA Ames, a Device and Process Modeling effort has been initiated recently with a view to address these issues. Our activities cover sub-micron device physics, process and equipment modeling, computational chemistry and material science. This talk would outline these efforts and emphasize the interaction among various components. The device physics component is largely based on integrating quantum effects into device simulators. We have two parallel efforts, one based on a quantum mechanics approach and the second, a semiclassical hydrodynamics approach with quantum correction terms. Under the first approach, three different quantum simulators are being developed and compared: a nonequlibrium Green's function (NEGF) approach, Wigner function approach, and a density matrix approach. In this talk, results using various codes will be presented. Our process modeling work focuses primarily on epitaxy and etching using first-principles models coupling reactor level and wafer level features. For the latter, we are using a novel approach based on Level Set theory. Sample results from this effort will also be presented.

Modeling and simulation of electronic structure, material interface and random doping in nano electronic devices

PubMed Central

Chen, Duan; Wei, Guo-Wei

2010-01-01

The miniaturization of nano-scale electronic devices, such as metal oxide semiconductor field effect transistors (MOSFETs), has given rise to a pressing demand in the new theoretical understanding and practical tactic for dealing with quantum mechanical effects in integrated circuits. Modeling and simulation of this class of problems have emerged as an important topic in applied and computational mathematics. This work presents mathematical models and computational algorithms for the simulation of nano-scale MOSFETs. We introduce a unified two-scale energy functional to describe the electrons and the continuum electrostatic potential of the nano-electronic device. This framework enables us to put microscopic and macroscopic descriptions in an equal footing at nano scale. By optimization of the energy functional, we derive consistently-coupled Poisson-Kohn-Sham equations. Additionally, layered structures are crucial to the electrostatic and transport properties of nano transistors. A material interface model is proposed for more accurate description of the electrostatics governed by the Poisson equation. Finally, a new individual dopant model that utilizes the Dirac delta function is proposed to understand the random doping effect in nano electronic devices. Two mathematical algorithms, the matched interface and boundary (MIB) method and the Dirichlet-to-Neumann mapping (DNM) technique, are introduced to improve the computational efficiency of nano-device simulations. Electronic structures are computed via subband decomposition and the transport properties, such as the I-V curves and electron density, are evaluated via the non-equilibrium Green's functions (NEGF) formalism. Two distinct device configurations, a double-gate MOSFET and a four-gate MOSFET, are considered in our three-dimensional numerical simulations. For these devices, the current fluctuation and voltage threshold lowering effect induced by the discrete dopant model are explored. Numerical convergence and model well-posedness are also investigated in the present work. PMID:20396650

SLD-MOSCNT: A new MOSCNT with step-linear doping profile in the source and drain regions

NASA Astrophysics Data System (ADS)

Tahne, Behrooz Abdi; Naderi, Ali

2017-01-01

In this paper, a new structure, step-linear doping MOSCNT (SLD-MOSCNT), is proposed to improve the performance of basic MOSCNTs. The basic structure suffers from band to band tunneling (BTBT). We show that using SLD profile for source and drain regions increases the horizontal distance between valence and conduction bands at gate to source/drain junction which reduces BTBT probability. SLD performance is compared with other similar structures which have recently been proposed to reduce BTBT such as MOSCNT with lightly-doped drain and source (LDDS), and with double-light doping in source and drain regions (DLD). The obtained results using a nonequilibrium Green’s function (NEGF) method show that the SLD-MOSCNT has the lowest leakage current, power consumption and delay time, and the highest current ratio and voltage gain. The ambipolar conduction in the proposed structure is very low and can be neglected. In addition, these structures can improve short-channel effects. Also, the investigation of cutoff frequency of the different structures shows that the SLD has the highest cutoff frequency. Device performance has been investigated for gate length from 8 to 20 nm which demonstrates all discussions regarding the superiority of the proposed structure are also valid for different channel lengths. This improvement is more significant especially for channel length less than 12 nm. Therefore, the SLD can be considered as a candidate to be used in the applications with high speed and low power consumption.

Role of Cyclin E as an Early Event in Ovarian Carcinogenesis

DTIC Science & Technology

2012-04-01

degradation . P27 is a powerful negative regulator of the cell cycle, preventing activation of cyclin E- cdk2 or cyclin D-cdk4 complexes and cell cycle...Ahmed M, Bavi P, et al. Bortezomib (Velcade) induces p27Kip1 expression through S-phase kinase protein 2 degradation in colorectal cancer. Cancer Res...CA1251CA72·4 CA 125 CA72-4 M-CSF CA 125/CA 72-4/M-CSFICA 15-3 CA125 CA 125/mesothelin CA 125/IL·6JIL·8NEGF;EGF CA 125/IL-6,G-CSFNEGF/EGF Leptin

Strain and deformations engineered germanene bilayer double gate-field effect transistor by first principles

NASA Astrophysics Data System (ADS)

Meher Abhinav, E.; Chandrasekaran, Gopalakrishnan; Kasmir Raja, S. V.

2017-10-01

Germanene, silicene, stanene, phosphorene and graphene are some of single atomic materials with novel properties. In this paper, we explored bilayer germanene-based Double Gate-Field Effect Transistor (DG-FET) with various strains and deformations using Density Functional Theory (DFT) and Green's approach by first-principle calculations. The DG-FET of 1.6 nm width, 6 nm channel length (Lch) and HfO2 as gate dielectric has been modeled. For intrinsic deformation of germanene bilayer, we have enforced minute mechanical deformation of wrap and twist (5°) and ripple (0.5 Å) on germanene bilayer channel material. By using NEGF formalism, I-V Characteristics of various strains and deformation tailored DG-FET was calculated. Our results show that rough edge and single vacancy (5-9) in bilayer germanene diminishes the current around 47% and 58% respectively as compared with pristine bilayer germanene. In case of strain tailored bilayer DG-FET, multiple NDR regions were observed which can be utilized in building stable multiple logic states in digital circuits and high frequency oscillators using negative resistive techniques.

The electronic transport properties of defected bilayer sliding armchair graphene nanoribbons

NASA Astrophysics Data System (ADS)

Mohammadi, Amin; Haji-Nasiri, Saeed

2018-04-01

By applying non-equilibrium Green's functions (NEGF) in combination with tight-binding (TB) model, we investigate and compare the electronic transport properties of perfect and defected bilayer armchair graphene nanoribbons (BAGNRs) under finite bias. Two typical defects which are placed in the middle of top layer (i.e. single vacancy (SV) and stone wale (SW) defects) are examined. The results reveal that in both perfect and defected bilayers, the maximum current refers to β-AB, AA and α-AB stacking orders, respectively, since the intermolecular interactions are stronger in them. Moreover it is observed that a SV decreases the current in all stacking orders, but the effects of a SW defect is nearly unpredictable. Besides, we introduced a sequential switching behavior and the effects of defects on the switching performance is studied as well. We found that a SW defect can significantly improve the switching behavior of a bilayer system. Transmission spectrum, band structure, molecular energy spectrum and molecular projected self-consistent Hamiltonian (MPSH) are analyzed subsequently to understand the electronic transport properties of these bilayer devices which can be used in developing nano-scale bilayer systems.

Negative differential resistance observed from vertical p+-n+ junction device with two-dimensional black phosphorous

NASA Astrophysics Data System (ADS)

Lee, Daeyeong; Jang, Young Dae; Kweon, Jaehwan; Ryu, Jungjin; Hwang, Euyheon; Yoo, Won Jong; Samsung-SKKU Graphene/2D Center (SSGC) Collaboration

A vertical p+-n+ homojunction was fabricated by using black phosphorus (BP) as a van der Waals two-dimensional (2D) material. The top and bottom layers of the materials were doped by chemical dopants of gold chloride (AuCl3) for p-type doping and benzyl viologen (BV) for n-type doping. The negative differential resistance (NDR) effect was clearly observed from the output curves of the fabricated BP vertical devices. The thickness range of the 2D material showing NDR and the peak to valley current ratio of NDR are found to be strongly dependent on doping condition, gate voltage, and BP's degradation level. Furthermore, the carrier transport of the p+-n+ junction was simulated by using density functional theory (DFT) and non-equilibrium Green's function (NEGF). Both the experimental and simulation results confirmed that the NDR is attributed to the band-to-band tunneling (BTBT) across the 2D BP p+-n+ junction, and further quantitative details on the carrier transport in the vertical p+-n+ junction devices were explored, according to the analyses of the measured transfer curves and the DFT simulation results. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (2013R1A2A2A01015516).

Transport properties and device-design of Z-shaped MoS2 nanoribbon planar junctions

NASA Astrophysics Data System (ADS)

Zhang, Hua; Zhou, Wenzhe; Liu, Qi; Yang, Zhixiong; Pan, Jiangling; Ouyang, Fangping; Xu, Hui

2017-09-01

Based on MoS2 nanoribbons, metal-semiconductor-metal planar junction devices were constructed. The electronic and transport properties of the devices were studied by using density function theory (DFT) and nonequilibrium Green's functions (NEGF). It is found that a band gap about 0.4 eV occurs in the planar junction. The electron and hole transmissions of the devices are mainly contributed by the Mo atomic orbitals. The electron transport channel is located at the edge of armchair MoS2 nanoribbon, while the hole transport channel is delocalized in the channel region. The I-V curve of the two-probe device shows typical transport behavior of Schottky barrier, and the threshold voltage is of about 0.2 V. The field effect transistors (FET) based on the planar junction turn out to be good bipolar transistors, the maximum current on/off ratio can reach up to 1 × 104, and the subthreshold swing is 243 mV/dec. It is found that the off-state current is dependent on the length and width of the channel, while the on-state current is almost unaffected. The switching performance of the FET is improved with increasing the length of the channel, and shows oscillation behavior with the change of the channel width.

2D Quantum Transport Modeling in Nanoscale MOSFETs

NASA Technical Reports Server (NTRS)

Svizhenko, Alexei; Anantram, M. P.; Govindan, T. R.; Biegel, Bryan

2001-01-01

With the onset of quantum confinement in the inversion layer in nanoscale MOSFETs, behavior of the resonant level inevitably determines all device characteristics. While most classical device simulators take quantization into account in some simplified manner, the important details of electrostatics are missing. Our work addresses this shortcoming and provides: (a) a framework to quantitatively explore device physics issues such as the source-drain and gate leakage currents, DIBL, and threshold voltage shift due to quantization, and b) a means of benchmarking quantum corrections to semiclassical models (such as density- gradient and quantum-corrected MEDICI). We have developed physical approximations and computer code capable of realistically simulating 2-D nanoscale transistors, using the non-equilibrium Green's function (NEGF) method. This is the most accurate full quantum model yet applied to 2-D device simulation. Open boundary conditions, oxide tunneling and phase-breaking scattering are treated on equal footing. Electrons in the ellipsoids of the conduction band are treated within the anisotropic effective mass approximation. Quantum simulations are focused on MIT 25, 50 and 90 nm "well- tempered" MOSFETs and compared to classical and quantum corrected models. The important feature of quantum model is smaller slope of Id-Vg curve and consequently higher threshold voltage. These results are quantitatively consistent with I D Schroedinger-Poisson calculations. The effect of gate length on gate-oxide leakage and sub-threshold current has been studied. The shorter gate length device has an order of magnitude smaller current at zero gate bias than the longer gate length device without a significant trade-off in on-current. This should be a device design consideration.

Improvement in the performance of graphene nanoribbon p-i-n tunneling field effect transistors by applying lightly doped profile on drain region

NASA Astrophysics Data System (ADS)

Naderi, Ali

2017-12-01

In this paper, an efficient structure with lightly doped drain region is proposed for p-i-n graphene nanoribbon field effect transistors (LD-PIN-GNRFET). Self-consistent solution of Poisson and Schrödinger equation within Nonequilibrium Green’s function (NEGF) formalism has been employed to simulate the quantum transport of the devices. In proposed structure, source region is doped by constant doping density, channel is an intrinsic GNR, and drain region contains two parts with lightly and heavily doped doping distributions. The important challenge in tunneling devices is obtaining higher current ratio. Our simulations demonstrate that LD-PIN-GNRFET is a steep slope device which not only reduces the leakage current and current ratio but also enhances delay, power delay product, and cutoff frequency in comparison with conventional PIN GNRFETs with uniform distribution of impurity and with linear doping profile in drain region. Also, the device is able to operate in higher drain-source voltages due to the effectively reduced electric field at drain side. Briefly, the proposed structure can be considered as a more reliable device for low standby-power logic applications operating at higher voltages and upper cutoff frequencies.

Negative differential resistance and rectification effects in zigzag graphene nanoribbon heterojunctions: Induced by edge oxidation and symmetry concept

NASA Astrophysics Data System (ADS)

Nazirfakhr, Maryam; Shahhoseini, Ali

2018-03-01

By applying non-equilibrium Green's functions (NEGF) in combination with tight-binding (TB) model, we investigate and compare the electronic transport properties of H-terminated zigzag graphene nanoribbon (H/ZGNR) and O-terminated ZGNR/H-terminated ZGNR (O/ZGNR-H/ZGNR) heterostructure under finite bias. Moreover, the effect of width and symmetry on the electronic transport properties of both models is also considered. The results reveal that asymmetric H/ZGNRs have linear I-V characteristics in whole bias range, but symmetric H-ZGNRs show negative differential resistance (NDR) behavior which is inversely proportional to the width of the H/ZGNR. It is also shown that the I-V characteristic of O/ZGNR-H/ZGNR heterostructure shows a rectification effect, whether the geometrical structure is symmetric or asymmetric. The fewer the number of zigzag chains, the bigger the rectification ratio. It should be mentioned that, the rectification ratios of symmetric heterostructures are much bigger than asymmetric one. Transmission spectrum, density of states (DOS), molecular projected self-consistent Hamiltonian (MPSH) and molecular eigenstates are analyzed subsequently to understand the electronic transport properties of these ZGNR devices. Our findings could be used in developing nanoscale rectifiers and NDR devices.

Thermal transport and thermoelectric properties of beta-graphyne nanostructures.

PubMed

Ouyang, Tao; Hu, Ming

2014-06-20

Graphyne, an allotrope of graphene, is currently a hot topic in the carbon-based nanomaterials research community. Taking beta-graphyne as an example, we performed a comprehensive study of thermal transport and related thermoelectric properties by means of nonequilibrium Green's function (NEGF). Our simulation demonstrated that thermal conductance of beta-graphyne is only approximately 26% of that of the graphene counterpart and also shows evident anisotropy. Meanwhile, thermal conductance of armchair beta-graphyne nanoribbons (A-BGYNRs) presents abnormal stepwise width dependence. As for the thermoelectric property, we found that zigzag beta-graphyne nanoribbons (Z-BGYNRs) possess superior thermoelectric performance with figure of merit value achieving 0.5 at room temperature, as compared with graphene nanoribbons (~0.05). Aiming at obtaining a better thermoelectric coefficient, we also investigated Z-BGYNRs with geometric modulations. The results show that the thermoelectric performance can be enhanced dramatically (figure of merit exceeding 1.5 at room temperature), and such enhancement strongly depends on the width of the nanoribbons and location and quantity of geometric modulation. Our findings shed light on transport properties of beta-graphyne as high efficiency thermoelectrics. We anticipate that our simulation results could offer useful guidance for the design and fabrication of future thermoelectric devices.

Selective gas adsorption and I-V response of monolayer boron phosphide introduced by dopants: A first-principle study

NASA Astrophysics Data System (ADS)

Cheng, Yongfa; Meng, Ruishen; Tan, Chunjian; Chen, Xianping; Xiao, Jing

2018-01-01

Two-dimensional (2D) materials have gained tremendous research interests for gas sensing applications because of their ultrahigh theoretical specific surface areas and unique electronic properties. Here, we investigate the adsorption of CO, SO2, NH3, O2, NO and NO2 gas molecules on pure and doped boron phosphide (BP) systems using first-principles calculations to exploit their potential in gas sensing. Our results predict that all six gas molecules show stronger adsorption interactions on impurities-doped BP over the pristine monolayer BP. Al-doped BP shows the highest sensitivity to all gas molecules, but N-doped BP is more suitable as a sensing material for SO2, NO and NO2 due to the feasibility of desorption. We further calculated the current-voltage (I-V) relation by mean of nonequilibrium Green's function (NEGF) formalism. The I-V curves indicate that the electronic properties of the doping systems change significantly with gas adsorption by studying the nonparamagnetic molecules NH3 and the paramagnetic molecules NO, which can be more likely to be measured experimentally compared to graphene and phosphorene. This work explores the possibility of BP as a superior sensor through introducing the appropriate dopants.

Theoretical investigations of molecular wires: Electronic spectra and electron transport

NASA Astrophysics Data System (ADS)

Palma, Julio Leopoldo

The results of theoretical and computational research are presented for two promising molecular wires, the Nanostar dendrimer, and a series of substituted azobenzene derivatives connected to aluminum electrodes. The electronic absorption spectra of the Nanostar (a phenylene-ethynylene dendrimer attached to an ethynylperylene chromophore) were calculated using a sequential Molecular Dynamics/Quantum Mechanics (MD/QM) method to perform an analysis of the temperature dependence of the electronic absorption process. We modeled the Nanostar as a series of connected units, and performed MD simulations for each chromophore at 10 K and 300 K to study how the temperature affected the structures and, consequently, the spectra. The absorption spectra of the Nanostar were computed using an ensemble of 8000 structures for each chromophore. Quantum Mechanical (QM) ZINDO/S calculations were performed for each conformation in the ensemble, including 16 excited states, for a total of 128,000 excitation energies. The spectral intensity was then scaled linearly with the number of conjugated units. Our calculations for both the individual chromophores and the Nanostar, are in good agreement with experiments. We explain in detail the effects of temperature and the consequences for the absorption process. The second part of this thesis presents a study of the effects of chemical substituents on the electron transport properties of the azobenzene molecule, which has been proposed recently as a component of a light-driven molecular switch. This molecule has two stable conformations (cis and trans) in its electronic ground state, with considerable differences in their conductance. The electron transport properties were calculated using first-principles methods combining non-equilibrium Green's function (NEGF) techniques with density functional theory (DFT). For the azobenzene studies, we included electron-donating groups and electron-withdrawing groups in meta- and ortho-positions with respect to the azo group. The results showed that the molecular structure is crucial in optimizing the electron transport properties of chemical structures, and that the transport properties in electronic devices at the molecular level can be manipulated, enhanced or suppressed by a careful consideration of the effects of chemical modification.

Nonequilibrium phase diagram of a one-dimensional quasiperiodic system with a single-particle mobility edge

NASA Astrophysics Data System (ADS)

Purkayastha, Archak; Dhar, Abhishek; Kulkarni, Manas

2017-11-01

We investigate and map out the nonequilibrium phase diagram of a generalization of the well known Aubry-André-Harper (AAH) model. This generalized AAH (GAAH) model is known to have a single-particle mobility edge which also has an additional self-dual property akin to that of the critical point of the AAH model. By calculating the population imbalance, we get hints of a rich phase diagram. We also find a fascinating connection between single particle wave functions near the mobility edge of the GAAH model and the wave functions of the critical AAH model. By placing this model far from equilibrium with the aid of two baths, we investigate the open system transport via system size scaling of nonequilibrium steady state (NESS) current, calculated by fully exact nonequilibrium Green's function (NEGF) formalism. The critical point of the AAH model now generalizes to a `critical' line separating regions of ballistic and localized transport. Like the critical point of the AAH model, current scales subdiffusively with system size on the `critical' line (I ˜N-2 ±0.1 ). However, remarkably, the scaling exponent on this line is distinctly different from that obtained for the critical AAH model (where I ˜N-1.4 ±0.05 ). All these results can be understood from the above-mentioned connection between states near the mobility edge of the GAAH model and those of the critical AAH model. A very interesting high temperature nonequilibrium phase diagram of the GAAH model emerges from our calculations.

2D Quantum Mechanical Study of Nanoscale MOSFETs

NASA Technical Reports Server (NTRS)

Svizhenko, Alexei; Anantram, M. P.; Govindan, T. R.; Biegel, B.; Kwak, Dochan (Technical Monitor)

2000-01-01

With the onset of quantum confinement in the inversion layer in nanoscale MOSFETs, behavior of the resonant level inevitably determines all device characteristics. While most classical device simulators take quantization into account in some simplified manner, the important details of electrostatics are missing. Our work addresses this shortcoming and provides: (a) a framework to quantitatively explore device physics issues such as the source-drain and gate leakage currents, DIBL, and threshold voltage shift due to quantization, and b) a means of benchmarking quantum corrections to semiclassical models (such as density-gradient and quantum-corrected MEDICI). We have developed physical approximations and computer code capable of realistically simulating 2-D nanoscale transistors, using the non-equilibrium Green's function (NEGF) method. This is the most accurate full quantum model yet applied to 2-D device simulation. Open boundary conditions and oxide tunneling are treated on an equal footing. Electrons in the ellipsoids of the conduction band are treated within the anisotropic effective mass approximation. We present the results of our simulations of MIT 25, 50 and 90 nm "well-tempered" MOSFETs and compare them to those of classical and quantum corrected models. The important feature of quantum model is smaller slope of Id-Vg curve and consequently higher threshold voltage. Surprisingly, the self-consistent potential profile shows lower injection barrier in the channel in quantum case. These results are qualitatively consistent with ID Schroedinger-Poisson calculations. The effect of gate length on gate-oxide leakage and subthreshold current has been studied. The shorter gate length device has an order of magnitude smaller current at zero gate bias than the longer gate length device without a significant trade-off in on-current. This should be a device design consideration.

Theory of terahertz intervalence band polaritons and antipolaritons

NASA Astrophysics Data System (ADS)

Faragai, Inuwa Aliyu

The work presented in this thesis is a theoretical investigation of the interaction of terahertz (THz) radiation with intersubband excitations in microcavities leading to THz polaritons and antipolaritons. The approach is based on the dielectric function formalism. The dielectric constant is derived from an optical susceptibility evaluated with Non Equilibrium Many Body Green's Functions (NEGF), which is then adjusted to a Lorentzian fit. Finally, the resulting expression is included in the wave equation describing the propagating electric field in the medium. This model is applied to GaAs/Al[0.3]Ga[0.7]As multiple quantum wells embedded in a microcavity. The energy dispersion relations leading to THz polaritons and antipolaritons are obtained and investigated for different carrier densities and cavity configurations. Recently, intersubband based THz polariton emitters and THz quantum cascade lasers are attracting major research interest due to their great importance in applications such as THz imaging, spectroscopy as well as in security control for detection of biological and hazardous materials and medical diagnosis. The coupling of THz radiation with intersubband transitions in semiconductor microcavities can lead to further tunability and improved quantum efficiency for THz devices. Here we propose a simple geometry and used a simplified modelling technique to investigate the interactions of transverse electric (TE-Mode) polarized THz cavity modes with intervalence band excitations. The model is applied to single and multiple transition problems and combinations of many body effects and scattering mechanism are included in the input dielectric constant.

The effect of electrodes on 11 acene molecular spin valve: Semi-empirical study

NASA Astrophysics Data System (ADS)

Aadhityan, A.; Preferencial Kala, C.; John Thiruvadigal, D.

2017-10-01

A new revolution in electronics is molecular spintronics, with the contemporary evolution of the two novel disciplines of spintronics and molecular electronics. The key point is the creation of molecular spin valve which consists of a diamagnetic molecule in between two magnetic leads. In this paper, non-equilibrium Green's function (NEGF) combined with Extended Huckel Theory (EHT); a semi-empirical approach is used to analyse the electron transport characteristics of 11 acene molecular spin valve. We examine the spin-dependence transport on 11 acene molecular junction with various semi-infinite electrodes as Iron, Cobalt and Nickel. To analyse the spin-dependence transport properties the left and right electrodes are joined to the central region in parallel and anti-parallel configurations. We computed spin polarised device density of states, projected device density of states of carbon and the electrode element, and transmission of these devices. The results demonstrate that the effect of electrodes modifying the spin-dependence behaviours of these systems in a controlled way. In Parallel and anti-parallel configuration the separation of spin up and spin down is lager in the case of iron electrode than nickel and cobalt electrodes. It shows that iron is the best electrode for 11 acene spin valve device. Our theoretical results are reasonably impressive and trigger our motivation for comprehending the transport properties of these molecular-sized contacts.

Thermoelectric effects in disordered branched nanowires

NASA Astrophysics Data System (ADS)

Roslyak, Oleksiy; Piriatinskiy, Andrei

2013-03-01

We shall develop formalism of thermal and electrical transport in Si1 - x Gex and BiTe nanowires. The key feature of those nanowires is the possibility of dendrimer type branching. The branching tree can be of size comparable to the short wavelength of phonons and by far smaller than the long wavelength of conducting electrons. Hence it is expected that the branching may suppress thermal and let alone electrical conductance. We demonstrate that the morphology of branches strongly affects the electronic conductance. The effect is important to the class of materials known as thermoelectrics. The small size of the branching region makes large temperature and electrical gradients. On the other hand the smallness of the region would allow the electrical transport being ballistic. As usual for the mesoscopic systems we have to solve macroscopic (temperature) and microscopic ((electric potential, current)) equations self-consistently. Electronic conductance is studied via NEGF formalism on the irreducible electron transfer graph. We also investigate the figure of merit ZT as a measure of the suppressed electron conductance.

Effect of the interfacial O and Mg vacancies on electronic structure and transport properties of the FeRh/MgO/FeRh (0 0 1) magnetic tunnel junction: DFT calculations

NASA Astrophysics Data System (ADS)

Sakhraoui, T.; Said, M.

2017-12-01

The electronic, magnetic and transport properties of oxygen or magnesium vacancies at the FeRh/MgO/FeRh (0 0 1) magnetic tunnel junction are studied within first principles. Configurations with one O or Mg vacancy per C(2 × 2) surface unit cell, which is located in the MgO interfacial layers, are investigated. We observed that the O and Mg vacancies defect have a very little influence on the magnetic state of the spacer. Very interestingly, the Fe atoms exhibit an enhanced magnetic moment in the case of Mg-vacancy, this latter was found to decrease in the case of O-vacancy. The variations in the spin polarization and magnetic moment values for Fe and Rh atoms at the interface were found to be larger in presence of Mg vacancy. An analysis of the charge densities of our systems was also performed; large variations in the Mg-vacancy system were observed. This affects more the t2g states of the interfacial Fe atom. Moreover, we present an ab initio calculated transmission and I-V characteristics for FeRh/MgO/FeRh (0 0 1) magnetic tunnel junction and we compare results to those of O and Mg-vacancy at the interface using the TRANSIESTA code, which combines the DFT electronic structure calculations with the non-equilibrium Green function formalism (NEGF) for transport properties. The results show that the zero-bias minority spin transmission is much larger than the majority spin transmission for all structures. In all systems and for all magnetic configurations, minority spin currents are higher than majority spin ones, this means that transport properties are, mainly, determined by minority spin channel.

A review of selected topics in physics based modeling for tunnel field-effect transistors

NASA Astrophysics Data System (ADS)

Esseni, David; Pala, Marco; Palestri, Pierpaolo; Alper, Cem; Rollo, Tommaso

2017-08-01

The research field on tunnel-FETs (TFETs) has been rapidly developing in the last ten years, driven by the quest for a new electronic switch operating at a supply voltage well below 1 V and thus delivering substantial improvements in the energy efficiency of integrated circuits. This paper reviews several aspects related to physics based modeling in TFETs, and shows how the description of these transistors implies a remarkable innovation and poses new challenges compared to conventional MOSFETs. A hierarchy of numerical models exist for TFETs covering a wide range of predictive capabilities and computational complexities. We start by reviewing seminal contributions on direct and indirect band-to-band tunneling (BTBT) modeling in semiconductors, from which most TCAD models have been actually derived. Then we move to the features and limitations of TCAD models themselves and to the discussion of what we define non-self-consistent quantum models, where BTBT is computed with rigorous quantum-mechanical models starting from frozen potential profiles and closed-boundary Schrödinger equation problems. We will then address models that solve the open-boundary Schrödinger equation problem, based either on the non-equilibrium Green’s function NEGF or on the quantum-transmitting-boundary formalism, and show how the computational burden of these models may vary in a wide range depending on the Hamiltonian employed in the calculations. A specific section is devoted to TFETs based on 2D crystals and van der Waals hetero-structures. The main goal of this paper is to provide the reader with an introduction to the most important physics based models for TFETs, and with a possible guidance to the wide and rapidly developing literature in this exciting research field.

Onset of Spin Polarization in Four-Gate Quantum Point Contacts

NASA Astrophysics Data System (ADS)

Jones, Alex

A series of simulations which utilize a Non-equilibrium Green's function (NEGF) formalism is suggested which can provide indirect evidence of the fine and non-local electrostatic tuning of the onset of spin polarization in two closely spaced quantum point contacts (QPCs) that experience a phenomenon known as lateral spin-orbit coupling (LSOC). Each of the QPCs that create the device also has its own pair of side gates (SGs) which are in-plane with the device channel. Numerical simulations of the conductance of the two closely spaced QPCs or four-gate QPC are carried out for different biasing conditions applied to two leftmost and rightmost SGs. Conductance plots are then calculated as a function of the variable, Vsweep, which is the common sweep voltage applied to the QPC. When Vsweep is only applied to two of the four side gates, the plots show several conductance anomalies, i.e., below G0 = 2e2/h, characterized by intrinsic bistability, i.e., hysteresis loops due to a difference in the conductance curves for forward and reverse common voltage sweep simulations. The appearance of hysteresis loops is attributed to the co-existence of multistable spin textures in the narrow channel of the four-gate QPC. The shape, location, and number of hysteresis loops are very sensitive to the biasing conditions on the four SGs. The shape and size of the conductance anomalies and hysteresis loops are shown to change when the biasing conditions on the leftmost and rightmost SGs are swapped, a rectifying behavior providing an additional indirect evidence for the onset of spontaneous spin polarization in nanoscale devices made of QPCs. The results of the simulations reveal that the occurrence and fine tuning of conductance anomalies in QPC structures are highly sensitive to the non-local action of closely spaced SGs. It is therefore imperative to take into account this proximity effect in the design of all electrical spin valves making use of middle gates to fine tune the spin precession between QPC based spin injector and detector contacts.

Envisaging quantum transport phenomenon in a muddled base pair of DNA

NASA Astrophysics Data System (ADS)

Vohra, Rajan; Sawhney, Ravinder Singh

2018-05-01

The effect of muddled base pair on electron transfer through a deoxyribonucleic acid (DNA) molecule connected to the gold electrodes has been elucidated using tight binding model. The effect of hydrogen and nitrogen bonds on the resistance of the base pair has been minutely observed. Using the semiempirical extended Huckel approach within NEGF regime, we have determined the current and conductance vs. bias voltage for disordered base pairs of DNA made of thymine (T) and adenine (A). The asymmetrical behaviour amid five times depreciation in the current characteristics has been observed for deviated Au-AT base pair-Au devices. An interesting revelation is that the conductance of the intrinsic AT base pair configuration attains dramatically high values with the symmetrical zig-zag pattern of current, which clearly indicates the transformation of the bond length within the strands of base pair when compared with other samples. A thorough investigation of the transmission coefficients T( E) and HOMO-LUMO gap reveals the misalignment of the strands in base pairs of DNA. The observed results present an insight to extend this work to build biosensing devices to predict the abnormality with the DNA.

Spin Transfer Torque in Spin Filter Tunnel Junctions

NASA Astrophysics Data System (ADS)

Ortiz Pauyac, Christian; Kalitsov, Alan; Manchon, Aurelien; Chshiev, Mair

2014-03-01

STT in MTJs is well known for its potential spin electronic applications. However, recently a new class of MTJs based on spin filtering across magnetic insulators (SFTJ) has been attracting much attention since in such MTJs electrons with a certain spin orientation tunnel much more efficiently. In this structure, STT remains to be addressed and clarified. Here we present a systematic study of its angular and voltage bias dependences consisting of one or two FM layers separated by a magnetic insulator (MI). The calculations were performed within the tight-binding model using NEGF technique in the framework of Keldysh formalism. We predict that STT is higher in magnitude compared to regular MTJs, which strongly depends in the relative directions of the magnetic states of the free layer (FM2) and MI. Namely, in case of parallel orientation of MI and FM2 moments in a FM1|MI|FM2 structure, the system behaves as a regular MTJ with a modest increase of STT magnitude. However, as the angle between MI and FM2 moments increases, the field-like torque becomes three orders of magnitude higher than the Slonczewski component and oscillates with bias as band-filling increases. This may have practical implications.

Many-body theory of electrical, thermal and optical response of molecular heterojunctions

NASA Astrophysics Data System (ADS)

Bergfield, Justin Phillip

In this work, we develop a many-body theory of electronic transport through single molecule junctions based on nonequilibrium Green's functions (NEGFs). The central quantity of this theory is the Coulomb self-energy matrix of the junction SigmaC. SigmaC is evaluated exactly in the sequential-tunneling limit, and the correction due to finite lead-molecule tunneling is evaluated using a conserving approximation based on diagrammatic perturbation theory on the Keldysh contour. In this way, tunneling processes are included to infinite order, meaning that any approximation utilized is a truncation in the physical processes considered rather than in the order of those processes. Our theory reproduces the key features of both the Coulomb blockade and coherent transport regimes simultaneously in a single unified theory. Nonperturbative effects of intramolecular correlations are included, which are necessary to accurately describe the highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap, essential for a quantitative theory of transport. This work covers four major topics related to transport in single-molecule junctions. First, we use our many-body theory to calculate the nonlinear electrical response of the archetypal Au-1,4-benzenedithiol-Au junction and find irregularly shaped 'molecular diamonds' which have been experimentally observed in some larger molecules but which are inaccessible to existing theoretical approaches. Next, we extend our theory to include heat transport and develop an exact expression for the heat current in an interacting nanostructure. Using this result, we discover that quantum coherence can strongly enhance the thermoelectric response of a device, a result with a number of technological applications. We then develop the formalism to include multi-orbital lead-molecule contacts and multi-channel leads, both of which strongly affect the observable transport. Lastly, we include a dynamic screening correction to Sigma C and investigate the optoelectric response of several molecular junctions.

Quantum ballistic analysis of transition metal dichalcogenides based double gate junctionless field effect transistor and its application in nano-biosensor

NASA Astrophysics Data System (ADS)

Shadman, Abir; Rahman, Ehsanur; Khosru, Quazi D. M.

2017-11-01

To reduce the thermal budget and the short channel effects in state of the art CMOS technology, Junctionless field effect transistor (JLFET) has been proposed in the literature. Numerous experimental, modeling, and simulation based works have been done on this new FET with bulk materials for various geometries until now. On the other hand, the two-dimensional layered material is considered as an alternative to current Si technology because of its ultra-thin body and high mobility. Very recently few simulation based works have been done on monolayer molybdenum disulfide based JLFET mainly to show the advantage of JLFET over conventional FET. However, no comprehensive simulation-based work has been done for double gate JLFET keeping in mind the prominent transition metal dichalcogenides (TMDC) to the authors' best knowledge. In this work, we have studied quantum ballistic drain current-gate voltage characteristics of such FETs within non-equilibrium Green's function (NEGF) framework. Our simulation results reveal that all these TMDC materials are viable options for implementing state of the art Junctionless MOSFET with emphasis on their performance at short gate lengths. Besides evaluating the prospect of TMDC materials in the digital logic application, the performance of Junctionless Double Gate trilayer TMDC heterostructure FET for the label-free electrical detection of biomolecules in dry environment has been investigated for the first time to the authors' best knowledge. The impact of charge neutral biomolecules on the electrical characteristics of the biosensor has been analyzed under dry environment situation. Our study shows that these materials could provide high sensitivity in the sub-threshold region as a channel material in nano-biosensor, a trend demonstrated by silicon on insulator FET sensor in the literature. Thus, going by the trend of replacing silicon with these novel materials in device level, TMDC heterostructure could be a viable alternative to silicon for potentiometric biosensing.

Carbon nanotube and graphene device modeling and simulation

NASA Astrophysics Data System (ADS)

Yoon, Young Ki

The performance of the semiconductors has been improved and the price has gone down for decades. It has been continuously scaled down in size year by year, and now it encounters the fundamental scaling limit. We, therefore, should prepare a new era beyond the conventional semiconductor technologies. One of the most promising devices is possible by carbon nanotube (CNT) or graphene nanoribbon (GNR) in terms of its excellent charge transport properties. Their fundamental material properties and device physics are totally different to those of the conventional devices. In this nano-regime, more sophisticated device modeling and simulation are really needed to elucidate nano-device operation and to save our resources from errors. The numerical simulation works in this dissertation will provide novel view points on the emerging devices. In this dissertation, CNT and GNR devices are numerically studied. The first part of this work is on CNT devices, and a common structure of CNT device has CNT channel, metal source and drain contacts, and gate electrode. We investigate the strain, geometry, and scattering effects on the device performance of CNT field-effect transistors (FETs). It is shown that even a small amount of strain can result in a large effect on the performance of CNTFETs due to the variation of the bandgap and band-structure-limited velocity. A type of strain which produces a larger bandgap results in increased Schottky barrier (SB) height and decreased band-structure-limited velocity, and hence a smaller minimum leakage current, smaller on current, larger maximum achievable Ion/Ioff, and larger intrinsic delay. We also examine geometry effect of partial gate CNTFETs. In the growth process of vertical CNT, underlap between the gate and the bottom electrode is advantageous for transistor operation because it suppresses ambipolar conduction of SBFETs. Both n-type and p-type transistor operations with balanced performance metrics can be achieved on a single partial gate FET by using proper bias schemes. The effect of phonon scattering on the intrinsic delay and cut-off frequency of Schottky barrier CNTFETs is also examined. Carriers are mostly scattered by optical and zone boundary phonons beyond the beginning of the channel. The scattering has a small direct effect on the DC on current of the CNTFET, but it results in significant decrease of intrinsic cut-off frequency and increase of intrinsic delay. Semiconducting CNT is useful for the channel in CNTFETs, whereas metallic CNT can be used as an electrode. If a porous CNT film is used as a source electrode, vertical thin-film transistors (TFTs) can be constructed. Vertical organic FET (OFET) shows clear transistor switching behavior allowing orders of magnitude modulation of the source-drain current even in the presence of electrostatic screening by the source electrode. The channel length should be carefully engineered due to the trade-off between device characteristics in the subthreshold and above-threshold regions. The second subject is device simulations of GNRFETs. Even though GNR is also graphene-based quasi-1D nanostructure like CNT, the differences in shape, boundary condition, and existence of edges and dangling bonds make it operate in a different way. Atomistic 3D simulation study of the performance of GNR SBFETs is presented. The impacts of non-idealities on device performance have been investigated. The edges of GNR, which do not exist in CNT, can be advantages or disadvantages. If an appropriate control by different edge atoms is possible, it would be definitely positive. Totally new electronic band structure is obtained by different edge-termination atoms. In addition, only a fraction of impurity atom can also much affect on the material properties of GNR. In order to perform device simulations of non-uniform GNR devices, multiscale simulation scheme can be used in non-equilibrium Green's function (NEGF) formalism and density-functional method.

Spin transport in lateral structures with semiconducting channel

NASA Astrophysics Data System (ADS)

Zainuddin, Abu Naser

Spintronics is an emerging field of electronics with the potential to be used in future integrated circuits. Spintronic devices are already making their mark in storage technologies in recent times and there are proposals for using spintronic effects in logic technologies as well. So far, major improvement in spintronic effects, for example, the `spin-valve' effect, is being achieved in metals or insulators as channel materials. But not much progress is made in semiconductors owing to the difficulty in injecting spins into them, which has only very recently been overcome with the combined efforts of many research groups around the world. The key motivations for semiconductor spintronics are their ease in integration with the existing semiconductor technology along with the gate controllability. At present semiconductor based spintronic devices are mostly lateral and are showing a very poor performance compared to their metal or insulator based vertical counterparts. The objective of this thesis is to analyze these devices based on spin-transport models and simulations. At first a lateral spin-valve device is modeled with the spin-diffusion equation based semiclassical approach. Identifying the important issues regarding the device performance, a compact circuit equivalent model is presented which would help to improve the device design. It is found that the regions outside the current path also have a significant influence on the device performance under certain conditions, which is ordinarily neglected when only charge transport is considered. Next, a modified spin-valve structure is studied where the spin signal is controlled with a gate in between the injecting and detecting contacts. The gate is used to modulate the rashba spin-orbit coupling of the channel which, in turn, modulates the spin-valve signal. The idea of gate controlled spin manipulation was originally proposed by Datta and Das back in 1990 and is called 'Datta-Das' effect. In this thesis, we have extended the model described in the original proposal to include the influence of channel dimensions on the nature of electron flow and the contact dimensions on the magnitude and phase of the spin-valve signal. In order to capture the spin-orbit effect a non-equilibrium Green's function (NEGF) based quantum transport model for spin-valve device have been developed which is also explained with simple theoretical treatment based on stationary phase approximation. The model is also compared against a recent experiment that demonstrated such gate modulated spin-valve effect. This thesis also evaluates the possibility of gate controlled magnetization reversal or spin-torque effect as a means to validate this, so called, 'Datta-Das' effect on a more solid footing. Finally, the scope for utilizing topological insulator material in semiconductor spintronics is discussed as a possible future work for this thesis.

Automated prediction of protein function and detection of functional sites from structure.

PubMed

Pazos, Florencio; Sternberg, Michael J E

2004-10-12

Current structural genomics projects are yielding structures for proteins whose functions are unknown. Accordingly, there is a pressing requirement for computational methods for function prediction. Here we present PHUNCTIONER, an automatic method for structure-based function prediction using automatically extracted functional sites (residues associated to functions). The method relates proteins with the same function through structural alignments and extracts 3D profiles of conserved residues. Functional features to train the method are extracted from the Gene Ontology (GO) database. The method extracts these features from the entire GO hierarchy and hence is applicable across the whole range of function specificity. 3D profiles associated with 121 GO annotations were extracted. We tested the power of the method both for the prediction of function and for the extraction of functional sites. The success of function prediction by our method was compared with the standard homology-based method. In the zone of low sequence similarity (approximately 15%), our method assigns the correct GO annotation in 90% of the protein structures considered, approximately 20% higher than inheritance of function from the closest homologue.

Simple Test Functions in Meshless Local Petrov-Galerkin Methods

NASA Technical Reports Server (NTRS)

Raju, Ivatury S.

2016-01-01

Two meshless local Petrov-Galerkin (MLPG) methods based on two different trial functions but that use a simple linear test function were developed for beam and column problems. These methods used generalized moving least squares (GMLS) and radial basis (RB) interpolation functions as trial functions. These two methods were tested on various patch test problems. Both methods passed the patch tests successfully. Then the methods were applied to various beam vibration problems and problems involving Euler and Beck's columns. Both methods yielded accurate solutions for all problems studied. The simple linear test function offers considerable savings in computing efforts as the domain integrals involved in the weak form are avoided. The two methods based on this simple linear test function method produced accurate results for frequencies and buckling loads. Of the two methods studied, the method with radial basis trial functions is very attractive as the method is simple, accurate, and robust.

Methods of Constructing a Blended Performance Function Suitable for Formation Flight

NASA Technical Reports Server (NTRS)

Ryan, John J.

2017-01-01

This paper presents two methods for constructing an approximate performance function of a desired parameter using correlated parameters. The methods are useful when real-time measurements of a desired performance function are not available to applications such as extremum-seeking control systems. The first method approximates an a priori measured or estimated desired performance function by combining real-time measurements of readily available correlated parameters. The parameters are combined using a weighting vector determined from a minimum-squares optimization to form a blended performance function. The blended performance function better matches the desired performance function mini- mum than single-measurement performance functions. The second method expands upon the first by replacing the a priori data with near-real-time measurements of the desired performance function. The resulting blended performance function weighting vector is up- dated when measurements of the desired performance function are available. Both methods are applied to data collected during formation- flight-for-drag-reduction flight experiments.

Comparison of genetic algorithms with conjugate gradient methods

NASA Technical Reports Server (NTRS)

Bosworth, J. L.; Foo, N. Y.; Zeigler, B. P.

1972-01-01

Genetic algorithms for mathematical function optimization are modeled on search strategies employed in natural adaptation. Comparisons of genetic algorithms with conjugate gradient methods, which were made on an IBM 1800 digital computer, show that genetic algorithms display superior performance over gradient methods for functions which are poorly behaved mathematically, for multimodal functions, and for functions obscured by additive random noise. Genetic methods offer performance comparable to gradient methods for many of the standard functions.

On computing closed forms for summations. [polynomials and rational functions

NASA Technical Reports Server (NTRS)

Moenck, R.

1977-01-01

The problem of finding closed forms for a summation involving polynomials and rational functions is considered. A method closely related to Hermite's method for integration of rational functions derived. The method expresses the sum of a rational function as a rational function part and a transcendental part involving derivatives of the gamma function.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

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.

Meshless Local Petrov-Galerkin Euler-Bernoulli Beam Problems: A Radial Basis Function Approach

NASA Technical Reports Server (NTRS)

Raju, I. S.; Phillips, D. R.; Krishnamurthy, T.

2003-01-01

A radial basis function implementation of the meshless local Petrov-Galerkin (MLPG) method is presented to study Euler-Bernoulli beam problems. Radial basis functions, rather than generalized moving least squares (GMLS) interpolations, are used to develop the trial functions. This choice yields a computationally simpler method as fewer matrix inversions and multiplications are required than when GMLS interpolations are used. Test functions are chosen as simple weight functions as in the conventional MLPG method. Compactly and noncompactly supported radial basis functions are considered. The non-compactly supported cubic radial basis function is found to perform very well. Results obtained from the radial basis MLPG method are comparable to those obtained using the conventional MLPG method for mixed boundary value problems and problems with discontinuous loading conditions.

Estimating parameter of Rayleigh distribution by using Maximum Likelihood method and Bayes method

NASA Astrophysics Data System (ADS)

Ardianti, Fitri; Sutarman

2018-01-01

In this paper, we use Maximum Likelihood estimation and Bayes method under some risk function to estimate parameter of Rayleigh distribution to know the best method. The prior knowledge which used in Bayes method is Jeffrey’s non-informative prior. Maximum likelihood estimation and Bayes method under precautionary loss function, entropy loss function, loss function-L 1 will be compared. We compare these methods by bias and MSE value using R program. After that, the result will be displayed in tables to facilitate the comparisons.

[Methodological aspects related to the determination of the relative renal function using 99mTC MAG3].

PubMed

Ladrón De Guevara Hernández, D; Ham, H; Franken, P; Piepsz, A; Lobo Sotomayor, G

2002-01-01

The aim of the study was to evaluate three different methods for calculating the split renal function in patients with only one functioning kidney, keeping in mind that the split function should be zero on the side of the non-functioning kidney. We retrospectively selected 28 99mTc MAG3 renograms performed in children, 12 with unilateral nephrectomy, 4 with unilateral agenesis and 12 with a non-functioning kidney. A renal and perirenal region of interest (ROI) were delineated around the functioning kidney. The ROIs around the empty kidney were drawn symmetrically to the contralateral side. The split renal function was calculated using three different methods, the integral method, the slope method and the Patlak-Rutland algorithm. For the whole group of 28 kidneys as well as for the three categories of patients, the three methods provided a split function on the side of the non-functioning kidney close to the zero value, regardless of whether the empty kidney was the left or the right one. We recommend the use of the integral method for the whole range of split renal function with 99mTc MAG3. No significant improvement was obtained by means of the more sophisticated Patlak-Rutland method.

Hip joint center localisation: A biomechanical application to hip arthroplasty population

PubMed Central

Bouffard, Vicky; Begon, Mickael; Champagne, Annick; Farhadnia, Payam; Vendittoli, Pascal-André; Lavigne, Martin; Prince, François

2012-01-01

AIM: To determine hip joint center (HJC) location on hip arthroplasty population comparing predictive and functional approaches with radiographic measurements. METHODS: The distance between the HJC and the mid-pelvis was calculated and compared between the three approaches. The localisation error between the predictive and functional approach was compared using the radiographic measurements as the reference. The operated leg was compared to the non-operated leg. RESULTS: A significant difference was found for the distance between the HJC and the mid-pelvis when comparing the predictive and functional method. The functional method leads to fewer errors. A statistical difference was found for the localization error between the predictive and functional method. The functional method is twice more precise. CONCLUSION: Although being more individualized, the functional method improves HJC localization and should be used in three-dimensional gait analysis. PMID:22919569

Quantum phase space with a basis of Wannier functions

NASA Astrophysics Data System (ADS)

Fang, Yuan; Wu, Fan; Wu, Biao

2018-02-01

A quantum phase space with Wannier basis is constructed: (i) classical phase space is divided into Planck cells; (ii) a complete set of Wannier functions are constructed with the combination of Kohn’s method and Löwdin method such that each Wannier function is localized at a Planck cell. With these Wannier functions one can map a wave function unitarily onto phase space. Various examples are used to illustrate our method and compare it to Wigner function. The advantage of our method is that it can smooth out the oscillations in wave functions without losing any information and is potentially a better tool in studying quantum-classical correspondence. In addition, we point out that our method can be used for time-frequency analysis of signals.

Relationships between the decoupled and coupled transfer functions: Theoretical studies and experimental validation

NASA Astrophysics Data System (ADS)

Wang, Zengwei; Zhu, Ping; Liu, Zhao

2018-01-01

A generalized method for predicting the decoupled transfer functions based on in-situ transfer functions is proposed. The method allows predicting the decoupled transfer functions using coupled transfer functions, without disassembling the system. Two ways to derive relationships between the decoupled and coupled transfer functions are presented. Issues related to immeasurability of coupled transfer functions are also discussed. The proposed method is validated by numerical and experimental case studies.

A review of contemporary methods for the presentation of scientific uncertainty.

PubMed

Makinson, K A; Hamby, D M; Edwards, J A

2012-12-01

Graphic methods for displaying uncertainty are often the most concise and informative way to communicate abstract concepts. Presentation methods currently in use for the display and interpretation of scientific uncertainty are reviewed. Numerous subjective and objective uncertainty display methods are presented, including qualitative assessments, node and arrow diagrams, standard statistical methods, box-and-whisker plots,robustness and opportunity functions, contribution indexes, probability density functions, cumulative distribution functions, and graphical likelihood functions.

Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data.

PubMed

Taugourdeau, Simon; Villerd, Jean; Plantureux, Sylvain; Huguenin-Elie, Olivier; Amiaud, Bernard

2014-04-01

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete-case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete-case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices.

Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data

PubMed Central

Taugourdeau, Simon; Villerd, Jean; Plantureux, Sylvain; Huguenin-Elie, Olivier; Amiaud, Bernard

2014-01-01

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete-case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete-case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices. PMID:24772273

Yager’s ranking method for solving the trapezoidal fuzzy number linear programming

NASA Astrophysics Data System (ADS)

Karyati; Wutsqa, D. U.; Insani, N.

2018-03-01

In the previous research, the authors have studied the fuzzy simplex method for trapezoidal fuzzy number linear programming based on the Maleki’s ranking function. We have found some theories related to the term conditions for the optimum solution of fuzzy simplex method, the fuzzy Big-M method, the fuzzy two-phase method, and the sensitivity analysis. In this research, we study about the fuzzy simplex method based on the other ranking function. It is called Yager's ranking function. In this case, we investigate the optimum term conditions. Based on the result of research, it is found that Yager’s ranking function is not like Maleki’s ranking function. Using the Yager’s function, the simplex method cannot work as well as when using the Maleki’s function. By using the Yager’s function, the value of the subtraction of two equal fuzzy numbers is not equal to zero. This condition makes the optimum table of the fuzzy simplex table is undetected. As a result, the simplified fuzzy simplex table becomes stopped and does not reach the optimum solution.

Measuring Spatial Accessibility of Health Care Providers – Introduction of a Variable Distance Decay Function within the Floating Catchment Area (FCA) Method

PubMed Central

Groneberg, David A.

2016-01-01

We integrated recent improvements within the floating catchment area (FCA) method family into an integrated ‘iFCA`method. Within this method we focused on the distance decay function and its parameter. So far only distance decay functions with constant parameters have been applied. Therefore, we developed a variable distance decay function to be used within the FCA method. We were able to replace the impedance coefficient β by readily available distribution parameter (i.e. median and standard deviation (SD)) within a logistic based distance decay function. Hence, the function is shaped individually for every single population location by the median and SD of all population-to-provider distances within a global catchment size. Theoretical application of the variable distance decay function showed conceptually sound results. Furthermore, the existence of effective variable catchment sizes defined by the asymptotic approach to zero of the distance decay function was revealed, satisfying the need for variable catchment sizes. The application of the iFCA method within an urban case study in Berlin (Germany) confirmed the theoretical fit of the suggested method. In summary, we introduced for the first time, a variable distance decay function within an integrated FCA method. This function accounts for individual travel behaviors determined by the distribution of providers. Additionally, the function inherits effective variable catchment sizes and therefore obviates the need for determining variable catchment sizes separately. PMID:27391649

The Relation of Finite Element and Finite Difference Methods

NASA Technical Reports Server (NTRS)

Vinokur, M.

1976-01-01

Finite element and finite difference methods are examined in order to bring out their relationship. It is shown that both methods use two types of discrete representations of continuous functions. They differ in that finite difference methods emphasize the discretization of independent variable, while finite element methods emphasize the discretization of dependent variable (referred to as functional approximations). An important point is that finite element methods use global piecewise functional approximations, while finite difference methods normally use local functional approximations. A general conclusion is that finite element methods are best designed to handle complex boundaries, while finite difference methods are superior for complex equations. It is also shown that finite volume difference methods possess many of the advantages attributed to finite element methods.

The solitary wave solution of coupled Klein-Gordon-Zakharov equations via two different numerical methods

NASA Astrophysics Data System (ADS)

Dehghan, Mehdi; Nikpour, Ahmad

2013-09-01

In this research, we propose two different methods to solve the coupled Klein-Gordon-Zakharov (KGZ) equations: the Differential Quadrature (DQ) and Globally Radial Basis Functions (GRBFs) methods. In the DQ method, the derivative value of a function with respect to a point is directly approximated by a linear combination of all functional values in the global domain. The principal work in this method is the determination of weight coefficients. We use two ways for obtaining these coefficients: cosine expansion (CDQ) and radial basis functions (RBFs-DQ), the former is a mesh-based method and the latter categorizes in the set of meshless methods. Unlike the DQ method, the GRBF method directly substitutes the expression of the function approximation by RBFs into the partial differential equation. The main problem in the GRBFs method is ill-conditioning of the interpolation matrix. Avoiding this problem, we study the bases introduced in Pazouki and Schaback (2011) [44]. Some examples are presented to compare the accuracy and easy implementation of the proposed methods. In numerical examples, we concentrate on Inverse Multiquadric (IMQ) and second-order Thin Plate Spline (TPS) radial basis functions. The variable shape parameter (exponentially and random) strategies are applied in the IMQ function and the results are compared with the constant shape parameter.

A survey of functional behavior assessment methods used by behavior analysts in practice.

PubMed

Oliver, Anthony C; Pratt, Leigh A; Normand, Matthew P

2015-12-01

To gather information about the functional behavior assessment (FBA) methods behavior analysts use in practice, we sent a web-based survey to 12,431 behavior analysts certified by the Behavior Analyst Certification Board. Ultimately, 724 surveys were returned, with the results suggesting that most respondents regularly use FBA methods, especially descriptive assessments. Moreover, the data suggest that the majority of students are being formally taught about the various FBA methods and that educators are emphasizing the range of FBA methods in their teaching. However, less than half of the respondents reported using functional analyses in practice, although many considered descriptive assessments and functional analyses to be the most useful FBA methods. Most respondents reported using informant and descriptive assessments more frequently than functional analyses, and a majority of respondents indicated that they "never" or "almost never" used functional analyses to identify the function of behavior. © Society for the Experimental Analysis of Behavior.

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.

Performance of wave function and density functional methods for water hydrogen bond spin-spin coupling constants.

PubMed

García de la Vega, J M; Omar, S; San Fabián, J

2017-04-01

Spin-spin coupling constants in water monomer and dimer have been calculated using several wave function and density functional-based methods. CCSD, MCSCF, and SOPPA wave functions methods yield similar results, specially when an additive approach is used with the MCSCF. Several functionals have been used to analyze their performance with the Jacob's ladder and a set of functionals with different HF exchange were tested. Functionals with large HF exchange appropriately predict 1 J O H , 2 J H H and 2h J O O couplings, while 1h J O H is better calculated with functionals that include a reduced fraction of HF exchange. Accurate functionals for 1 J O H and 2 J H H have been tested in a tetramer water model. The hydrogen bond effects on these intramolecular couplings are additive when they are calculated by SOPPA(CCSD) wave function and DFT methods. Graphical Abstract Evaluation of the additive effect of the hydrogen bond on spin-spin coupling constants of water using WF and DFT methods.

Improvements to the kernel function method of steady, subsonic lifting surface theory

NASA Technical Reports Server (NTRS)

Medan, R. T.

1974-01-01

The application of a kernel function lifting surface method to three dimensional, thin wing theory is discussed. A technique for determining the influence functions is presented. The technique is shown to require fewer quadrature points, while still calculating the influence functions accurately enough to guarantee convergence with an increasing number of spanwise quadrature points. The method also treats control points on the wing leading and trailing edges. The report introduces and employs an aspect of the kernel function method which apparently has never been used before and which significantly enhances the efficiency of the kernel function approach.

On the Convergence Analysis of the Optimized Gradient Method.

PubMed

Kim, Donghwan; Fessler, Jeffrey A

2017-01-01

This paper considers the problem of unconstrained minimization of smooth convex functions having Lipschitz continuous gradients with known Lipschitz constant. We recently proposed the optimized gradient method for this problem and showed that it has a worst-case convergence bound for the cost function decrease that is twice as small as that of Nesterov's fast gradient method, yet has a similarly efficient practical implementation. Drori showed recently that the optimized gradient method has optimal complexity for the cost function decrease over the general class of first-order methods. This optimality makes it important to study fully the convergence properties of the optimized gradient method. The previous worst-case convergence bound for the optimized gradient method was derived for only the last iterate of a secondary sequence. This paper provides an analytic convergence bound for the primary sequence generated by the optimized gradient method. We then discuss additional convergence properties of the optimized gradient method, including the interesting fact that the optimized gradient method has two types of worstcase functions: a piecewise affine-quadratic function and a quadratic function. These results help complete the theory of an optimal first-order method for smooth convex minimization.

On the Convergence Analysis of the Optimized Gradient Method

PubMed Central

Kim, Donghwan; Fessler, Jeffrey A.

2016-01-01

This paper considers the problem of unconstrained minimization of smooth convex functions having Lipschitz continuous gradients with known Lipschitz constant. We recently proposed the optimized gradient method for this problem and showed that it has a worst-case convergence bound for the cost function decrease that is twice as small as that of Nesterov’s fast gradient method, yet has a similarly efficient practical implementation. Drori showed recently that the optimized gradient method has optimal complexity for the cost function decrease over the general class of first-order methods. This optimality makes it important to study fully the convergence properties of the optimized gradient method. The previous worst-case convergence bound for the optimized gradient method was derived for only the last iterate of a secondary sequence. This paper provides an analytic convergence bound for the primary sequence generated by the optimized gradient method. We then discuss additional convergence properties of the optimized gradient method, including the interesting fact that the optimized gradient method has two types of worstcase functions: a piecewise affine-quadratic function and a quadratic function. These results help complete the theory of an optimal first-order method for smooth convex minimization. PMID:28461707

A Meshless Method Using Radial Basis Functions for Beam Bending Problems

NASA Technical Reports Server (NTRS)

Raju, I. S.; Phillips, D. R.; Krishnamurthy, T.

2004-01-01

A meshless local Petrov-Galerkin (MLPG) method that uses radial basis functions (RBFs) as trial functions in the study of Euler-Bernoulli beam problems is presented. RBFs, rather than generalized moving least squares (GMLS) interpolations, are used to develop the trial functions. This choice yields a computationally simpler method as fewer matrix inversions and multiplications are required than when GMLS interpolations are used. Test functions are chosen as simple weight functions as they are in the conventional MLPG method. Compactly and noncompactly supported RBFs are considered. Noncompactly supported cubic RBFs are found to be preferable. Patch tests, mixed boundary value problems, and problems with complex loading conditions are considered. Results obtained from the radial basis MLPG method are either of comparable or better accuracy than those obtained when using the conventional MLPG method.

Solutions to Kuessner's integral equation in unsteady flow using local basis functions

NASA Technical Reports Server (NTRS)

Fromme, J. A.; Halstead, D. W.

1975-01-01

The computational procedure and numerical results are presented for a new method to solve Kuessner's integral equation in the case of subsonic compressible flow about harmonically oscillating planar surfaces with controls. Kuessner's equation is a linear transformation from pressure to normalwash. The unknown pressure is expanded in terms of prescribed basis functions and the unknown basis function coefficients are determined in the usual manner by satisfying the given normalwash distribution either collocationally or in the complex least squares sense. The present method of solution differs from previous ones in that the basis functions are defined in a continuous fashion over a relatively small portion of the aerodynamic surface and are zero elsewhere. This method, termed the local basis function method, combines the smoothness and accuracy of distribution methods with the simplicity and versatility of panel methods. Predictions by the local basis function method for unsteady flow are shown to be in excellent agreement with other methods. Also, potential improvements to the present method and extensions to more general classes of solutions are discussed.

Computer program for calculating and fitting thermodynamic functions

NASA Technical Reports Server (NTRS)

Mcbride, Bonnie J.; Gordon, Sanford

1992-01-01

A computer program is described which (1) calculates thermodynamic functions (heat capacity, enthalpy, entropy, and free energy) for several optional forms of the partition function, (2) fits these functions to empirical equations by means of a least-squares fit, and (3) calculates, as a function of temperture, heats of formation and equilibrium constants. The program provides several methods for calculating ideal gas properties. For monatomic gases, three methods are given which differ in the technique used for truncating the partition function. For diatomic and polyatomic molecules, five methods are given which differ in the corrections to the rigid-rotator harmonic-oscillator approximation. A method for estimating thermodynamic functions for some species is also given.

Revealing protein functions based on relationships of interacting proteins and GO terms.

PubMed

Teng, Zhixia; Guo, Maozu; Liu, Xiaoyan; Tian, Zhen; Che, Kai

2017-09-20

In recent years, numerous computational methods predicted protein function based on the protein-protein interaction (PPI) network. These methods supposed that two proteins share the same function if they interact with each other. However, it is reported by recent studies that the functions of two interacting proteins may be just related. It will mislead the prediction of protein function. Therefore, there is a need for investigating the functional relationship between interacting proteins. In this paper, the functional relationship between interacting proteins is studied and a novel method, called as GoDIN, is advanced to annotate functions of interacting proteins in Gene Ontology (GO) context. It is assumed that the functional difference between interacting proteins can be expressed by semantic difference between GO term and its relatives. Thus, the method uses GO term and its relatives to annotate the interacting proteins separately according to their functional roles in the PPI network. The method is validated by a series of experiments and compared with the concerned method. The experimental results confirm the assumption and suggest that GoDIN is effective on predicting functions of protein. This study demonstrates that: (1) interacting proteins are not equal in the PPI network, and their function may be same or similar, or just related; (2) functional difference between interacting proteins can be measured by their degrees in the PPI network; (3) functional relationship between interacting proteins can be expressed by relationship between GO term and its relatives.

Prediction of EST functional relationships via literature mining with user-specified parameters.

PubMed

Wang, Hei-Chia; Huang, Tian-Hsiang

2009-04-01

The massive amount of expressed sequence tags (ESTs) gathered over recent years has triggered great interest in efficient applications for genomic research. In particular, EST functional relationships can be used to determine a possible gene network for biological processes of interest. In recent years, many researchers have tried to determine EST functional relationships by analyzing the biological literature. However, it has been challenging to find efficient prediction methods. Moreover, an annotated EST is usually associated with many functions, so successful methods must be able to distinguish between relevant and irrelevant functions based on user specifications. This paper proposes a method to discover functional relationships between ESTs of interest by analyzing literature from the Medical Literature Analysis and Retrieval System Online, with user-specified parameters for selecting keywords. This method performs better than the multiple kernel documents method in setting up a specific threshold for gathering materials. The method is also able to uncover known functional relationships, as shown by a comparison with the Kyoto Encyclopedia of Genes and Genomes database. The reliable EST relationships predicted by the proposed method can help to construct gene networks for specific biological functions of interest.

Dual number algebra method for Green's function derivatives in 3D magneto-electro-elasticity

NASA Astrophysics Data System (ADS)

Dziatkiewicz, Grzegorz

2018-01-01

The Green functions are the basic elements of the boundary element method. To obtain the boundary integral formulation the Green function and its derivative should be known for the considered differential operator. Today the interesting group of materials are electronic composites. The special case of the electronic composite is the magnetoelectroelastic continuum. The mentioned continuum is a model of the piezoelectric-piezomagnetic composites. The anisotropy of their physical properties makes the problem of Green's function determination very difficult. For that reason Green's functions for the magnetoelectroelastic continuum are not known in the closed form and numerical methods should be applied to determine such Green's functions. These means that the problem of the accurate and simply determination of Green's function derivatives is even harder. Therefore in the present work the dual number algebra method is applied to calculate numerically the derivatives of 3D Green's functions for the magnetoelectroelastic materials. The introduced method is independent on the step size and it can be treated as a special case of the automatic differentiation method. Therefore, the dual number algebra method can be applied as a tool for checking the accuracy of the well-known finite difference schemes.

Relationships between the generalized functional method and other methods of nonimaging optical design.

PubMed

Bortz, John; Shatz, Narkis

2011-04-01

The recently developed generalized functional method provides a means of designing nonimaging concentrators and luminaires for use with extended sources and receivers. We explore the mathematical relationships between optical designs produced using the generalized functional method and edge-ray, aplanatic, and simultaneous multiple surface (SMS) designs. Edge-ray and dual-surface aplanatic designs are shown to be special cases of generalized functional designs. In addition, it is shown that dual-surface SMS designs are closely related to generalized functional designs and that certain computational advantages accrue when the two design methods are combined. A number of examples are provided. © 2011 Optical Society of America

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.

Implementation and benchmark of a long-range corrected functional in the density functional based tight-binding method

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

Lutsker, V.; Niehaus, T. A., E-mail: thomas.niehaus@physik.uni-regensburg.de; Aradi, B.

2015-11-14

Bridging the gap between first principles methods and empirical schemes, the density functional based tight-binding method (DFTB) has become a versatile tool in predictive atomistic simulations over the past years. One of the major restrictions of this method is the limitation to local or gradient corrected exchange-correlation functionals. This excludes the important class of hybrid or long-range corrected functionals, which are advantageous in thermochemistry, as well as in the computation of vibrational, photoelectron, and optical spectra. The present work provides a detailed account of the implementation of DFTB for a long-range corrected functional in generalized Kohn-Sham theory. We apply themore » method to a set of organic molecules and compare ionization potentials and electron affinities with the original DFTB method and higher level theory. The new scheme cures the significant overpolarization in electric fields found for local DFTB, which parallels the functional dependence in first principles density functional theory (DFT). At the same time, the computational savings with respect to full DFT calculations are not compromised as evidenced by numerical benchmark data.« less

A computational method for solving stochastic Itô–Volterra integral equations based on stochastic operational matrix for generalized hat basis functions

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

Heydari, M.H., E-mail: heydari@stu.yazd.ac.ir; The Laboratory of Quantum Information Processing, Yazd University, Yazd; Hooshmandasl, M.R., E-mail: hooshmandasl@yazd.ac.ir

2014-08-01

In this paper, a new computational method based on the generalized hat basis functions is proposed for solving stochastic Itô–Volterra integral equations. In this way, a new stochastic operational matrix for generalized hat functions on the finite interval [0,T] is obtained. By using these basis functions and their stochastic operational matrix, such problems can be transformed into linear lower triangular systems of algebraic equations which can be directly solved by forward substitution. Also, the rate of convergence of the proposed method is considered and it has been shown that it is O(1/(n{sup 2}) ). Further, in order to show themore » accuracy and reliability of the proposed method, the new approach is compared with the block pulse functions method by some examples. The obtained results reveal that the proposed method is more accurate and efficient in comparison with the block pule functions method.« less

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2013-01-01

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

A threshold selection method based on edge preserving

NASA Astrophysics Data System (ADS)

Lou, Liantang; Dan, Wei; Chen, Jiaqi

2015-12-01

A method of automatic threshold selection for image segmentation is presented. An optimal threshold is selected in order to preserve edge of image perfectly in image segmentation. The shortcoming of Otsu's method based on gray-level histograms is analyzed. The edge energy function of bivariate continuous function is expressed as the line integral while the edge energy function of image is simulated by discretizing the integral. An optimal threshold method by maximizing the edge energy function is given. Several experimental results are also presented to compare with the Otsu's method.

Compositions and methods for hydrocarbon functionalization

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

Gunnoe, Thomas Brent; Fortman, George; Boaz, Nicholas C.

Embodiments of the present disclosure provide for methods of hydrocarbon functionalization, methods and systems for converting a hydrocarbon into a compound including at least one group ((e.g., hydroxyl group) (e.g., methane to methanol)), functionalized hydrocarbons, and the like.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

PubMed

Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

2016-11-01

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. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is usually limited by sampling size. Sequence conservation-based methods are further confounded by structural constraints and multifunctionality of proteins. Here we present a method that can systematically identify and annotate functional residues of a given protein. We used a high-throughput functional profiling platform to identify essential residues. Coupling it with homologous-structure comparison, we were able to annotate multiple functions of proteins. We demonstrated the method with the PB1 protein of influenza A virus and identified novel functional residues in addition to its canonical function as an RNA-dependent RNA polymerase. Not limited to virology, this method is generally applicable to other proteins that can be functionally selected and about which homologous-structure information is available. Copyright © 2016 Du et al.

An indirect method for numerical optimization using the Kreisselmeir-Steinhauser function

NASA Technical Reports Server (NTRS)

Wrenn, Gregory A.

1989-01-01

A technique is described for converting a constrained optimization problem into an unconstrained problem. The technique transforms one of more objective functions into reduced objective functions, which are analogous to goal constraints used in the goal programming method. These reduced objective functions are appended to the set of constraints and an envelope of the entire function set is computed using the Kreisselmeir-Steinhauser function. This envelope function is then searched for an unconstrained minimum. The technique may be categorized as a SUMT algorithm. Advantages of this approach are the use of unconstrained optimization methods to find a constrained minimum without the draw down factor typical of penalty function methods, and that the technique may be started from the feasible or infeasible design space. In multiobjective applications, the approach has the advantage of locating a compromise minimum design without the need to optimize for each individual objective function separately.

Functional comparison of microarray data across multiple platforms using the method of percentage of overlapping functions.

PubMed

Li, Zhiguang; Kwekel, Joshua C; Chen, Tao

2012-01-01

Functional comparison across microarray platforms is used to assess the comparability or similarity of the biological relevance associated with the gene expression data generated by multiple microarray platforms. Comparisons at the functional level are very important considering that the ultimate purpose of microarray technology is to determine the biological meaning behind the gene expression changes under a specific condition, not just to generate a list of genes. Herein, we present a method named percentage of overlapping functions (POF) and illustrate how it is used to perform the functional comparison of microarray data generated across multiple platforms. This method facilitates the determination of functional differences or similarities in microarray data generated from multiple array platforms across all the functions that are presented on these platforms. This method can also be used to compare the functional differences or similarities between experiments, projects, or laboratories.

Three-dimensional computed tomographic volumetry precisely predicts the postoperative pulmonary function.

PubMed

Kobayashi, Keisuke; Saeki, Yusuke; Kitazawa, Shinsuke; Kobayashi, Naohiro; Kikuchi, Shinji; Goto, Yukinobu; Sakai, Mitsuaki; Sato, Yukio

2017-11-01

It is important to accurately predict the patient's postoperative pulmonary function. The aim of this study was to compare the accuracy of predictions of the postoperative residual pulmonary function obtained with three-dimensional computed tomographic (3D-CT) volumetry with that of predictions obtained with the conventional segment-counting method. Fifty-three patients scheduled to undergo lung cancer resection, pulmonary function tests, and computed tomography were enrolled in this study. The postoperative residual pulmonary function was predicted based on the segment-counting and 3D-CT volumetry methods. The predicted postoperative values were compared with the results of postoperative pulmonary function tests. Regarding the linear correlation coefficients between the predicted postoperative values and the measured values, those obtained using the 3D-CT volumetry method tended to be higher than those acquired using the segment-counting method. In addition, the variations between the predicted and measured values were smaller with the 3D-CT volumetry method than with the segment-counting method. These results were more obvious in COPD patients than in non-COPD patients. Our findings suggested that the 3D-CT volumetry was able to predict the residual pulmonary function more accurately than the segment-counting method, especially in patients with COPD. This method might lead to the selection of appropriate candidates for surgery among patients with a marginal pulmonary function.

Biologically plausible particulate air pollution mortality concentration-response functions.

PubMed Central

Roberts, Steven

2004-01-01

In this article I introduce an alternative method for estimating particulate air pollution mortality concentration-response functions. This method constrains the particulate air pollution mortality concentration-response function to be biologically plausible--that is, a non-decreasing function of the particulate air pollution concentration. Using time-series data from Cook County, Illinois, the proposed method yields more meaningful particulate air pollution mortality concentration-response function estimates with an increase in statistical accuracy. PMID:14998745

Functional connectivity change as shared signal dynamics

PubMed Central

Cole, Michael W.; Yang, Genevieve J.; Murray, John D.; Repovš, Grega; Anticevic, Alan

2015-01-01

Background An increasing number of neuroscientific studies gain insights by focusing on differences in functional connectivity – between groups, individuals, temporal windows, or task conditions. We found using simulations that additional insights into such differences can be gained by forgoing variance normalization, a procedure used by most functional connectivity measures. Simulations indicated that these functional connectivity measures are sensitive to increases in independent fluctuations (unshared signal) in time series, consistently reducing functional connectivity estimates (e.g., correlations) even though such changes are unrelated to corresponding fluctuations (shared signal) between those time series. This is inconsistent with the common notion of functional connectivity as the amount of inter-region interaction. New Method Simulations revealed that a version of correlation without variance normalization – covariance – was able to isolate differences in shared signal, increasing interpretability of observed functional connectivity change. Simulations also revealed cases problematic for non-normalized methods, leading to a “covariance conjunction” method combining the benefits of both normalized and non-normalized approaches. Results We found that covariance and covariance conjunction methods can detect functional connectivity changes across a variety of tasks and rest in both clinical and non-clinical functional MRI datasets. Comparison with Existing Method(s) We verified using a variety of tasks and rest in both clinical and non-clinical functional MRI datasets that it matters in practice whether correlation, covariance, or covariance conjunction methods are used. Conclusions These results demonstrate the practical and theoretical utility of isolating changes in shared signal, improving the ability to interpret observed functional connectivity change. PMID:26642966

Reliability of functional and predictive methods to estimate the hip joint centre in human motion analysis in healthy adults.

PubMed

Kainz, Hans; Hajek, Martin; Modenese, Luca; Saxby, David J; Lloyd, David G; Carty, Christopher P

2017-03-01

In human motion analysis predictive or functional methods are used to estimate the location of the hip joint centre (HJC). It has been shown that the Harrington regression equations (HRE) and geometric sphere fit (GSF) method are the most accurate predictive and functional methods, respectively. To date, the comparative reliability of both approaches has not been assessed. The aims of this study were to (1) compare the reliability of the HRE and the GSF methods, (2) analyse the impact of the number of thigh markers used in the GSF method on the reliability, (3) evaluate how alterations to the movements that comprise the functional trials impact HJC estimations using the GSF method, and (4) assess the influence of the initial guess in the GSF method on the HJC estimation. Fourteen healthy adults were tested on two occasions using a three-dimensional motion capturing system. Skin surface marker positions were acquired while participants performed quite stance, perturbed and non-perturbed functional trials, and walking trials. Results showed that the HRE were more reliable in locating the HJC than the GSF method. However, comparison of inter-session hip kinematics during gait did not show any significant difference between the approaches. Different initial guesses in the GSF method did not result in significant differences in the final HJC location. The GSF method was sensitive to the functional trial performance and therefore it is important to standardize the functional trial performance to ensure a repeatable estimate of the HJC when using the GSF method. Copyright © 2017 Elsevier B.V. All rights reserved.

On a method for generating inequalities for the zeros of certain functions

NASA Astrophysics Data System (ADS)

Gatteschi, Luigi; Giordano, Carla

2007-10-01

In this paper we describe a general procedure which yields inequalities satisfied by the zeros of a given function. The method requires the knowledge of a two-term approximation of the function with bound for the error term. The method was successfully applied many years ago [L. Gatteschi, On the zeros of certain functions with application to Bessel functions, Nederl. Akad. Wetensch. Proc. Ser. 55(3)(1952), Indag. Math. 14(1952) 224-229] and more recently too [L. Gatteschi and C. Giordano, Error bounds for McMahon's asymptotic approximations of the zeros of the Bessel functions, Integral Transform Special Functions, 10(2000) 41-56], to the zeros of the Bessel functions of the first kind. Here, we present the results of the application of the method to get inequalities satisfied by the zeros of the derivative of the function . This function plays an important role in the asymptotic study of the stationary points of the solutions of certain differential equations.

Protein-protein interaction network-based detection of functionally similar proteins within species.

PubMed

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

A time-frequency analysis method to obtain stable estimates of magnetotelluric response function based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Cai, Jianhua

2017-05-01

The time-frequency analysis method represents signal as a function of time and frequency, and it is considered a powerful tool for handling arbitrary non-stationary time series by using instantaneous frequency and instantaneous amplitude. It also provides a possible alternative to the analysis of the non-stationary magnetotelluric (MT) signal. Based on the Hilbert-Huang transform (HHT), a time-frequency analysis method is proposed to obtain stable estimates of the magnetotelluric response function. In contrast to conventional methods, the response function estimation is performed in the time-frequency domain using instantaneous spectra rather than in the frequency domain, which allows for imaging the response parameter content as a function of time and frequency. The theory of the method is presented and the mathematical model and calculation procedure, which are used to estimate response function based on HHT time-frequency spectrum, are discussed. To evaluate the results, response function estimates are compared with estimates from a standard MT data processing method based on the Fourier transform. All results show that apparent resistivities and phases, which are calculated from the HHT time-frequency method, are generally more stable and reliable than those determined from the simple Fourier analysis. The proposed method overcomes the drawbacks of the traditional Fourier methods, and the resulting parameter minimises the estimation bias caused by the non-stationary characteristics of the MT data.

An Influence Function Method for Predicting Store Aerodynamic Characteristics during Weapon Separation,

DTIC Science & Technology

1981-05-14

8217 AO-Ail 777 GRUMMAN AEROSPACE CORP BETHPAGE NY F/G 20/4 AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC C--ETCCU) MAY 8 1 R MEYER, A...CENKO, S YARDS UNCLASSIFIED N ’.**~~N**n I EHEEKI j~j .25 Q~4 111110 111_L 5. AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC...extended to their logical conclusion one is led quite naturally to consideration of an " Influence Function Method" for I predicting store aerodynamic

Hierarchical Ensemble Methods for Protein Function Prediction

PubMed Central

2014-01-01

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

A Cubic Radial Basis Function in the MLPG Method for Beam Problems

NASA Technical Reports Server (NTRS)

Raju, I. S.; Phillips, D. R.

2002-01-01

A non-compactly supported cubic radial basis function implementation of the MLPG method for beam problems is presented. The evaluation of the derivatives of the shape functions obtained from the radial basis function interpolation is much simpler than the evaluation of the moving least squares shape function derivatives. The radial basis MLPG yields results as accurate or better than those obtained by the conventional MLPG method for problems with discontinuous and other complex loading conditions.

General method of solving the Schroedinger equation of atoms and molecules

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

Nakatsuji, Hiroshi

2005-12-15

We propose a general method of solving the Schroedinger equation of atoms and molecules. We first construct the wave function having the exact structure, using the ICI (iterative configuration or complement interaction) method and then optimize the variables involved by the variational principle. Based on the scaled Schroedinger equation and related principles, we can avoid the singularity problem of atoms and molecules and formulate a general method of calculating the exact wave functions in an analytical expansion form. We choose initial function {psi}{sub 0} and scaling g function, and then the ICI method automatically generates the wave function that hasmore » the exact structure by using the Hamiltonian of the system. The Hamiltonian contains all the information of the system. The free ICI method provides a flexible and variationally favorable procedure of constructing the exact wave function. We explain the computational procedure of the analytical ICI method routinely performed in our laboratory. Simple examples are given using hydrogen atom for the nuclear singularity case, the Hooke's atom for the electron singularity case, and the helium atom for both cases.« less

A measurement fusion method for nonlinear system identification using a cooperative learning algorithm.

PubMed

Xia, Youshen; Kamel, Mohamed S

2007-06-01

Identification of a general nonlinear noisy system viewed as an estimation of a predictor function is studied in this article. A measurement fusion method for the predictor function estimate is proposed. In the proposed scheme, observed data are first fused by using an optimal fusion technique, and then the optimal fused data are incorporated in a nonlinear function estimator based on a robust least squares support vector machine (LS-SVM). A cooperative learning algorithm is proposed to implement the proposed measurement fusion method. Compared with related identification methods, the proposed method can minimize both the approximation error and the noise error. The performance analysis shows that the proposed optimal measurement fusion function estimate has a smaller mean square error than the LS-SVM function estimate. Moreover, the proposed cooperative learning algorithm can converge globally to the optimal measurement fusion function estimate. Finally, the proposed measurement fusion method is applied to ARMA signal and spatial temporal signal modeling. Experimental results show that the proposed measurement fusion method can provide a more accurate model.

Boundary-integral methods in elasticity and plasticity. [solutions of boundary value problems

NASA Technical Reports Server (NTRS)

Mendelson, A.

1973-01-01

Recently developed methods that use boundary-integral equations applied to elastic and elastoplastic boundary value problems are reviewed. Direct, indirect, and semidirect methods using potential functions, stress functions, and displacement functions are described. Examples of the use of these methods for torsion problems, plane problems, and three-dimensional problems are given. It is concluded that the boundary-integral methods represent a powerful tool for the solution of elastic and elastoplastic problems.

Maximum entropy formalism for the analytic continuation of matrix-valued Green's functions

NASA Astrophysics Data System (ADS)

Kraberger, Gernot J.; Triebl, Robert; Zingl, Manuel; Aichhorn, Markus

2017-10-01

We present a generalization of the maximum entropy method to the analytic continuation of matrix-valued Green's functions. To treat off-diagonal elements correctly based on Bayesian probability theory, the entropy term has to be extended for spectral functions that are possibly negative in some frequency ranges. In that way, all matrix elements of the Green's function matrix can be analytically continued; we introduce a computationally cheap element-wise method for this purpose. However, this method cannot ensure important constraints on the mathematical properties of the resulting spectral functions, namely positive semidefiniteness and Hermiticity. To improve on this, we present a full matrix formalism, where all matrix elements are treated simultaneously. We show the capabilities of these methods using insulating and metallic dynamical mean-field theory (DMFT) Green's functions as test cases. Finally, we apply the methods to realistic material calculations for LaTiO3, where off-diagonal matrix elements in the Green's function appear due to the distorted crystal structure.

Application of Entropy Method in River Health Evaluation Based on Aquatic Ecological Function Regionalization

NASA Astrophysics Data System (ADS)

Shi, Yan-ting; Liu, Jie; Wang, Peng; Zhang, Xu-nuo; Wang, Jun-qiang; Guo, Liang

2017-05-01

With the implementation of water environment management in key basins in China, the monitoring and evaluation system of basins are in urgent need of innovation and upgrading. In view of the heavy workload of existing evaluation methods and the cumbersome calculation of multi-factor weighting method, the idea of using entroy method to assess river health based on aquatic ecological function regionalization was put forward. According to the monitoring data of songhua river in the year of 2011-2015, the entropy weight method was used to calculate the weight of 9 evaluation factors of 29 monitoring sections, and the river health assessment was carried out. In the study area, the river health status of the biodiversity conservation function area (4.111 point) was good, the water conservation function area (3.371 point), the habitat maintenance functional area (3.262 point), the agricultural production maintenance functional area (3.695 point) and the urban supporting functional area (3.399 point) was light pollution.

Methods of Constructing a Blended Performance Function Suitable for Formation Flight

NASA Technical Reports Server (NTRS)

Ryan, Jack

2017-01-01

Two methods for constructing performance functions for formation fight-for-drag-reduction suitable for use with an extreme-seeking control system are presented. The first method approximates an a prior measured or estimated drag-reduction performance function by combining real-time measurements of readily available parameters. The parameters are combined with weightings determined from a minimum squares optimization to form a blended performance function.

Comprehensive reliability allocation method for CNC lathes based on cubic transformed functions of failure mode and effects analysis

NASA Astrophysics Data System (ADS)

Yang, Zhou; Zhu, Yunpeng; Ren, Hongrui; Zhang, Yimin

2015-03-01

Reliability allocation of computerized numerical controlled(CNC) lathes is very important in industry. Traditional allocation methods only focus on high-failure rate components rather than moderate failure rate components, which is not applicable in some conditions. Aiming at solving the problem of CNC lathes reliability allocating, a comprehensive reliability allocation method based on cubic transformed functions of failure modes and effects analysis(FMEA) is presented. Firstly, conventional reliability allocation methods are introduced. Then the limitations of direct combination of comprehensive allocation method with the exponential transformed FMEA method are investigated. Subsequently, a cubic transformed function is established in order to overcome these limitations. Properties of the new transformed functions are discussed by considering the failure severity and the failure occurrence. Designers can choose appropriate transform amplitudes according to their requirements. Finally, a CNC lathe and a spindle system are used as an example to verify the new allocation method. Seven criteria are considered to compare the results of the new method with traditional methods. The allocation results indicate that the new method is more flexible than traditional methods. By employing the new cubic transformed function, the method covers a wider range of problems in CNC reliability allocation without losing the advantages of traditional methods.

Coupled double-distribution-function lattice Boltzmann method for the compressible Navier-Stokes equations.

PubMed

Li, Q; He, Y L; Wang, Y; Tao, W Q

2007-11-01

A coupled double-distribution-function lattice Boltzmann method is developed for the compressible Navier-Stokes equations. Different from existing thermal lattice Boltzmann methods, this method can recover the compressible Navier-Stokes equations with a flexible specific-heat ratio and Prandtl number. In the method, a density distribution function based on a multispeed lattice is used to recover the compressible continuity and momentum equations, while the compressible energy equation is recovered by an energy distribution function. The energy distribution function is then coupled to the density distribution function via the thermal equation of state. In order to obtain an adjustable specific-heat ratio, a constant related to the specific-heat ratio is introduced into the equilibrium energy distribution function. Two different coupled double-distribution-function lattice Boltzmann models are also proposed in the paper. Numerical simulations are performed for the Riemann problem, the double-Mach-reflection problem, and the Couette flow with a range of specific-heat ratios and Prandtl numbers. The numerical results are found to be in excellent agreement with analytical and/or other solutions.

An improved local radial point interpolation method for transient heat conduction analysis

NASA Astrophysics Data System (ADS)

Wang, Feng; Lin, Gao; Zheng, Bao-Jing; Hu, Zhi-Qiang

2013-06-01

The smoothing thin plate spline (STPS) interpolation using the penalty function method according to the optimization theory is presented to deal with transient heat conduction problems. The smooth conditions of the shape functions and derivatives can be satisfied so that the distortions hardly occur. Local weak forms are developed using the weighted residual method locally from the partial differential equations of the transient heat conduction. Here the Heaviside step function is used as the test function in each sub-domain to avoid the need for a domain integral. Essential boundary conditions can be implemented like the finite element method (FEM) as the shape functions possess the Kronecker delta property. The traditional two-point difference method is selected for the time discretization scheme. Three selected numerical examples are presented in this paper to demonstrate the availability and accuracy of the present approach comparing with the traditional thin plate spline (TPS) radial basis functions.

Radiative heat transfer in strongly forward scattering media using the discrete ordinates method

NASA Astrophysics Data System (ADS)

Granate, Pedro; Coelho, Pedro J.; Roger, Maxime

2016-03-01

The discrete ordinates method (DOM) is widely used to solve the radiative transfer equation, often yielding satisfactory results. However, in the presence of strongly forward scattering media, this method does not generally conserve the scattering energy and the phase function asymmetry factor. Because of this, the normalization of the phase function has been proposed to guarantee that the scattering energy and the asymmetry factor are conserved. Various authors have used different normalization techniques. Three of these are compared in the present work, along with two other methods, one based on the finite volume method (FVM) and another one based on the spherical harmonics discrete ordinates method (SHDOM). In addition, the approximation of the Henyey-Greenstein phase function by a different one is investigated as an alternative to the phase function normalization. The approximate phase function is given by the sum of a Dirac delta function, which accounts for the forward scattering peak, and a smoother scaled phase function. In this study, these techniques are applied to three scalar radiative transfer test cases, namely a three-dimensional cubic domain with a purely scattering medium, an axisymmetric cylindrical enclosure containing an emitting-absorbing-scattering medium, and a three-dimensional transient problem with collimated irradiation. The present results show that accurate predictions are achieved for strongly forward scattering media when the phase function is normalized in such a way that both the scattered energy and the phase function asymmetry factor are conserved. The normalization of the phase function may be avoided using the FVM or the SHDOM to evaluate the in-scattering term of the radiative transfer equation. Both methods yield results whose accuracy is similar to that obtained using the DOM along with normalization of the phase function. Very satisfactory predictions were also achieved using the delta-M phase function, while the delta-Eddington phase function and the transport approximation may perform poorly.

F-Expansion Method and New Exact Solutions of the Schrödinger-KdV Equation

PubMed Central

Filiz, Ali; Ekici, Mehmet; Sonmezoglu, Abdullah

2014-01-01

F-expansion method is proposed to seek exact solutions of nonlinear evolution equations. With the aid of symbolic computation, we choose the Schrödinger-KdV equation with a source to illustrate the validity and advantages of the proposed method. A number of Jacobi-elliptic function solutions are obtained including the Weierstrass-elliptic function solutions. When the modulus m of Jacobi-elliptic function approaches to 1 and 0, soliton-like solutions and trigonometric-function solutions are also obtained, respectively. The proposed method is a straightforward, short, promising, and powerful method for the nonlinear evolution equations in mathematical physics. PMID:24672327

F-expansion method and new exact solutions of the Schrödinger-KdV equation.

PubMed

Filiz, Ali; Ekici, Mehmet; Sonmezoglu, Abdullah

2014-01-01

F-expansion method is proposed to seek exact solutions of nonlinear evolution equations. With the aid of symbolic computation, we choose the Schrödinger-KdV equation with a source to illustrate the validity and advantages of the proposed method. A number of Jacobi-elliptic function solutions are obtained including the Weierstrass-elliptic function solutions. When the modulus m of Jacobi-elliptic function approaches to 1 and 0, soliton-like solutions and trigonometric-function solutions are also obtained, respectively. The proposed method is a straightforward, short, promising, and powerful method for the nonlinear evolution equations in mathematical physics.

Robust, Adaptive Functional Regression in Functional Mixed Model Framework.

PubMed

Zhu, Hongxiao; Brown, Philip J; Morris, Jeffrey S

2011-09-01

Functional data are increasingly encountered in scientific studies, and their high dimensionality and complexity lead to many analytical challenges. Various methods for functional data analysis have been developed, including functional response regression methods that involve regression of a functional response on univariate/multivariate predictors with nonparametrically represented functional coefficients. In existing methods, however, the functional regression can be sensitive to outlying curves and outlying regions of curves, so is not robust. In this paper, we introduce a new Bayesian method, robust functional mixed models (R-FMM), for performing robust functional regression within the general functional mixed model framework, which includes multiple continuous or categorical predictors and random effect functions accommodating potential between-function correlation induced by the experimental design. The underlying model involves a hierarchical scale mixture model for the fixed effects, random effect and residual error functions. These modeling assumptions across curves result in robust nonparametric estimators of the fixed and random effect functions which down-weight outlying curves and regions of curves, and produce statistics that can be used to flag global and local outliers. These assumptions also lead to distributions across wavelet coefficients that have outstanding sparsity and adaptive shrinkage properties, with great flexibility for the data to determine the sparsity and the heaviness of the tails. Together with the down-weighting of outliers, these within-curve properties lead to fixed and random effect function estimates that appear in our simulations to be remarkably adaptive in their ability to remove spurious features yet retain true features of the functions. We have developed general code to implement this fully Bayesian method that is automatic, requiring the user to only provide the functional data and design matrices. It is efficient enough to handle large data sets, and yields posterior samples of all model parameters that can be used to perform desired Bayesian estimation and inference. Although we present details for a specific implementation of the R-FMM using specific distributional choices in the hierarchical model, 1D functions, and wavelet transforms, the method can be applied more generally using other heavy-tailed distributions, higher dimensional functions (e.g. images), and using other invertible transformations as alternatives to wavelets.

Robust, Adaptive Functional Regression in Functional Mixed Model Framework

PubMed Central

Zhu, Hongxiao; Brown, Philip J.; Morris, Jeffrey S.

2012-01-01

Functional data are increasingly encountered in scientific studies, and their high dimensionality and complexity lead to many analytical challenges. Various methods for functional data analysis have been developed, including functional response regression methods that involve regression of a functional response on univariate/multivariate predictors with nonparametrically represented functional coefficients. In existing methods, however, the functional regression can be sensitive to outlying curves and outlying regions of curves, so is not robust. In this paper, we introduce a new Bayesian method, robust functional mixed models (R-FMM), for performing robust functional regression within the general functional mixed model framework, which includes multiple continuous or categorical predictors and random effect functions accommodating potential between-function correlation induced by the experimental design. The underlying model involves a hierarchical scale mixture model for the fixed effects, random effect and residual error functions. These modeling assumptions across curves result in robust nonparametric estimators of the fixed and random effect functions which down-weight outlying curves and regions of curves, and produce statistics that can be used to flag global and local outliers. These assumptions also lead to distributions across wavelet coefficients that have outstanding sparsity and adaptive shrinkage properties, with great flexibility for the data to determine the sparsity and the heaviness of the tails. Together with the down-weighting of outliers, these within-curve properties lead to fixed and random effect function estimates that appear in our simulations to be remarkably adaptive in their ability to remove spurious features yet retain true features of the functions. We have developed general code to implement this fully Bayesian method that is automatic, requiring the user to only provide the functional data and design matrices. It is efficient enough to handle large data sets, and yields posterior samples of all model parameters that can be used to perform desired Bayesian estimation and inference. Although we present details for a specific implementation of the R-FMM using specific distributional choices in the hierarchical model, 1D functions, and wavelet transforms, the method can be applied more generally using other heavy-tailed distributions, higher dimensional functions (e.g. images), and using other invertible transformations as alternatives to wavelets. PMID:22308015

Numerical simulation of electromagnetic waves in Schwarzschild space-time by finite difference time domain method and Green function method

NASA Astrophysics Data System (ADS)

Jia, Shouqing; La, Dongsheng; Ma, Xuelian

2018-04-01

The finite difference time domain (FDTD) algorithm and Green function algorithm are implemented into the numerical simulation of electromagnetic waves in Schwarzschild space-time. FDTD method in curved space-time is developed by filling the flat space-time with an equivalent medium. Green function in curved space-time is obtained by solving transport equations. Simulation results validate both the FDTD code and Green function code. The methods developed in this paper offer a tool to solve electromagnetic scattering problems.

A kernel function method for computing steady and oscillatory supersonic aerodynamics with interference.

NASA Technical Reports Server (NTRS)

Cunningham, A. M., Jr.

1973-01-01

The method presented uses a collocation technique with the nonplanar kernel function to solve supersonic lifting surface problems with and without interference. A set of pressure functions are developed based on conical flow theory solutions which account for discontinuities in the supersonic pressure distributions. These functions permit faster solution convergence than is possible with conventional supersonic pressure functions. An improper integral of a 3/2 power singularity along the Mach hyperbola of the nonplanar supersonic kernel function is described and treated. The method is compared with other theories and experiment for a variety of cases.

Problems and methods of calculating the Legendre functions of arbitrary degree and order

NASA Astrophysics Data System (ADS)

Novikova, Elena; Dmitrenko, Alexander

2016-12-01

The known standard recursion methods of computing the full normalized associated Legendre functions do not give the necessary precision due to application of IEEE754-2008 standard, that creates a problems of underflow and overflow. The analysis of the problems of the calculation of the Legendre functions shows that the problem underflow is not dangerous by itself. The main problem that generates the gross errors in its calculations is the problem named the effect of "absolute zero". Once appeared in a forward column recursion, "absolute zero" converts to zero all values which are multiplied by it, regardless of whether a zero result of multiplication is real or not. Three methods of calculating of the Legendre functions, that removed the effect of "absolute zero" from the calculations are discussed here. These methods are also of interest because they almost have no limit for the maximum degree of Legendre functions. It is shown that the numerical accuracy of these three methods is the same. But, the CPU calculation time of the Legendre functions with Fukushima method is minimal. Therefore, the Fukushima method is the best. Its main advantage is computational speed which is an important factor in calculation of such large amount of the Legendre functions as 2 401 336 for EGM2008.

Finite Temperature Densities via the S-Function Method with Application to Electron Screening in Plasmas

NASA Astrophysics Data System (ADS)

Watrous, Mitchell James

1997-12-01

A new approach to the Green's-function method for the calculation of equilibrium densities within the finite temperature, Kohn-Sham formulation of density functional theory is presented, which extends the method to all temperatures. The contour of integration in the complex energy plane is chosen such that the density is given by a sum of Green's function differences evaluated at the Matsubara frequencies, rather than by the calculation and summation of Kohn-Sham single-particle wave functions. The Green's functions are written in terms of their spectral representation and are calculated as the solutions of their defining differential equations. These differential equations are boundary value problems as opposed to the standard eigenvalue problems. For large values of the complex energy, the differential equations are further simplified from second to first-order by writing the Green's functions in terms of logarithmic derivatives. An asymptotic expression for the Green's functions is derived, which allows the sum over Matsubara poles to be approximated. The method is applied to the screening of nuclei by electrons in finite temperature plasmas. To demonstrate the method's utility, and to illustrate its advantages, the results of previous wave function type calculations for protons and neon nuclei are reproduced. The method is also used to formulate a new screening model for fusion reactions in the solar core, and the predicted reaction rate enhancements factors are compared with existing models.

Relaxed Fidelity CFD Methods Applied to Store Separation Problems

DTIC Science & Technology

2004-06-01

accuracy-productivity characteristics of influence function methods and time-accurate CFD methods. Two methods are presented in this paper, both of...which provide significant accuracy improvements over influence function methods while providing rapid enough turn around times to support parameter and

Assessment of parametric uncertainty for groundwater reactive transport modeling,

USGS Publications Warehouse

Shi, Xiaoqing; Ye, Ming; Curtis, Gary P.; Miller, Geoffery L.; Meyer, Philip D.; Kohler, Matthias; Yabusaki, Steve; Wu, Jichun

2014-01-01

The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM(zs)) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM(ZS)-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood functions, improve model calibration, and reduce predictive uncertainty in other groundwater reactive transport and environmental modeling.

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…

Optimized Vertex Method and Hybrid Reliability

NASA Technical Reports Server (NTRS)

Smith, Steven A.; Krishnamurthy, T.; Mason, B. H.

2002-01-01

A method of calculating the fuzzy response of a system is presented. This method, called the Optimized Vertex Method (OVM), is based upon the vertex method but requires considerably fewer function evaluations. The method is demonstrated by calculating the response membership function of strain-energy release rate for a bonded joint with a crack. The possibility of failure of the bonded joint was determined over a range of loads. After completing the possibilistic analysis, the possibilistic (fuzzy) membership functions were transformed to probability density functions and the probability of failure of the bonded joint was calculated. This approach is called a possibility-based hybrid reliability assessment. The possibility and probability of failure are presented and compared to a Monte Carlo Simulation (MCS) of the bonded joint.

Relative contributions of three descriptive methods: implications for behavioral assessment.

PubMed

Pence, Sacha T; Roscoe, Eileen M; Bourret, Jason C; Ahearn, William H

2009-01-01

This study compared the outcomes of three descriptive analysis methods-the ABC method, the conditional probability method, and the conditional and background probability method-to each other and to the results obtained from functional analyses. Six individuals who had been diagnosed with developmental delays and exhibited problem behavior participated. Functional analyses indicated that participants' problem behavior was maintained by social positive reinforcement (n = 2), social negative reinforcement (n = 2), or automatic reinforcement (n = 2). Results showed that for all but 1 participant, descriptive analysis outcomes were similar across methods. In addition, for all but 1 participant, the descriptive analysis outcome differed substantially from the functional analysis outcome. This supports the general finding that descriptive analysis is a poor means of determining functional relations.

Thermoelectric Properties of Novel One-dimensional and Two-dimensional Systems Based on MoS2 Nanoribbons and Sheets

NASA Astrophysics Data System (ADS)

Arab, Abbas

Atomically thin materials such as hexagonal boron nitride (h-BN) and transition metal dichalcogenides (TMDCs) have attracted a lot of interest since the discovery of Graphene. Potential use of Graphene in semiconductor industry has been hindered by the fact that graphene is a semi metal with zero band gap. The difficulties in engineering band gap in graphene turn the focus light to inherent semiconducting two-dimensional (2D) materials; TMDCs. Bulk of TMDCs are formed by layers vertically stacked and weakly bonded together via weak van der Waals interactions. These weak interlayer forces make it possible to obtain monolayer by using scotch tape exfoliation or lithium-ion intercalation. Among the semiconducting members of TMDCs, MoS 2 is the most appealing candidate, partly due to its thermal stability and also for its natural abundance. Intensive study of electronic properties of MoS2 has revealed the desirable band gap (1.2 eV), good carrier xmobility (which is close to those of silicon thin films and graphene nanoribbons), thermal stability and a surface free from dangling bonds make it a perfect candidate for electronic and opto-electronic applications. Despite the fact that MoS2 has a high Seebeck coefficient, its thermoelectric properties have not studied as well as it should be. In this work, we have studied thermoelectric properties of monolayer and fewlayer MoS2 sheets in both armchair and zigzag orientations and also of monolayer MoS2 armchair nanoribbons. Density functional theory (DFT) using non-equilibrium Green's function (NEGF) method in ballistic transport regime of Landauer-Buttiker formulation in linear transport approximation has been implemented to calculate the transmission spectra and consequently electronic transport coefficients. Phonon transmission spectra are calculated based on parameterization of Stillinger-Weber potential. Thermoelectric figure of merit, ZT, is calculated using these electronic and phonon transmission spectra. In the case of MoS2 sheets, thermoelectric properties of monolayer, bilayer, trilayer and quadlayer in armchair and zigzag directions have been studied. Our results show that as number of layers increase from monolayer to quadlayer, both transmission spectrum and phonon thermal conductance increase. In addition, strong electronic and thermal anisotropy is found between zigzag and armchair orientations. Transmission coefficient and phonon thermal conductance of zigzag orientation is higher than those of armchair with the same number of layers. Electrical conductance and phonon thermal conductance are competing forces in achieving a high thermoelectric figure of merit. Advantage of having a higher electrical conductance in zigzag orientation has been nullified by having a higher phonon thermal conductance. In fact, our results show higher thermoelectric xifigure of merit for armchair oriented than zigzag oriented sheets. Also as number of layer decreases from quadlayer to monolayer, we are witnessing a higher thermoelectric figure of merit for both armchair and zigzag oriented sheets. Hence, the highest achieved thermoelectric figure of merit was obtained by monolayer armchair MoS2 sheet for both p-type and n-type semiconducting behavior. In case of MoS2 armchair nanoribbons, effect of several factors has been studied; width of nanoribbon, Sulfur vacancy and edge roughness. The electronic properties of nanoribbons are dominated by the presence of edge states that are dependent on the number of zigzag chains across the nanoribbon. In addition, it is found that the phonon thermal conductance of monolayer MoS2 armchair nanoribbon is smaller compared to MoS2 monolayer armchair sheet. This outcome can be explained by phonon edge scattering. The effect of this phonon edge scattering is more pronounced in narrower nanoribbons compared to wide ones which leads to higher thermoelectric figure of merit for narrow nanoribbons. The effect of edge roughness and sulfur vacancy on thermoelectric behavior of MoS2 nanoribbons is also studied. Our result shows that edge roughness decreased the thermoelectric figure of merit compared to those of a perfect nanoribbon as its impact on electrical conductance is more severe than on phonon thermal conductance. Sulfur vacancy, however, improved thermoelectric figure of merit of MoS2 nanoribbons. It has been shown that thermoelectric figure of merit as high as 4 and 3 at T = 500K can be achieved n-doped and p-doped MoS2 nanoribbons. The ability of getting a high thermoelectric figure of merit for both n-type and p-type behavior from the same material will be a huge boost to thermoelectric industry if realized.

Restricted random search method based on taboo search in the multiple minima problem

NASA Astrophysics Data System (ADS)

Hong, Seung Do; Jhon, Mu Shik

1997-03-01

The restricted random search method is proposed as a simple Monte Carlo sampling method to search minima fast in the multiple minima problem. This method is based on taboo search applied recently to continuous test functions. The concept of the taboo region instead of the taboo list is used and therefore the sampling of a region near an old configuration is restricted in this method. This method is applied to 2-dimensional test functions and the argon clusters. This method is found to be a practical and efficient method to search near-global configurations of test functions and the argon clusters.

A hybrid-perturbation-Galerkin technique which combines multiple expansions

NASA Technical Reports Server (NTRS)

Geer, James F.; Andersen, Carl M.

1989-01-01

A two-step hybrid perturbation-Galerkin method for the solution of a variety of differential equations type problems is found to give better results when multiple perturbation expansions are employed. The method assumes that there is parameter in the problem formulation and that a perturbation method can be sued to construct one or more expansions in this perturbation coefficient functions multiplied by computed amplitudes. In step one, regular and/or singular perturbation methods are used to determine the perturbation coefficient functions. The results of step one are in the form of one or more expansions each expressed as a sum of perturbation coefficient functions multiplied by a priori known gauge functions. In step two the classical Bubnov-Galerkin method uses the perturbation coefficient functions computed in step one to determine a set of amplitudes which replace and improve upon the gauge functions. The hybrid method has the potential of overcoming some of the drawbacks of the perturbation and Galerkin methods as applied separately, while combining some of their better features. The proposed method is applied, with two perturbation expansions in each case, to a variety of model ordinary differential equations problems including: a family of linear two-boundary-value problems, a nonlinear two-point boundary-value problem, a quantum mechanical eigenvalue problem and a nonlinear free oscillation problem. The results obtained from the hybrid methods are compared with approximate solutions obtained by other methods, and the applicability of the hybrid method to broader problem areas is discussed.

A projection gradient method for computing ground state of spin-2 Bose–Einstein condensates

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

Wang, Hanquan, E-mail: hanquan.wang@gmail.com; Yunnan Tongchang Scientific Computing and Data Mining Research Center, Kunming, Yunnan Province, 650221

In this paper, a projection gradient method is presented for computing ground state of spin-2 Bose–Einstein condensates (BEC). We first propose the general projection gradient method for solving energy functional minimization problem under multiple constraints, in which the energy functional takes real functions as independent variables. We next extend the method to solve a similar problem, where the energy functional now takes complex functions as independent variables. We finally employ the method into finding the ground state of spin-2 BEC. The key of our method is: by constructing continuous gradient flows (CGFs), the ground state of spin-2 BEC can bemore » computed as the steady state solution of such CGFs. We discretized the CGFs by a conservative finite difference method along with a proper way to deal with the nonlinear terms. We show that the numerical discretization is normalization and magnetization conservative and energy diminishing. Numerical results of the ground state and their energy of spin-2 BEC are reported to demonstrate the effectiveness of the numerical method.« less

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

PubMed

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

SGFSC: speeding the gene functional similarity calculation based on hash tables.

PubMed

Tian, Zhen; Wang, Chunyu; Guo, Maozu; Liu, Xiaoyan; Teng, Zhixia

2016-11-04

In recent years, many measures of gene functional similarity have been proposed and widely used in all kinds of essential research. These methods are mainly divided into two categories: pairwise approaches and group-wise approaches. However, a common problem with these methods is their time consumption, especially when measuring the gene functional similarities of a large number of gene pairs. The problem of computational efficiency for pairwise approaches is even more prominent because they are dependent on the combination of semantic similarity. Therefore, the efficient measurement of gene functional similarity remains a challenging problem. To speed current gene functional similarity calculation methods, a novel two-step computing strategy is proposed: (1) establish a hash table for each method to store essential information obtained from the Gene Ontology (GO) graph and (2) measure gene functional similarity based on the corresponding hash table. There is no need to traverse the GO graph repeatedly for each method with the help of the hash table. The analysis of time complexity shows that the computational efficiency of these methods is significantly improved. We also implement a novel Speeding Gene Functional Similarity Calculation tool, namely SGFSC, which is bundled with seven typical measures using our proposed strategy. Further experiments show the great advantage of SGFSC in measuring gene functional similarity on the whole genomic scale. The proposed strategy is successful in speeding current gene functional similarity calculation methods. SGFSC is an efficient tool that is freely available at http://nclab.hit.edu.cn/SGFSC . The source code of SGFSC can be downloaded from http://pan.baidu.com/s/1dFFmvpZ .

Bayesian extraction of the parton distribution amplitude from the Bethe-Salpeter wave function

NASA Astrophysics Data System (ADS)

Gao, Fei; Chang, Lei; Liu, Yu-xin

2017-07-01

We propose a new numerical method to compute the parton distribution amplitude (PDA) from the Euclidean Bethe-Salpeter wave function. The essential step is to extract the weight function in the Nakanishi representation of the Bethe-Salpeter wave function in Euclidean space, which is an ill-posed inversion problem, via the maximum entropy method (MEM). The Nakanishi weight function as well as the corresponding light-front parton distribution amplitude (PDA) can be well determined. We confirm prior work on PDA computations, which was based on different methods.

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.

Solution of Volterra and Fredholm Classes of Equations via Triangular Orthogonal Function (A Combination of Right Hand Triangular Function and Left Hand Triangular Function) and Hybrid Orthogonal Function (A Combination of Sample Hold Function and Right Hand Triangular Function)

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Anirban; Ganguly, Anindita; Chatterjee, Saumya Deep

2018-04-01

In this paper the authors have dealt with seven kinds of non-linear Volterra and Fredholm classes of equations. The authors have formulated an algorithm for solving the aforementioned equation types via Hybrid Function (HF) and Triangular Function (TF) piecewise-linear orthogonal approach. In this approach the authors have reduced integral equation or integro-differential equation into equivalent system of simultaneous non-linear equation and have employed either Newton's method or Broyden's method to solve the simultaneous non-linear equations. The authors have calculated the L2-norm error and the max-norm error for both HF and TF method for each kind of equations. Through the illustrated examples, the authors have shown that the HF based algorithm produces stable result, on the contrary TF-computational method yields either stable, anomalous or unstable results.

Investigating a hybrid perturbation-Galerkin technique using computer algebra

NASA Technical Reports Server (NTRS)

Andersen, Carl M.; Geer, James F.

1988-01-01

A two-step hybrid perturbation-Galerkin method is presented for the solution of a variety of differential equations type problems which involve a scalar parameter. The resulting (approximate) solution has the form of a sum where each term consists of the product of two functions. The first function is a function of the independent field variable(s) x, and the second is a function of the parameter lambda. In step one the functions of x are determined by forming a perturbation expansion in lambda. In step two the functions of lambda are determined through the use of the classical Bubnov-Gelerkin method. The resulting hybrid method has the potential of overcoming some of the drawbacks of the perturbation and Bubnov-Galerkin methods applied separately, while combining some of the good features of each. In particular, the results can be useful well beyond the radius of convergence associated with the perturbation expansion. The hybrid method is applied with the aid of computer algebra to a simple two-point boundary value problem where the radius of convergence is finite and to a quantum eigenvalue problem where the radius of convergence is zero. For both problems the hybrid method apparently converges for an infinite range of the parameter lambda. The results obtained from the hybrid method are compared with approximate solutions obtained by other methods, and the applicability of the hybrid method to broader problem areas is discussed.

Inverse solution of ear-canal area function from reflectance

PubMed Central

Rasetshwane, Daniel M.; Neely, Stephen T.

2011-01-01

A number of acoustical applications require the transformation of acoustical quantities, such as impedance and pressure that are measured at the entrance of the ear canal, to quantities at the eardrum. This transformation often requires knowledge of the shape of the ear canal. Previous attempts to measure ear-canal area functions were either invasive, non-reproducible, or could only measure the area function up to a point mid-way along the canal. A method to determine the area function of the ear canal from measurements of acoustic impedance at the entrance of the ear canal is described. The method is based on a solution to the inverse problem in which measurements of impedance are used to calculate reflectance, which is then used to determine the area function of the canal. The mean ear-canal area function determined using this method is similar to mean ear-canal area functions measured by other researchers using different techniques. The advantage of the proposed method over previous methods is that it is non- invasive, fast, and reproducible. PMID:22225043

New method to incorporate Type B uncertainty into least-squares procedures in radionuclide metrology.

PubMed

Han, Jubong; Lee, K B; Lee, Jong-Man; Park, Tae Soon; Oh, J S; Oh, Pil-Jei

2016-03-01

We discuss a new method to incorporate Type B uncertainty into least-squares procedures. The new method is based on an extension of the likelihood function from which a conventional least-squares function is derived. The extended likelihood function is the product of the original likelihood function with additional PDFs (Probability Density Functions) that characterize the Type B uncertainties. The PDFs are considered to describe one's incomplete knowledge on correction factors being called nuisance parameters. We use the extended likelihood function to make point and interval estimations of parameters in the basically same way as the least-squares function used in the conventional least-squares method is derived. Since the nuisance parameters are not of interest and should be prevented from appearing in the final result, we eliminate such nuisance parameters by using the profile likelihood. As an example, we present a case study for a linear regression analysis with a common component of Type B uncertainty. In this example we compare the analysis results obtained from using our procedure with those from conventional methods. Copyright © 2015. Published by Elsevier Ltd.

Doubly stochastic radial basis function methods

NASA Astrophysics Data System (ADS)

Yang, Fenglian; Yan, Liang; Ling, Leevan

2018-06-01

We propose a doubly stochastic radial basis function (DSRBF) method for function recoveries. Instead of a constant, we treat the RBF shape parameters as stochastic variables whose distribution were determined by a stochastic leave-one-out cross validation (LOOCV) estimation. A careful operation count is provided in order to determine the ranges of all the parameters in our methods. The overhead cost for setting up the proposed DSRBF method is O (n2) for function recovery problems with n basis. Numerical experiments confirm that the proposed method not only outperforms constant shape parameter formulation (in terms of accuracy with comparable computational cost) but also the optimal LOOCV formulation (in terms of both accuracy and computational cost).

Continuous, One-pot Synthesis and Post-Synthetic Modification of NanoMOFs Using Droplet Nanoreactors

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

Jambovane, Sachin R.; Nune, Satish K.; Kelly, Ryan T.

Metal-organic frameworks (MOFs); also known as porous coordination polymers (PCP) are a class of porous crystalline materials constructed by connecting metal clusters via organic linkers. The possibility of functionalization leads to virtually infinite MOF designs using generic modular methods. Functionalized MOFs can exhibit interesting physical and chemical properties including accelerated adsorption kinetics and catalysis. Although there are discrete methods to synthesize well-defined nanoscale MOFs, rapid and flexible methods are not available for continuous, one-pot synthesis and post synthesis modification (functionalization) of MOFs. Here, we show a continuous, scalable nanodroplet-based microfluidic route that not only facilitates the synthesis of MOFs atmore » nanoscale, but also offers flexibility for direct functionalization with desired functional groups (e.g., -NH 2, -COCH 3, fluorescein isothiocyanate; FITC). In addition, the presented route of continuous manufacturing of functionalized MOFs takes significantly less time compared to state-of-the-art batch methods currently available (1 hr vs. several days). We envisage our approach to be a breakthrough method for synthesizing complex functionalized nanomaterials (metal, metal oxides, quantum dots and MOFs) that are not accessible by direct batch processing, and expand the range of a new class of functionalized MOF-based functional nanomaterials.« less

Assessment of protein set coherence using functional annotations

PubMed Central

Chagoyen, Monica; Carazo, Jose M; Pascual-Montano, Alberto

2008-01-01

Background Analysis of large-scale experimental datasets frequently produces one or more sets of proteins that are subsequently mined for functional interpretation and validation. To this end, a number of computational methods have been devised that rely on the analysis of functional annotations. Although current methods provide valuable information (e.g. significantly enriched annotations, pairwise functional similarities), they do not specifically measure the degree of homogeneity of a protein set. Results In this work we present a method that scores the degree of functional homogeneity, or coherence, of a set of proteins on the basis of the global similarity of their functional annotations. The method uses statistical hypothesis testing to assess the significance of the set in the context of the functional space of a reference set. As such, it can be used as a first step in the validation of sets expected to be homogeneous prior to further functional interpretation. Conclusion We evaluate our method by analysing known biologically relevant sets as well as random ones. The known relevant sets comprise macromolecular complexes, cellular components and pathways described for Saccharomyces cerevisiae, which are mostly significantly coherent. Finally, we illustrate the usefulness of our approach for validating 'functional modules' obtained from computational analysis of protein-protein interaction networks. Matlab code and supplementary data are available at PMID:18937846

A radial basis function Galerkin method for inhomogeneous nonlocal diffusion

DOE PAGES

Lehoucq, Richard B.; Rowe, Stephen T.

2016-02-01

We introduce a discretization for a nonlocal diffusion problem using a localized basis of radial basis functions. The stiffness matrix entries are assembled by a special quadrature routine unique to the localized basis. Combining the quadrature method with the localized basis produces a well-conditioned, sparse, symmetric positive definite stiffness matrix. We demonstrate that both the continuum and discrete problems are well-posed and present numerical results for the convergence behavior of the radial basis function method. As a result, we explore approximating the solution to anisotropic differential equations by solving anisotropic nonlocal integral equations using the radial basis function method.

The Potential of "Function" as an Archival Descriptor

ERIC Educational Resources Information Center

Chaudron, Gerald

2008-01-01

Functional analysis has been incorporated widely into appraisal methods for decades. These methods, from documentation strategy to macroappraisal, are discussed, and the usefulness and limitations of functional analysis in appraisal are examined. Yet, while archival thinkers have focused on function in appraisal, little has been written on…

Rosetta stone method for detecting protein function and protein-protein interactions from genome sequences

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Pellegrini, Matteo; Thompson, Michael J.; Yeates, Todd O.

2002-10-15

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Thick-target transmission method for excitation functions of interaction cross sections

NASA Astrophysics Data System (ADS)

Aikawa, M.; Ebata, S.; Imai, S.

2016-09-01

We propose a method, called as thick-target transmission (T3) method, to obtain an excitation function of interaction cross sections. In an ordinal experiment to measure the excitation function of interaction cross sections by the transmission method, we need to change the beam energy for each cross section. In the T3 method, the excitation function is derived from the beam attenuations measured at the targets of different thicknesses without changing the beam energy. The advantage of the T3 method is the simplicity and availability for radioactive beams. To confirm the availability, we perform a simulation for the 12C + 27Al system with the PHITS code instead of actual experiments. Our results have large uncertainties but well reproduce the tendency of the experimental data.

Irreducible Green's functions method for a quantum dot coupled to metallic and superconducting leads

NASA Astrophysics Data System (ADS)

Górski, Grzegorz; Kucab, Krzysztof

2017-05-01

Using irreducible Green's functions (IGF) method we analyse the Coulomb interaction dependence of the spectral functions and the transport properties of a quantum dot coupled to isotropic superconductor and metallic leads (SC-QD-N). The irreducible Green's functions method is the modification of classical equation of motion technique. The IGF scheme is based on differentiation of double-time Green's functions, both over the primary and secondary times. The IGF method allows to obtain the spectral functions for equilibrium and non-equilibrium impurity Anderson model used for SC-QD-N system. By the numerical computations, we show the change of spectral and the anomalous densities under the influence of the Coulomb interactions. The observed sign change of the anomalous spectral density can be used as the criterion of the SC singlet-Kondo singlet transition.

The dimension split element-free Galerkin method for three-dimensional potential problems

NASA Astrophysics Data System (ADS)

Meng, Z. J.; Cheng, H.; Ma, L. D.; Cheng, Y. M.

2018-06-01

This paper presents the dimension split element-free Galerkin (DSEFG) method for three-dimensional potential problems, and the corresponding formulae are obtained. The main idea of the DSEFG method is that a three-dimensional potential problem can be transformed into a series of two-dimensional problems. For these two-dimensional problems, the improved moving least-squares (IMLS) approximation is applied to construct the shape function, which uses an orthogonal function system with a weight function as the basis functions. The Galerkin weak form is applied to obtain a discretized system equation, and the penalty method is employed to impose the essential boundary condition. The finite difference method is selected in the splitting direction. For the purposes of demonstration, some selected numerical examples are solved using the DSEFG method. The convergence study and error analysis of the DSEFG method are presented. The numerical examples show that the DSEFG method has greater computational precision and computational efficiency than the IEFG method.

Use of adjoint methods in the probabilistic finite element approach to fracture mechanics

NASA Technical Reports Server (NTRS)

Liu, Wing Kam; Besterfield, Glen; Lawrence, Mark; Belytschko, Ted

1988-01-01

The adjoint method approach to probabilistic finite element methods (PFEM) is presented. When the number of objective functions is small compared to the number of random variables, the adjoint method is far superior to the direct method in evaluating the objective function derivatives with respect to the random variables. The PFEM is extended to probabilistic fracture mechanics (PFM) using an element which has the near crack-tip singular strain field embedded. Since only two objective functions (i.e., mode I and II stress intensity factors) are needed for PFM, the adjoint method is well suited.

Covalently functionalized carbon nanostructures and methods for their separation

DOEpatents

Wang, YuHuang; Brozena, Alexandra H; Deng, Shunliu; Zhang, Yin

2015-03-17

The present invention is directed to carbon nanostructures, e.g., carbon nanotubes, methods of covalently functionalizing carbon nanostructures, and methods of separating and isolating covalently functionalized carbon. In some embodiments, carbon nanotubes are reacted with alkylating agents to provide water soluble covalently functionalized carbon nanotubes. In other embodiments, carbon nanotubes are reacted with a thermally-responsive agent and exposed to light in order to separate carbon nanotubes of a specific chirality from a mixture of carbon nanotubes.

Separation of fNIRS Signals into Functional and Systemic Components Based on Differences in Hemodynamic Modalities

PubMed Central

Yamada, Toru; Umeyama, Shinji; Matsuda, Keiji

2012-01-01

In conventional functional near-infrared spectroscopy (fNIRS), systemic physiological fluctuations evoked by a body's motion and psychophysiological changes often contaminate fNIRS signals. We propose a novel method for separating functional and systemic signals based on their hemodynamic differences. Considering their physiological origins, we assumed a negative and positive linear relationship between oxy- and deoxyhemoglobin changes of functional and systemic signals, respectively. Their coefficients are determined by an empirical procedure. The proposed method was compared to conventional and multi-distance NIRS. The results were as follows: (1) Nonfunctional tasks evoked substantial oxyhemoglobin changes, and comparatively smaller deoxyhemoglobin changes, in the same direction by conventional NIRS. The systemic components estimated by the proposed method were similar to the above finding. The estimated functional components were very small. (2) During finger-tapping tasks, laterality in the functional component was more distinctive using our proposed method than that by conventional fNIRS. The systemic component indicated task-evoked changes, regardless of the finger used to perform the task. (3) For all tasks, the functional components were highly coincident with signals estimated by multi-distance NIRS. These results strongly suggest that the functional component obtained by the proposed method originates in the cerebral cortical layer. We believe that the proposed method could improve the reliability of fNIRS measurements without any modification in commercially available instruments. PMID:23185590

Incorporating Objective Function Information Into the Feasibility Rule for Constrained Evolutionary Optimization.

PubMed

Wang, Yong; Wang, Bing-Chuan; Li, Han-Xiong; Yen, Gary G

2016-12-01

When solving constrained optimization problems by evolutionary algorithms, an important issue is how to balance constraints and objective function. This paper presents a new method to address the above issue. In our method, after generating an offspring for each parent in the population by making use of differential evolution (DE), the well-known feasibility rule is used to compare the offspring and its parent. Since the feasibility rule prefers constraints to objective function, the objective function information has been exploited as follows: if the offspring cannot survive into the next generation and if the objective function value of the offspring is better than that of the parent, then the offspring is stored into a predefined archive. Subsequently, the individuals in the archive are used to replace some individuals in the population according to a replacement mechanism. Moreover, a mutation strategy is proposed to help the population jump out of a local optimum in the infeasible region. Note that, in the replacement mechanism and the mutation strategy, the comparison of individuals is based on objective function. In addition, the information of objective function has also been utilized to generate offspring in DE. By the above processes, this paper achieves an effective balance between constraints and objective function in constrained evolutionary optimization. The performance of our method has been tested on two sets of benchmark test functions, namely, 24 test functions at IEEE CEC2006 and 18 test functions with 10-D and 30-D at IEEE CEC2010. The experimental results have demonstrated that our method shows better or at least competitive performance against other state-of-the-art methods. Furthermore, the advantage of our method increases with the increase of the number of decision variables.

Polynomial dual energy inverse functions for bone Calcium/Phosphorus ratio determination and experimental evaluation.

PubMed

Sotiropoulou, P; Fountos, G; Martini, N; Koukou, V; Michail, C; Kandarakis, I; Nikiforidis, G

2016-12-01

An X-ray dual energy (XRDE) method was examined, using polynomial nonlinear approximation of inverse functions for the determination of the bone Calcium-to-Phosphorus (Ca/P) mass ratio. Inverse fitting functions with the least-squares estimation were used, to determine calcium and phosphate thicknesses. The method was verified by measuring test bone phantoms with a dedicated dual energy system and compared with previously published dual energy data. The accuracy in the determination of the calcium and phosphate thicknesses improved with the polynomial nonlinear inverse function method, introduced in this work, (ranged from 1.4% to 6.2%), compared to the corresponding linear inverse function method (ranged from 1.4% to 19.5%). Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Efficient reliability analysis of structures with the rotational quasi-symmetric point- and the maximum entropy methods

NASA Astrophysics Data System (ADS)

Xu, Jun; Dang, Chao; Kong, Fan

2017-10-01

This paper presents a new method for efficient structural reliability analysis. In this method, a rotational quasi-symmetric point method (RQ-SPM) is proposed for evaluating the fractional moments of the performance function. Then, the derivation of the performance function's probability density function (PDF) is carried out based on the maximum entropy method in which constraints are specified in terms of fractional moments. In this regard, the probability of failure can be obtained by a simple integral over the performance function's PDF. Six examples, including a finite element-based reliability analysis and a dynamic system with strong nonlinearity, are used to illustrate the efficacy of the proposed method. All the computed results are compared with those by Monte Carlo simulation (MCS). It is found that the proposed method can provide very accurate results with low computational effort.

Accelerating large scale Kohn-Sham density functional theory calculations with semi-local functionals and hybrid functionals

NASA Astrophysics Data System (ADS)

Lin, Lin

The computational cost of standard Kohn-Sham density functional theory (KSDFT) calculations scale cubically with respect to the system size, which limits its use in large scale applications. In recent years, we have developed an alternative procedure called the pole expansion and selected inversion (PEXSI) method. The PEXSI method solves KSDFT without solving any eigenvalue and eigenvector, and directly evaluates physical quantities including electron density, energy, atomic force, density of states, and local density of states. The overall algorithm scales as at most quadratically for all materials including insulators, semiconductors and the difficult metallic systems. The PEXSI method can be efficiently parallelized over 10,000 - 100,000 processors on high performance machines. The PEXSI method has been integrated into a number of community electronic structure software packages such as ATK, BigDFT, CP2K, DGDFT, FHI-aims and SIESTA, and has been used in a number of applications with 2D materials beyond 10,000 atoms. The PEXSI method works for LDA, GGA and meta-GGA functionals. The mathematical structure for hybrid functional KSDFT calculations is significantly different. I will also discuss recent progress on using adaptive compressed exchange method for accelerating hybrid functional calculations. DOE SciDAC Program, DOE CAMERA Program, LBNL LDRD, Sloan Fellowship.

Maximum likelihood solution for inclination-only data in paleomagnetism

NASA Astrophysics Data System (ADS)

Arason, P.; Levi, S.

2010-08-01

We have developed a new robust maximum likelihood method for estimating the unbiased mean inclination from inclination-only data. In paleomagnetic analysis, the arithmetic mean of inclination-only data is known to introduce a shallowing bias. Several methods have been introduced to estimate the unbiased mean inclination of inclination-only data together with measures of the dispersion. Some inclination-only methods were designed to maximize the likelihood function of the marginal Fisher distribution. However, the exact analytical form of the maximum likelihood function is fairly complicated, and all the methods require various assumptions and approximations that are often inappropriate. For some steep and dispersed data sets, these methods provide estimates that are significantly displaced from the peak of the likelihood function to systematically shallower inclination. The problem locating the maximum of the likelihood function is partly due to difficulties in accurately evaluating the function for all values of interest, because some elements of the likelihood function increase exponentially as precision parameters increase, leading to numerical instabilities. In this study, we succeeded in analytically cancelling exponential elements from the log-likelihood function, and we are now able to calculate its value anywhere in the parameter space and for any inclination-only data set. Furthermore, we can now calculate the partial derivatives of the log-likelihood function with desired accuracy, and locate the maximum likelihood without the assumptions required by previous methods. To assess the reliability and accuracy of our method, we generated large numbers of random Fisher-distributed data sets, for which we calculated mean inclinations and precision parameters. The comparisons show that our new robust Arason-Levi maximum likelihood method is the most reliable, and the mean inclination estimates are the least biased towards shallow values.

Functional classification of protein structures by local structure matching in graph representation.

PubMed

Mills, Caitlyn L; Garg, Rohan; Lee, Joslynn S; Tian, Liang; Suciu, Alexandru; Cooperman, Gene; Beuning, Penny J; Ondrechen, Mary Jo

2018-03-31

As a result of high-throughput protein structure initiatives, over 14,400 protein structures have been solved by structural genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP-Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP-Func method to our previously reported method, structurally aligned local sites of activity (SALSA), using the ribulose phosphate binding barrel (RPBB), 6-hairpin glycosidase (6-HG), and Concanavalin A-like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP-Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP-Func methods to predict function. Forty-one SG proteins in the RPBB superfamily, nine SG proteins in the 6-HG superfamily, and one SG protein in the CAL/G superfamily were successfully classified into one of the functional families in their respective superfamily by both methods. This improved, faster, validated computational method can yield more reliable predictions of function that can be used for a wide variety of applications by the community. © 2018 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

FUN-LDA: A Latent Dirichlet Allocation Model for Predicting Tissue-Specific Functional Effects of Noncoding Variation: Methods and Applications.

PubMed

Backenroth, Daniel; He, Zihuai; Kiryluk, Krzysztof; Boeva, Valentina; Pethukova, Lynn; Khurana, Ekta; Christiano, Angela; Buxbaum, Joseph D; Ionita-Laza, Iuliana

2018-05-03

We describe a method based on a latent Dirichlet allocation model for predicting functional effects of noncoding genetic variants in a cell-type- and/or tissue-specific way (FUN-LDA). Using this unsupervised approach, we predict tissue-specific functional effects for every position in the human genome in 127 different tissues and cell types. We demonstrate the usefulness of our predictions by using several validation experiments. Using eQTL data from several sources, including the GTEx project, Geuvadis project, and TwinsUK cohort, we show that eQTLs in specific tissues tend to be most enriched among the predicted functional variants in relevant tissues in Roadmap. We further show how these integrated functional scores can be used for (1) deriving the most likely cell or tissue type causally implicated for a complex trait by using summary statistics from genome-wide association studies and (2) estimating a tissue-based correlation matrix of various complex traits. We found large enrichment of heritability in functional components of relevant tissues for various complex traits, and FUN-LDA yielded higher enrichment estimates than existing methods. Finally, using experimentally validated functional variants from the literature and variants possibly implicated in disease by previous studies, we rigorously compare FUN-LDA with state-of-the-art functional annotation methods and show that FUN-LDA has better prediction accuracy and higher resolution than these methods. In particular, our results suggest that tissue- and cell-type-specific functional prediction methods tend to have substantially better prediction accuracy than organism-level prediction methods. Scores for each position in the human genome and for each ENCODE and Roadmap tissue are available online (see Web Resources). Copyright © 2018 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Increasing Accuracy of Tissue Shear Modulus Reconstruction Using Ultrasonic Strain Tensor Measurement

NASA Astrophysics Data System (ADS)

Sumi, C.

Previously, we developed three displacement vector measurement methods, i.e., the multidimensional cross-spectrum phase gradient method (MCSPGM), the multidimensional autocorrelation method (MAM), and the multidimensional Doppler method (MDM). To increase the accuracies and stabilities of lateral and elevational displacement measurements, we also developed spatially variant, displacement component-dependent regularization. In particular, the regularization of only the lateral/elevational displacements is advantageous for the lateral unmodulated case. The demonstrated measurements of the displacement vector distributions in experiments using an inhomogeneous shear modulus agar phantom confirm that displacement-component-dependent regularization enables more stable shear modulus reconstruction. In this report, we also review our developed lateral modulation methods that use Parabolic functions, Hanning windows, and Gaussian functions in the apodization function and the optimized apodization function that realizes the designed point spread function (PSF). The modulations significantly increase the accuracy of the strain tensor measurement and shear modulus reconstruction (demonstrated using an agar phantom).

New Treatment of Strongly Anisotropic Scattering Phase Functions: The Delta-M+ Method

NASA Astrophysics Data System (ADS)

Stamnes, K. H.; Lin, Z.; Chen, N.; Fan, Y.; Li, W.; Stamnes, S.

2017-12-01

The treatment of strongly anisotropic scattering phase functions is still a challenge for accurate radiance computations. The new Delta-M+ method resolves this problem by introducing a reliable, fast, accurate, and easy-to-use Legendre expansion of the scattering phase function with modified moments. Delta-M+ is an upgrade of the widely-used Delta-M method that truncates the forward scattering cone into a Dirac-delta-function (a direct beam), where the + symbol indicates that it essentially matches moments above the first 2M terms. Compared with the original Delta-M method, Delta-M+ has the same computational efficiency, but the accuracy has been increased dramatically. Tests show that the errors for strongly forward-peaked scattering phase functions are greatly reduced. Furthermore, the accuracy and stability of radiance computations are also significantly improved by applying the new Delta-M+ method.

Variational Methods in Design Optimization and Sensitivity Analysis for Two-Dimensional Euler Equations

NASA Technical Reports Server (NTRS)

Ibrahim, A. H.; Tiwari, S. N.; Smith, R. E.

1997-01-01

Variational methods (VM) sensitivity analysis employed to derive the costate (adjoint) equations, the transversality conditions, and the functional sensitivity derivatives. In the derivation of the sensitivity equations, the variational methods use the generalized calculus of variations, in which the variable boundary is considered as the design function. The converged solution of the state equations together with the converged solution of the costate equations are integrated along the domain boundary to uniquely determine the functional sensitivity derivatives with respect to the design function. The application of the variational methods to aerodynamic shape optimization problems is demonstrated for internal flow problems at supersonic Mach number range. The study shows, that while maintaining the accuracy of the functional sensitivity derivatives within the reasonable range for engineering prediction purposes, the variational methods show a substantial gain in computational efficiency, i.e., computer time and memory, when compared with the finite difference sensitivity analysis.

Computer method for identification of boiler transfer functions

NASA Technical Reports Server (NTRS)

Miles, J. H.

1971-01-01

An iterative computer method is described for identifying boiler transfer functions using frequency response data. An objective penalized performance measure and a nonlinear minimization technique are used to cause the locus of points generated by a transfer function to resemble the locus of points obtained from frequency response measurements. Different transfer functions can be tried until a satisfactory empirical transfer function to the system is found. To illustrate the method, some examples and some results from a study of a set of data consisting of measurements of the inlet impedance of a single tube forced flow boiler with inserts are given.

Oscillatory supersonic kernel function method for interfering surfaces

NASA Technical Reports Server (NTRS)

Cunningham, A. M., Jr.

1974-01-01

In the method presented in this paper, a collocation technique is used with the nonplanar supersonic kernel function to solve multiple lifting surface problems with interference in steady or oscillatory flow. The pressure functions used are based on conical flow theory solutions and provide faster solution convergence than is possible with conventional functions. In the application of the nonplanar supersonic kernel function, an improper integral of a 3/2 power singularity along the Mach hyperbola is described and treated. The method is compared with other theories and experiment for two wing-tail configurations in steady and oscillatory flow.

Determining protein function and interaction from genome analysis

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Thompson, Michael J.; Pellegrini, Matteo; Yeates, Todd O.

2004-08-03

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Assigning protein functions by comparative genome analysis protein phylogenetic profiles

DOEpatents

Pellegrini, Matteo; Marcotte, Edward M.; Thompson, Michael J.; Eisenberg, David; Grothe, Robert; Yeates, Todd O.

2003-05-13

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Fast calculation of the line-spread-function by transversal directions decoupling

NASA Astrophysics Data System (ADS)

Parravicini, Jacopo; Tartara, Luca; Hasani, Elton; Tomaselli, Alessandra

2016-07-01

We propose a simplified method to calculate the optical spread function of a paradigmatic system constituted by a pupil-lens with a line-shaped illumination (‘line-spread-function’). Our approach is based on decoupling the two transversal directions of the beam and treating the propagation by means of the Fourier optics formalism. This requires simpler calculations with respect to the more usual Bessel-function-based method. The model is discussed and compared with standard calculation methods by carrying out computer simulations. The proposed approach is found to be much faster than the Bessel-function-based one (CPU time ≲ 5% of the standard method), while the results of the two methods present a very good mutual agreement.

A method for surface topography measurement using a new focus function based on dual-tree complex wavelet transform

NASA Astrophysics Data System (ADS)

Li, Shimiao; Guo, Tong; Yuan, Lin; Chen, Jinping

2018-01-01

Surface topography measurement is an important tool widely used in many fields to determine the characteristics and functionality of a part or material. Among existing methods for this purpose, the focus variation method has proved high performance particularly in large slope scenarios. However, its performance depends largely on the effectiveness of focus function. This paper presents a method for surface topography measurement using a new focus measurement function based on dual-tree complex wavelet transform. Experiments are conducted on simulated defocused images to prove its high performance in comparison with other traditional approaches. The results showed that the new algorithm has better unimodality and sharpness. The method was also verified by measuring a MEMS micro resonator structure.

Store Separation Lessons Learned During the Last 30 Years

DTIC Science & Technology

2010-01-01

the same time period the Influence Function Method (IFM) was also developed5. This method allowed for a straight STORE SEPARATION LESSONS LEARNED...developed at Grumman under an Air Force contract. The Influence Function Method (IFM)5,6,7 was used to determine the effect of the aircraft flowfield on...A Chimera Grid Scheme,” Advances in Grid Generation, ASME, June 1983. 5. Meyer, R., Cenko, A., and Yaros, S., “An Influence Function Method for

Query3d: a new method for high-throughput analysis of functional residues in protein structures.

PubMed

Ausiello, Gabriele; Via, Allegra; Helmer-Citterich, Manuela

2005-12-01

The identification of local similarities between two protein structures can provide clues of a common function. Many different methods exist for searching for similar subsets of residues in proteins of known structure. However, the lack of functional and structural information on single residues, together with the low level of integration of this information in comparison methods, is a limitation that prevents these methods from being fully exploited in high-throughput analyses. Here we describe Query3d, a program that is both a structural DBMS (Database Management System) and a local comparison method. The method conserves a copy of all the residues of the Protein Data Bank annotated with a variety of functional and structural information. New annotations can be easily added from a variety of methods and known databases. The algorithm makes it possible to create complex queries based on the residues' function and then to compare only subsets of the selected residues. Functional information is also essential to speed up the comparison and the analysis of the results. With Query3d, users can easily obtain statistics on how many and which residues share certain properties in all proteins of known structure. At the same time, the method also finds their structural neighbours in the whole PDB. Programs and data can be accessed through the PdbFun web interface.

Query3d: a new method for high-throughput analysis of functional residues in protein structures

PubMed Central

Ausiello, Gabriele; Via, Allegra; Helmer-Citterich, Manuela

2005-01-01

Background The identification of local similarities between two protein structures can provide clues of a common function. Many different methods exist for searching for similar subsets of residues in proteins of known structure. However, the lack of functional and structural information on single residues, together with the low level of integration of this information in comparison methods, is a limitation that prevents these methods from being fully exploited in high-throughput analyses. Results Here we describe Query3d, a program that is both a structural DBMS (Database Management System) and a local comparison method. The method conserves a copy of all the residues of the Protein Data Bank annotated with a variety of functional and structural information. New annotations can be easily added from a variety of methods and known databases. The algorithm makes it possible to create complex queries based on the residues' function and then to compare only subsets of the selected residues. Functional information is also essential to speed up the comparison and the analysis of the results. Conclusion With Query3d, users can easily obtain statistics on how many and which residues share certain properties in all proteins of known structure. At the same time, the method also finds their structural neighbours in the whole PDB. Programs and data can be accessed through the PdbFun web interface. PMID:16351754

Orbital dependent functionals: An atom projector augmented wave method implementation

NASA Astrophysics Data System (ADS)

Xu, Xiao

This thesis explores the formulation and numerical implementation of orbital dependent exchange-correlation functionals within electronic structure calculations. These orbital-dependent exchange-correlation functionals have recently received renewed attention as a means to improve the physical representation of electron interactions within electronic structure calculations. In particular, electron self-interaction terms can be avoided. In this thesis, an orbital-dependent functional is considered in the context of Hartree-Fock (HF) theory as well as the Optimized Effective Potential (OEP) method and the approximate OEP method developed by Krieger, Li, and Iafrate, known as the KLI approximation. In this thesis, the Fock exchange term is used as a simple well-defined example of an orbital-dependent functional. The Projected Augmented Wave (PAW) method developed by P. E. Blochl has proven to be accurate and efficient for electronic structure calculations for local and semi-local functions because of its accurate evaluation of interaction integrals by controlling multiple moments. We have extended the PAW method to treat orbital-dependent functionals in Hartree-Fock theory and the Optimized Effective Potential method, particularly in the KLI approximation. In the course of study we develop a frozen-core orbital approximation that accurately treats the core electron contributions for above three methods. The main part of the thesis focuses on the treatment of spherical atoms. We have investigated the behavior of PAW-Hartree Fock and PAW-KLI basis, projector, and pseudopotential functions for several elements throughout the periodic table. We have also extended the formalism to the treatment of solids in a plane wave basis and implemented PWPAW-KLI code, which will appear in future publications.

General MoM Solutions for Large Arrays

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

Fasenfest, B; Capolino, F; Wilton, D R

2003-07-22

This paper focuses on a numerical procedure that addresses the difficulties of dealing with large, finite arrays while preserving the generality and robustness of full-wave methods. We present a fast method based on approximating interactions between sufficiently separated array elements via a relatively coarse interpolation of the Green's function on a uniform grid commensurate with the array's periodicity. The interaction between the basis and testing functions is reduced to a three-stage process. The first stage is a projection of standard (e.g., RWG) subdomain bases onto a set of interpolation functions that interpolate the Green's function on the array face. Thismore » projection, which is used in a matrix/vector product for each array cell in an iterative solution process, need only be carried out once for a single cell and results in a low-rank matrix. An intermediate stage matrix/vector product computation involving the uniformly sampled Green's function is of convolutional form in the lateral (transverse) directions so that a 2D FFT may be used. The final stage is a third matrix/vector product computation involving a matrix resulting from projecting testing functions onto the Green's function interpolation functions; the low-rank matrix is either identical to (using Galerkin's method) or similar to that for the bases projection. An effective MoM solution scheme is developed for large arrays using a modification of the AIM (Adaptive Integral Method) method. The method permits the analysis of arrays with arbitrary contours and nonplanar elements. Both fill and solve times within the MoM method are improved with respect to more standard MoM solvers.« less

The invariant of the stiffness filter function with the weight filter function of the power function form

NASA Astrophysics Data System (ADS)

Shang, Zhen; Sui, Yun-Kang

2012-12-01

Based on the independent, continuous and mapping (ICM) method and homogenization method, a research model is constructed to propose and deduce a theorem and corollary from the invariant between the weight filter function and the corresponding stiffness filter function of the form of power function. The efficiency in searching for optimum solution will be raised via the choice of rational filter functions, so the above mentioned results are very important to the further study of structural topology optimization.

Dissociations between behavioural and functional magnetic resonance imaging-based evaluations of cognitive function after brain injury

PubMed Central

Bardin, Jonathan C.; Fins, Joseph J.; Katz, Douglas I.; Hersh, Jennifer; Heier, Linda A.; Tabelow, Karsten; Dyke, Jonathan P.; Ballon, Douglas J.; Schiff, Nicholas D.

2011-01-01

Functional neuroimaging methods hold promise for the identification of cognitive function and communication capacity in some severely brain-injured patients who may not retain sufficient motor function to demonstrate their abilities. We studied seven severely brain-injured patients and a control group of 14 subjects using a novel hierarchical functional magnetic resonance imaging assessment utilizing mental imagery responses. Whereas the control group showed consistent and accurate (for communication) blood-oxygen-level-dependent responses without exception, the brain-injured subjects showed a wide variation in the correlation of blood-oxygen-level-dependent responses and overt behavioural responses. Specifically, the brain-injured subjects dissociated bedside and functional magnetic resonance imaging-based command following and communication capabilities. These observations reveal significant challenges in developing validated functional magnetic resonance imaging-based methods for clinical use and raise interesting questions about underlying brain function assayed using these methods in brain-injured subjects. PMID:21354974

Computer method for identification of boiler transfer functions

NASA Technical Reports Server (NTRS)

Miles, J. H.

1972-01-01

Iterative computer aided procedure was developed which provides for identification of boiler transfer functions using frequency response data. Method uses frequency response data to obtain satisfactory transfer function for both high and low vapor exit quality data.

Auxiliary-field-based trial wave functions in quantum Monte Carlo calculations

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

Chang, Chia -Chen; Rubenstein, Brenda M.; Morales, Miguel A.

2016-12-19

Quantum Monte Carlo (QMC) algorithms have long relied on Jastrow factors to incorporate dynamic correlation into trial wave functions. While Jastrow-type wave functions have been widely employed in real-space algorithms, they have seen limited use in second-quantized QMC methods, particularly in projection methods that involve a stochastic evolution of the wave function in imaginary time. Here we propose a scheme for generating Jastrow-type correlated trial wave functions for auxiliary-field QMC methods. The method is based on decoupling the two-body Jastrow into one-body projectors coupled to auxiliary fields, which then operate on a single determinant to produce a multideterminant trial wavemore » function. We demonstrate that intelligent sampling of the most significant determinants in this expansion can produce compact trial wave functions that reduce errors in the calculated energies. Lastly, our technique may be readily generalized to accommodate a wide range of two-body Jastrow factors and applied to a variety of model and chemical systems.« less

Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana.

PubMed

Hansen, Bjoern Oest; Meyer, Etienne H; Ferrari, Camilla; Vaid, Neha; Movahedi, Sara; Vandepoele, Klaas; Nikoloski, Zoran; Mutwil, Marek

2018-03-01

Recent advances in gene function prediction rely on ensemble approaches that integrate results from multiple inference methods to produce superior predictions. Yet, these developments remain largely unexplored in plants. We have explored and compared two methods to integrate 10 gene co-function networks for Arabidopsis thaliana and demonstrate how the integration of these networks produces more accurate gene function predictions for a larger fraction of genes with unknown function. These predictions were used to identify genes involved in mitochondrial complex I formation, and for five of them, we confirmed the predictions experimentally. The ensemble predictions are provided as a user-friendly online database, EnsembleNet. The methods presented here demonstrate that ensemble gene function prediction is a powerful method to boost prediction performance, whereas the EnsembleNet database provides a cutting-edge community tool to guide experimentalists. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

An efficient method for hybrid density functional calculation with spin-orbit coupling

NASA Astrophysics Data System (ADS)

Wang, Maoyuan; Liu, Gui-Bin; Guo, Hong; Yao, Yugui

2018-03-01

In first-principles calculations, hybrid functional is often used to improve accuracy from local exchange correlation functionals. A drawback is that evaluating the hybrid functional needs significantly more computing effort. When spin-orbit coupling (SOC) is taken into account, the non-collinear spin structure increases computing effort by at least eight times. As a result, hybrid functional calculations with SOC are intractable in most cases. In this paper, we present an approximate solution to this problem by developing an efficient method based on a mixed linear combination of atomic orbital (LCAO) scheme. We demonstrate the power of this method using several examples and we show that the results compare very well with those of direct hybrid functional calculations with SOC, yet the method only requires a computing effort similar to that without SOC. The presented technique provides a good balance between computing efficiency and accuracy, and it can be extended to magnetic materials.

The conservation and function of RNA secondary structure in plants

PubMed Central

Vandivier, Lee E.; Anderson, Stephen J.; Foley, Shawn W.; Gregory, Brian D.

2016-01-01

RNA transcripts fold into secondary structures via intricate patterns of base pairing. These secondary structures impart catalytic, ligand binding, and scaffolding functions to a wide array of RNAs, forming a critical node of biological regulation. Among their many functions, RNA structural elements modulate epigenetic marks, alter mRNA stability and translation, regulate alternative splicing, transduce signals, and scaffold large macromolecular complexes. Thus, the study of RNA secondary structure is critical to understanding the function and regulation of RNA transcripts. Here, we review the origins, form, and function of RNA secondary structure, focusing on plants. We then provide an overview of methods for probing secondary structure, from physical methods such as X-ray crystallography and nuclear magnetic resonance imaging (NMR) to chemical and nuclease probing methods. Marriage with high-throughput sequencing has enabled these latter methods to scale across whole transcriptomes, yielding tremendous new insights into the form and function of RNA secondary structure. PMID:26865341

A transformation method for constrained-function minimization

NASA Technical Reports Server (NTRS)

Park, S. K.

1975-01-01

A direct method for constrained-function minimization is discussed. The method involves the construction of an appropriate function mapping all of one finite dimensional space onto the region defined by the constraints. Functions which produce such a transformation are constructed for a variety of constraint regions including, for example, those arising from linear and quadratic inequalities and equalities. In addition, the computational performance of this method is studied in the situation where the Davidon-Fletcher-Powell algorithm is used to solve the resulting unconstrained problem. Good performance is demonstrated for 19 test problems by achieving rapid convergence to a solution from several widely separated starting points.

Effects of Anchor Item Methods on the Detection of Differential Item Functioning within the Family of Rasch Models

ERIC Educational Resources Information Center

Wang, Wen-Chung

2004-01-01

Scale indeterminacy in analysis of differential item functioning (DIF) within the framework of item response theory can be resolved by imposing 3 anchor item methods: the equal-mean-difficulty method, the all-other anchor item method, and the constant anchor item method. In this article, applicability and limitations of these 3 methods are…

An optimized method to calculate error correction capability of tool influence function in frequency domain

NASA Astrophysics Data System (ADS)

Wang, Jia; Hou, Xi; Wan, Yongjian; Shi, Chunyan

2017-10-01

An optimized method to calculate error correction capability of tool influence function (TIF) in certain polishing conditions will be proposed based on smoothing spectral function. The basic mathematical model for this method will be established in theory. A set of polishing experimental data with rigid conformal tool is used to validate the optimized method. The calculated results can quantitatively indicate error correction capability of TIF for different spatial frequency errors in certain polishing conditions. The comparative analysis with previous method shows that the optimized method is simpler in form and can get the same accuracy results with less calculating time in contrast to previous method.

Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics

NASA Astrophysics Data System (ADS)

Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.

2018-02-01

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics.

PubMed

Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L

2018-02-07

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

Systematic study of inorganic functionalization of ZnO nanorods by Sol-Gel method

NASA Astrophysics Data System (ADS)

Gamarra, J. K.; Solano, C.; Piñeres, I.; Gómez, H.; Mass, J.; Montenegro, D. N.

2017-01-01

A systematic study of the inorganic surface functionalization of ZnO nanostructures by sol-gel method is shown. We have emphasized on the evolution of morphology properties of samples as a function of functionalization parameters. In addition, the effects on thermal stability and some optical properties of samples are discussed.

Locating the Discontinuities of a Bounded Function by the Partial Sums of its Fourier Series I: Periodical Case

NASA Technical Reports Server (NTRS)

Kvernadze, George; Hagstrom,Thomas; Shapiro, Henry

1997-01-01

A key step for some methods dealing with the reconstruction of a function with jump discontinuities is the accurate approximation of the jumps and their locations. Various methods have been suggested in the literature to obtain this valuable information. In the present paper, we develop an algorithm based on identities which determine the jumps of a 2(pi)-periodic bounded not-too-highly oscillating function by the partial sums of its differentiated Fourier series. The algorithm enables one to approximate the locations of discontinuities and the magnitudes of jumps of a bounded function. We study the accuracy of approximation and establish asymptotic expansions for the approximations of a 27(pi)-periodic piecewise smooth function with one discontinuity. By an appropriate linear combination, obtained via derivatives of different order, we significantly improve the accuracy. Next, we use Richardson's extrapolation method to enhance the accuracy even more. For a function with multiple discontinuities we establish simple formulae which "eliminate" all discontinuities of the function but one. Then we treat the function as if it had one singularity following the method described above.

Fitting psychometric functions using a fixed-slope parameter: an advanced alternative for estimating odor thresholds with data generated by ASTM E679.

PubMed

Peng, Mei; Jaeger, Sara R; Hautus, Michael J

2014-03-01

Psychometric functions are predominately used for estimating detection thresholds in vision and audition. However, the requirement of large data quantities for fitting psychometric functions (>30 replications) reduces their suitability in olfactory studies because olfactory response data are often limited (<4 replications) due to the susceptibility of human olfactory receptors to fatigue and adaptation. This article introduces a new method for fitting individual-judge psychometric functions to olfactory data obtained using the current standard protocol-American Society for Testing and Materials (ASTM) E679. The slope parameter of the individual-judge psychometric function is fixed to be the same as that of the group function; the same-shaped symmetrical sigmoid function is fitted only using the intercept. This study evaluated the proposed method by comparing it with 2 available methods. Comparison to conventional psychometric functions (fitted slope and intercept) indicated that the assumption of a fixed slope did not compromise precision of the threshold estimates. No systematic difference was obtained between the proposed method and the ASTM method in terms of group threshold estimates or threshold distributions, but there were changes in the rank, by threshold, of judges in the group. Overall, the fixed-slope psychometric function is recommended for obtaining relatively reliable individual threshold estimates when the quantity of data is limited.

Methods for attaching polymerizable ceragenins to water treatment membranes using amine and amide linkages

DOEpatents

Hibbs, Michael; Altman, Susan J.; Jones, Howland D.T.; Savage, Paul B.

2013-10-15

This invention relates to methods for chemically grafting and attaching ceragenin molecules to polymer substrates; methods for synthesizing ceragenin-containing copolymers; methods for making ceragenin-modified water treatment membranes and spacers; and methods of treating contaminated water using ceragenin-modified treatment membranes and spacers. Ceragenins are synthetically produced antimicrobial peptide mimics that display broad-spectrum bactericidal activity. Alkene-functionalized ceragenins (e.g., acrylamide-functionalized ceragenins) can be attached to polyamide reverse osmosis membranes using amine-linking, amide-linking, UV-grafting, or silane-coating methods. In addition, silane-functionalized ceragenins can be directly attached to polymer surfaces that have free hydroxyls.

Methods for attaching polymerizable ceragenins to water treatment membranes using silane linkages

DOEpatents

Hibbs, Michael; Altman, Susan J.; Jones, Howland D. T.; Savage, Paul B.

2013-09-10

This invention relates to methods for chemically grafting and attaching ceragenin molecules to polymer substrates; methods for synthesizing ceragenin-containing copolymers; methods for making ceragenin-modified water treatment membranes and spacers; and methods of treating contaminated water using ceragenin-modified treatment membranes and spacers. Ceragenins are synthetically produced antimicrobial peptide mimics that display broad-spectrum bactericidal activity. Alkene-functionalized ceragenins (e.g., acrylamide-functionalized ceragenins) can be attached to polyamide reverse osmosis membranes using amine-linking, amide-linking, UV-grafting, or silane-coating methods. In addition, silane-functionalized ceragenins can be directly attached to polymer surfaces that have free hydroxyls.

Computational Prediction of the Global Functional Genomic Landscape: Applications, Methods and Challenges

PubMed Central

Zhou, Weiqiang; Sherwood, Ben; Ji, Hongkai

2017-01-01

Technological advances have led to an explosive growth of high-throughput functional genomic data. Exploiting the correlation among different data types, it is possible to predict one functional genomic data type from other data types. Prediction tools are valuable in understanding the relationship among different functional genomic signals. They also provide a cost-efficient solution to inferring the unknown functional genomic profiles when experimental data are unavailable due to resource or technological constraints. The predicted data may be used for generating hypotheses, prioritizing targets, interpreting disease variants, facilitating data integration, quality control, and many other purposes. This article reviews various applications of prediction methods in functional genomics, discusses analytical challenges, and highlights some common and effective strategies used to develop prediction methods for functional genomic data. PMID:28076869

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

Partitioning of functional gene expression data using principal points.

PubMed

Kim, Jaehee; Kim, Haseong

2017-10-12

DNA microarrays offer motivation and hope for the simultaneous study of variations in multiple genes. Gene expression is a temporal process that allows variations in expression levels with a characterized gene function over a period of time. Temporal gene expression curves can be treated as functional data since they are considered as independent realizations of a stochastic process. This process requires appropriate models to identify patterns of gene functions. The partitioning of the functional data can find homogeneous subgroups of entities for the massive genes within the inherent biological networks. Therefor it can be a useful technique for the analysis of time-course gene expression data. We propose a new self-consistent partitioning method of functional coefficients for individual expression profiles based on the orthonormal basis system. A principal points based functional partitioning method is proposed for time-course gene expression data. The method explores the relationship between genes using Legendre coefficients as principal points to extract the features of gene functions. Our proposed method provides high connectivity in connectedness after clustering for simulated data and finds a significant subsets of genes with the increased connectivity. Our approach has comparative advantages that fewer coefficients are used from the functional data and self-consistency of principal points for partitioning. As real data applications, we are able to find partitioned genes through the gene expressions found in budding yeast data and Escherichia coli data. The proposed method benefitted from the use of principal points, dimension reduction, and choice of orthogonal basis system as well as provides appropriately connected genes in the resulting subsets. We illustrate our method by applying with each set of cell-cycle-regulated time-course yeast genes and E. coli genes. The proposed method is able to identify highly connected genes and to explore the complex dynamics of biological systems in functional genomics.

The Nonlinear Dynamic Response of an Elastic-Plastic Thin Plate under Impulsive Loading,

DTIC Science & Technology

1987-06-11

Among those numerical methods, the finite element method is the most effective one. The method presented in this paper is an " influence function " numerical...computational time is much less than the finite element method. Its precision is higher also. II. Basic Assumption and the Influence Function of a Simple...calculation. Fig. 1 3 2. The Influence function of a Simple Supported Plate The motion differential equation of a thin plate can be written as DV’w+ _.eluq() (1

A Tomographic Method for the Reconstruction of Local Probability Density Functions

NASA Technical Reports Server (NTRS)

Sivathanu, Y. R.; Gore, J. P.

1993-01-01

A method of obtaining the probability density function (PDF) of local properties from path integrated measurements is described. The approach uses a discrete probability function (DPF) method to infer the PDF of the local extinction coefficient from measurements of the PDFs of the path integrated transmittance. The local PDFs obtained using the method are compared with those obtained from direct intrusive measurements in propylene/air and ethylene/air diffusion flames. The results of this comparison are good.

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).

A path-based measurement for human miRNA functional similarities using miRNA-disease associations

NASA Astrophysics Data System (ADS)

Ding, Pingjian; Luo, Jiawei; Xiao, Qiu; Chen, Xiangtao

2016-09-01

Compared with the sequence and expression similarity, miRNA functional similarity is so important for biology researches and many applications such as miRNA clustering, miRNA function prediction, miRNA synergism identification and disease miRNA prioritization. However, the existing methods always utilized the predicted miRNA target which has high false positive and false negative to calculate the miRNA functional similarity. Meanwhile, it is difficult to achieve high reliability of miRNA functional similarity with miRNA-disease associations. Therefore, it is increasingly needed to improve the measurement of miRNA functional similarity. In this study, we develop a novel path-based calculation method of miRNA functional similarity based on miRNA-disease associations, called MFSP. Compared with other methods, our method obtains higher average functional similarity of intra-family and intra-cluster selected groups. Meanwhile, the lower average functional similarity of inter-family and inter-cluster miRNA pair is obtained. In addition, the smaller p-value is achieved, while applying Wilcoxon rank-sum test and Kruskal-Wallis test to different miRNA groups. The relationship between miRNA functional similarity and other information sources is exhibited. Furthermore, the constructed miRNA functional network based on MFSP is a scale-free and small-world network. Moreover, the higher AUC for miRNA-disease prediction indicates the ability of MFSP uncovering miRNA functional similarity.

A numerical method to solve the 1D and the 2D reaction diffusion equation based on Bessel functions and Jacobian free Newton-Krylov subspace methods

NASA Astrophysics Data System (ADS)

Parand, K.; Nikarya, M.

2017-11-01

In this paper a novel method will be introduced to solve a nonlinear partial differential equation (PDE). In the proposed method, we use the spectral collocation method based on Bessel functions of the first kind and the Jacobian free Newton-generalized minimum residual (JFNGMRes) method with adaptive preconditioner. In this work a nonlinear PDE has been converted to a nonlinear system of algebraic equations using the collocation method based on Bessel functions without any linearization, discretization or getting the help of any other methods. Finally, by using JFNGMRes, the solution of the nonlinear algebraic system is achieved. To illustrate the reliability and efficiency of the proposed method, we solve some examples of the famous Fisher equation. We compare our results with other methods.

Flexible functional regression methods for estimating individualized treatment regimes.

PubMed

Ciarleglio, Adam; Petkova, Eva; Tarpey, Thaddeus; Ogden, R Todd

2016-01-01

A major focus of personalized medicine is on the development of individualized treatment rules. Good decision rules have the potential to significantly advance patient care and reduce the burden of a host of diseases. Statistical methods for developing such rules are progressing rapidly, but few methods have considered the use of pre-treatment functional data to guide in decision-making. Furthermore, those methods that do allow for the incorporation of functional pre-treatment covariates typically make strong assumptions about the relationships between the functional covariates and the response of interest. We propose two approaches for using functional data to select an optimal treatment that address some of the shortcomings of previously developed methods. Specifically, we combine the flexibility of functional additive regression models with Q -learning or A -learning in order to obtain treatment decision rules. Properties of the corresponding estimators are discussed. Our approaches are evaluated in several realistic settings using synthetic data and are applied to real data arising from a clinical trial comparing two treatments for major depressive disorder in which baseline imaging data are available for subjects who are subsequently treated.

Stochastic reconstructions of spectral functions: Application to lattice QCD

NASA Astrophysics Data System (ADS)

Ding, H.-T.; Kaczmarek, O.; Mukherjee, Swagato; Ohno, H.; Shu, H.-T.

2018-05-01

We present a detailed study of the applications of two stochastic approaches, stochastic optimization method (SOM) and stochastic analytical inference (SAI), to extract spectral functions from Euclidean correlation functions. SOM has the advantage that it does not require prior information. On the other hand, SAI is a more generalized method based on Bayesian inference. Under mean field approximation SAI reduces to the often-used maximum entropy method (MEM) and for a specific choice of the prior SAI becomes equivalent to SOM. To test the applicability of these two stochastic methods to lattice QCD, firstly, we apply these methods to various reasonably chosen model correlation functions and present detailed comparisons of the reconstructed spectral functions obtained from SOM, SAI and MEM. Next, we present similar studies for charmonia correlation functions obtained from lattice QCD computations using clover-improved Wilson fermions on large, fine, isotropic lattices at 0.75 and 1.5 Tc, Tc being the deconfinement transition temperature of a pure gluon plasma. We find that SAI and SOM give consistent results to MEM at these two temperatures.

MIMIC Methods for Assessing Differential Item Functioning in Polytomous Items

ERIC Educational Resources Information Center

Wang, Wen-Chung; Shih, Ching-Lin

2010-01-01

Three multiple indicators-multiple causes (MIMIC) methods, namely, the standard MIMIC method (M-ST), the MIMIC method with scale purification (M-SP), and the MIMIC method with a pure anchor (M-PA), were developed to assess differential item functioning (DIF) in polytomous items. In a series of simulations, it appeared that all three methods…

In search of functional association from time-series microarray data based on the change trend and level of gene expression

PubMed Central

He, Feng; Zeng, An-Ping

2006-01-01

Background The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional linkages between genes from expression data are mainly based on a point-to-point comparison. Change trends between consecutive time points in time-series data have been so far not well explored. Results In this work we present a new method based on extracting main features of the change trend and level of gene expression between consecutive time points. The method, termed as trend correlation (TC), includes two major steps: 1, calculating a maximal local alignment of change trend score by dynamic programming and a change trend correlation coefficient between the maximal matched change levels of each gene pair; 2, inferring relationships of gene pairs based on two statistical extraction procedures. The new method considers time shifts and inverted relationships in a similar way as the local clustering (LC) method but the latter is merely based on a point-to-point comparison. The TC method is demonstrated with data from yeast cell cycle and compared with the LC method and the widely used Pearson correlation coefficient (PCC) based clustering method. The biological significance of the gene pairs is examined with several large-scale yeast databases. Although the TC method predicts an overall lower number of gene pairs than the other two methods at a same p-value threshold, the additional number of gene pairs inferred by the TC method is considerable: e.g. 20.5% compared with the LC method and 49.6% with the PCC method for a p-value threshold of 2.7E-3. Moreover, the percentage of the inferred gene pairs consistent with databases by our method is generally higher than the LC method and similar to the PCC method. A significant number of the gene pairs only inferred by the TC method are process-identity or function-similarity pairs or have well-documented biological interactions, including 443 known protein interactions and some known cell cycle related regulatory interactions. It should be emphasized that the overlapping of gene pairs detected by the three methods is normally not very high, indicating a necessity of combining the different methods in search of functional association of genes from time-series data. For a p-value threshold of 1E-5 the percentage of process-identity and function-similarity gene pairs among the shared part of the three methods reaches 60.2% and 55.6% respectively, building a good basis for further experimental and functional study. Furthermore, the combined use of methods is important to infer more complete regulatory circuits and network as exemplified in this study. Conclusion The TC method can significantly augment the current major methods to infer functional linkages and biological network and is well suitable for exploring temporal relationships of gene expression in time-series data. PMID:16478547

Couple of the Variational Iteration Method and Fractional-Order Legendre Functions Method for Fractional Differential Equations

PubMed Central

Song, Junqiang; Leng, Hongze; Lu, Fengshun

2014-01-01

We present a new numerical method to get the approximate solutions of fractional differential equations. A new operational matrix of integration for fractional-order Legendre functions (FLFs) is first derived. Then a modified variational iteration formula which can avoid “noise terms” is constructed. Finally a numerical method based on variational iteration method (VIM) and FLFs is developed for fractional differential equations (FDEs). Block-pulse functions (BPFs) are used to calculate the FLFs coefficient matrices of the nonlinear terms. Five examples are discussed to demonstrate the validity and applicability of the technique. PMID:24511303

Biofouling-resistant ceragenin-modified materials and structures for water treatment

DOEpatents

Hibbs, Michael; Altman, Susan J.; Jones, Howland D. T.; Savage, Paul B.

2013-09-10

This invention relates to methods for chemically grafting and attaching ceragenin molecules to polymer substrates; methods for synthesizing ceragenin-containing copolymers; methods for making ceragenin-modified water treatment membranes and spacers; and methods of treating contaminated water using ceragenin-modified treatment membranes and spacers. Ceragenins are synthetically produced antimicrobial peptide mimics that display broad-spectrum bactericidal activity. Alkene-functionalized ceragenins (e.g., acrylamide-functionalized ceragenins) can be attached to polyamide reverse osmosis membranes using amine-linking, amide-linking, UV-grafting, or silane-coating methods. In addition, silane-functionalized ceragenins can be directly attached to polymer surfaces that have free hydroxyls.

Methods for selective functionalization and separation of carbon nanotubes

NASA Technical Reports Server (NTRS)

Strano, Michael S. (Inventor); Usrey, Monica (Inventor); Barone, Paul (Inventor); Dyke, Christopher A. (Inventor); Tour, James M. (Inventor); Kittrell, W. Carter (Inventor); Hauge, Robert H (Inventor); Smalley, Richard E. (Inventor); Marek, legal representative, Irene Marie (Inventor)

2011-01-01

The present invention is directed toward methods of selectively functionalizing carbon nanotubes of a specific type or range of types, based on their electronic properties, using diazonium chemistry. The present invention is also directed toward methods of separating carbon nanotubes into populations of specific types or range(s) of types via selective functionalization and electrophoresis, and also to the novel compositions generated by such separations.

Recursive search method for the image elements of functionally defined surfaces

NASA Astrophysics Data System (ADS)

Vyatkin, S. I.

2017-05-01

This paper touches upon the synthesis of high-quality images in real time and the technique for specifying three-dimensional objects on the basis of perturbation functions. The recursive search method for the image elements of functionally defined objects with the use of graphics processing units is proposed. The advantages of such an approach over the frame-buffer visualization method are shown.

Inversion of the strain-life and strain-stress relationships for use in metal fatigue analysis

NASA Technical Reports Server (NTRS)

Manson, S. S.

1979-01-01

The paper presents closed-form solutions (collocation method and spline-function method) for the constants of the cyclic fatigue life equation so that they can be easily incorporated into cumulative damage analysis. The collocation method involves conformity with the experimental curve at specific life values. The spline-function method is such that the basic life relation is expressed as a two-part function, one applicable at strains above the transition strain (strain at intersection of elastic and plastic lines), the other below. An illustrative example is treated by both methods. It is shown that while the collocation representation has the advantage of simplicity of form, the spline-function representation can be made more accurate over a wider life range, and is simpler to use.

Geometrical comparison of two protein structures using Wigner-D functions.

PubMed

Saberi Fathi, S M; White, Diana T; Tuszynski, Jack A

2014-10-01

In this article, we develop a quantitative comparison method for two arbitrary protein structures. This method uses a root-mean-square deviation characterization and employs a series expansion of the protein's shape function in terms of the Wigner-D functions to define a new criterion, which is called a "similarity value." We further demonstrate that the expansion coefficients for the shape function obtained with the help of the Wigner-D functions correspond to structure factors. Our method addresses the common problem of comparing two proteins with different numbers of atoms. We illustrate it with a worked example. © 2014 Wiley Periodicals, Inc.

An Efficient Functional Test Generation Method For Processors Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Hudec, Ján; Gramatová, Elena

2015-07-01

The paper presents a new functional test generation method for processors testing based on genetic algorithms and evolutionary strategies. The tests are generated over an instruction set architecture and a processor description. Such functional tests belong to the software-oriented testing. Quality of the tests is evaluated by code coverage of the processor description using simulation. The presented test generation method uses VHDL models of processors and the professional simulator ModelSim. The rules, parameters and fitness functions were defined for various genetic algorithms used in automatic test generation. Functionality and effectiveness were evaluated using the RISC type processor DP32.

One-pot preparation of unsaturated polyester nanocomposites containing functionalized graphene sheets via a novel solvent-exchange method

USDA-ARS?s Scientific Manuscript database

This paper reports a convenient one-pot method integrating a novel solvent-exchange method into in situ melt polycondensation to fabricate unsaturated polyester nanocomposites containing functionalized graphene sheets (FGS). A novel solvent-exchange method was first developed to prepare graphene oxi...

Developing rapid methods for analyzing upland riparian functions and values.

PubMed

Hruby, Thomas

2009-06-01

Regulators protecting riparian areas need to understand the integrity, health, beneficial uses, functions, and values of this resource. Up to now most methods providing information about riparian areas are based on analyzing condition or integrity. These methods, however, provide little information about functions and values. Different methods are needed that specifically address this aspect of riparian areas. In addition to information on functions and values, regulators have very specific needs that include: an analysis at the site scale, low cost, usability, and inclusion of policy interpretations. To meet these needs a rapid method has been developed that uses a multi-criteria decision matrix to categorize riparian areas in Washington State, USA. Indicators are used to identify the potential of the site to provide a function, the potential of the landscape to support the function, and the value the function provides to society. To meet legal needs fixed boundaries for assessment units are established based on geomorphology, the distance from "Ordinary High Water Mark" and different categories of land uses. Assessment units are first classified based on ecoregions, geomorphic characteristics, and land uses. This simplifies the data that need to be collected at a site, but it requires developing and calibrating a separate model for each "class." The approach to developing methods is adaptable to other locations as its basic structure is not dependent on local conditions.

Statistical technique for analysing functional connectivity of multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman

2011-03-15

A new statistical technique, the Cox method, used for analysing functional connectivity of simultaneously recorded multiple spike trains is presented. This method is based on the theory of modulated renewal processes and it estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connectivity an "influence function" is identified. This function recognises the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. In comparison to existing techniques, the Cox method has the following advantages: it does not use bins (binless method); it is applicable to cases where the sample size is small; it is sufficiently sensitive such that it estimates weak influences; it supports the simultaneous analysis of multiple influences; it is able to identify a correct connectivity scheme in difficult cases of "common source" or "indirect" connectivity. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analysing functional connectivity of simultaneously recorded multiple spike trains. Copyright © 2011 Elsevier B.V. All rights reserved.

New deconvolution method for microscopic images based on the continuous Gaussian radial basis function interpolation model.

PubMed

Chen, Zhaoxue; Chen, Hao

2014-01-01

A deconvolution method based on the Gaussian radial basis function (GRBF) interpolation is proposed. Both the original image and Gaussian point spread function are expressed as the same continuous GRBF model, thus image degradation is simplified as convolution of two continuous Gaussian functions, and image deconvolution is converted to calculate the weighted coefficients of two-dimensional control points. Compared with Wiener filter and Lucy-Richardson algorithm, the GRBF method has an obvious advantage in the quality of restored images. In order to overcome such a defect of long-time computing, the method of graphic processing unit multithreading or increasing space interval of control points is adopted, respectively, to speed up the implementation of GRBF method. The experiments show that based on the continuous GRBF model, the image deconvolution can be efficiently implemented by the method, which also has a considerable reference value for the study of three-dimensional microscopic image deconvolution.

Habitat suitability criteria via parametric distributions: estimation, model selection and uncertainty

USGS Publications Warehouse

Som, Nicholas A.; Goodman, Damon H.; Perry, Russell W.; Hardy, Thomas B.

2016-01-01

Previous methods for constructing univariate habitat suitability criteria (HSC) curves have ranged from professional judgement to kernel-smoothed density functions or combinations thereof. We present a new method of generating HSC curves that applies probability density functions as the mathematical representation of the curves. Compared with previous approaches, benefits of our method include (1) estimation of probability density function parameters directly from raw data, (2) quantitative methods for selecting among several candidate probability density functions, and (3) concise methods for expressing estimation uncertainty in the HSC curves. We demonstrate our method with a thorough example using data collected on the depth of water used by juvenile Chinook salmon (Oncorhynchus tschawytscha) in the Klamath River of northern California and southern Oregon. All R code needed to implement our example is provided in the appendix. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

A Model for Minimizing Numeric Function Generator Complexity and Delay

DTIC Science & Technology

2007-12-01

allow computation of difficult mathematical functions in less time and with less hardware than commonly employed methods. They compute piecewise...Programmable Gate Arrays (FPGAs). The algorithms and estimation techniques apply to various NFG architectures and mathematical functions. This...thesis compares hardware utilization and propagation delay for various NFG architectures, mathematical functions, word widths, and segmentation methods

Developing Mathematical Knowledge for Teaching in a Methods Course: The Case of Function

ERIC Educational Resources Information Center

Steele, Michael D.; Hillen, Amy F.; Smith, Margaret S.

2013-01-01

This study describes teacher learning in a teaching experiment consisting of a content-focused methods course involving the mathematical knowledge for teaching function. Prospective and practicing teachers in the course showed growth in their ability to define function, to provide examples of functions and link them to the definition, in the…

A Mixed-Method Exploration of Functioning in Safe Schools/Healthy Students Partnerships

ERIC Educational Resources Information Center

Merrill, Marina L.; Taylor, Nicole L.; Martin, Alison J.; Maxim, Lauren A.; D'Ambrosio, Ryan; Gabriel, Roy M.; Wendt, Staci J.; Mannix, Danyelle; Wells, Michael E.

2012-01-01

This paper presents a mixed-method approach to measuring the functioning of Safe Schools/Healthy Students (SS/HS) Initiative partnerships. The SS/HS national evaluation team developed a survey to collect partners' perceptions of functioning within SS/HS partnerships. Average partnership functioning scores were used to rank each site from lowest to…

Parametric Bayesian priors and better choice of negative examples improve protein function prediction.

PubMed

Youngs, Noah; Penfold-Brown, Duncan; Drew, Kevin; Shasha, Dennis; Bonneau, Richard

2013-05-01

Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key parameters. The improper choice of negative examples, in particular, can hamper the accuracy of protein function prediction. We present a novel approach for choosing negative examples, using a parameterizable Bayesian prior computed from all observed annotation data, which also generates priors used during function prediction. We incorporate this new method into the GeneMANIA function prediction algorithm and demonstrate improved accuracy of our algorithm over current top-performing function prediction methods on the yeast and mouse proteomes across all metrics tested. Code and Data are available at: http://bonneaulab.bio.nyu.edu/funcprop.html

Functional renormalization group and Kohn-Sham scheme in density functional theory

NASA Astrophysics Data System (ADS)

Liang, Haozhao; Niu, Yifei; Hatsuda, Tetsuo

2018-04-01

Deriving accurate energy density functional is one of the central problems in condensed matter physics, nuclear physics, and quantum chemistry. We propose a novel method to deduce the energy density functional by combining the idea of the functional renormalization group and the Kohn-Sham scheme in density functional theory. The key idea is to solve the renormalization group flow for the effective action decomposed into the mean-field part and the correlation part. Also, we propose a simple practical method to quantify the uncertainty associated with the truncation of the correlation part. By taking the φ4 theory in zero dimension as a benchmark, we demonstrate that our method shows extremely fast convergence to the exact result even for the highly strong coupling regime.

Functional linear models to test for differences in prairie wetland hydraulic gradients

USGS Publications Warehouse

Greenwood, Mark C.; Sojda, Richard S.; Preston, Todd M.; Swayne, David A.; Yang, Wanhong; Voinov, A.A.; Rizzoli, A.; Filatova, T.

2010-01-01

Functional data analysis provides a framework for analyzing multiple time series measured frequently in time, treating each series as a continuous function of time. Functional linear models are used to test for effects on hydraulic gradient functional responses collected from three types of land use in Northeastern Montana at fourteen locations. Penalized regression-splines are used to estimate the underlying continuous functions based on the discretely recorded (over time) gradient measurements. Permutation methods are used to assess the statistical significance of effects. A method for accommodating missing observations in each time series is described. Hydraulic gradients may be an initial and fundamental ecosystem process that responds to climate change. We suggest other potential uses of these methods for detecting evidence of climate change.

Comparison of some optimal control methods for the design of turbine blades

NASA Technical Reports Server (NTRS)

Desilva, B. M. E.; Grant, G. N. C.

1977-01-01

This paper attempts a comparative study of some numerical methods for the optimal control design of turbine blades whose vibration characteristics are approximated by Timoshenko beam idealizations with shear and incorporating simple boundary conditions. The blade was synthesized using the following methods: (1) conjugate gradient minimization of the system Hamiltonian in function space incorporating penalty function transformations, (2) projection operator methods in a function space which includes the frequencies of vibration and the control function, (3) epsilon-technique penalty function transformation resulting in a highly nonlinear programming problem, (4) finite difference discretization of the state equations again resulting in a nonlinear program, (5) second variation methods with complex state differential equations to include damping effects resulting in systems of inhomogeneous matrix Riccatti equations some of which are stiff, (6) quasi-linear methods based on iterative linearization of the state and adjoint equation. The paper includes a discussion of some substantial computational difficulties encountered in the implementation of these techniques together with a resume of work presently in progress using a differential dynamic programming approach.

Coupling Finite Element and Meshless Local Petrov-Galerkin Methods for Two-Dimensional Potential Problems

NASA Technical Reports Server (NTRS)

Chen, T.; Raju, I. S.

2002-01-01

A coupled finite element (FE) method and meshless local Petrov-Galerkin (MLPG) method for analyzing two-dimensional potential problems is presented in this paper. The analysis domain is subdivided into two regions, a finite element (FE) region and a meshless (MM) region. A single weighted residual form is written for the entire domain. Independent trial and test functions are assumed in the FE and MM regions. A transition region is created between the two regions. The transition region blends the trial and test functions of the FE and MM regions. The trial function blending is achieved using a technique similar to the 'Coons patch' method that is widely used in computer-aided geometric design. The test function blending is achieved by using either FE or MM test functions on the nodes in the transition element. The technique was evaluated by applying the coupled method to two potential problems governed by the Poisson equation. The coupled method passed all the patch test problems and gave accurate solutions for the problems studied.

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

A multi-label learning based kernel automatic recommendation method for support vector machine.

PubMed

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

A Multi-Label Learning Based Kernel Automatic Recommendation Method for Support Vector Machine

PubMed Central

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance. PMID:25893896

Complementary and alternative medicine used by persons with functional gastrointestinal disorders to alleviate symptom distress.

PubMed

Stake-Nilsson, Kerstin; Hultcrantz, Rolf; Unge, Peter; Wengström, Yvonne

2012-03-01

The aim of this study was to describe the complementary and alternative medicine methods most commonly used to alleviate symptom distress in persons with functional gastrointestinal disorders. People with functional gastrointestinal disorders face many challenges in their everyday lives, and each individual has his/her own way of dealing with this illness. The experience of illness often leads persons with functional gastrointestinal disorders to complementary and alternative medicine as a viable healthcare choice. Quantitative and describing design. A study-specific complementary and alternative medicine questionnaire was used, including questions about complementary and alternative medicine methods used and the perceived effects of each method. Efficacy assessments for each method were preventive effect, partial symptom relief, total symptom relief or no effect. A total of 137 persons with functional gastrointestinal disorders answered the questionnaire, 62% (n = 85) women and 38% (n = 52) men. A total of 28 different complementary and alternative medicine methods were identified and grouped into four categories: nutritional, drug/biological, psychological activity and physical activity. All persons had tried at least one method, and most methods provided partial symptom relief. Persons with functional gastrointestinal disorders commonly use complementary and alternative medicine methods to alleviate symptoms. Nurses have a unique opportunity to expand their roles in this group of patients. Increased knowledge of complementary and alternative medicine practices would enable a more comprehensive patient assessment and a better plan for meaningful interventions that meet the needs of individual patients. © 2011 Blackwell Publishing Ltd.

Contact resistance extraction methods for short- and long-channel carbon nanotube field-effect transistors

NASA Astrophysics Data System (ADS)

Pacheco-Sanchez, Anibal; Claus, Martin; Mothes, Sven; Schröter, Michael

2016-11-01

Three different methods for the extraction of the contact resistance based on both the well-known transfer length method (TLM) and two variants of the Y-function method have been applied to simulation and experimental data of short- and long-channel CNTFETs. While for TLM special CNT test structures are mandatory, standard electrical device characteristics are sufficient for the Y-function methods. The methods have been applied to CNTFETs with low and high channel resistance. It turned out that the standard Y-function method fails to deliver the correct contact resistance in case of a relatively high channel resistance compared to the contact resistances. A physics-based validation is also given for the application of these methods based on applying traditional Si MOSFET theory to quasi-ballistic CNTFETs.

Methods of Attaching or Grafting Carbon Nanotubes to Silicon Surfaces and Composite Structures Derived Therefrom

NASA Technical Reports Server (NTRS)

Tour, James M. (Inventor); Chen, Bo (Inventor); Flatt, Austen K. (Inventor); Stewart, Michael P. (Inventor); Dyke, Christopher A. (Inventor); Maya, Francisco (Inventor)

2012-01-01

The present invention is directed toward methods of attaching or grafting carbon nanotubes (CNTs) to silicon surfaces. In some embodiments, such attaching or grafting occurs via functional groups on either or both of the CNTs and silicon surface. In some embodiments, the methods of the present invention include: (1) reacting a silicon surface with a functionalizing agent (such as oligo(phenylene ethynylene)) to form a functionalized silicon surface; (2) dispersing a quantity of CNTs in a solvent to form dispersed CNTs; and (3) reacting the functionalized silicon surface with the dispersed CNTs. The present invention is also directed to the novel compositions produced by such methods.

Numerical solution to generalized Burgers'-Fisher equation using Exp-function method hybridized with heuristic computation.

PubMed

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems.

Numerical Solution to Generalized Burgers'-Fisher Equation Using Exp-Function Method Hybridized with Heuristic Computation

PubMed Central

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems. PMID:25811858

Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.

PubMed

Zou, Ling; Guo, Qian; Xu, Yi; Yang, Biao; Jiao, Zhuqing; Xiang, Jianbo

2016-04-29

Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.

Power Series Approximation for the Correlation Kernel Leading to Kohn-Sham Methods Combining Accuracy, Computational Efficiency, and General Applicability

NASA Astrophysics Data System (ADS)

Erhard, Jannis; Bleiziffer, Patrick; Görling, Andreas

2016-09-01

A power series approximation for the correlation kernel of time-dependent density-functional theory is presented. Using this approximation in the adiabatic-connection fluctuation-dissipation (ACFD) theorem leads to a new family of Kohn-Sham methods. The new methods yield reaction energies and barriers of unprecedented accuracy and enable a treatment of static (strong) correlation with an accuracy of high-level multireference configuration interaction methods but are single-reference methods allowing for a black-box-like handling of static correlation. The new methods exhibit a better scaling of the computational effort with the system size than rivaling wave-function-based electronic structure methods. Moreover, the new methods do not suffer from the problem of singularities in response functions plaguing previous ACFD methods and therefore are applicable to any type of electronic system.

New approach to canonical partition functions computation in Nf=2 lattice QCD at finite baryon density

NASA Astrophysics Data System (ADS)

Bornyakov, V. G.; Boyda, D. L.; Goy, V. A.; Molochkov, A. V.; Nakamura, Atsushi; Nikolaev, A. A.; Zakharov, V. I.

2017-05-01

We propose and test a new approach to computation of canonical partition functions in lattice QCD at finite density. We suggest a few steps procedure. We first compute numerically the quark number density for imaginary chemical potential i μq I . Then we restore the grand canonical partition function for imaginary chemical potential using the fitting procedure for the quark number density. Finally we compute the canonical partition functions using high precision numerical Fourier transformation. Additionally we compute the canonical partition functions using the known method of the hopping parameter expansion and compare results obtained by two methods in the deconfining as well as in the confining phases. The agreement between two methods indicates the validity of the new method. Our numerical results are obtained in two flavor lattice QCD with clover improved Wilson fermions.

A large-scale evaluation of computational protein function prediction

PubMed Central

Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

2013-01-01

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

Incorporating molecular and functional context into the analysis and prioritization of human variants associated with cancer

PubMed Central

Peterson, Thomas A; Nehrt, Nathan L; Park, DoHwan

2012-01-01

Background and objective With recent breakthroughs in high-throughput sequencing, identifying deleterious mutations is one of the key challenges for personalized medicine. At the gene and protein level, it has proven difficult to determine the impact of previously unknown variants. A statistical method has been developed to assess the significance of disease mutation clusters on protein domains by incorporating domain functional annotations to assist in the functional characterization of novel variants. Methods Disease mutations aggregated from multiple databases were mapped to domains, and were classified as either cancer- or non-cancer-related. The statistical method for identifying significantly disease-associated domain positions was applied to both sets of mutations and to randomly generated mutation sets for comparison. To leverage the known function of protein domain regions, the method optionally distributes significant scores to associated functional feature positions. Results Most disease mutations are localized within protein domains and display a tendency to cluster at individual domain positions. The method identified significant disease mutation hotspots in both the cancer and non-cancer datasets. The domain significance scores (DS-scores) for cancer form a bimodal distribution with hotspots in oncogenes forming a second peak at higher DS-scores than non-cancer, and hotspots in tumor suppressors have scores more similar to non-cancers. In addition, on an independent mutation benchmarking set, the DS-score method identified mutations known to alter protein function with very high precision. Conclusion By aggregating mutations with known disease association at the domain level, the method was able to discover domain positions enriched with multiple occurrences of deleterious mutations while incorporating relevant functional annotations. The method can be incorporated into translational bioinformatics tools to characterize rare and novel variants within large-scale sequencing studies. PMID:22319177

Multimethod Investigation of Interpersonal Functioning in Borderline Personality Disorder

PubMed Central

Stepp, Stephanie D.; Hallquist, Michael N.; Morse, Jennifer Q.; Pilkonis, Paul A.

2011-01-01

Even though interpersonal functioning is of great clinical importance for patients with borderline personality disorder (BPD), the comparative validity of different assessment methods for interpersonal dysfunction has not yet been tested. This study examined multiple methods of assessing interpersonal functioning, including self- and other-reports, clinical ratings, electronic diaries, and social cognitions in three groups of psychiatric patients (N=138): patients with (1) BPD, (2) another personality disorder, and (3) Axis I psychopathology only. Using dominance analysis, we examined the predictive validity of each method in detecting changes in symptom distress and social functioning six months later. Across multiple methods, the BPD group often reported higher interpersonal dysfunction scores compared to other groups. Predictive validity results demonstrated that self-report and electronic diary ratings were the most important predictors of distress and social functioning. Our findings suggest that self-report scores and electronic diary ratings have high clinical utility, as these methods appear most sensitive to change. PMID:21808661

Penalized Nonlinear Least Squares Estimation of Time-Varying Parameters in Ordinary Differential Equations

PubMed Central

Cao, Jiguo; Huang, Jianhua Z.; Wu, Hulin

2012-01-01

Ordinary differential equations (ODEs) are widely used in biomedical research and other scientific areas to model complex dynamic systems. It is an important statistical problem to estimate parameters in ODEs from noisy observations. In this article we propose a method for estimating the time-varying coefficients in an ODE. Our method is a variation of the nonlinear least squares where penalized splines are used to model the functional parameters and the ODE solutions are approximated also using splines. We resort to the implicit function theorem to deal with the nonlinear least squares objective function that is only defined implicitly. The proposed penalized nonlinear least squares method is applied to estimate a HIV dynamic model from a real dataset. Monte Carlo simulations show that the new method can provide much more accurate estimates of functional parameters than the existing two-step local polynomial method which relies on estimation of the derivatives of the state function. Supplemental materials for the article are available online. PMID:23155351

A novel edge-preserving nonnegative matrix factorization method for spectral unmixing

NASA Astrophysics Data System (ADS)

Bao, Wenxing; Ma, Ruishi

2015-12-01

Spectral unmixing technique is one of the key techniques to identify and classify the material in the hyperspectral image processing. A novel robust spectral unmixing method based on nonnegative matrix factorization(NMF) is presented in this paper. This paper used an edge-preserving function as hypersurface cost function to minimize the nonnegative matrix factorization. To minimize the hypersurface cost function, we constructed the updating functions for signature matrix of end-members and abundance fraction respectively. The two functions are updated alternatively. For evaluation purpose, synthetic data and real data have been used in this paper. Synthetic data is used based on end-members from USGS digital spectral library. AVIRIS Cuprite dataset have been used as real data. The spectral angle distance (SAD) and abundance angle distance(AAD) have been used in this research for assessment the performance of proposed method. The experimental results show that this method can obtain more ideal results and good accuracy for spectral unmixing than present methods.

An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

PubMed

Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng

2018-04-20

Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.

Meshless Local Petrov-Galerkin Method for Bending Problems

NASA Technical Reports Server (NTRS)

Phillips, Dawn R.; Raju, Ivatury S.

2002-01-01

Recent literature shows extensive research work on meshless or element-free methods as alternatives to the versatile Finite Element Method. One such meshless method is the Meshless Local Petrov-Galerkin (MLPG) method. In this report, the method is developed for bending of beams - C1 problems. A generalized moving least squares (GMLS) interpolation is used to construct the trial functions, and spline and power weight functions are used as the test functions. The method is applied to problems for which exact solutions are available to evaluate its effectiveness. The accuracy of the method is demonstrated for problems with load discontinuities and continuous beam problems. A Petrov-Galerkin implementation of the method is shown to greatly reduce computational time and effort and is thus preferable over the previously developed Galerkin approach. The MLPG method for beam problems yields very accurate deflections and slopes and continuous moment and shear forces without the need for elaborate post-processing techniques.

System and method for determining stability of a neural system

NASA Technical Reports Server (NTRS)

Curtis, Steven A. (Inventor)

2011-01-01

Disclosed are methods, systems, and computer-readable media for determining stability of a neural system. The method includes tracking a function world line of an N element neural system within at least one behavioral space, determining whether the tracking function world line is approaching a psychological stability surface, and implementing a quantitative solution that corrects instability if the tracked function world line is approaching the psychological stability surface.

A Decision Analysis Framework for Evaluation of Helmet Mounted Display Alternatives for Fighter Aircraft

DTIC Science & Technology

2014-12-26

additive value function, which assumes mutual preferential independence (Gregory S. Parnell, 2013). In other words, this method can be used if the... additive value function method to calculate the aggregate value of multiple objectives. Step 9 : Sensitivity Analysis Once the global values are...gravity metric, the additive method will be applied using equal weights for each axis value function. Pilot Satisfaction (Usability) As expressed

Multi-scale and Multi-physics Numerical Methods for Modeling Transport in Mesoscopic Systems

DTIC Science & Technology

2014-10-13

function and wide band Fast multipole methods for Hankel waves. (2) a new linear scaling discontinuous Galerkin density functional theory, which provide a...inflow boundary condition for Wigner quantum transport equations. Also, a book titled "Computational Methods for Electromagnetic Phenomena...equationsin layered media with FMM for Bessel functions , Science China Mathematics, (12 2013): 2561. doi: TOTAL: 6 Number of Papers published in peer

Multivariate spline methods in surface fitting

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator); Schumaker, L. L.

1984-01-01

The use of spline functions in the development of classification algorithms is examined. In particular, a method is formulated for producing spline approximations to bivariate density functions where the density function is decribed by a histogram of measurements. The resulting approximations are then incorporated into a Bayesiaan classification procedure for which the Bayes decision regions and the probability of misclassification is readily computed. Some preliminary numerical results are presented to illustrate the method.

Comparison of two fractal interpolation methods

NASA Astrophysics Data System (ADS)

Fu, Yang; Zheng, Zeyu; Xiao, Rui; Shi, Haibo

2017-03-01

As a tool for studying complex shapes and structures in nature, fractal theory plays a critical role in revealing the organizational structure of the complex phenomenon. Numerous fractal interpolation methods have been proposed over the past few decades, but they differ substantially in the form features and statistical properties. In this study, we simulated one- and two-dimensional fractal surfaces by using the midpoint displacement method and the Weierstrass-Mandelbrot fractal function method, and observed great differences between the two methods in the statistical characteristics and autocorrelation features. From the aspect of form features, the simulations of the midpoint displacement method showed a relatively flat surface which appears to have peaks with different height as the fractal dimension increases. While the simulations of the Weierstrass-Mandelbrot fractal function method showed a rough surface which appears to have dense and highly similar peaks as the fractal dimension increases. From the aspect of statistical properties, the peak heights from the Weierstrass-Mandelbrot simulations are greater than those of the middle point displacement method with the same fractal dimension, and the variances are approximately two times larger. When the fractal dimension equals to 1.2, 1.4, 1.6, and 1.8, the skewness is positive with the midpoint displacement method and the peaks are all convex, but for the Weierstrass-Mandelbrot fractal function method the skewness is both positive and negative with values fluctuating in the vicinity of zero. The kurtosis is less than one with the midpoint displacement method, and generally less than that of the Weierstrass-Mandelbrot fractal function method. The autocorrelation analysis indicated that the simulation of the midpoint displacement method is not periodic with prominent randomness, which is suitable for simulating aperiodic surface. While the simulation of the Weierstrass-Mandelbrot fractal function method has strong periodicity, which is suitable for simulating periodic surface.

A non-linear regression analysis program for describing electrophysiological data with multiple functions using Microsoft Excel.

PubMed

Brown, Angus M

2006-04-01

The objective of this present study was to demonstrate a method for fitting complex electrophysiological data with multiple functions using the SOLVER add-in of the ubiquitous spreadsheet Microsoft Excel. SOLVER minimizes the difference between the sum of the squares of the data to be fit and the function(s) describing the data using an iterative generalized reduced gradient method. While it is a straightforward procedure to fit data with linear functions, and we have previously demonstrated a method of non-linear regression analysis of experimental data based upon a single function, it is more complex to fit data with multiple functions, usually requiring specialized expensive computer software. In this paper we describe an easily understood program for fitting experimentally acquired data, in this case the stimulus-evoked compound action potential from the mouse optic nerve, with multiple Gaussian functions. The program is flexible and can be applied to describe data with a wide variety of user-input functions.

Towards fully automated structure-based function prediction in structural genomics: a case study.

PubMed

Watson, James D; Sanderson, Steve; Ezersky, Alexandra; Savchenko, Alexei; Edwards, Aled; Orengo, Christine; Joachimiak, Andrzej; Laskowski, Roman A; Thornton, Janet M

2007-04-13

As the global Structural Genomics projects have picked up pace, the number of structures annotated in the Protein Data Bank as hypothetical protein or unknown function has grown significantly. A major challenge now involves the development of computational methods to assign functions to these proteins accurately and automatically. As part of the Midwest Center for Structural Genomics (MCSG) we have developed a fully automated functional analysis server, ProFunc, which performs a battery of analyses on a submitted structure. The analyses combine a number of sequence-based and structure-based methods to identify functional clues. After the first stage of the Protein Structure Initiative (PSI), we review the success of the pipeline and the importance of structure-based function prediction. As a dataset, we have chosen all structures solved by the MCSG during the 5 years of the first PSI. Our analysis suggests that two of the structure-based methods are particularly successful and provide examples of local similarity that is difficult to identify using current sequence-based methods. No one method is successful in all cases, so, through the use of a number of complementary sequence and structural approaches, the ProFunc server increases the chances that at least one method will find a significant hit that can help elucidate function. Manual assessment of the results is a time-consuming process and subject to individual interpretation and human error. We present a method based on the Gene Ontology (GO) schema using GO-slims that can allow the automated assessment of hits with a success rate approaching that of expert manual assessment.

The heritability of the functional connectome is robust to common nonlinear registration methods

NASA Astrophysics Data System (ADS)

Hafzalla, George W.; Prasad, Gautam; Baboyan, Vatche G.; Faskowitz, Joshua; Jahanshad, Neda; McMahon, Katie L.; de Zubicaray, Greig I.; Wright, Margaret J.; Braskie, Meredith N.; Thompson, Paul M.

2016-03-01

Nonlinear registration algorithms are routinely used in brain imaging, to align data for inter-subject and group comparisons, and for voxelwise statistical analyses. To understand how the choice of registration method affects maps of functional brain connectivity in a sample of 611 twins, we evaluated three popular nonlinear registration methods: Advanced Normalization Tools (ANTs), Automatic Registration Toolbox (ART), and FMRIB's Nonlinear Image Registration Tool (FNIRT). Using both structural and functional MRI, we used each of the three methods to align the MNI152 brain template, and 80 regions of interest (ROIs), to each subject's T1-weighted (T1w) anatomical image. We then transformed each subject's ROIs onto the associated resting state functional MRI (rs-fMRI) scans and computed a connectivity network or functional connectome for each subject. Given the different degrees of genetic similarity between pairs of monozygotic (MZ) and same-sex dizygotic (DZ) twins, we used structural equation modeling to estimate the additive genetic influences on the elements of the function networks, or their heritability. The functional connectome and derived statistics were relatively robust to nonlinear registration effects.

STM contrast of a CO dimer on a Cu(1 1 1) surface: a wave-function analysis.

PubMed

Gustafsson, Alexander; Paulsson, Magnus

2017-12-20

We present a method used to intuitively interpret the scanning tunneling microscopy (STM) contrast by investigating individual wave functions originating from the substrate and tip side. We use localized basis orbital density functional theory, and propagate the wave functions into the vacuum region at a real-space grid, including averaging over the lateral reciprocal space. Optimization by means of the method of Lagrange multipliers is implemented to perform a unitary transformation of the wave functions in the middle of the vacuum region. The method enables (i) reduction of the number of contributing tip-substrate wave function combinations used in the corresponding transmission matrix, and (ii) to bundle up wave functions with similar symmetry in the lateral plane, so that (iii) an intuitive understanding of the STM contrast can be achieved. The theory is applied to a CO dimer adsorbed on a Cu(1 1 1) surface scanned by a single-atom Cu tip, whose STM image is discussed in detail by the outlined method.

STM contrast of a CO dimer on a Cu(1 1 1) surface: a wave-function analysis

NASA Astrophysics Data System (ADS)

Gustafsson, Alexander; Paulsson, Magnus

2017-12-01

We present a method used to intuitively interpret the scanning tunneling microscopy (STM) contrast by investigating individual wave functions originating from the substrate and tip side. We use localized basis orbital density functional theory, and propagate the wave functions into the vacuum region at a real-space grid, including averaging over the lateral reciprocal space. Optimization by means of the method of Lagrange multipliers is implemented to perform a unitary transformation of the wave functions in the middle of the vacuum region. The method enables (i) reduction of the number of contributing tip-substrate wave function combinations used in the corresponding transmission matrix, and (ii) to bundle up wave functions with similar symmetry in the lateral plane, so that (iii) an intuitive understanding of the STM contrast can be achieved. The theory is applied to a CO dimer adsorbed on a Cu(1 1 1) surface scanned by a single-atom Cu tip, whose STM image is discussed in detail by the outlined method.

The MIMIC Method with Scale Purification for Detecting Differential Item Functioning

ERIC Educational Resources Information Center

Wang, Wen-Chung; Shih, Ching-Lin; Yang, Chih-Chien

2009-01-01

This study implements a scale purification procedure onto the standard MIMIC method for differential item functioning (DIF) detection and assesses its performance through a series of simulations. It is found that the MIMIC method with scale purification (denoted as M-SP) outperforms the standard MIMIC method (denoted as M-ST) in controlling…

A method of PSF generation for 3D brightfield deconvolution.

PubMed

Tadrous, P J

2010-02-01

This paper addresses the problem of 3D deconvolution of through focus widefield microscope datasets (Z-stacks). One of the most difficult stages in brightfield deconvolution is finding the point spread function. A theoretically calculated point spread function (called a 'synthetic PSF' in this paper) requires foreknowledge of many system parameters and still gives only approximate results. A point spread function measured from a sub-resolution bead suffers from low signal-to-noise ratio, compounded in the brightfield setting (by contrast to fluorescence) by absorptive, refractive and dispersal effects. This paper describes a method of point spread function estimation based on measurements of a Z-stack through a thin sample. This Z-stack is deconvolved by an idealized point spread function derived from the same Z-stack to yield a point spread function of high signal-to-noise ratio that is also inherently tailored to the imaging system. The theory is validated by a practical experiment comparing the non-blind 3D deconvolution of the yeast Saccharomyces cerevisiae with the point spread function generated using the method presented in this paper (called the 'extracted PSF') to a synthetic point spread function. Restoration of both high- and low-contrast brightfield structures is achieved with fewer artefacts using the extracted point spread function obtained with this method. Furthermore the deconvolution progresses further (more iterations are allowed before the error function reaches its nadir) with the extracted point spread function compared to the synthetic point spread function indicating that the extracted point spread function is a better fit to the brightfield deconvolution model than the synthetic point spread function.

Xenon-enhanced CT using subtraction CT: Basic and preliminary clinical studies for comparison of its efficacy with that of dual-energy CT and ventilation SPECT/CT to assess regional ventilation and pulmonary functional loss in smokers.

PubMed

Ohno, Yoshiharu; Yoshikawa, Takeshi; Takenaka, Daisuke; Fujisawa, Yasuko; Sugihara, Naoki; Kishida, Yuji; Seki, Shinichiro; Koyama, Hisanobu; Sugimura, Kazuro

2017-01-01

To prospectively and directly compare the capability for assessments of regional ventilation and pulmonary functional loss in smokers of xenon-ventilation CT obtained with the dual-energy CT (DE-CT) and subtraction CT (Sub-CT) MATERIALS AND METHODS: Twenty-three consecutive smokers (15 men and 8 women, mean age: 69.7±8.7years) underwent prospective unenhanced and xenon-enhanced CTs, the latter by Sub-CT and DE-CT methods, ventilation SPECT and pulmonary function tests. Sub-CT was generated from unenhanced and xenon-enhanced CT, and all co-registered SPECT/CT data were produced from SPECT and unenhanced CT data. For each method, regional ventilation was assessed by using a 11-point scoring system on a per-lobe basis. To determine the functional lung volume by each method, it was also calculated for individual sublets with a previously reported method. To determine inter-observer agreement for each method, ventilation defect assessment was evaluated by using the χ2 test with weighted kappa statistics. For evaluation of the efficacy of each method for pulmonary functional loss assessment, functional lung volume was correlated with%FEV 1 . Each inter-observer agreement was rated as substantial (Sub-CT: κ=0.69, p<0.0001; DE-CT: κ=0.64, p<0.0001; SPECT/CT: κ=0.64, p<0.0001). Functional lung volume for each method showed significant to good correlation with%FEV 1 (Sub-CT: r=0.72, p=0.0001; DE-CT: r=0.74, p<0.0001; SPECT/CT: r=0.66, p=0.0006). Xenon-enhanced CT obtained by Sub-CT can be considered at least as efficacious as that obtained by DE-CT and SPECT/CT for assessment of ventilation abnormality and pulmonary functional loss in smokers. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Two-dimensional analytic weighting functions for limb scattering

NASA Astrophysics Data System (ADS)

Zawada, D. J.; Bourassa, A. E.; Degenstein, D. A.

2017-10-01

Through the inversion of limb scatter measurements it is possible to obtain vertical profiles of trace species in the atmosphere. Many of these inversion methods require what is often referred to as weighting functions, or derivatives of the radiance with respect to concentrations of trace species in the atmosphere. Several radiative transfer models have implemented analytic methods to calculate weighting functions, alleviating the computational burden of traditional numerical perturbation methods. Here we describe the implementation of analytic two-dimensional weighting functions, where derivatives are calculated relative to atmospheric constituents in a two-dimensional grid of altitude and angle along the line of sight direction, in the SASKTRAN-HR radiative transfer model. Two-dimensional weighting functions are required for two-dimensional inversions of limb scatter measurements. Examples are presented where the analytic two-dimensional weighting functions are calculated with an underlying one-dimensional atmosphere. It is shown that the analytic weighting functions are more accurate than ones calculated with a single scatter approximation, and are orders of magnitude faster than a typical perturbation method. Evidence is presented that weighting functions for stratospheric aerosols calculated under a single scatter approximation may not be suitable for use in retrieval algorithms under solar backscatter conditions.

Functional evaluation of peripheral nerve regeneration and target reinnervation in animal models: a critical overview.

PubMed

Navarro, Xavier

2016-02-01

Peripheral nerve injuries usually lead to severe loss of motor, sensory and autonomic functions in the patients. Due to the complex requirements for adequate axonal regeneration, functional recovery is often poorly achieved. Experimental models are useful to investigate the mechanisms related to axonal regeneration and tissue reinnervation, and to test new therapeutic strategies to improve functional recovery. Therefore, objective and reliable evaluation methods should be applied for the assessment of regeneration and function restitution after nerve injury in animal models. This review gives an overview of the most useful methods to assess nerve regeneration, target reinnervation and recovery of complex sensory and motor functions, their values and limitations. The selection of methods has to be adequate to the main objective of the research study, either enhancement of axonal regeneration, improving regeneration and reinnervation of target organs by different types of nerve fibres, or increasing recovery of complex sensory and motor functions. It is generally recommended to use more than one functional method for each purpose, and also to perform morphological studies of the injured nerve and the reinnervated targets. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Generation of the neutron response function of an NE213 scintillator for fusion applications

NASA Astrophysics Data System (ADS)

Binda, F.; Eriksson, J.; Ericsson, G.; Hellesen, C.; Conroy, S.; Nocente, M.; Sundén, E. Andersson; JET Contributors

2017-09-01

In this work we present a method to evaluate the neutron response function of an NE213 liquid scintillator. This method is particularly useful when the proton light yield function of the detector has not been measured, since it is based on a proton light yield function taken from literature, MCNPX simulations, measurements of gamma-rays from a calibration source and measurements of neutrons from fusion experiments with ohmic plasmas. The inclusion of the latter improves the description of the proton light yield function in the energy range of interest (around 2.46 MeV). We apply this method to an NE213 detector installed at JET, inside the radiation shielding of the magnetic proton recoil (MPRu) spectrometer, and present the results from the calibration along with some examples of application of the response function to perform neutron emission spectroscopy (NES) of fusion plasmas. We also investigate how the choice of the proton light yield function affects the NES analysis, finding that the result does not change significantly. This points to the fact that the method for the evaluation of the neutron response function is robust and gives reliable results.

An estimation of distribution method for infrared target detection based on Copulas

NASA Astrophysics Data System (ADS)

Wang, Shuo; Zhang, Yiqun

2015-10-01

Track-before-detect (TBD) based target detection involves a hypothesis test of merit functions which measure each track as a possible target track. Its accuracy depends on the precision of the distribution of merit functions, which determines the threshold for a test. Generally, merit functions are regarded Gaussian, and on this basis the distribution is estimated, which is true for most methods such as the multiple hypothesis tracking (MHT). However, merit functions for some other methods such as the dynamic programming algorithm (DPA) are non-Guassian and cross-correlated. Since existing methods cannot reasonably measure the correlation, the exact distribution can hardly be estimated. If merit functions are assumed Guassian and independent, the error between an actual distribution and its approximation may occasionally over 30 percent, and is divergent by propagation. Hence, in this paper, we propose a novel estimation of distribution method based on Copulas, by which the distribution can be estimated precisely, where the error is less than 1 percent without propagation. Moreover, the estimation merely depends on the form of merit functions and the structure of a tracking algorithm, and is invariant to measurements. Thus, the distribution can be estimated in advance, greatly reducing the demand for real-time calculation of distribution functions.

Reconstruction of the unknown optimization cost functions from experimental recordings during static multi-finger prehension

PubMed Central

Niu, Xun; Terekhov, Alexander V.; Latash, Mark L.; Zatsiorsky, Vladimir M.

2013-01-01

The goal of the research is to reconstruct the unknown cost (objective) function(s) presumably used by the neural controller for sharing the total force among individual fingers in multi-finger prehension. The cost function was determined from experimental data by applying the recently developed Analytical Inverse Optimization (ANIO) method (Terekhov et al 2010). The core of the ANIO method is the Theorem of Uniqueness that specifies conditions for unique (with some restrictions) estimation of the objective functions. In the experiment, subjects (n=8) grasped an instrumented handle and maintained it at rest in the air with various external torques, loads, and target grasping forces applied to the object. The experimental data recorded from 80 trials showed a tendency to lie on a 2-dimensional hyperplane in the 4-dimensional finger-force space. Because the constraints in each trial were different, such a propensity is a manifestation of a neural mechanism (not the task mechanics). In agreement with the Lagrange principle for the inverse optimization, the plane of experimental observations was close to the plane resulting from the direct optimization. The latter plane was determined using the ANIO method. The unknown cost function was reconstructed successfully for each performer, as well as for the group data. The cost functions were found to be quadratic with non-zero linear terms. The cost functions obtained with the ANIO method yielded more accurate results than other optimization methods. The ANIO method has an evident potential for addressing the problem of optimization in motor control. PMID:22104742

Delay-slope-dependent stability results of recurrent neural networks.

PubMed

Li, Tao; Zheng, Wei Xing; Lin, Chong

2011-12-01

By using the fact that the neuron activation functions are sector bounded and nondecreasing, this brief presents a new method, named the delay-slope-dependent method, for stability analysis of a class of recurrent neural networks with time-varying delays. This method includes more information on the slope of neuron activation functions and fewer matrix variables in the constructed Lyapunov-Krasovskii functional. Then some improved delay-dependent stability criteria with less computational burden and conservatism are obtained. Numerical examples are given to illustrate the effectiveness and the benefits of the proposed method.

Using Anatomic Magnetic Resonance Image Information to Enhance Visualization and Interpretation of Functional Images: A Comparison of Methods Applied to Clinical Arterial Spin Labeling Images

PubMed Central

Dai, Weiying; Soman, Salil; Hackney, David B.; Wong, Eric T.; Robson, Philip M.; Alsop, David C.

2017-01-01

Functional imaging provides hemodynamic and metabolic information and is increasingly being incorporated into clinical diagnostic and research studies. Typically functional images have reduced signal-to-noise ratio and spatial resolution compared to other non-functional cross sectional images obtained as part of a routine clinical protocol. We hypothesized that enhancing visualization and interpretation of functional images with anatomic information could provide preferable quality and superior diagnostic value. In this work, we implemented five methods (frequency addition, frequency multiplication, wavelet transform, non-subsampled contourlet transform and intensity-hue-saturation) and a newly proposed ShArpening by Local Similarity with Anatomic images (SALSA) method to enhance the visualization of functional images, while preserving the original functional contrast and quantitative signal intensity characteristics over larger spatial scales. Arterial spin labeling blood flow MR images of the brain were visualization enhanced using anatomic images with multiple contrasts. The algorithms were validated on a numerical phantom and their performance on images of brain tumor patients were assessed by quantitative metrics and neuroradiologist subjective ratings. The frequency multiplication method had the lowest residual error for preserving the original functional image contrast at larger spatial scales (55%–98% of the other methods with simulated data and 64%–86% with experimental data). It was also significantly more highly graded by the radiologists (p<0.005 for clear brain anatomy around the tumor). Compared to other methods, the SALSA provided 11%–133% higher similarity with ground truth images in the simulation and showed just slightly lower neuroradiologist grading score. Most of these monochrome methods do not require any prior knowledge about the functional and anatomic image characteristics, except the acquired resolution. Hence, automatic implementation on clinical images should be readily feasible. PMID:27723582

A new class of methods for functional connectivity estimation

NASA Astrophysics Data System (ADS)

Lin, Wutu

Measuring functional connectivity from neural recordings is important in understanding processing in cortical networks. The covariance-based methods are the current golden standard for functional connectivity estimation. However, the link between the pair-wise correlations and the physiological connections inside the neural network is unclear. Therefore, the power of inferring physiological basis from functional connectivity estimation is limited. To build a stronger tie and better understand the relationship between functional connectivity and physiological neural network, we need (1) a realistic model to simulate different types of neural recordings with known ground truth for benchmarking; (2) a new functional connectivity method that produce estimations closely reflecting the physiological basis. In this thesis, (1) I tune a spiking neural network model to match with human sleep EEG data, (2) introduce a new class of methods for estimating connectivity from different kinds of neural signals and provide theory proof for its superiority, (3) apply it to simulated fMRI data as an application.

An integrated miRNA functional screening and target validation method for organ morphogenesis.

PubMed

Rebustini, Ivan T; Vlahos, Maryann; Packer, Trevor; Kukuruzinska, Maria A; Maas, Richard L

2016-03-16

The relative ease of identifying microRNAs and their increasing recognition as important regulators of organogenesis motivate the development of methods to efficiently assess microRNA function during organ morphogenesis. In this context, embryonic organ explants provide a reliable and reproducible system that recapitulates some of the important early morphogenetic processes during organ development. Here we present a method to target microRNA function in explanted mouse embryonic organs. Our method combines the use of peptide-based nanoparticles to transfect specific microRNA inhibitors or activators into embryonic organ explants, with a microRNA pulldown assay that allows direct identification of microRNA targets. This method provides effective assessment of microRNA function during organ morphogenesis, allows prioritization of multiple microRNAs in parallel for subsequent genetic approaches, and can be applied to a variety of embryonic organs.

deepNF: Deep network fusion for protein function prediction.

PubMed

Gligorijevic, Vladimir; Barot, Meet; Bonneau, Richard

2018-06-01

The prevalence of high-throughput experimental methods has resulted in an abundance of large-scale molecular and functional interaction networks. The connectivity of these networks provides a rich source of information for inferring functional annotations for genes and proteins. An important challenge has been to develop methods for combining these heterogeneous networks to extract useful protein feature representations for function prediction. Most of the existing approaches for network integration use shallow models that encounter difficulty in capturing complex and highly-nonlinear network structures. Thus, we propose deepNF, a network fusion method based on Multimodal Deep Autoencoders to extract high-level features of proteins from multiple heterogeneous interaction networks. We apply this method to combine STRING networks to construct a common low-dimensional representation containing high-level protein features. We use separate layers for different network types in the early stages of the multimodal autoencoder, later connecting all the layers into a single bottleneck layer from which we extract features to predict protein function. We compare the cross-validation and temporal holdout predictive performance of our method with state-of-the-art methods, including the recently proposed method Mashup. Our results show that our method outperforms previous methods for both human and yeast STRING networks. We also show substantial improvement in the performance of our method in predicting GO terms of varying type and specificity. deepNF is freely available at: https://github.com/VGligorijevic/deepNF. vgligorijevic@flatironinstitute.org, rb133@nyu.edu. Supplementary data are available at Bioinformatics online.

Transport Coefficients from Large Deviation Functions

NASA Astrophysics Data System (ADS)

Gao, Chloe; Limmer, David

2017-10-01

We describe a method for computing transport coefficients from the direct evaluation of large deviation function. This method is general, relying on only equilibrium fluctuations, and is statistically efficient, employing trajectory based importance sampling. Equilibrium fluctuations of molecular currents are characterized by their large deviation functions, which is a scaled cumulant generating function analogous to the free energy. A diffusion Monte Carlo algorithm is used to evaluate the large deviation functions, from which arbitrary transport coefficients are derivable. We find significant statistical improvement over traditional Green-Kubo based calculations. The systematic and statistical errors of this method are analyzed in the context of specific transport coefficient calculations, including the shear viscosity, interfacial friction coefficient, and thermal conductivity.

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.

SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

PubMed

Li, Ying Hong; Xu, Jing Yu; Tao, Lin; Li, Xiao Feng; Li, Shuang; Zeng, Xian; Chen, Shang Ying; Zhang, Peng; Qin, Chu; Zhang, Cheng; Chen, Zhe; Zhu, Feng; Chen, Yu Zong

2016-01-01

Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi.

Investigation of another approach in topology optimization

NASA Astrophysics Data System (ADS)

Krotkikh, A. A.; Maximov, P. V.

2018-05-01

The paper presents investigation of another approach in topology optimization. The authors realized the method of topology optimization with using ideas of the SIMP method which was created by Martin P. Bends0e. There are many ways in objective function formulation of topology optimization methods. In terms of elasticity theory, the objective function of the SIMP method is a compliance of an object which should be minimized. The main idea of this paper was avoiding the filtering procedure in the SIMP method. Reformulation of the statement of the problem in terms of function minimization allows us to solve this by big variety of methods. The authors decided to use the interior point method which was realized in Wolfram Mathematica. This way can generate side effects which should be investigated for preventing their appearing in future. Results comparison of the SIMP method and the suggested method are presented in paper and analyzed.

New quantitative method for evaluation of motor functions applicable to spinal muscular atrophy.

PubMed

Matsumaru, Naoki; Hattori, Ryo; Ichinomiya, Takashi; Tsukamoto, Katsura; Kato, Zenichiro

2018-03-01

The aim of this study was to develop and introduce new method to quantify motor functions of the upper extremity. The movement was recorded using a three-dimensional motion capture system, and the movement trajectory was analyzed using newly developed two indices, which measure precise repeatability and directional smoothness. Our target task was shoulder flexion repeated ten times. We applied our method to a healthy adult without and with a weight, simulating muscle impairment. We also applied our method to assess the efficacy of a drug therapy for amelioration of motor functions in a non-ambulatory patient with spinal muscular atrophy. Movement trajectories before and after thyrotropin-releasing hormone therapy were analyzed. In the healthy adult, we found the values of both indices increased significantly when holding a weight so that the weight-induced deterioration in motor function was successfully detected. From the efficacy assessment of drug therapy in the patient, the directional smoothness index successfully detected improvements in motor function, which were also clinically observed by the patient's doctors. We have developed a new quantitative evaluation method of motor functions of the upper extremity. Clinical usability of this method is also greatly enhanced by reducing the required number of body-attached markers to only one. This simple but universal approach to quantify motor functions will provide additional insights into the clinical phenotypes of various neuromuscular diseases and developmental disorders. Copyright © 2017 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

DFT-based method for more accurate adsorption energies: An adaptive sum of energies from RPBE and vdW density functionals

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

Hensley, Alyssa J. R.; Ghale, Kushal; Rieg, Carolin

In recent years, the popularity of density functional theory with periodic boundary conditions (DFT) has surged for the design and optimization of functional materials. However, no single DFT exchange–correlation functional currently available gives accurate adsorption energies on transition metals both when bonding to the surface is dominated by strong covalent or ionic bonding and when it has strong contributions from van der Waals interactions (i.e., dispersion forces). Here we present a new, simple method for accurately predicting adsorption energies on transition-metal surfaces based on DFT calculations, using an adaptively weighted sum of energies from RPBE and optB86b-vdW (or optB88-vdW) densitymore » functionals. This method has been benchmarked against a set of 39 reliable experimental energies for adsorption reactions. Our results show that this method has a mean absolute error and root mean squared error relative to experiments of 13.4 and 19.3 kJ/mol, respectively, compared to 20.4 and 26.4 kJ/mol for the BEEF-vdW functional. For systems with large van der Waals contributions, this method decreases these errors to 11.6 and 17.5 kJ/mol. Furthermore, this method provides predictions of adsorption energies both for processes dominated by strong covalent or ionic bonding and for those dominated by dispersion forces that are more accurate than those of any current standard DFT functional alone.« less

DFT-based method for more accurate adsorption energies: An adaptive sum of energies from RPBE and vdW density functionals

DOE PAGES

Hensley, Alyssa J. R.; Ghale, Kushal; Rieg, Carolin; ...

2017-01-26

In recent years, the popularity of density functional theory with periodic boundary conditions (DFT) has surged for the design and optimization of functional materials. However, no single DFT exchange–correlation functional currently available gives accurate adsorption energies on transition metals both when bonding to the surface is dominated by strong covalent or ionic bonding and when it has strong contributions from van der Waals interactions (i.e., dispersion forces). Here we present a new, simple method for accurately predicting adsorption energies on transition-metal surfaces based on DFT calculations, using an adaptively weighted sum of energies from RPBE and optB86b-vdW (or optB88-vdW) densitymore » functionals. This method has been benchmarked against a set of 39 reliable experimental energies for adsorption reactions. Our results show that this method has a mean absolute error and root mean squared error relative to experiments of 13.4 and 19.3 kJ/mol, respectively, compared to 20.4 and 26.4 kJ/mol for the BEEF-vdW functional. For systems with large van der Waals contributions, this method decreases these errors to 11.6 and 17.5 kJ/mol. Furthermore, this method provides predictions of adsorption energies both for processes dominated by strong covalent or ionic bonding and for those dominated by dispersion forces that are more accurate than those of any current standard DFT functional alone.« less

An accurate and efficient method for piezoelectric coated functional devices based on the two-dimensional Green’s function for a normal line force and line charge

NASA Astrophysics Data System (ADS)

Hou, Peng-Fei; Zhang, Yang

2017-09-01

Because most piezoelectric functional devices, including sensors, actuators and energy harvesters, are in the form of a piezoelectric coated structure, it is valuable to present an accurate and efficient method for obtaining the electro-mechanical coupling fields of this coated structure under mechanical and electrical loads. With this aim, the two-dimensional Green’s function for a normal line force and line charge on the surface of coated structure, which is a combination of an orthotropic piezoelectric coating and orthotropic elastic substrate, is presented in the form of elementary functions based on the general solution method. The corresponding electro-mechanical coupling fields of this coated structure under arbitrary mechanical and electrical loads can then be obtained by the superposition principle and Gauss integration. Numerical results show that the presented method has high computational precision, efficiency and stability. It can be used to design the best coating thickness in functional devices, improve the sensitivity of sensors, and improve the efficiency of actuators and energy harvesters. This method could be an efficient tool for engineers in engineering applications.

Analytical and numerical analysis of inverse optimization problems: conditions of uniqueness and computational methods

PubMed Central

Zatsiorsky, Vladimir M.

2011-01-01

One of the key problems of motor control is the redundancy problem, in particular how the central nervous system (CNS) chooses an action out of infinitely many possible. A promising way to address this question is to assume that the choice is made based on optimization of a certain cost function. A number of cost functions have been proposed in the literature to explain performance in different motor tasks: from force sharing in grasping to path planning in walking. However, the problem of uniqueness of the cost function(s) was not addressed until recently. In this article, we analyze two methods of finding additive cost functions in inverse optimization problems with linear constraints, so-called linear-additive inverse optimization problems. These methods are based on the Uniqueness Theorem for inverse optimization problems that we proved recently (Terekhov et al., J Math Biol 61(3):423–453, 2010). Using synthetic data, we show that both methods allow for determining the cost function. We analyze the influence of noise on the both methods. Finally, we show how a violation of the conditions of the Uniqueness Theorem may lead to incorrect solutions of the inverse optimization problem. PMID:21311907

Phosphorus allotropes: Stability of black versus red phosphorus re-examined by means of the van der Waals inclusive density functional method

NASA Astrophysics Data System (ADS)

Aykol, Muratahan; Doak, Jeff W.; Wolverton, C.

2017-06-01

We evaluate the energetic stabilities of white, red, and black allotropes of phosphorus using density functional theory (DFT) and hybrid functional methods, van der Waals (vdW) corrections (DFT+vdW and hybrid+vdW), vdW density functionals, and random phase approximation (RPA). We find that stability of black phosphorus over red-V (i.e., the violet form) is not ubiquitous among these methods, and the calculated enthalpies for the reaction phosphorus (red-V)→phosphorus (black) are scattered between -20 and 40 meV/atom. With local density and generalized gradient approximations, and hybrid functionals, mean absolute errors (MAEs) in densities of P allotropes relative to experiments are found to be around 10%-25%, whereas with vdW-inclusive methods, MAEs in densities drop below ˜5 %. While the inconsistency among the density functional methods could not shed light on the stability puzzle of black versus red phosphorus, comparison of their accuracy in predicting densities and the supplementary RPA results on relative stabilities indicate that opposite to the common belief, black and red phosphorus are almost degenerate, or the red-V (violet) form of phosphorus might even be the ground state.

Genetic Algorithm for Initial Orbit Determination with Too Short Arc (Continued)

NASA Astrophysics Data System (ADS)

Li, X. R.; Wang, X.

2016-03-01

When using the genetic algorithm to solve the problem of too-short-arc (TSA) determination, due to the difference of computing processes between the genetic algorithm and classical method, the methods for outliers editing are no longer applicable. In the genetic algorithm, the robust estimation is acquired by means of using different loss functions in the fitness function, then the outlier problem of TSAs is solved. Compared with the classical method, the application of loss functions in the genetic algorithm is greatly simplified. Through the comparison of results of different loss functions, it is clear that the methods of least median square and least trimmed square can greatly improve the robustness of TSAs, and have a high breakdown point.

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

A Method for the Alignment of Heterogeneous Macromolecules from Electron Microscopy

PubMed Central

Shatsky, Maxim; Hall, Richard J.; Brenner, Steven E.; Glaeser, Robert M.

2009-01-01

We propose a feature-based image alignment method for single-particle electron microscopy that is able to accommodate various similarity scoring functions while efficiently sampling the two-dimensional transformational space. We use this image alignment method to evaluate the performance of a scoring function that is based on the Mutual Information (MI) of two images rather than one that is based on the cross-correlation function. We show that alignment using MI for the scoring function has far less model-dependent bias than is found with cross-correlation based alignment. We also demonstrate that MI improves the alignment of some types of heterogeneous data, provided that the signal to noise ratio is relatively high. These results indicate, therefore, that use of MI as the scoring function is well suited for the alignment of class-averages computed from single particle images. Our method is tested on data from three model structures and one real dataset. PMID:19166941

Estimates on Functional Integrals of Quantum Mechanics and Non-relativistic Quantum Field Theory

NASA Astrophysics Data System (ADS)

Bley, Gonzalo A.; Thomas, Lawrence E.

2017-01-01

We provide a unified method for obtaining upper bounds for certain functional integrals appearing in quantum mechanics and non-relativistic quantum field theory, functionals of the form {E[{exp}(A_T)]} , the (effective) action {A_T} being a function of particle trajectories up to time T. The estimates in turn yield rigorous lower bounds for ground state energies, via the Feynman-Kac formula. The upper bounds are obtained by writing the action for these functional integrals in terms of stochastic integrals. The method is illustrated in familiar quantum mechanical settings: for the hydrogen atom, for a Schrödinger operator with {1/|x|^2} potential with small coupling, and, with a modest adaptation of the method, for the harmonic oscillator. We then present our principal applications of the method, in the settings of non-relativistic quantum field theories for particles moving in a quantized Bose field, including the optical polaron and Nelson models.

A machine learning approach for efficient uncertainty quantification using multiscale methods

NASA Astrophysics Data System (ADS)

Chan, Shing; Elsheikh, Ahmed H.

2018-02-01

Several multiscale methods account for sub-grid scale features using coarse scale basis functions. For example, in the Multiscale Finite Volume method the coarse scale basis functions are obtained by solving a set of local problems over dual-grid cells. We introduce a data-driven approach for the estimation of these coarse scale basis functions. Specifically, we employ a neural network predictor fitted using a set of solution samples from which it learns to generate subsequent basis functions at a lower computational cost than solving the local problems. The computational advantage of this approach is realized for uncertainty quantification tasks where a large number of realizations has to be evaluated. We attribute the ability to learn these basis functions to the modularity of the local problems and the redundancy of the permeability patches between samples. The proposed method is evaluated on elliptic problems yielding very promising results.

MIPS bacterial genomes functional annotation benchmark dataset.

PubMed

Tetko, Igor V; Brauner, Barbara; Dunger-Kaltenbach, Irmtraud; Frishman, Goar; Montrone, Corinna; Fobo, Gisela; Ruepp, Andreas; Antonov, Alexey V; Surmeli, Dimitrij; Mewes, Hans-Wernen

2005-05-15

Any development of new methods for automatic functional annotation of proteins according to their sequences requires high-quality data (as benchmark) as well as tedious preparatory work to generate sequence parameters required as input data for the machine learning methods. Different program settings and incompatible protocols make a comparison of the analyzed methods difficult. The MIPS Bacterial Functional Annotation Benchmark dataset (MIPS-BFAB) is a new, high-quality resource comprising four bacterial genomes manually annotated according to the MIPS functional catalogue (FunCat). These resources include precalculated sequence parameters, such as sequence similarity scores, InterPro domain composition and other parameters that could be used to develop and benchmark methods for functional annotation of bacterial protein sequences. These data are provided in XML format and can be used by scientists who are not necessarily experts in genome annotation. BFAB is available at http://mips.gsf.de/proj/bfab

Novel transform for image description and compression with implementation by neural architectures

NASA Astrophysics Data System (ADS)

Ben-Arie, Jezekiel; Rao, Raghunath K.

1991-10-01

A general method for signal representation using nonorthogonal basis functions that are composed of Gaussians are described. The Gaussians can be combined into groups with predetermined configuration that can approximate any desired basis function. The same configuration at different scales forms a set of self-similar wavelets. The general scheme is demonstrated by representing a natural signal employing an arbitrary basis function. The basic methodology is demonstrated by two novel schemes for efficient representation of 1-D and 2- D signals using Gaussian basis functions (BFs). Special methods are required here since the Gaussian functions are nonorthogonal. The first method employs a paradigm of maximum energy reduction interlaced with the A* heuristic search. The second method uses an adaptive lattice system to find the minimum-squared error of the BFs onto the signal, and a lateral-vertical suppression network to select the most efficient representation in terms of data compression.

Test functions for three-dimensional control-volume mixed finite-element methods on irregular grids

USGS Publications Warehouse

Naff, R.L.; Russell, T.F.; Wilson, J.D.; ,; ,; ,; ,; ,

2000-01-01

Numerical methods based on unstructured grids, with irregular cells, usually require discrete shape functions to approximate the distribution of quantities across cells. For control-volume mixed finite-element methods, vector shape functions are used to approximate the distribution of velocities across cells and vector test functions are used to minimize the error associated with the numerical approximation scheme. For a logically cubic mesh, the lowest-order shape functions are chosen in a natural way to conserve intercell fluxes that vary linearly in logical space. Vector test functions, while somewhat restricted by the mapping into the logical reference cube, admit a wider class of possibilities. Ideally, an error minimization procedure to select the test function from an acceptable class of candidates would be the best procedure. Lacking such a procedure, we first investigate the effect of possible test functions on the pressure distribution over the control volume; specifically, we look for test functions that allow for the elimination of intermediate pressures on cell faces. From these results, we select three forms for the test function for use in a control-volume mixed method code and subject them to an error analysis for different forms of grid irregularity; errors are reported in terms of the discrete L2 norm of the velocity error. Of these three forms, one appears to produce optimal results for most forms of grid irregularity.

Physiologic measures of sexual function in women: a review.

PubMed

Woodard, Terri L; Diamond, Michael P

2009-07-01

To review and describe physiologic measures of assessing sexual function in women. Literature review. Studies that use instruments designed to measure female sexual function. Women participating in studies of female sexual function. Various instruments that measure physiologic features of female sexual function. Appraisal of the various instruments, including their advantages and disadvantages. Many unique physiologic methods of evaluating female sexual function have been developed during the past four decades. Each method has its benefits and limitations. Many physiologic methods exist, but most are not well-validated. In addition there has been an inability to correlate most physiologic measures with subjective measures of sexual arousal. Furthermore, given the complex nature of the sexual response in women, physiologic measures should be considered in context of other data, including the history, physical examination, and validated questionnaires. Nonetheless, the existence of appropriate physiologic measures is vital to our understanding of female sexual function and dysfunction.

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

Functional Analyses and Treatment of Precursor Behavior

PubMed Central

Najdowski, Adel C; Wallace, Michele D; Ellsworth, Carrie L; MacAleese, Alicia N; Cleveland, Jackie M

2008-01-01

Functional analysis has been demonstrated to be an effective method to identify environmental variables that maintain problem behavior. However, there are cases when conducting functional analyses of severe problem behavior may be contraindicated. The current study applied functional analysis procedures to a class of behavior that preceded severe problem behavior (precursor behavior) and evaluated treatments based on the outcomes of the functional analyses of precursor behavior. Responding for all participants was differentiated during the functional analyses, and individualized treatments eliminated precursor behavior. These results suggest that functional analysis of precursor behavior may offer an alternative, indirect method to assess the operant function of severe problem behavior. PMID:18468282

A robust functional-data-analysis method for data recovery in multichannel sensor systems.

PubMed

Sun, Jian; Liao, Haitao; Upadhyaya, Belle R

2014-08-01

Multichannel sensor systems are widely used in condition monitoring for effective failure prevention of critical equipment or processes. However, loss of sensor readings due to malfunctions of sensors and/or communication has long been a hurdle to reliable operations of such integrated systems. Moreover, asynchronous data sampling and/or limited data transmission are usually seen in multiple sensor channels. To reliably perform fault diagnosis and prognosis in such operating environments, a data recovery method based on functional principal component analysis (FPCA) can be utilized. However, traditional FPCA methods are not robust to outliers and their capabilities are limited in recovering signals with strongly skewed distributions (i.e., lack of symmetry). This paper provides a robust data-recovery method based on functional data analysis to enhance the reliability of multichannel sensor systems. The method not only considers the possibly skewed distribution of each channel of signal trajectories, but is also capable of recovering missing data for both individual and correlated sensor channels with asynchronous data that may be sparse as well. In particular, grand median functions, rather than classical grand mean functions, are utilized for robust smoothing of sensor signals. Furthermore, the relationship between the functional scores of two correlated signals is modeled using multivariate functional regression to enhance the overall data-recovery capability. An experimental flow-control loop that mimics the operation of coolant-flow loop in a multimodular integral pressurized water reactor is used to demonstrate the effectiveness and adaptability of the proposed data-recovery method. The computational results illustrate that the proposed method is robust to outliers and more capable than the existing FPCA-based method in terms of the accuracy in recovering strongly skewed signals. In addition, turbofan engine data are also analyzed to verify the capability of the proposed method in recovering non-skewed signals.

Finite-time output feedback stabilization of high-order uncertain nonlinear systems

NASA Astrophysics Data System (ADS)

Jiang, Meng-Meng; Xie, Xue-Jun; Zhang, Kemei

2018-06-01

This paper studies the problem of finite-time output feedback stabilization for a class of high-order nonlinear systems with the unknown output function and control coefficients. Under the weaker assumption that output function is only continuous, by using homogeneous domination method together with adding a power integrator method, introducing a new analysis method, the maximal open sector Ω of output function is given. As long as output function belongs to any closed sector included in Ω, an output feedback controller can be developed to guarantee global finite-time stability of the closed-loop system.

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.

Methods of epigenome editing for probing the function of genomic imprinting.

PubMed

Rienecker, Kira DA; Hill, Matthew J; Isles, Anthony R

2016-10-01

The curious patterns of imprinted gene expression draw interest from several scientific disciplines to the functional consequences of genomic imprinting. Methods of probing the function of imprinting itself have largely been indirect and correlational, relying heavily on conventional transgenics. Recently, the burgeoning field of epigenome editing has provided new tools and suggested strategies for asking causal questions with site specificity. This perspective article aims to outline how these new methods may be applied to questions of functional imprinting and, with this aim in mind, to suggest new dimensions for the expansion of these epigenome-editing tools.

Individualized Functional Parcellation of the Human Amygdala Using a Semi-supervised Clustering Method: A 7T Resting State fMRI Study.

PubMed

Zhang, Xianchang; Cheng, Hewei; Zuo, Zhentao; Zhou, Ke; Cong, Fei; Wang, Bo; Zhuo, Yan; Chen, Lin; Xue, Rong; Fan, Yong

2018-01-01

The amygdala plays an important role in emotional functions and its dysfunction is considered to be associated with multiple psychiatric disorders in humans. Cytoarchitectonic mapping has demonstrated that the human amygdala complex comprises several subregions. However, it's difficult to delineate boundaries of these subregions in vivo even if using state of the art high resolution structural MRI. Previous attempts to parcellate this small structure using unsupervised clustering methods based on resting state fMRI data suffered from the low spatial resolution of typical fMRI data, and it remains challenging for the unsupervised methods to define subregions of the amygdala in vivo . In this study, we developed a novel brain parcellation method to segment the human amygdala into spatially contiguous subregions based on 7T high resolution fMRI data. The parcellation was implemented using a semi-supervised spectral clustering (SSC) algorithm at an individual subject level. Under guidance of prior information derived from the Julich cytoarchitectonic atlas, our method clustered voxels of the amygdala into subregions according to similarity measures of their functional signals. As a result, three distinct amygdala subregions can be obtained in each hemisphere for every individual subject. Compared with the cytoarchitectonic atlas, our method achieved better performance in terms of subregional functional homogeneity. Validation experiments have also demonstrated that the amygdala subregions obtained by our method have distinctive, lateralized functional connectivity (FC) patterns. Our study has demonstrated that the semi-supervised brain parcellation method is a powerful tool for exploring amygdala subregional functions.

A direct method to solve optimal knots of B-spline curves: An application for non-uniform B-spline curves fitting.

PubMed

Dung, Van Than; Tjahjowidodo, Tegoeh

2017-01-01

B-spline functions are widely used in many industrial applications such as computer graphic representations, computer aided design, computer aided manufacturing, computer numerical control, etc. Recently, there exist some demands, e.g. in reverse engineering (RE) area, to employ B-spline curves for non-trivial cases that include curves with discontinuous points, cusps or turning points from the sampled data. The most challenging task in these cases is in the identification of the number of knots and their respective locations in non-uniform space in the most efficient computational cost. This paper presents a new strategy for fitting any forms of curve by B-spline functions via local algorithm. A new two-step method for fast knot calculation is proposed. In the first step, the data is split using a bisecting method with predetermined allowable error to obtain coarse knots. Secondly, the knots are optimized, for both locations and continuity levels, by employing a non-linear least squares technique. The B-spline function is, therefore, obtained by solving the ordinary least squares problem. The performance of the proposed method is validated by using various numerical experimental data, with and without simulated noise, which were generated by a B-spline function and deterministic parametric functions. This paper also discusses the benchmarking of the proposed method to the existing methods in literature. The proposed method is shown to be able to reconstruct B-spline functions from sampled data within acceptable tolerance. It is also shown that, the proposed method can be applied for fitting any types of curves ranging from smooth ones to discontinuous ones. In addition, the method does not require excessive computational cost, which allows it to be used in automatic reverse engineering applications.

Comparison of Objective and Subjective Methods on Determination of Differential Item Functioning

ERIC Educational Resources Information Center

Sahin, Melek Gülsah

2017-01-01

Research objective is comparing the objective methods often used in literature for determination of differential item functioning (DIF) and the subjective method based on the opinions of the experts which are not used so often in literature. Mantel-Haenszel (MH), Logistic Regression (LR) and SIBTEST are chosen as objective methods. While the data…

A (2+1)-dimensional Korteweg-de Vries type equation in water waves: Lie symmetry analysis; multiple exp-function method; conservation laws

NASA Astrophysics Data System (ADS)

Adem, Abdullahi Rashid

2016-05-01

We consider a (2+1)-dimensional Korteweg-de Vries type equation which models the shallow-water waves, surface and internal waves. In the analysis, we use the Lie symmetry method and the multiple exp-function method. Furthermore, conservation laws are computed using the multiplier method.

An improved adaptive weighting function method for State Estimation in Power Systems with VSC-MTDC

NASA Astrophysics Data System (ADS)

Zhao, Kun; Yang, Xiaonan; Lang, Yansheng; Song, Xuri; Wang, Minkun; Luo, Yadi; Wu, Lingyun; Liu, Peng

2017-04-01

This paper presents an effective approach for state estimation in power systems that include multi-terminal voltage source converter based high voltage direct current (VSC-MTDC), called improved adaptive weighting function method. The proposed approach is simplified in which the VSC-MTDC system is solved followed by the AC system. Because the new state estimation method only changes the weight and keeps the matrix dimension unchanged. Accurate and fast convergence of AC/DC system can be realized by adaptive weight function method. This method also provides the technical support for the simulation analysis and accurate regulation of AC/DC system. Both the oretical analysis and numerical tests verify practicability, validity and convergence of new method.

An improved peak frequency shift method for Q estimation based on generalized seismic wavelet function

NASA Astrophysics Data System (ADS)

Wang, Qian; Gao, Jinghuai

2018-02-01

As a powerful tool for hydrocarbon detection and reservoir characterization, the quality factor, Q, provides useful information in seismic data processing and interpretation. In this paper, we propose a novel method for Q estimation. The generalized seismic wavelet (GSW) function was introduced to fit the amplitude spectrum of seismic waveforms with two parameters: fractional value and reference frequency. Then we derive an analytical relation between the GSW function and the Q factor of the medium. When a seismic wave propagates through a viscoelastic medium, the GSW function can be employed to fit the amplitude spectrum of the source and attenuated wavelets, then the fractional values and reference frequencies can be evaluated numerically from the discrete Fourier spectrum. After calculating the peak frequency based on the obtained fractional value and reference frequency, the relationship between the GSW function and the Q factor can be built by the conventional peak frequency shift method. Synthetic tests indicate that our method can achieve higher accuracy and be more robust to random noise compared with existing methods. Furthermore, the proposed method is applicable to different types of source wavelet. Field data application also demonstrates the effectiveness of our method in seismic attenuation and the potential in the reservoir characteristic.

[Spectral scatter correction of coal samples based on quasi-linear local weighted method].

PubMed

Lei, Meng; Li, Ming; Ma, Xiao-Ping; Miao, Yan-Zi; Wang, Jian-Sheng

2014-07-01

The present paper puts forth a new spectral correction method based on quasi-linear expression and local weighted function. The first stage of the method is to search 3 quasi-linear expressions to replace the original linear expression in MSC method, such as quadratic, cubic and growth curve expression. Then the local weighted function is constructed by introducing 4 kernel functions, such as Gaussian, Epanechnikov, Biweight and Triweight kernel function. After adding the function in the basic estimation equation, the dependency between the original and ideal spectra is described more accurately and meticulously at each wavelength point. Furthermore, two analytical models were established respectively based on PLS and PCA-BP neural network method, which can be used for estimating the accuracy of corrected spectra. At last, the optimal correction mode was determined by the analytical results with different combination of quasi-linear expression and local weighted function. The spectra of the same coal sample have different noise ratios while the coal sample was prepared under different particle sizes. To validate the effectiveness of this method, the experiment analyzed the correction results of 3 spectral data sets with the particle sizes of 0.2, 1 and 3 mm. The results show that the proposed method can eliminate the scattering influence, and also can enhance the information of spectral peaks. This paper proves a more efficient way to enhance the correlation between corrected spectra and coal qualities significantly, and improve the accuracy and stability of the analytical model substantially.

A novel sampling method for multiple multiscale targets from scattering amplitudes at a fixed frequency

NASA Astrophysics Data System (ADS)

Liu, Xiaodong

2017-08-01

A sampling method by using scattering amplitude is proposed for shape and location reconstruction in inverse acoustic scattering problems. Only matrix multiplication is involved in the computation, thus the novel sampling method is very easy and simple to implement. With the help of the factorization of the far field operator, we establish an inf-criterion for characterization of underlying scatterers. This result is then used to give a lower bound of the proposed indicator functional for sampling points inside the scatterers. While for the sampling points outside the scatterers, we show that the indicator functional decays like the bessel functions as the sampling point goes away from the boundary of the scatterers. We also show that the proposed indicator functional continuously depends on the scattering amplitude, this further implies that the novel sampling method is extremely stable with respect to errors in the data. Different to the classical sampling method such as the linear sampling method or the factorization method, from the numerical point of view, the novel indicator takes its maximum near the boundary of the underlying target and decays like the bessel functions as the sampling points go away from the boundary. The numerical simulations also show that the proposed sampling method can deal with multiple multiscale case, even the different components are close to each other.

Measuring School Functioning in Students with Chronic Fatigue Syndrome: A Systematic Review

ERIC Educational Resources Information Center

Tollit, Michelle; Politis, Jennifer; Knight, Sarah

2018-01-01

Background: It is often surmised that school functioning is significantly impacted in chronic fatigue syndrome (CFS); however, how this phenomenon manifests itself has rarely been characterized. Methods: This systematic review synthesized and critically appraised methods, constructs, and instruments used to assess school functioning in students…

A Qualitative Approach to Sketch the Graph of a Function.

ERIC Educational Resources Information Center

Alson, Pedro

1992-01-01

Presents a qualitative and global method of graphing functions that involves transformations of the graph of a known function in the cartesian coordinate system referred to as graphic operators. Explains how the method has been taught to students and some comments about the results obtained. (MDH)

A Comparison of Methods for Detecting Differential Distractor Functioning

ERIC Educational Resources Information Center

Koon, Sharon

2010-01-01

This study examined the effectiveness of the odds-ratio method (Penfield, 2008) and the multinomial logistic regression method (Kato, Moen, & Thurlow, 2009) for measuring differential distractor functioning (DDF) effects in comparison to the standardized distractor analysis approach (Schmitt & Bleistein, 1987). Students classified as participating…

[Application of numerical convolution in in vivo/in vitro correlation research].

PubMed

Yue, Peng

2009-01-01

This paper introduced the conception and principle of in vivo/in vitro correlation (IVIVC) and convolution/deconvolution methods, and elucidated in details the convolution strategy and method for calculating the in vivo absorption performance of the pharmaceutics according to the their pharmacokinetic data in Excel, then put the results forward to IVIVC research. Firstly, the pharmacokinetic data ware fitted by mathematical software to make up the lost points. Secondly, the parameters of the optimal fitted input function were defined by trail-and-error method according to the convolution principle in Excel under the hypothesis that all the input functions fit the Weibull functions. Finally, the IVIVC between in vivo input function and the in vitro dissolution was studied. In the examples, not only the application of this method was demonstrated in details but also its simplicity and effectiveness were proved by comparing with the compartment model method and deconvolution method. It showed to be a powerful tool for IVIVC research.

A direct method for unfolding the resolution function from measurements of neutron induced reactions

NASA Astrophysics Data System (ADS)

Žugec, P.; Colonna, N.; Sabate-Gilarte, M.; Vlachoudis, V.; Massimi, C.; Lerendegui-Marco, J.; Stamatopoulos, A.; Bacak, M.; Warren, S. G.; n TOF Collaboration

2017-12-01

The paper explores the numerical stability and the computational efficiency of a direct method for unfolding the resolution function from the measurements of the neutron induced reactions. A detailed resolution function formalism is laid out, followed by an overview of challenges present in a practical implementation of the method. A special matrix storage scheme is developed in order to facilitate both the memory management of the resolution function matrix, and to increase the computational efficiency of the matrix multiplication and decomposition procedures. Due to its admirable computational properties, a Cholesky decomposition is at the heart of the unfolding procedure. With the smallest but necessary modification of the matrix to be decomposed, the method is successfully applied to system of 105 × 105. However, the amplification of the uncertainties during the direct inversion procedures limits the applicability of the method to high-precision measurements of neutron induced reactions.

Effective Biot theory and its generalization to poroviscoelastic models

NASA Astrophysics Data System (ADS)

Liu, Xu; Greenhalgh, Stewart; Zhou, Bing; Greenhalgh, Mark

2018-02-01

A method is suggested to express the effective bulk modulus of the solid frame of a poroelastic material as a function of the saturated bulk modulus. This method enables effective Biot theory to be described through the use of seismic dispersion measurements or other models developed for the effective saturated bulk modulus. The effective Biot theory is generalized to a poroviscoelastic model of which the moduli are represented by the relaxation functions of the generalized fractional Zener model. The latter covers the general Zener and the Cole-Cole models as special cases. A global search method is described to determine the parameters of the relaxation functions, and a simple deterministic method is also developed to find the defining parameters of the single Cole-Cole model. These methods enable poroviscoelastic models to be constructed, which are based on measured seismic attenuation functions, and ensure that the model dispersion characteristics match the observations.

Description of quasiparticle and satellite properties via cumulant expansions of the retarded one-particle Green's function

DOE PAGES

Mayers, Matthew Z.; Hybertsen, Mark S.; Reichman, David R.

2016-08-22

A cumulant-based GW approximation for the retarded one-particle Green's function is proposed, motivated by an exact relation between the improper Dyson self-energy and the cumulant generating function. We explore qualitative aspects of this method within a simple one-electron independent phonon model, where it is seen that the method preserves the energy moment of the spectral weight while also reproducing the exact Green's function in the weak-coupling limit. For the three-dimensional electron gas, this method predicts multiple satellites at the bottom of the band, albeit with inaccurate peak spacing. But, its quasiparticle properties and correlation energies are more accurate than bothmore » previous cumulant methods and standard G0W0. These results point to features that may be exploited within the framework of cumulant-based methods and suggest promising directions for future exploration and improvements of cumulant-based GW approaches.« less

The exact solutions and approximate analytic solutions of the (2 + 1)-dimensional KP equation based on symmetry method.

PubMed

Gai, Litao; Bilige, Sudao; Jie, Yingmo

2016-01-01

In this paper, we successfully obtained the exact solutions and the approximate analytic solutions of the (2 + 1)-dimensional KP equation based on the Lie symmetry, the extended tanh method and the homotopy perturbation method. In first part, we obtained the symmetries of the (2 + 1)-dimensional KP equation based on the Wu-differential characteristic set algorithm and reduced it. In the second part, we constructed the abundant exact travelling wave solutions by using the extended tanh method. These solutions are expressed by the hyperbolic functions, the trigonometric functions and the rational functions respectively. It should be noted that when the parameters are taken as special values, some solitary wave solutions are derived from the hyperbolic function solutions. Finally, we apply the homotopy perturbation method to obtain the approximate analytic solutions based on four kinds of initial conditions.

Label-free functional nucleic acid sensors for detecting target agents

DOEpatents

Lu, Yi; Xiang, Yu

2015-01-13

A general methodology to design label-free fluorescent functional nucleic acid sensors using a vacant site approach and an abasic site approach is described. In one example, a method for designing label-free fluorescent functional nucleic acid sensors (e.g., those that include a DNAzyme, aptamer or aptazyme) that have a tunable dynamic range through the introduction of an abasic site (e.g., dSpacer) or a vacant site into the functional nucleic acids. Also provided is a general method for designing label-free fluorescent aptamer sensors based on the regulation of malachite green (MG) fluorescence. A general method for designing label-free fluorescent catalytic and molecular beacons (CAMBs) is also provided. The methods demonstrated here can be used to design many other label-free fluorescent sensors to detect a wide range of analytes. Sensors and methods of using the disclosed sensors are also provided.

Homotopy method for optimization of variable-specific-impulse low-thrust trajectories

NASA Astrophysics Data System (ADS)

Chi, Zhemin; Yang, Hongwei; Chen, Shiyu; Li, Junfeng

2017-11-01

The homotopy method has been used as a useful tool in solving fuel-optimal trajectories with constant-specific-impulse low thrust. However, the specific impulse is often variable for many practical solar electric power-limited thrusters. This paper investigates the application of the homotopy method for optimization of variable-specific-impulse low-thrust trajectories. Difficulties arise when the two commonly-used homotopy functions are employed for trajectory optimization. The optimal power throttle level and the optimal specific impulse are coupled with the commonly-used quadratic and logarithmic homotopy functions. To overcome these difficulties, a modified logarithmic homotopy function is proposed to serve as a gateway for trajectory optimization, leading to decoupled expressions of both the optimal power throttle level and the optimal specific impulse. The homotopy method based on this homotopy function is proposed. Numerical simulations validate the feasibility and high efficiency of the proposed method.

Numerical solution of the nonlinear Schrodinger equation by feedforward neural networks

NASA Astrophysics Data System (ADS)

Shirvany, Yazdan; Hayati, Mohsen; Moradian, Rostam

2008-12-01

We present a method to solve boundary value problems using artificial neural networks (ANN). A trial solution of the differential equation is written as a feed-forward neural network containing adjustable parameters (the weights and biases). From the differential equation and its boundary conditions we prepare the energy function which is used in the back-propagation method with momentum term to update the network parameters. We improved energy function of ANN which is derived from Schrodinger equation and the boundary conditions. With this improvement of energy function we can use unsupervised training method in the ANN for solving the equation. Unsupervised training aims to minimize a non-negative energy function. We used the ANN method to solve Schrodinger equation for few quantum systems. Eigenfunctions and energy eigenvalues are calculated. Our numerical results are in agreement with their corresponding analytical solution and show the efficiency of ANN method for solving eigenvalue problems.

Modeling Sound Propagation Through Non-Axisymmetric Jets

NASA Technical Reports Server (NTRS)

Leib, Stewart J.

2014-01-01

A method for computing the far-field adjoint Green's function of the generalized acoustic analogy equations under a locally parallel mean flow approximation is presented. The method is based on expanding the mean-flow-dependent coefficients in the governing equation and the scalar Green's function in truncated Fourier series in the azimuthal direction and a finite difference approximation in the radial direction in circular cylindrical coordinates. The combined spectral/finite difference method yields a highly banded system of algebraic equations that can be efficiently solved using a standard sparse system solver. The method is applied to test cases, with mean flow specified by analytical functions, corresponding to two noise reduction concepts of current interest: the offset jet and the fluid shield. Sample results for the Green's function are given for these two test cases and recommendations made as to the use of the method as part of a RANS-based jet noise prediction code.

A Galerkin discretisation-based identification for parameters in nonlinear mechanical systems

NASA Astrophysics Data System (ADS)

Liu, Zuolin; Xu, Jian

2018-04-01

In the paper, a new parameter identification method is proposed for mechanical systems. Based on the idea of Galerkin finite-element method, the displacement over time history is approximated by piecewise linear functions, and the second-order terms in model equation are eliminated by integrating by parts. In this way, the lost function of integration form is derived. Being different with the existing methods, the lost function actually is a quadratic sum of integration over the whole time history. Then for linear or nonlinear systems, the optimisation of the lost function can be applied with traditional least-squares algorithm or the iterative one, respectively. Such method could be used to effectively identify parameters in linear and arbitrary nonlinear mechanical systems. Simulation results show that even under the condition of sparse data or low sampling frequency, this method could still guarantee high accuracy in identifying linear and nonlinear parameters.

Variational method for calculating the binding energy of the base state of an impurity D- centered on a quantum dot of GaAs-Ga1-xAlxAs

NASA Astrophysics Data System (ADS)

Durán-Flórez, F.; Caicedo, L. C.; Gonzalez, J. E.

2018-04-01

In quantum mechanics it is very difficult to obtain exact solutions, therefore, it is necessary to resort to tools and methods that facilitate the calculations of the solutions of these systems, one of these methods is the variational method that consists in proposing a wave function that depend on several parameters that are adjusted to get close to the exact solution. Authors in the past have performed calculations applying this method using exponential and Gaussian orbital functions with linear and quadratic correlation factors. In this paper, a Gaussian function with a linear correlation factor is proposed, for the calculation of the binding energy of an impurity D ‑ centered on a quantum dot of radius r, the Gaussian function is dependent on the radius of the quantum dot.

Functional group placement in protein binding sites: a comparison of GRID and MCSS

NASA Astrophysics Data System (ADS)

Bitetti-Putzer, Ryan; Joseph-McCarthy, Diane; Hogle, James M.; Karplus, Martin

2001-10-01

One approach to combinatorial ligand design begins by determining optimal locations (i.e., local potential energy minima) for functional groups in the binding site of a target macromolecule. MCSS and GRID are two methods, based on significantly different algorithms, which are used for this purpose. A comparison of the two methods for the same functional groups is reported. Calculations were performed for nonpolar and polar functional groups in the internal hydrophobic pocket of the poliovirus capsid protein, and on the binding surface of the src SH3 domain. The two approaches are shown to agree qualitatively; i.e., the global characteristics of the functional group maps generated by MCSS and GRID are similar. However, there are significant differences in the relative interaction energies of the two sets of minima, a consequence of the different functional form used to evaluate polar interactions (electrostatics and hydrogen bonding) in the two methods. The single sphere representation used by GRID affords only positional information, supplemented by the identification of hydrogen bonding interactions. By contrast, the multi-atom representation of most MCSS groups yields in both positional and orientational information. The two methods are most similar for small functional groups, while for larger functional groups MCSS yields results consistent with GRID but superior in detail. These results are in accord with the somewhat different purposes for which the two methods were developed. GRID has been used mainly to introduce functionalities at specific positions in lead compounds, in which case the orientation is predetermined by the structure of the latter. The orientational information provided by MCSS is important for its use in the de novo design of large, multi-functional ligands, as well as for improving lead compounds.

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context.

PubMed

Wang, Yong-Cui; Wang, Yong; Yang, Zhi-Xia; Deng, Nai-Yang

2011-06-20

Enzymes are known as the largest class of proteins and their functions are usually annotated by the Enzyme Commission (EC), which uses a hierarchy structure, i.e., four numbers separated by periods, to classify the function of enzymes. Automatically categorizing enzyme into the EC hierarchy is crucial to understand its specific molecular mechanism. In this paper, we introduce two key improvements in predicting enzyme function within the machine learning framework. One is to introduce the efficient sequence encoding methods for representing given proteins. The second one is to develop a structure-based prediction method with low computational complexity. In particular, we propose to use the conjoint triad feature (CTF) to represent the given protein sequences by considering not only the composition of amino acids but also the neighbor relationships in the sequence. Then we develop a support vector machine (SVM)-based method, named as SVMHL (SVM for hierarchy labels), to output enzyme function by fully considering the hierarchical structure of EC. The experimental results show that our SVMHL with the CTF outperforms SVMHL with the amino acid composition (AAC) feature both in predictive accuracy and Matthew's correlation coefficient (MCC). In addition, SVMHL with the CTF obtains the accuracy and MCC ranging from 81% to 98% and 0.82 to 0.98 when predicting the first three EC digits on a low-homologous enzyme dataset. We further demonstrate that our method outperforms the methods which do not take account of hierarchical relationship among enzyme categories and alternative methods which incorporate prior knowledge about inter-class relationships. Our structure-based prediction model, SVMHL with the CTF, reduces the computational complexity and outperforms the alternative approaches in enzyme function prediction. Therefore our new method will be a useful tool for enzyme function prediction community.

Comparison of Response Surface Construction Methods for Derivative Estimation Using Moving Least Squares, Kriging and Radial Basis Functions

NASA Technical Reports Server (NTRS)

Krishnamurthy, Thiagarajan

2005-01-01

Response construction methods using Moving Least Squares (MLS), Kriging and Radial Basis Functions (RBF) are compared with the Global Least Squares (GLS) method in three numerical examples for derivative generation capability. Also, a new Interpolating Moving Least Squares (IMLS) method adopted from the meshless method is presented. It is found that the response surface construction methods using the Kriging and RBF interpolation yields more accurate results compared with MLS and GLS methods. Several computational aspects of the response surface construction methods also discussed.

EFFECTS OF LASER RADIATION ON MATTER: Distribution function of microinclusions in polymethylmethacrylate and its evolution under the influence of a series of laser pulses

NASA Astrophysics Data System (ADS)

Glauberman, G. Ya; Savanin, S. Yu; Shkunov, V. V.; Shumov, D. E.

1990-08-01

A new method is proposed for the derivation of the distribution function of the experimentally determined breakdown thresholds of absorbing microinclusions in a transparent insulator. Expressions are obtained for describing the evolution of this function in the course of irradiation of the insulator with laser pulses of constant energy density. The method is applied to calculate the distribution function of microinclusions in polymethylmethacrylate and the evolution of this function.

Functional Techniques for Data Analysis

NASA Technical Reports Server (NTRS)

Tomlinson, John R.

1997-01-01

This dissertation develops a new general method of solving Prony's problem. Two special cases of this new method have been developed previously. They are the Matrix Pencil and the Osculatory Interpolation. The dissertation shows that they are instances of a more general solution type which allows a wide ranging class of linear functional to be used in the solution of the problem. This class provides a continuum of functionals which provide new methods that can be used to solve Prony's problem.

Extensive complementarity between gene function prediction methods.

PubMed

Vidulin, Vedrana; Šmuc, Tomislav; Supek, Fran

2016-12-01

The number of sequenced genomes rises steadily but we still lack the knowledge about the biological roles of many genes. Automated function prediction (AFP) is thus a necessity. We hypothesized that AFP approaches that draw on distinct genome features may be useful for predicting different types of gene functions, motivating a systematic analysis of the benefits gained by obtaining and integrating such predictions. Our pipeline amalgamates 5 133 543 genes from 2071 genomes in a single massive analysis that evaluates five established genomic AFP methodologies. While 1227 Gene Ontology (GO) terms yielded reliable predictions, the majority of these functions were accessible to only one or two of the methods. Moreover, different methods tend to assign a GO term to non-overlapping sets of genes. Thus, inferences made by diverse genomic AFP methods display a striking complementary, both gene-wise and function-wise. Because of this, a viable integration strategy is to rely on a single most-confident prediction per gene/function, rather than enforcing agreement across multiple AFP methods. Using an information-theoretic approach, we estimate that current databases contain 29.2 bits/gene of known Escherichia coli gene functions. This can be increased by up to 5.5 bits/gene using individual AFP methods or by 11 additional bits/gene upon integration, thereby providing a highly-ranking predictor on the Critical Assessment of Function Annotation 2 community benchmark. Availability of more sequenced genomes boosts the predictive accuracy of AFP approaches and also the benefit from integrating them. The individual and integrated GO predictions for the complete set of genes are available from http://gorbi.irb.hr/ CONTACT: fran.supek@irb.hrSupplementary information: Supplementary materials are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia.

PubMed

Rodriguez-Sabate, Clara; Morales, Ingrid; Sanchez, Alberto; Rodriguez, Manuel

2017-01-01

The complexity of basal ganglia (BG) interactions is often condensed into simple models mainly based on animal data and that present BG in closed-loop cortico-subcortical circuits of excitatory/inhibitory pathways which analyze the incoming cortical data and return the processed information to the cortex. This study was aimed at identifying functional relationships in the BG motor-loop of 24 healthy-subjects who provided written, informed consent and whose BOLD-activity was recorded by MRI methods. The analysis of the functional interaction between these centers by correlation techniques and multiple linear regression showed non-linear relationships which cannot be suitably addressed with these methods. The multiple correspondence analysis (MCA), an unsupervised multivariable procedure which can identify non-linear interactions, was used to study the functional connectivity of BG when subjects were at rest. Linear methods showed different functional interactions expected according to current BG models. MCA showed additional functional interactions which were not evident when using lineal methods. Seven functional configurations of BG were identified with MCA, two involving the primary motor and somatosensory cortex, one involving the deepest BG (external-internal globus pallidum, subthalamic nucleus and substantia nigral), one with the input-output BG centers (putamen and motor thalamus), two linking the input-output centers with other BG (external pallidum and subthalamic nucleus), and one linking the external pallidum and the substantia nigral. The results provide evidence that the non-linear MCA and linear methods are complementary and should be best used in conjunction to more fully understand the nature of functional connectivity of brain centers.

Methods for measuring right ventricular function and hemodynamic coupling with the pulmonary vasculature.

PubMed

Bellofiore, Alessandro; Chesler, Naomi C

2013-07-01

The right ventricle (RV) is a pulsatile pump, the efficiency of which depends on proper hemodynamic coupling with the compliant pulmonary circulation. The RV and pulmonary circulation exhibit structural and functional differences with the more extensively investigated left ventricle (LV) and systemic circulation. In light of these differences, metrics of LV function and efficiency of coupling to the systemic circulation cannot be used without modification to characterize RV function and efficiency of coupling to the pulmonary circulation. In this article, we review RV physiology and mechanics, established and novel methods for measuring RV function and hemodynamic coupling, and findings from application of these methods to RV function and coupling changes with pulmonary hypertension. We especially focus on non-invasive measurements, as these may represent the future for clinical monitoring of disease progression and the effect of drug therapies.

Time-domain representation of frequency-dependent foundation impedance functions

USGS Publications Warehouse

Safak, E.

2006-01-01

Foundation impedance functions provide a simple means to account for soil-structure interaction (SSI) when studying seismic response of structures. Impedance functions represent the dynamic stiffness of the soil media surrounding the foundation. The fact that impedance functions are frequency dependent makes it difficult to incorporate SSI in standard time-history analysis software. This paper introduces a simple method to convert frequency-dependent impedance functions into time-domain filters. The method is based on the least-squares approximation of impedance functions by ratios of two complex polynomials. Such ratios are equivalent, in the time-domain, to discrete-time recursive filters, which are simple finite-difference equations giving the relationship between foundation forces and displacements. These filters can easily be incorporated into standard time-history analysis programs. Three examples are presented to show the applications of the method.

Mapping genomic features to functional traits through microbial whole genome sequences.

PubMed

Zhang, Wei; Zeng, Erliang; Liu, Dan; Jones, Stuart E; Emrich, Scott

2014-01-01

Recently, the utility of trait-based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. We proposed a machine learning framework to quantitatively link the genomic features with functional traits. Genes from bacteria genomes belonging to different functional traits were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. Extensive experimental results demonstrated that functional trait related genes can be detected using our method. Further, the method has the potential to provide novel biological insights.

Electron-Ion Dynamics with Time-Dependent Density Functional Theory: Towards Predictive Solar Cell Modeling: Final Technical Report

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

Maitra, Neepa

2016-07-14

This project investigates the accuracy of currently-used functionals in time-dependent density functional theory, which is today routinely used to predict and design materials and computationally model processes in solar energy conversion. The rigorously-based electron-ion dynamics method developed here sheds light on traditional methods and overcomes challenges those methods have. The fundamental research undertaken here is important for building reliable and practical methods for materials discovery. The ultimate goal is to use these tools for the computational design of new materials for solar cell devices of high efficiency.

The method of generating functions in exact scalar field inflationary cosmology

NASA Astrophysics Data System (ADS)

Chervon, Sergey V.; Fomin, Igor V.; Beesham, Aroonkumar

2018-04-01

The construction of exact solutions in scalar field inflationary cosmology is of growing interest. In this work, we review the results which have been obtained with the help of one of the most effective methods, viz., the method of generating functions for the construction of exact solutions in scalar field cosmology. We also include in the debate the superpotential method, which may be considered as the bridge to the slow roll approximation equations. Based on the review, we suggest a classification for the generating functions, and find a connection for all of them with the superpotential.

Single Cell Spectroscopy: Noninvasive Measures of Small-Scale Structure and Function

PubMed Central

Mousoulis, Charilaos; Xu, Xin; Reiter, David A.; Neu, Corey P.

2013-01-01

The advancement of spectroscopy methods attained through increases in sensitivity, and often with the coupling of complementary techniques, has enabled real-time structure and function measurements of single cells. The purpose of this review is to illustrate, in light of advances, the strengths and the weaknesses of these methods. Included also is an assessment of the impact of the experimental setup and conditions of each method on cellular function and integrity. A particular emphasis is placed on noninvasive and nondestructive techniques for achieving single cell detection, including nuclear magnetic resonance, in addition to physical, optical, and vibrational methods. PMID:23886910

Voltage transfer function as an optical method to characterize electrical properties of liquid crystal devices.

PubMed

Bateman, J; Proctor, M; Buchnev, O; Podoliak, N; D'Alessandro, G; Kaczmarek, M

2014-07-01

The voltage transfer function is a rapid and visually effective method to determine the electrical response of liquid crystal (LC) systems using optical measurements. This method relies on crosspolarized intensity measurements as a function of the frequency and amplitude of the voltage applied to the device. Coupled with a mathematical model of the device it can be used to determine the device time constants and electrical properties. We validate the method using photorefractive LC cells and determine the main time constants and the voltage dropped across the layers using a simple nonlinear filter model.

Paired Pulse Basis Functions for the Method of Moments EFIE Solution of Electromagnetic Problems Involving Arbitrarily-shaped, Three-dimensional Dielectric Scatterers

NASA Technical Reports Server (NTRS)

MacKenzie, Anne I.; Rao, Sadasiva M.; Baginski, Michael E.

2007-01-01

A pair of basis functions is presented for the surface integral, method of moment solution of scattering by arbitrarily-shaped, three-dimensional dielectric bodies. Equivalent surface currents are represented by orthogonal unit pulse vectors in conjunction with triangular patch modeling. The electric field integral equation is employed with closed geometries for dielectric bodies; the method may also be applied to conductors. Radar cross section results are shown for dielectric bodies having canonical spherical, cylindrical, and cubic shapes. Pulse basis function results are compared to results by other methods.

Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.

PubMed

Cheng, Wei; Rolls, Edmund T; Zhang, Jie; Sheng, Wenbo; Ma, Liang; Wan, Lin; Luo, Qiang; Feng, Jianfeng

2017-03-01

A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity. Copyright © 2017. Published by Elsevier Inc.

QUEST+: A general multidimensional Bayesian adaptive psychometric method.

PubMed

Watson, Andrew B

2017-03-01

QUEST+ is a Bayesian adaptive psychometric testing method that allows an arbitrary number of stimulus dimensions, psychometric function parameters, and trial outcomes. It is a generalization and extension of the original QUEST procedure and incorporates many subsequent developments in the area of parametric adaptive testing. With a single procedure, it is possible to implement a wide variety of experimental designs, including conventional threshold measurement; measurement of psychometric function parameters, such as slope and lapse; estimation of the contrast sensitivity function; measurement of increment threshold functions; measurement of noise-masking functions; Thurstone scale estimation using pair comparisons; and categorical ratings on linear and circular stimulus dimensions. QUEST+ provides a general method to accelerate data collection in many areas of cognitive and perceptual science.

BLUES function method in computational physics

NASA Astrophysics Data System (ADS)

Indekeu, Joseph O.; Müller-Nedebock, Kristian K.

2018-04-01

We introduce a computational method in physics that goes ‘beyond linear use of equation superposition’ (BLUES). A BLUES function is defined as a solution of a nonlinear differential equation (DE) with a delta source that is at the same time a Green’s function for a related linear DE. For an arbitrary source, the BLUES function can be used to construct an exact solution to the nonlinear DE with a different, but related source. Alternatively, the BLUES function can be used to construct an approximate piecewise analytical solution to the nonlinear DE with an arbitrary source. For this alternative use the related linear DE need not be known. The method is illustrated in a few examples using analytical calculations and numerical computations. Areas for further applications are suggested.

Glycoconjugates and methods

DOEpatents

Bertozzi, Carolyn C [Albany, CA; Yarema, Kevin J [Albany, CA; Mahal, Lara K [Berkeley, CA

2008-04-01

Methods for making the functionalized glycoconjugates include (a) contacting a cell with a first monosaccharide, and (b) incubating the cell under conditions whereby the cell (i) internalizes the first monosaccharide, (ii) biochemically processes the first monosaccharide into a second saccharide, (iii) conjugates the saccharide to a carrier to form a glycoconjugate, and (iv) extracellularly expresses the glycoconjugate to form an extracellular glycoconjugate comprising a selectively reactive functional group. Methods for forming products at a cell further comprise contacting the functional group of the extracellularly expressed glycoconjugate with an agent which selectively reacts with the functional group to form a product. Subject compositions include cyto-compatible monosaccharides comprising a nitrogen or ether linked functional group selectively reactive at a cell surface and compositions and cells comprising such saccharides.

Multiple imputation methods for nonparametric inference on cumulative incidence with missing cause of failure

PubMed Central

Lee, Minjung; Dignam, James J.; Han, Junhee

2014-01-01

We propose a nonparametric approach for cumulative incidence estimation when causes of failure are unknown or missing for some subjects. Under the missing at random assumption, we estimate the cumulative incidence function using multiple imputation methods. We develop asymptotic theory for the cumulative incidence estimators obtained from multiple imputation methods. We also discuss how to construct confidence intervals for the cumulative incidence function and perform a test for comparing the cumulative incidence functions in two samples with missing cause of failure. Through simulation studies, we show that the proposed methods perform well. The methods are illustrated with data from a randomized clinical trial in early stage breast cancer. PMID:25043107

Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

PubMed

Roche, Daniel Barry; Brackenridge, Danielle Allison; McGuffin, Liam James

2015-12-15

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein-ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein-ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein-ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

Real-time system for extracting and monitoring the cerebral functional component during fNIRS measurements

NASA Astrophysics Data System (ADS)

Yamada, Toru; Ohashi, Mitsuo; Umeyama, Shinji

2015-12-01

Functional near-infrared spectroscopy (fNIRS) can non-invasively detect hemodynamic changes associated with cerebral neural activation in human subjects. However, its signal is often affected by changes in the optical characteristics of tissues in the head other than brain. To conduct fNIRS measurements precisely and efficiently, the extraction and realtime monitoring of the cerebral functional component is crucial. We previously developed methods for extracting the cerebral functional component—the multidistance optode arrangement (MD) method and the hemodynamic modality separation (HMS) method. In this study, we implemented these methods in a software used with the fNIRS system OEG- 17APD (Spectratech, Japan), and realized a real-time display of the extracted results. When using this system for human subject experiments, the baselines obtained with the MD and HMS methods were highly stabilized, whereas originally, the fNIRS signal fluctuated significantly when the subject moved. Through a functional experiment with repetitive single-sided hand clasping tasks, the extracted signals showed distinctively higher reproducibility than that obtained in the conventional measurements.

Dynamic Mesh Adaptation for Front Evolution Using Discontinuous Galerkin Based Weighted Condition Number Mesh Relaxation

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

Greene, Patrick T.; Schofield, Samuel P.; Nourgaliev, Robert

2016-06-21

A new mesh smoothing method designed to cluster mesh cells near a dynamically evolving interface is presented. The method is based on weighted condition number mesh relaxation with the weight function being computed from a level set representation of the interface. The weight function is expressed as a Taylor series based discontinuous Galerkin projection, which makes the computation of the derivatives of the weight function needed during the condition number optimization process a trivial matter. For cases when a level set is not available, a fast method for generating a low-order level set from discrete cell-centered elds, such as amore » volume fraction or index function, is provided. Results show that the low-order level set works equally well for the weight function as the actual level set. Meshes generated for a number of interface geometries are presented, including cases with multiple level sets. Dynamic cases for moving interfaces are presented to demonstrate the method's potential usefulness to arbitrary Lagrangian Eulerian (ALE) methods.« less

High-order time-marching reinitialization for regional level-set functions

NASA Astrophysics Data System (ADS)

Pan, Shucheng; Lyu, Xiuxiu; Hu, Xiangyu Y.; Adams, Nikolaus A.

2018-02-01

In this work, the time-marching reinitialization method is extended to compute the unsigned distance function in multi-region systems involving arbitrary number of regions. High order and interface preservation are achieved by applying a simple mapping that transforms the regional level-set function to the level-set function and a high-order two-step reinitialization method which is a combination of the closest point finding procedure and the HJ-WENO scheme. The convergence failure of the closest point finding procedure in three dimensions is addressed by employing a proposed multiple junction treatment and a directional optimization algorithm. Simple test cases show that our method exhibits 4th-order accuracy for reinitializing the regional level-set functions and strictly satisfies the interface-preserving property. The reinitialization results for more complex cases with randomly generated diagrams show the capability our method for arbitrary number of regions N, with a computational effort independent of N. The proposed method has been applied to dynamic interfaces with different types of flows, and the results demonstrate high accuracy and robustness.

Solving Nonlinear Fractional Differential Equation by Generalized Mittag-Leffler Function Method

NASA Astrophysics Data System (ADS)

Arafa, A. A. M.; Rida, S. Z.; Mohammadein, A. A.; Ali, H. M.

2013-06-01

In this paper, we use Mittag—Leffler function method for solving some nonlinear fractional differential equations. A new solution is constructed in power series. The fractional derivatives are described by Caputo's sense. To illustrate the reliability of the method, some examples are provided.

Discovery of a general method of solving the Schrödinger and dirac equations that opens a way to accurately predictive quantum chemistry.

PubMed

Nakatsuji, Hiroshi

2012-09-18

Just as Newtonian law governs classical physics, the Schrödinger equation (SE) and the relativistic Dirac equation (DE) rule the world of chemistry. So, if we can solve these equations accurately, we can use computation to predict chemistry precisely. However, for approximately 80 years after the discovery of these equations, chemists believed that they could not solve SE and DE for atoms and molecules that included many electrons. This Account reviews ideas developed over the past decade to further the goal of predictive quantum chemistry. Between 2000 and 2005, I discovered a general method of solving the SE and DE accurately. As a first inspiration, I formulated the structure of the exact wave function of the SE in a compact mathematical form. The explicit inclusion of the exact wave function's structure within the variational space allows for the calculation of the exact wave function as a solution of the variational method. Although this process sounds almost impossible, it is indeed possible, and I have published several formulations and applied them to solve the full configuration interaction (CI) with a very small number of variables. However, when I examined analytical solutions for atoms and molecules, the Hamiltonian integrals in their secular equations diverged. This singularity problem occurred in all atoms and molecules because it originates from the singularity of the Coulomb potential in their Hamiltonians. To overcome this problem, I first introduced the inverse SE and then the scaled SE. The latter simpler idea led to immediate and surprisingly accurate solution for the SEs of the hydrogen atom, helium atom, and hydrogen molecule. The free complement (FC) method, also called the free iterative CI (free ICI) method, was efficient for solving the SEs. In the FC method, the basis functions that span the exact wave function are produced by the Hamiltonian of the system and the zeroth-order wave function. These basis functions are called complement functions because they are the elements of the complete functions for the system under consideration. We extended this idea to solve the relativistic DE and applied it to the hydrogen and helium atoms, without observing any problems such as variational collapse. Thereafter, we obtained very accurate solutions of the SE for the ground and excited states of the Born-Oppenheimer (BO) and non-BO states of very small systems like He, H(2)(+), H(2), and their analogues. For larger systems, however, the overlap and Hamiltonian integrals over the complement functions are not always known mathematically (integration difficulty); therefore we formulated the local SE (LSE) method as an integral-free method. Without any integration, the LSE method gave fairly accurate energies and wave functions for small atoms and molecules. We also calculated continuous potential curves of the ground and excited states of small diatomic molecules by introducing the transferable local sampling method. Although the FC-LSE method is simple, the achievement of chemical accuracy in the absolute energy of larger systems remains time-consuming. The development of more efficient methods for the calculations of ordinary molecules would allow researchers to make these calculations more easily.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network.

PubMed

Guo, Hao; Qin, Mengna; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network

PubMed Central

Qin, Mengna; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%. PMID:29387141

Functionalization of Probe Tips and Supports for Single-Molecule Recognition Force Microscopy

NASA Astrophysics Data System (ADS)

Ebner, Andreas; Wildling, Linda; Zhu, Rong; Rankl, Christian; Haselgrübler, Thomas; Hinterdorfer, Peter; Gruber, Hermann J.

The measuring tip of a force microscope can be converted into a monomolecular sensor if one or few "ligand" molecules are attached to the apex of the tip while maintaining ligand function. Functionalized tips are used to study fine details of receptor-ligand interaction by force spectroscopy or to map cognate "receptor" molecules on the sample surface. The receptor (or target) molecules can be present on the surface of a biological specimen; alternatively, soluble target molecules must be immobilized on ultraflat supports. This review describes the methods of tip functionalization, as well as target molecule immobilization. Silicon nitride tips, silicon chips, and mica have usually been functionalized in three steps: (1) aminofunctionalization, (2) crosslinker attachment, and (3) ligand/receptor coupling, whereby numerous crosslinkers are available to couple widely different ligand molecules. Gold-covered tips and/or supports have usually been coated with a self-assembled monolayer, on top of which the ligand/receptor molecule has been coupled either directly or via a crosslinker molecule. Apart from these general strategies, many simplified methods have been used for tip and/or support functionalization, even single-step methods such as adsorption or chemisorption being very efficient under suitable circumstances. All methods are described with the same explicitness and critical parameters are discussed. In conclusion, this review should help to find suitable methods for specific problems of tip and support functionalization.

A survey of kernel-type estimators for copula and their applications

NASA Astrophysics Data System (ADS)

Sumarjaya, I. W.

2017-10-01

Copulas have been widely used to model nonlinear dependence structure. Main applications of copulas include areas such as finance, insurance, hydrology, rainfall to name but a few. The flexibility of copula allows researchers to model dependence structure beyond Gaussian distribution. Basically, a copula is a function that couples multivariate distribution functions to their one-dimensional marginal distribution functions. In general, there are three methods to estimate copula. These are parametric, nonparametric, and semiparametric method. In this article we survey kernel-type estimators for copula such as mirror reflection kernel, beta kernel, transformation method and local likelihood transformation method. Then, we apply these kernel methods to three stock indexes in Asia. The results of our analysis suggest that, albeit variation in information criterion values, the local likelihood transformation method performs better than the other kernel methods.

Solving the Schroedinger equation for helium atom and its isoelectronic ions with the free iterative complement interaction (ICI) method

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

Nakashima, Hiroyuki; Nakatsuji, Hiroshi

2007-12-14

The Schroedinger equation was solved very accurately for helium atom and its isoelectronic ions (Z=1-10) with the free iterative complement interaction (ICI) method followed by the variational principle. We obtained highly accurate wave functions and energies of helium atom and its isoelectronic ions. For helium, the calculated energy was -2.903 724 377 034 119 598 311 159 245 194 404 446 696 905 37 a.u., correct over 40 digit accuracy, and for H{sup -}, it was -0.527 751 016 544 377 196 590 814 566 747 511 383 045 02 a.u. These results prove numerically that with the free ICImore » method, we can calculate the solutions of the Schroedinger equation as accurately as one desires. We examined several types of scaling function g and initial function {psi}{sub 0} of the free ICI method. The performance was good when logarithm functions were used in the initial function because the logarithm function is physically essential for three-particle collision area. The best performance was obtained when we introduce a new logarithm function containing not only r{sub 1} and r{sub 2} but also r{sub 12} in the same logarithm function.« less

Multiscale moment-based technique for object matching and recognition

NASA Astrophysics Data System (ADS)

Thio, HweeLi; Chen, Liya; Teoh, Eam-Khwang

2000-03-01

A new method is proposed to extract features from an object for matching and recognition. The features proposed are a combination of local and global characteristics -- local characteristics from the 1-D signature function that is defined to each pixel on the object boundary, global characteristics from the moments that are generated from the signature function. The boundary of the object is first extracted, then the signature function is generated by computing the angle between two lines from every point on the boundary as a function of position along the boundary. This signature function is position, scale and rotation invariant (PSRI). The shape of the signature function is then described quantitatively by using moments. The moments of the signature function are the global characters of a local feature set. Using moments as the eventual features instead of the signature function reduces the time and complexity of an object matching application. Multiscale moments are implemented to produce several sets of moments that will generate more accurate matching. Basically multiscale technique is a coarse to fine procedure and makes the proposed method more robust to noise. This method is proposed to match and recognize objects under simple transformation, such as translation, scale changes, rotation and skewing. A simple logo indexing system is implemented to illustrate the performance of the proposed method.

Robust estimation for ordinary differential equation models.

PubMed

Cao, J; Wang, L; Xu, J

2011-12-01

Applied scientists often like to use ordinary differential equations (ODEs) to model complex dynamic processes that arise in biology, engineering, medicine, and many other areas. It is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. We propose a robust method to address this problem. The dynamic process is represented with a nonparametric function, which is a linear combination of basis functions. The nonparametric function is estimated by a robust penalized smoothing method. The penalty term is defined with the parametric ODE model, which controls the roughness of the nonparametric function and maintains the fidelity of the nonparametric function to the ODE model. The basis coefficients and ODE parameters are estimated in two nested levels of optimization. The coefficient estimates are treated as an implicit function of ODE parameters, which enables one to derive the analytic gradients for optimization using the implicit function theorem. Simulation studies show that the robust method gives satisfactory estimates for the ODE parameters from noisy data with outliers. The robust method is demonstrated by estimating a predator-prey ODE model from real ecological data. © 2011, The International Biometric Society.

Function combined method for design innovation of children's bike

NASA Astrophysics Data System (ADS)

Wu, Xiaoli; Qiu, Tingting; Chen, Huijuan

2013-03-01

As children mature, bike products for children in the market develop at the same time, and the conditions are frequently updated. Certain problems occur when using a bike, such as cycle overlapping, repeating function, and short life cycle, which go against the principles of energy conservation and the environmental protection intensive design concept. In this paper, a rational multi-function method of design through functional superposition, transformation, and technical implementation is proposed. An organic combination of frog-style scooter and children's tricycle is developed using the multi-function method. From the ergonomic perspective, the paper elaborates on the body size of children aged 5 to 12 and effectively extracts data for a multi-function children's bike, which can be used for gliding and riding. By inverting the body, parts can be interchanged between the handles and the pedals of the bike. Finally, the paper provides a detailed analysis of the components and structural design, body material, and processing technology of the bike. The study of Industrial Product Innovation Design provides an effective design method to solve the bicycle problems, extends the function problems, improves the product market situation, and enhances the energy saving feature while implementing intensive product development effectively at the same time.

On a modified streamline curvature method for the Euler equations

NASA Technical Reports Server (NTRS)

Cordova, Jeffrey Q.; Pearson, Carl E.

1988-01-01

A modification of the streamline curvature method leads to a quasilinear second-order partial differential equation for the streamline coordinate function. The existence of a stream function is not required. The method is applied to subsonic and supersonic nozzle flow, and to axially symmetric flow with swirl. For many situations, the associated numerical method is both fast and accurate.

Course 4: Density Functional Theory, Methods, Techniques, and Applications

NASA Astrophysics Data System (ADS)

Chrétien, S.; Salahub, D. R.

Contents 1 Introduction 2 Density functional theory 2.1 Hohenberg and Kohn theorems 2.2 Levy's constrained search 2.3 Kohn-Sham method 3 Density matrices and pair correlation functions 4 Adiabatic connection or coupling strength integration 5 Comparing and constrasting KS-DFT and HF-CI 6 Preparing new functionals 7 Approximate exchange and correlation functionals 7.1 The Local Spin Density Approximation (LSDA) 7.2 Gradient Expansion Approximation (GEA) 7.3 Generalized Gradient Approximation (GGA) 7.4 meta-Generalized Gradient Approximation (meta-GGA) 7.5 Hybrid functionals 7.6 The Optimized Effective Potential method (OEP) 7.7 Comparison between various approximate functionals 8 LAP correlation functional 9 Solving the Kohn-Sham equations 9.1 The Kohn-Sham orbitals 9.2 Coulomb potential 9.3 Exchange-correlation potential 9.4 Core potential 9.5 Other choices and sources of error 9.6 Functionality 10 Applications 10.1 Ab initio molecular dynamics for an alanine dipeptide model 10.2 Transition metal clusters: The ecstasy, and the agony... 10.3 The conversion of acetylene to benzene on Fe clusters 11 Conclusions

A network function-based definition of communities in complex networks.

PubMed

Chauhan, Sanjeev; Girvan, Michelle; Ott, Edward

2012-09-01

We consider an alternate definition of community structure that is functionally motivated. We define network community structure based on the function the network system is intended to perform. In particular, as a specific example of this approach, we consider communities whose function is enhanced by the ability to synchronize and/or by resilience to node failures. Previous work has shown that, in many cases, the largest eigenvalue of the network's adjacency matrix controls the onset of both synchronization and percolation processes. Thus, for networks whose functional performance is dependent on these processes, we propose a method that divides a given network into communities based on maximizing a function of the largest eigenvalues of the adjacency matrices of the resulting communities. We also explore the differences between the partitions obtained by our method and the modularity approach (which is based solely on consideration of network structure). We do this for several different classes of networks. We find that, in many cases, modularity-based partitions do almost as well as our function-based method in finding functional communities, even though modularity does not specifically incorporate consideration of function.

Fracture mechanics analysis of cracked structures using weight function and neural network method

NASA Astrophysics Data System (ADS)

Chen, J. G.; Zang, F. G.; Yang, Y.; Shi, K. K.; Fu, X. L.

2018-06-01

Stress intensity factors(SIFs) due to thermal-mechanical load has been established by using weight function method. Two reference stress states sere used to determine the coefficients in the weight function. Results were evaluated by using data from literature and show a good agreement between them. So, the SIFs can be determined quickly using the weight function obtained when cracks subjected to arbitrary loads, and presented method can be used for probabilistic fracture mechanics analysis. A probabilistic methodology considering Monte-Carlo with neural network (MCNN) has been developed. The results indicate that an accurate probabilistic characteristic of the KI can be obtained by using the developed method. The probability of failure increases with the increasing of loads, and the relationship between is nonlinear.

Hierarchical Adaptive Regression Kernels for Regression with Functional Predictors.

PubMed

Woodard, Dawn B; Crainiceanu, Ciprian; Ruppert, David

2013-01-01

We propose a new method for regression using a parsimonious and scientifically interpretable representation of functional predictors. Our approach is designed for data that exhibit features such as spikes, dips, and plateaus whose frequency, location, size, and shape varies stochastically across subjects. We propose Bayesian inference of the joint functional and exposure models, and give a method for efficient computation. We contrast our approach with existing state-of-the-art methods for regression with functional predictors, and show that our method is more effective and efficient for data that include features occurring at varying locations. We apply our methodology to a large and complex dataset from the Sleep Heart Health Study, to quantify the association between sleep characteristics and health outcomes. Software and technical appendices are provided in online supplemental materials.

RELATIVE CONTRIBUTIONS OF THREE DESCRIPTIVE METHODS: IMPLICATIONS FOR BEHAVIORAL ASSESSMENT

PubMed Central

Pence, Sacha T; Roscoe, Eileen M; Bourret, Jason C; Ahearn, William H

2009-01-01

This study compared the outcomes of three descriptive analysis methods—the ABC method, the conditional probability method, and the conditional and background probability method—to each other and to the results obtained from functional analyses. Six individuals who had been diagnosed with developmental delays and exhibited problem behavior participated. Functional analyses indicated that participants' problem behavior was maintained by social positive reinforcement (n  =  2), social negative reinforcement (n  =  2), or automatic reinforcement (n  =  2). Results showed that for all but 1 participant, descriptive analysis outcomes were similar across methods. In addition, for all but 1 participant, the descriptive analysis outcome differed substantially from the functional analysis outcome. This supports the general finding that descriptive analysis is a poor means of determining functional relations. PMID:19949536

Searching for globally optimal functional forms for interatomic potentials using genetic programming with parallel tempering.

PubMed

Slepoy, A; Peters, M D; Thompson, A P

2007-11-30

Molecular dynamics and other molecular simulation methods rely on a potential energy function, based only on the relative coordinates of the atomic nuclei. Such a function, called a force field, approximately represents the electronic structure interactions of a condensed matter system. Developing such approximate functions and fitting their parameters remains an arduous, time-consuming process, relying on expert physical intuition. To address this problem, a functional programming methodology was developed that may enable automated discovery of entirely new force-field functional forms, while simultaneously fitting parameter values. The method uses a combination of genetic programming, Metropolis Monte Carlo importance sampling and parallel tempering, to efficiently search a large space of candidate functional forms and parameters. The methodology was tested using a nontrivial problem with a well-defined globally optimal solution: a small set of atomic configurations was generated and the energy of each configuration was calculated using the Lennard-Jones pair potential. Starting with a population of random functions, our fully automated, massively parallel implementation of the method reproducibly discovered the original Lennard-Jones pair potential by searching for several hours on 100 processors, sampling only a minuscule portion of the total search space. This result indicates that, with further improvement, the method may be suitable for unsupervised development of more accurate force fields with completely new functional forms. Copyright (c) 2007 Wiley Periodicals, Inc.

Azide functionalized poly(3-hexylthiophene) and method of forming same

DOEpatents

Qin, Yang; Grubbs, Robert B; Park, Young Suk

2014-03-25

The invention relates azide functionalized poly(3-hexylthiophene)s. Various azide functionalized poly(3-hexylthiophene)s and intermediates are disclosed and described, as well as method for making novel monomers that are synthesized and transformed into P3HT-N.sub.mp for use as organic conducting polymers in organic photovoltaic devices.

Computerized Method for the Generation of Molecular Transmittance Functions in the Infrared.

DTIC Science & Technology

1980-04-01

predict this behavior, we conclude that the first method using linear function of x is accurate enough to be used in the actual application. The...PIECEWISE- ANALITICAL TRANSMISSION FUNCTION.’//20X, * ’STANDARD DEVIATIONS BETWEEN THE ACTUAL TAU AND THE RECOMPUTED’, * ’ TAU VALUES ARE COMPUTED.’////) 77

Photoreactive synthetic regulator of protein function and methods of use thereof

DOEpatents

Trauner, Dirk; Isacoff, Ehud Y; Kramer, Richard H; Banghart, Matthew R; Fortin, Doris L; Mourot, Alexandre

2015-03-31

The present disclosure provides a photoreactive synthetic regulator of protein function. The present disclosure further provides a light-regulated polypeptide that includes a subject synthetic regulator. Also provided are cells and membranes comprising a subject light-regulated polypeptide. The present disclosure further provides methods of modulating protein function, involving use of light.

Using Loss Functions for DIF Detection: An Empirical Bayes Approach.

ERIC Educational Resources Information Center

Zwick, Rebecca; Thayer, Dorothy; Lewis, Charles

2000-01-01

Studied a method for flagging differential item functioning (DIF) based on loss functions. Builds on earlier research that led to the development of an empirical Bayes enhancement to the Mantel-Haenszel DIF analysis. Tested the method through simulation and found its performance better than some commonly used DIF classification systems. (SLD)

CRISPR Display: A modular method for locus-specific targeting of long noncoding RNAs and synthetic RNA devices in vivo

PubMed Central

Shechner, David M.; Hacisüleyman, Ezgi; Younger, Scott T.; Rinn, John L.

2016-01-01

Noncoding RNAs (ncRNAs) comprise an important class of regulatory molecules that mediate a vast array of biological processes. This broad functional capacity has also facilitated the design of artificial ncRNAs with novel functions. To further investigate and harness these capabilities, we developed CRISPR-Display (“CRISP-Disp”), a targeted localization method that uses Sp. Cas9 to deploy large RNA cargos to DNA loci. We demonstrate that exogenous RNA domains can be functionally appended onto the CRISPR scaffold at multiple insertion points, allowing the construction of Cas9 complexes with protein-binding cassettes, artificial aptamers, pools of random sequences, and RNAs up to 4.8 kilobases in length, including natural lncRNAs. Unlike most existing CRISPR methods, CRISP-Disp allows simultaneous multiplexing of distinct functions at multiple targets, limited only by the number of available functional RNA motifs. We anticipate that this technology will provide a powerful method with which to ectopically localize functional RNAs and ribonucleoprotein (RNP) complexes at specified genomic loci. PMID:26030444

Computing the Evans function via solving a linear boundary value ODE

NASA Astrophysics Data System (ADS)

Wahl, Colin; Nguyen, Rose; Ventura, Nathaniel; Barker, Blake; Sandstede, Bjorn

2015-11-01

Determining the stability of traveling wave solutions to partial differential equations can oftentimes be computationally intensive but of great importance to understanding the effects of perturbations on the physical systems (chemical reactions, hydrodynamics, etc.) they model. For waves in one spatial dimension, one may linearize around the wave and form an Evans function - an analytic Wronskian-like function which has zeros that correspond in multiplicity to the eigenvalues of the linearized system. If eigenvalues with a positive real part do not exist, the traveling wave will be stable. Two methods exist for calculating the Evans function numerically: the exterior-product method and the method of continuous orthogonalization. The first is numerically expensive, and the second reformulates the originally linear system as a nonlinear system. We develop a new algorithm for computing the Evans function through appropriate linear boundary-value problems. This algorithm is cheaper than the previous methods, and we prove that it preserves analyticity of the Evans function. We also provide error estimates and implement it on some classical one- and two-dimensional systems, one being the Swift-Hohenberg equation in a channel, to show the advantages.

Corrected confidence bands for functional data using principal components.

PubMed

Goldsmith, J; Greven, S; Crainiceanu, C

2013-03-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. Copyright © 2013, The International Biometric Society.

Corrected Confidence Bands for Functional Data Using Principal Components

PubMed Central

Goldsmith, J.; Greven, S.; Crainiceanu, C.

2014-01-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. PMID:23003003

Feasibility of inverse problem solution for determination of city emission function from night sky radiance measurements

NASA Astrophysics Data System (ADS)

Petržala, Jaromír

2018-07-01

The knowledge of the emission function of a city is crucial for simulation of sky glow in its vicinity. The indirect methods to achieve this function from radiances measured over a part of the sky have been recently developed. In principle, such methods represent an ill-posed inverse problem. This paper deals with the theoretical feasibility study of various approaches to solving of given inverse problem. Particularly, it means testing of fitness of various stabilizing functionals within the Tikhonov's regularization. Further, the L-curve and generalized cross validation methods were investigated as indicators of an optimal regularization parameter. At first, we created the theoretical model for calculation of a sky spectral radiance in the form of a functional of an emission spectral radiance. Consequently, all the mentioned approaches were examined in numerical experiments with synthetical data generated for the fictitious city and loaded by random errors. The results demonstrate that the second order Tikhonov's regularization method together with regularization parameter choice by the L-curve maximum curvature criterion provide solutions which are in good agreement with the supposed model emission functions.

Classical density functional theory and the phase-field crystal method using a rational function to describe the two-body direct correlation function.

PubMed

Pisutha-Arnond, N; Chan, V W L; Iyer, M; Gavini, V; Thornton, K

2013-01-01

We introduce a new approach to represent a two-body direct correlation function (DCF) in order to alleviate the computational demand of classical density functional theory (CDFT) and enhance the predictive capability of the phase-field crystal (PFC) method. The approach utilizes a rational function fit (RFF) to approximate the two-body DCF in Fourier space. We use the RFF to show that short-wavelength contributions of the two-body DCF play an important role in determining the thermodynamic properties of materials. We further show that using the RFF to empirically parametrize the two-body DCF allows us to obtain the thermodynamic properties of solids and liquids that agree with the results of CDFT simulations with the full two-body DCF without incurring significant computational costs. In addition, the RFF can also be used to improve the representation of the two-body DCF in the PFC method. Last, the RFF allows for a real-space reformulation of the CDFT and PFC method, which enables descriptions of nonperiodic systems and the use of nonuniform and adaptive grids.

Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz

2017-07-15

This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.

Mutant fatty acid desaturase and methods for directed mutagenesis

DOEpatents

Shanklin, John [Shoreham, NY; Whittle, Edward J [Greenport, NY

2008-01-29

The present invention relates to methods for producing fatty acid desaturase mutants having a substantially increased activity towards substrates with fewer than 18 carbon atom chains relative to an unmutagenized precursor desaturase having an 18 carbon chain length specificity, the sequences encoding the desaturases and to the desaturases that are produced by the methods. The present invention further relates to a method for altering a function of a protein, including a fatty acid desaturase, through directed mutagenesis involving identifying candidate amino acid residues, producing a library of mutants of the protein by simultaneously randomizing all amino acid candidates, and selecting for mutants which exhibit the desired alteration of function. Candidate amino acids are identified by a combination of methods. Enzymatic, binding, structural and other functions of proteins can be altered by the method.

Stripe nonuniformity correction for infrared imaging system based on single image optimization

NASA Astrophysics Data System (ADS)

Hua, Weiping; Zhao, Jufeng; Cui, Guangmang; Gong, Xiaoli; Ge, Peng; Zhang, Jiang; Xu, Zhihai

2018-06-01

Infrared imaging is often disturbed by stripe nonuniformity noise. Scene-based correction method can effectively reduce the impact of stripe noise. In this paper, a stripe nonuniformity correction method based on differential constraint is proposed. Firstly, the gray distribution of stripe nonuniformity is analyzed and the penalty function is constructed by the difference of horizontal gradient and vertical gradient. With the weight function, the penalty function is optimized to obtain the corrected image. Comparing with other single-frame approaches, experiments show that the proposed method performs better in both subjective and objective analysis, and does less damage to edge and detail. Meanwhile, the proposed method runs faster. We have also discussed the differences between the proposed idea and multi-frame methods. Our method is finally well applied in hardware system.

REMOVAL OF CRYPTOSPORIDIUM BY IN-LINE FILTRATION AS A FUNCTION OF OOCYST AGE AND PRESERVATION METHOD

EPA Science Inventory

This study examined the impacts of oocyst preservation method and age on the removal of seeded Cryptosporidium oocysts by in-line filtration. An existing study has investigated the infectivity of Cryptosporidium parvum as a function of preservation method and oocyst age. Simila...

REMOVAL OF CRYPTOSPORIDIUM BY IN-LINE FILTRATION AS A FUNCTION OF OOCYST AGE AND PRESERVATION METHOD

EPA Science Inventory

This study examined the impacts of oocyst preservation method and age on the removal of seeded Cryptosporidium oocysts by in-line filtration. An existing study has investigated the infectivity of Cryptosporidium Parvum as a function of preservation method and oocyst age. Simila...

Methods to assess Drosophila heart development, function and aging

PubMed Central

Ocorr, Karen; Vogler, Georg; Bodmer, Rolf

2014-01-01

In recent years the Drosophila heart has become an established model of many different aspects of human cardiac disease. This model has allowed identification of disease-causing mechanisms underlying congenital heart disease and cardiomyopathies and has permitted the study underlying genetic, metabolic and age-related contributions to heart function. In this review we discuss methods currently employed in the analysis of the Drosophila heart structure and function, such as optical methods to infer heart function and performance, electrophysiological and mechanical approaches to characterize cardiac tissue properties, and conclude with histological techniques used in the study of heart development and adult structure. PMID:24727147

Coherent mode decomposition using mixed Wigner functions of Hermite-Gaussian beams.

PubMed

Tanaka, Takashi

2017-04-15

A new method of coherent mode decomposition (CMD) is proposed that is based on a Wigner-function representation of Hermite-Gaussian beams. In contrast to the well-known method using the cross spectral density (CSD), it directly determines the mode functions and their weights without solving the eigenvalue problem. This facilitates the CMD of partially coherent light whose Wigner functions (and thus CSDs) are not separable, in which case the conventional CMD requires solving an eigenvalue problem with a large matrix and thus is numerically formidable. An example is shown regarding the CMD of synchrotron radiation, one of the most important applications of the proposed method.

A Novel Feature-Tracking Echocardiographic Method for the Quantitation of Regional Myocardial Function

PubMed Central

Pirat, Bahar; Khoury, Dirar S.; Hartley, Craig J.; Tiller, Les; Rao, Liyun; Schulz, Daryl G.; Nagueh, Sherif F.; Zoghbi, William A.

2012-01-01

Objectives The aim of this study was to validate a novel, angle-independent, feature-tracking method for the echocardiographic quantitation of regional function. Background A new echocardiographic method, Velocity Vector Imaging (VVI) (syngo Velocity Vector Imaging technology, Siemens Medical Solutions, Ultrasound Division, Mountain View, California), has been introduced, based on feature tracking—incorporating speckle and endocardial border tracking, that allows the quantitation of endocardial strain, strain rate (SR), and velocity. Methods Seven dogs were studied during baseline, and various interventions causing alterations in regional function: dobutamine, 5-min coronary occlusion with reperfusion up to 1 h, followed by dobutamine and esmolol infusions. Echocardiographic images were acquired from short- and long-axis views of the left ventricle. Segment-length sonomicrometry crystals were used as the reference method. Results Changes in systolic strain in ischemic segments were tracked well with VVI during the different states of regional function. There was a good correlation between circumferential and longitudinal systolic strain by VVI and sonomicrometry (r = 0.88 and r = 0.83, respectively, p < 0.001). Strain measurements in the nonischemic basal segments also demonstrated a significant correlation between the 2 methods (r = 0.65, p < 0.001). Similarly, a significant relation was observed for circumferential and longitudinal SR between the 2 methods (r = 0.94, p < 0.001 and r = 0.90, p < 0.001, respectively). The endocardial velocity relation to changes in strain by sonomicrometry was weaker owing to significant cardiac translation. Conclusions Velocity Vector Imaging, a new feature-tracking method, can accurately assess regional myocardial function at the endocardial level and is a promising clinical tool for the simultaneous quantification of regional and global myocardial function. PMID:18261685

Local Approximation and Hierarchical Methods for Stochastic Optimization

NASA Astrophysics Data System (ADS)

Cheng, Bolong

In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the PJM Interconnect and show that it outperforms the baseline approach used in the industry.

Binder model system to be used for determination of prepolymer functionality

NASA Technical Reports Server (NTRS)

Martinelli, F. J.; Hodgkin, J. H.

1971-01-01

Development of a method for determining the functionality distribution of prepolymers used for rocket binders is discussed. Research has been concerned with accurately determining the gel point of a model polyester system containing a single trifunctional crosslinker, and the application of these methods to more complicated model systems containing a second trifunctional crosslinker, monofunctional ingredients, or a higher functionality crosslinker. Correlations of observed with theoretical gel points for these systems would allow the methods to be applied directly to prepolymers.

Application of Two-Parameter Stabilizing Functions in Solving a Convolution-Type Integral Equation by Regularization Method

NASA Astrophysics Data System (ADS)

Maslakov, M. L.

2018-04-01

This paper examines the solution of convolution-type integral equations of the first kind by applying the Tikhonov regularization method with two-parameter stabilizing functions. The class of stabilizing functions is expanded in order to improve the accuracy of the resulting solution. The features of the problem formulation for identification and adaptive signal correction are described. A method for choosing regularization parameters in problems of identification and adaptive signal correction is suggested.

Application of 3-signal coherence to core noise transmission

NASA Technical Reports Server (NTRS)

Krejsa, E. A.

1983-01-01

A method for determining transfer functions across turbofan engine components and from the engine to the far-field is developed. The method is based on the three-signal coherence technique used previously to obtain far-field core noise levels. This method eliminates the bias error in transfer function measurements due to contamination of measured pressures by nonpropagating pressure fluctuations. Measured transfer functions from the engine to the far-field, across the tailpipe, and across the turbine are presented for three turbofan engines.

Method of making low work function component

DOEpatents

Robinson, Vance [Niskayuna, NY; Weaver, Stanton Earl [Northville, NY; Michael, Joseph Darryl [Delmar, NY

2011-11-15

A method for fabricating a component is disclosed. The method includes: providing a member having an effective work function of an initial value, disposing a sacrificial layer on a surface of the member, disposing a first agent within the member to obtain a predetermined concentration of the agent at said surface of the member, annealing the member, and removing the sacrificial layer to expose said surface of the member, wherein said surface has a post-process effective work function that is different from the initial value.

From Commodity Polymers to Functional Polymers

PubMed Central

Xiang, Tao; Wang, Ling-Ren; Ma, Lang; Han, Zhi-Yuan; Wang, Rui; Cheng, Chong; Xia, Yi; Qin, Hui; Zhao, Chang-Sheng

2014-01-01

Functional polymers bear specified chemical groups, and have specified physical, chemical, biological, pharmacological, or other uses. To adjust the properties while keeping material usage low, a method for direct synthesis of functional polymers is indispensable. Here we show that various functional polymers can be synthesized by in situ cross-linked polymerization/copolymerization. We demonstrate that the polymers synthesized by the facile method using different functional monomers own outstanding pH-sensitivity and pH-reversibility, antifouling property, antibacterial, and anticoagulant property. Our study opens a route for the functionalization of commodity polymers, which lead to important advances in polymeric materials applications. PMID:24710333

An historical survey of computational methods in optimal control.

NASA Technical Reports Server (NTRS)

Polak, E.

1973-01-01

Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.

A MAP-based image interpolation method via Viterbi decoding of Markov chains of interpolation functions.

PubMed

Vedadi, Farhang; Shirani, Shahram

2014-01-01

A new method of image resolution up-conversion (image interpolation) based on maximum a posteriori sequence estimation is proposed. Instead of making a hard decision about the value of each missing pixel, we estimate the missing pixels in groups. At each missing pixel of the high resolution (HR) image, we consider an ensemble of candidate interpolation methods (interpolation functions). The interpolation functions are interpreted as states of a Markov model. In other words, the proposed method undergoes state transitions from one missing pixel position to the next. Accordingly, the interpolation problem is translated to the problem of estimating the optimal sequence of interpolation functions corresponding to the sequence of missing HR pixel positions. We derive a parameter-free probabilistic model for this to-be-estimated sequence of interpolation functions. Then, we solve the estimation problem using a trellis representation and the Viterbi algorithm. Using directional interpolation functions and sequence estimation techniques, we classify the new algorithm as an adaptive directional interpolation using soft-decision estimation techniques. Experimental results show that the proposed algorithm yields images with higher or comparable peak signal-to-noise ratios compared with some benchmark interpolation methods in the literature while being efficient in terms of implementation and complexity considerations.

Overtaking method based on sand-sifter mechanism: Why do optimistic value functions find optimal solutions in multi-armed bandit problems?

PubMed

Ochi, Kento; Kamiura, Moto

2015-09-01

A multi-armed bandit problem is a search problem on which a learning agent must select the optimal arm among multiple slot machines generating random rewards. UCB algorithm is one of the most popular methods to solve multi-armed bandit problems. It achieves logarithmic regret performance by coordinating balance between exploration and exploitation. Since UCB algorithms, researchers have empirically known that optimistic value functions exhibit good performance in multi-armed bandit problems. The terms optimistic or optimism might suggest that the value function is sufficiently larger than the sample mean of rewards. The first definition of UCB algorithm is focused on the optimization of regret, and it is not directly based on the optimism of a value function. We need to think the reason why the optimism derives good performance in multi-armed bandit problems. In the present article, we propose a new method, which is called Overtaking method, to solve multi-armed bandit problems. The value function of the proposed method is defined as an upper bound of a confidence interval with respect to an estimator of expected value of reward: the value function asymptotically approaches to the expected value of reward from the upper bound. If the value function is larger than the expected value under the asymptote, then the learning agent is almost sure to be able to obtain the optimal arm. This structure is called sand-sifter mechanism, which has no regrowth of value function of suboptimal arms. It means that the learning agent can play only the current best arm in each time step. Consequently the proposed method achieves high accuracy rate and low regret and some value functions of it can outperform UCB algorithms. This study suggests the advantage of optimism of agents in uncertain environment by one of the simplest frameworks. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.

PubMed

Harper, Angela F; Leuthaeuser, Janelle B; Babbitt, Patricia C; Morris, John H; Ferrin, Thomas E; Poole, Leslie B; Fetrow, Jacquelyn S

2017-02-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences.

A novel method for identifying disease associated protein complexes based on functional similarity protein complex networks.

PubMed

Le, Duc-Hau

2015-01-01

Protein complexes formed by non-covalent interaction among proteins play important roles in cellular functions. Computational and purification methods have been used to identify many protein complexes and their cellular functions. However, their roles in terms of causing disease have not been well discovered yet. There exist only a few studies for the identification of disease-associated protein complexes. However, they mostly utilize complicated heterogeneous networks which are constructed based on an out-of-date database of phenotype similarity network collected from literature. In addition, they only apply for diseases for which tissue-specific data exist. In this study, we propose a method to identify novel disease-protein complex associations. First, we introduce a framework to construct functional similarity protein complex networks where two protein complexes are functionally connected by either shared protein elements, shared annotating GO terms or based on protein interactions between elements in each protein complex. Second, we propose a simple but effective neighborhood-based algorithm, which yields a local similarity measure, to rank disease candidate protein complexes. Comparing the predictive performance of our proposed algorithm with that of two state-of-the-art network propagation algorithms including one we used in our previous study, we found that it performed statistically significantly better than that of these two algorithms for all the constructed functional similarity protein complex networks. In addition, it ran about 32 times faster than these two algorithms. Moreover, our proposed method always achieved high performance in terms of AUC values irrespective of the ways to construct the functional similarity protein complex networks and the used algorithms. The performance of our method was also higher than that reported in some existing methods which were based on complicated heterogeneous networks. Finally, we also tested our method with prostate cancer and selected the top 100 highly ranked candidate protein complexes. Interestingly, 69 of them were evidenced since at least one of their protein elements are known to be associated with prostate cancer. Our proposed method, including the framework to construct functional similarity protein complex networks and the neighborhood-based algorithm on these networks, could be used for identification of novel disease-protein complex associations.

Functional MRI registration with tissue-specific patch-based functional correlation tensors.

PubMed

Zhou, Yujia; Zhang, Han; Zhang, Lichi; Cao, Xiaohuan; Yang, Ru; Feng, Qianjin; Yap, Pew-Thian; Shen, Dinggang

2018-06-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) rely on accurate intersubject registration of functional areas. This is typically achieved through registration using high-resolution structural images with more spatial details and better tissue contrast. However, accumulating evidence has suggested that such strategy cannot align functional regions well because functional areas are not necessarily consistent with anatomical structures. To alleviate this problem, a number of registration algorithms based directly on rs-fMRI data have been developed, most of which utilize functional connectivity (FC) features for registration. However, most of these methods usually extract functional features only from the thin and highly curved cortical grey matter (GM), posing great challenges to accurate estimation of whole-brain deformation fields. In this article, we demonstrate that additional useful functional features can also be extracted from the whole brain, not restricted to the GM, particularly the white-matter (WM), for improving the overall functional registration. Specifically, we quantify local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals using tissue-specific patch-based functional correlation tensors (ts-PFCTs) in both GM and WM. Functional registration is then performed by integrating the features from different tissues using the multi-channel large deformation diffeomorphic metric mapping (mLDDMM) algorithm. Experimental results show that our method achieves superior functional registration performance, compared with conventional registration methods. © 2018 Wiley Periodicals, Inc.

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

Massively parallel sparse matrix function calculations with NTPoly

NASA Astrophysics Data System (ADS)

Dawson, William; Nakajima, Takahito

2018-04-01

We present NTPoly, a massively parallel library for computing the functions of sparse, symmetric matrices. The theory of matrix functions is a well developed framework with a wide range of applications including differential equations, graph theory, and electronic structure calculations. One particularly important application area is diagonalization free methods in quantum chemistry. When the input and output of the matrix function are sparse, methods based on polynomial expansions can be used to compute matrix functions in linear time. We present a library based on these methods that can compute a variety of matrix functions. Distributed memory parallelization is based on a communication avoiding sparse matrix multiplication algorithm. OpenMP task parallellization is utilized to implement hybrid parallelization. We describe NTPoly's interface and show how it can be integrated with programs written in many different programming languages. We demonstrate the merits of NTPoly by performing large scale calculations on the K computer.

Mechanical analysis of non-uniform bi-directional functionally graded intelligent micro-beams using modified couple stress theory

NASA Astrophysics Data System (ADS)

Bakhshi Khaniki, Hossein; Rajasekaran, Sundaramoorthy

2018-05-01

This study develops a comprehensive investigation on mechanical behavior of non-uniform bi-directional functionally graded beam sensors in the framework of modified couple stress theory. Material variation is modelled through both length and thickness directions using power-law, sigmoid and exponential functions. Moreover, beam is assumed with linear, exponential and parabolic cross-section variation through the length using power-law and sigmoid varying functions. Using these assumptions, a general model for microbeams is presented and formulated by employing Hamilton’s principle. Governing equations are solved using a mixed finite element method with Lagrangian interpolation technique, Gaussian quadrature method and Wilson’s Lagrangian multiplier method. It is shown that by using bi-directional functionally graded materials in nonuniform microbeams, mechanical behavior of such structures could be affected noticeably and scale parameter has a significant effect in changing the rigidity of nonuniform bi-directional functionally graded beams.

Increasing accuracy in the interval analysis by the improved format of interval extension based on the first order Taylor series

NASA Astrophysics Data System (ADS)

Li, Yi; Xu, Yan Long

2018-05-01

When the dependence of the function on uncertain variables is non-monotonic in interval, the interval of function obtained by the classic interval extension based on the first order Taylor series will exhibit significant errors. In order to reduce theses errors, the improved format of the interval extension with the first order Taylor series is developed here considering the monotonicity of function. Two typical mathematic examples are given to illustrate this methodology. The vibration of a beam with lumped masses is studied to demonstrate the usefulness of this method in the practical application, and the necessary input data of which are only the function value at the central point of interval, sensitivity and deviation of function. The results of above examples show that the interval of function from the method developed by this paper is more accurate than the ones obtained by the classic method.

Characterizing Bonding Patterns in Diradicals and Triradicals by Density-Based Wave Function Analysis: A Uniform Approach.

PubMed

Orms, Natalie; Rehn, Dirk R; Dreuw, Andreas; Krylov, Anna I

2018-02-13

Density-based wave function analysis enables unambiguous comparisons of the electronic structure computed by different methods and removes ambiguity of orbital choices. We use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high- and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such as polyradicals. We show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of the bonding pattern.

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Quadrature, Interpolation and Observability

NASA Technical Reports Server (NTRS)

Hodges, Lucille McDaniel

1997-01-01

Methods of interpolation and quadrature have been used for over 300 years. Improvements in the techniques have been made by many, most notably by Gauss, whose technique applied to polynomials is referred to as Gaussian Quadrature. Stieltjes extended Gauss's method to certain non-polynomial functions as early as 1884. Conditions that guarantee the existence of quadrature formulas for certain collections of functions were studied by Tchebycheff, and his work was extended by others. Today, a class of functions which satisfies these conditions is called a Tchebycheff System. This thesis contains the definition of a Tchebycheff System, along with the theorems, proofs, and definitions necessary to guarantee the existence of quadrature formulas for such systems. Solutions of discretely observable linear control systems are of particular interest, and observability with respect to a given output function is defined. The output function is written as a linear combination of a collection of orthonormal functions. Orthonormal functions are defined, and their properties are discussed. The technique for evaluating the coefficients in the output function involves evaluating the definite integral of functions which can be shown to form a Tchebycheff system. Therefore, quadrature formulas for these integrals exist, and in many cases are known. The technique given is useful in cases where the method of direct calculation is unstable. The condition number of a matrix is defined and shown to be an indication of the the degree to which perturbations in data affect the accuracy of the solution. In special cases, the number of data points required for direct calculation is the same as the number required by the method presented in this thesis. But the method is shown to require more data points in other cases. A lower bound for the number of data points required is given.

Whole Brain Functional Connectivity Pattern Homogeneity Mapping.

PubMed

Wang, Lijie; Xu, Jinping; Wang, Chao; Wang, Jiaojian

2018-01-01

Mounting studies have demonstrated that brain functions are determined by its external functional connectivity patterns. However, how to characterize the voxel-wise similarity of whole brain functional connectivity pattern is still largely unknown. In this study, we introduced a new method called functional connectivity homogeneity (FcHo) to delineate the voxel-wise similarity of whole brain functional connectivity patterns. FcHo was defined by measuring the whole brain functional connectivity patterns similarity of a given voxel with its nearest 26 neighbors using Kendall's coefficient concordance (KCC). The robustness of this method was tested in four independent datasets selected from a large repository of MRI. Furthermore, FcHo mapping results were further validated using the nearest 18 and six neighbors and intra-subject reproducibility with each subject scanned two times. We also compared FcHo distribution patterns with local regional homogeneity (ReHo) to identify the similarity and differences of the two methods. Finally, FcHo method was used to identify the differences of whole brain functional connectivity patterns between professional Chinese chess players and novices to test its application. FcHo mapping consistently revealed that the high FcHo was mainly distributed in association cortex including parietal lobe, frontal lobe, occipital lobe and default mode network (DMN) related areas, whereas the low FcHo was mainly found in unimodal cortex including primary visual cortex, sensorimotor cortex, paracentral lobule and supplementary motor area. These results were further supported by analyses of the nearest 18 and six neighbors and intra-subject similarity. Moreover, FcHo showed both similar and different whole brain distribution patterns compared to ReHo. Finally, we demonstrated that FcHo can effectively identify the whole brain functional connectivity pattern differences between professional Chinese chess players and novices. Our findings indicated that FcHo is a reliable method to delineate the whole brain functional connectivity pattern similarity and may provide a new way to study the functional organization and to reveal neuropathological basis for brain disorders.

Band-limited Green's Functions for Quantitative Evaluation of Acoustic Emission Using the Finite Element Method

NASA Technical Reports Server (NTRS)

Leser, William P.; Yuan, Fuh-Gwo; Leser, William P.

2013-01-01

A method of numerically estimating dynamic Green's functions using the finite element method is proposed. These Green's functions are accurate in a limited frequency range dependent on the mesh size used to generate them. This range can often match or exceed the frequency sensitivity of the traditional acoustic emission sensors. An algorithm is also developed to characterize an acoustic emission source by obtaining information about its strength and temporal dependence. This information can then be used to reproduce the source in a finite element model for further analysis. Numerical examples are presented that demonstrate the ability of the band-limited Green's functions approach to determine the moment tensor coefficients of several reference signals to within seven percent, as well as accurately reproduce the source-time function.

A step-by-step guide to non-linear regression analysis of experimental data using a Microsoft Excel spreadsheet.

PubMed

Brown, A M

2001-06-01

The objective of this present study was to introduce a simple, easily understood method for carrying out non-linear regression analysis based on user input functions. While it is relatively straightforward to fit data with simple functions such as linear or logarithmic functions, fitting data with more complicated non-linear functions is more difficult. Commercial specialist programmes are available that will carry out this analysis, but these programmes are expensive and are not intuitive to learn. An alternative method described here is to use the SOLVER function of the ubiquitous spreadsheet programme Microsoft Excel, which employs an iterative least squares fitting routine to produce the optimal goodness of fit between data and function. The intent of this paper is to lead the reader through an easily understood step-by-step guide to implementing this method, which can be applied to any function in the form y=f(x), and is well suited to fast, reliable analysis of data in all fields of biology.

The Boundary Function Method. Fundamentals

NASA Astrophysics Data System (ADS)

Kot, V. A.

2017-03-01

The boundary function method is proposed for solving applied problems of mathematical physics in the region defined by a partial differential equation of the general form involving constant or variable coefficients with a Dirichlet, Neumann, or Robin boundary condition. In this method, the desired function is defined by a power polynomial, and a boundary function represented in the form of the desired function or its derivative at one of the boundary points is introduced. Different sequences of boundary equations have been set up with the use of differential operators. Systems of linear algebraic equations constructed on the basis of these sequences allow one to determine the coefficients of a power polynomial. Constitutive equations have been derived for initial boundary-value problems of all the main types. With these equations, an initial boundary-value problem is transformed into the Cauchy problem for the boundary function. The determination of the boundary function by its derivative with respect to the time coordinate completes the solution of the problem.

Computational Methods to Work as First-Pass Filter in Deleterious SNP Analysis of Alkaptonuria

PubMed Central

Magesh, R.; George Priya Doss, C.

2012-01-01

A major challenge in the analysis of human genetic variation is to distinguish functional from nonfunctional SNPs. Discovering these functional SNPs is one of the main goals of modern genetics and genomics studies. There is a need to effectively and efficiently identify functionally important nsSNPs which may be deleterious or disease causing and to identify their molecular effects. The prediction of phenotype of nsSNPs by computational analysis may provide a good way to explore the function of nsSNPs and its relationship with susceptibility to disease. In this context, we surveyed and compared variation databases along with in silico prediction programs to assess the effects of deleterious functional variants on protein functions. In other respects, we attempted these methods to work as first-pass filter to identify the deleterious substitutions worth pursuing for further experimental research. In this analysis, we used the existing computational methods to explore the mutation-structure-function relationship in HGD gene causing alkaptonuria. PMID:22606059

Comparison of different eigensolvers for calculating vibrational spectra using low-rank, sum-of-product basis functions

NASA Astrophysics Data System (ADS)

Leclerc, Arnaud; Thomas, Phillip S.; Carrington, Tucker

2017-08-01

Vibrational spectra and wavefunctions of polyatomic molecules can be calculated at low memory cost using low-rank sum-of-product (SOP) decompositions to represent basis functions generated using an iterative eigensolver. Using a SOP tensor format does not determine the iterative eigensolver. The choice of the interative eigensolver is limited by the need to restrict the rank of the SOP basis functions at every stage of the calculation. We have adapted, implemented and compared different reduced-rank algorithms based on standard iterative methods (block-Davidson algorithm, Chebyshev iteration) to calculate vibrational energy levels and wavefunctions of the 12-dimensional acetonitrile molecule. The effect of using low-rank SOP basis functions on the different methods is analysed and the numerical results are compared with those obtained with the reduced rank block power method. Relative merits of the different algorithms are presented, showing that the advantage of using a more sophisticated method, although mitigated by the use of reduced-rank SOP functions, is noticeable in terms of CPU time.

A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data.

PubMed

Onojima, Takayuki; Goto, Takahiro; Mizuhara, Hiroaki; Aoyagi, Toshio

2018-01-01

Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results.

Solving the Schroedinger Equation of Atoms and Molecules without Analytical Integration Based on the Free Iterative-Complement-Interaction Wave Function

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

Nakatsuji, H.; Nakashima, H.; Department of Synthetic Chemistry and Biological Chemistry, Graduate School of Engineering, Kyoto University, Nishikyo-ku, Kyoto 615-8510

2007-12-14

A local Schroedinger equation (LSE) method is proposed for solving the Schroedinger equation (SE) of general atoms and molecules without doing analytic integrations over the complement functions of the free ICI (iterative-complement-interaction) wave functions. Since the free ICI wave function is potentially exact, we can assume a flatness of its local energy. The variational principle is not applicable because the analytic integrations over the free ICI complement functions are very difficult for general atoms and molecules. The LSE method is applied to several 2 to 5 electron atoms and molecules, giving an accuracy of 10{sup -5} Hartree in total energy.more » The potential energy curves of H{sub 2} and LiH molecules are calculated precisely with the free ICI LSE method. The results show the high potentiality of the free ICI LSE method for developing accurate predictive quantum chemistry with the solutions of the SE.« less

Multiphase Interface Tracking with Fast Semi-Lagrangian Contouring.

PubMed

Li, Xiaosheng; He, Xiaowei; Liu, Xuehui; Zhang, Jian J; Liu, Baoquan; Wu, Enhua

2016-08-01

We propose a semi-Lagrangian method for multiphase interface tracking. In contrast to previous methods, our method maintains an explicit polygonal mesh, which is reconstructed from an unsigned distance function and an indicator function, to track the interface of arbitrary number of phases. The surface mesh is reconstructed at each step using an efficient multiphase polygonization procedure with precomputed stencils while the distance and indicator function are updated with an accurate semi-Lagrangian path tracing from the meshes of the last step. Furthermore, we provide an adaptive data structure, multiphase distance tree, to accelerate the updating of both the distance function and the indicator function. In addition, the adaptive structure also enables us to contour the distance tree accurately with simple bisection techniques. The major advantage of our method is that it can easily handle topological changes without ambiguities and preserve both the sharp features and the volume well. We will evaluate its efficiency, accuracy and robustness in the results part with several examples.

Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR library

PubMed Central

Zhu, Shiyou; Li, Wei; Liu, Jingze; Chen, Chen-Hao; Liao, Qi; Xu, Ping; Xu, Han; Xiao, Tengfei; Cao, Zhongzheng; Peng, Jingyu; Yuan, Pengfei; Brown, Myles; Liu, Xiaole Shirley; Wei, Wensheng

2017-01-01

CRISPR/Cas9 screens have been widely adopted to analyse coding gene functions, but high throughput screening of non-coding elements using this method is more challenging, because indels caused by a single cut in non-coding regions are unlikely to produce a functional knockout. A high-throughput method to produce deletions of non-coding DNA is needed. Herein, we report a high throughput genomic deletion strategy to screen for functional long non-coding RNAs (lncRNAs) that is based on a lentiviral paired-guide RNA (pgRNA) library. Applying our screening method, we identified 51 lncRNAs that can positively or negatively regulate human cancer cell growth. We individually validated 9 lncRNAs using CRISPR/Cas9-mediated genomic deletion and functional rescue, CRISPR activation or inhibition, and gene expression profiling. Our high-throughput pgRNA genome deletion method should enable rapid identification of functional mammalian non-coding elements. PMID:27798563

Study of the Socratic method during cognitive restructuring.

PubMed

Froján-Parga, María Xesús; Calero-Elvira, Ana; Montaño-Fidalgo, Montserrat

2011-01-01

Cognitive restructuring, in particular in the form of the Socratic method, is widely used by clinicians. However, little research has been published with respect to underlying processes, which has hindered well-accepted explanations of its effectiveness. The aim of this study is to present a new method of analysis of the Socratic method during cognitive restructuring based on the observation of the therapist's verbal behaviour. Using recordings from clinical sessions, 18 sequences were selected in which the Socratic method was applied by six cognitive-behavioural therapists working at a private clinical centre in Madrid. The recordings involved eight patients requiring therapy for various psychological problems. Observations were coded using a category system designed by the authors and that classifies the therapist's verbal behaviour into seven hypothesized functions based on basic behavioural operations. We used the Observer XT software to code the observed sequences. The results are summarized through a preliminary model which considers three different phases of the Socratic method and some functions of the therapist's verbal behaviour in each of these phases: discriminative and reinforcement functions in the starting phase, informative and motivational functions in the course of the debate, and instructional and reinforcement functions in the final phase. We discuss the long-term potential clinical benefits of the current proposal.  Copyright © 2010 John Wiley & Sons, Ltd.

Fitting a function to time-dependent ensemble averaged data.

PubMed

Fogelmark, Karl; Lomholt, Michael A; Irbäck, Anders; Ambjörnsson, Tobias

2018-05-03

Time-dependent ensemble averages, i.e., trajectory-based averages of some observable, are of importance in many fields of science. A crucial objective when interpreting such data is to fit these averages (for instance, squared displacements) with a function and extract parameters (such as diffusion constants). A commonly overlooked challenge in such function fitting procedures is that fluctuations around mean values, by construction, exhibit temporal correlations. We show that the only available general purpose function fitting methods, correlated chi-square method and the weighted least squares method (which neglects correlation), fail at either robust parameter estimation or accurate error estimation. We remedy this by deriving a new closed-form error estimation formula for weighted least square fitting. The new formula uses the full covariance matrix, i.e., rigorously includes temporal correlations, but is free of the robustness issues, inherent to the correlated chi-square method. We demonstrate its accuracy in four examples of importance in many fields: Brownian motion, damped harmonic oscillation, fractional Brownian motion and continuous time random walks. We also successfully apply our method, weighted least squares including correlation in error estimation (WLS-ICE), to particle tracking data. The WLS-ICE method is applicable to arbitrary fit functions, and we provide a publically available WLS-ICE software.

Application of the principal fractional meta-trigonometric functions for the solution of linear commensurate-order time-invariant fractional differential equations.

PubMed

Lorenzo, C F; Hartley, T T; Malti, R

2013-05-13

A new and simplified method for the solution of linear constant coefficient fractional differential equations of any commensurate order is presented. The solutions are based on the R-function and on specialized Laplace transform pairs derived from the principal fractional meta-trigonometric functions. The new method simplifies the solution of such fractional differential equations and presents the solutions in the form of real functions as opposed to fractional complex exponential functions, and thus is directly applicable to real-world physics.

Probabilistic Density Function Method for Stochastic ODEs of Power Systems with Uncertain Power Input

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

Wang, Peng; Barajas-Solano, David A.; Constantinescu, Emil

Wind and solar power generators are commonly described by a system of stochastic ordinary differential equations (SODEs) where random input parameters represent uncertainty in wind and solar energy. The existing methods for SODEs are mostly limited to delta-correlated random parameters (white noise). Here we use the Probability Density Function (PDF) method for deriving a closed-form deterministic partial differential equation (PDE) for the joint probability density function of the SODEs describing a power generator with time-correlated power input. The resulting PDE is solved numerically. A good agreement with Monte Carlo Simulations shows accuracy of the PDF method.

Simulations of Coulomb systems confined by polarizable surfaces using periodic Green functions.

PubMed

Dos Santos, Alexandre P; Girotto, Matheus; Levin, Yan

2017-11-14

We present an efficient approach for simulating Coulomb systems confined by planar polarizable surfaces. The method is based on the solution of the Poisson equation using periodic Green functions. It is shown that the electrostatic energy arising from the surface polarization can be decoupled from the energy due to the direct Coulomb interaction between the ions. This allows us to combine an efficient Ewald summation method, or any other fast method for summing over the replicas, with the polarization contribution calculated using Green function techniques. We apply the method to calculate density profiles of ions confined between the charged dielectric and metal surfaces.

A Novel Polygonal Finite Element Method: Virtual Node Method

NASA Astrophysics Data System (ADS)

Tang, X. H.; Zheng, C.; Zhang, J. H.

2010-05-01

Polygonal finite element method (PFEM), which can construct shape functions on polygonal elements, provides greater flexibility in mesh generation. However, the non-polynomial form of traditional PFEM, such as Wachspress method and Mean Value method, leads to inexact numerical integration. Since the integration technique for non-polynomial functions is immature. To overcome this shortcoming, a great number of integration points have to be used to obtain sufficiently exact results, which increases computational cost. In this paper, a novel polygonal finite element method is proposed and called as virtual node method (VNM). The features of present method can be list as: (1) It is a PFEM with polynomial form. Thereby, Hammer integral and Gauss integral can be naturally used to obtain exact numerical integration; (2) Shape functions of VNM satisfy all the requirements of finite element method. To test the performance of VNM, intensive numerical tests are carried out. It found that, in standard patch test, VNM can achieve significantly better results than Wachspress method and Mean Value method. Moreover, it is observed that VNM can achieve better results than triangular 3-node elements in the accuracy test.

A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

NASA Astrophysics Data System (ADS)

Feng, Shou; Fu, Ping; Zheng, Wenbin

2018-03-01

Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

Improved dynamical scaling analysis using the kernel method for nonequilibrium relaxation.

PubMed

Echinaka, Yuki; Ozeki, Yukiyasu

2016-10-01

The dynamical scaling analysis for the Kosterlitz-Thouless transition in the nonequilibrium relaxation method is improved by the use of Bayesian statistics and the kernel method. This allows data to be fitted to a scaling function without using any parametric model function, which makes the results more reliable and reproducible and enables automatic and faster parameter estimation. Applying this method, the bootstrap method is introduced and a numerical discrimination for the transition type is proposed.

Life prediction for high temperature low cycle fatigue of two kinds of titanium alloys based on exponential function

NASA Astrophysics Data System (ADS)

Mu, G. Y.; Mi, X. Z.; Wang, F.

2018-01-01

The high temperature low cycle fatigue tests of TC4 titanium alloy and TC11 titanium alloy are carried out under strain controlled. The relationships between cyclic stress-life and strain-life are analyzed. The high temperature low cycle fatigue life prediction model of two kinds of titanium alloys is established by using Manson-Coffin method. The relationship between failure inverse number and plastic strain range presents nonlinear in the double logarithmic coordinates. Manson-Coffin method assumes that they have linear relation. Therefore, there is bound to be a certain prediction error by using the Manson-Coffin method. In order to solve this problem, a new method based on exponential function is proposed. The results show that the fatigue life of the two kinds of titanium alloys can be predicted accurately and effectively by using these two methods. Prediction accuracy is within ±1.83 times scatter zone. The life prediction capability of new methods based on exponential function proves more effective and accurate than Manson-Coffin method for two kinds of titanium alloys. The new method based on exponential function can give better fatigue life prediction results with the smaller standard deviation and scatter zone than Manson-Coffin method. The life prediction results of two methods for TC4 titanium alloy prove better than TC11 titanium alloy.

Family Functioning in Families with a Child with Down Syndrome: A Mixed Methods Approach

ERIC Educational Resources Information Center

Povee, K.; Roberts, L.; Bourke, J.; Leonard, H.

2012-01-01

Background: This study aimed to explore the factors that predict functioning in families with a child with Down syndrome using a mixed methods design. The quantitative component examined the effect of maladaptive and autism-spectrum behaviours on the functioning of the family while the qualitative component explored the impact of having a child…

Assessment of Murine Retinal Function by Electroretinography

PubMed Central

Benchorin, Gillie; Calton, Melissa A.; Beaulieu, Marielle O.; Vollrath, Douglas

2017-01-01

The electroretinogram (ERG) is a sensitive and noninvasive method for testing retinal function. In this protocol, we describe a method for performing ERGs in mice. Contact lenses on the mouse cornea measure the electrical response to a light stimulus of photoreceptors and downstream retinal cells, and the collected data are analyzed to evaluate retinal function. PMID:29177186

Series Expansion of Functions with He's Homotopy Perturbation Method

ERIC Educational Resources Information Center

Khattri, Sanjay Kumar

2012-01-01

Finding a series expansion, such as Taylor series, of functions is an important mathematical concept with many applications. Homotopy perturbation method (HPM) is a new, easy to use and effective tool for solving a variety of mathematical problems. In this study, we present how to apply HPM to obtain a series expansion of functions. Consequently,…

Collaborative Modelling of the Vascular System--Designing and Evaluating a New Learning Method for Secondary Students

ERIC Educational Resources Information Center

Haugwitz, Marion; Sandmann, Angela

2010-01-01

Understanding biological structures and functions is often difficult because of their complexity and micro-structure. For example, the vascular system is a complex and only partly visible system. Constructing models to better understand biological functions is seen as a suitable learning method. Models function as simplified versions of real…

Functional porous composites by blending with solution-processable molecular pores.

PubMed

Jiang, S; Chen, L; Briggs, M E; Hasell, T; Cooper, A I

2016-05-25

We present a simple method for rendering non-porous materials porous by solution co-processing with organic cage molecules. This method can be used both for small functional molecules and for polymers, thus creating porous composites by molecular blending, rather than the more traditional approach of supporting functional molecules on pre-frabricated porous supports.

New Results on the Linear Equating Methods for the Non-Equivalent-Groups Design

ERIC Educational Resources Information Center

von Davier, Alina A.

2008-01-01

The two most common observed-score equating functions are the linear and equipercentile functions. These are often seen as different methods, but von Davier, Holland, and Thayer showed that any equipercentile equating function can be decomposed into linear and nonlinear parts. They emphasized the dominant role of the linear part of the nonlinear…

Methods and Models for the Construction of Weakly Parallel Tests. Research Report 90-4.

ERIC Educational Resources Information Center

Adema, Jos J.

Methods are proposed for the construction of weakly parallel tests, that is, tests with the same test information function. A mathematical programing model for constructing tests with a prespecified test information function and a heuristic for assigning items to tests such that their information functions are equal play an important role in the…

20 CFR 200.2 - The general course and method by which the Board's functions are channeled and determined.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false The general course and method by which the Board's functions are channeled and determined. 200.2 Section 200.2 Employees' Benefits RAILROAD... the Board's functions are channeled and determined. (a) Retirement and death benefits. (1) Retirement...

Systems and methods for producing low work function electrodes

DOEpatents

Kippelen, Bernard; Fuentes-Hernandez, Canek; Zhou, Yinhua; Kahn, Antoine; Meyer, Jens; Shim, Jae Won; Marder, Seth R.

2015-07-07

According to an exemplary embodiment of the invention, systems and methods are provided for producing low work function electrodes. According to an exemplary embodiment, a method is provided for reducing a work function of an electrode. The method includes applying, to at least a portion of the electrode, a solution comprising a Lewis basic oligomer or polymer; and based at least in part on applying the solution, forming an ultra-thin layer on a surface of the electrode, wherein the ultra-thin layer reduces the work function associated with the electrode by greater than 0.5 eV. According to another exemplary embodiment of the invention, a device is provided. The device includes a semiconductor; at least one electrode disposed adjacent to the semiconductor and configured to transport electrons in or out of the semiconductor.

Coupling functions: Universal insights into dynamical interaction mechanisms

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav; Pereira, Tiago; McClintock, Peter V. E.; Stefanovska, Aneta

2017-10-01

The dynamical systems found in nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how an interaction occurs. A coherent and comprehensive review is presented encompassing the rapid progress made recently in the analysis, understanding, and applications of coupling functions. The basic concepts and characteristics of coupling functions are presented through demonstrative examples of different domains, revealing the mechanisms and emphasizing their multivariate nature. The theory of coupling functions is discussed through gradually increasing complexity from strong and weak interactions to globally coupled systems and networks. A variety of methods that have been developed for the detection and reconstruction of coupling functions from measured data is described. These methods are based on different statistical techniques for dynamical inference. Stemming from physics, such methods are being applied in diverse areas of science and technology, including chemistry, biology, physiology, neuroscience, social sciences, mechanics, and secure communications. This breadth of application illustrates the universality of coupling functions for studying the interaction mechanisms of coupled dynamical systems.

A Survey of Functional Behavior Assessment Methods Used by Behavior Analysts in Practice

ERIC Educational Resources Information Center

Oliver, Anthony C.; Pratt, Leigh A.; Normand, Matthew P.

2015-01-01

To gather information about the functional behavior assessment (FBA) methods behavior analysts use in practice, we sent a web-based survey to 12,431 behavior analysts certified by the Behavior Analyst Certification Board. Ultimately, 724 surveys were returned, with the results suggesting that most respondents regularly use FBA methods, especially…

The Effects of Consequence Manipulation during Functional Analysis of Problem Behavior Maintained by Negative Reinforcement

ERIC Educational Resources Information Center

Potoczak, Kathryn; Carr, James E.; Michael, Jack

2007-01-01

Two distinct analytic methods have been used to identify the function of problem behavior. The antecedent-behavior-consequence (ABC) method (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) includes the delivery of consequences for problem behavior. The AB method (Carr & Durand, 1985) does not include consequence delivery, instead relying…

Assessing Paraprofessionals' Perceived Educational Needs and Skill Level with Function-Based Behavioral Intervention

ERIC Educational Resources Information Center

Walker, Virginia L.

2017-01-01

The purpose of this survey study was to assess the perceived skill level and educational needs of special education paraprofessionals in the area of function-based intervention and to identify paraprofessionals' preferred training delivery method(s) and any variables that affect paraprofessionals' preference for these methods. Special education…

Sometimes "Newton's Method" Always "Cycles"

ERIC Educational Resources Information Center

Latulippe, Joe; Switkes, Jennifer

2012-01-01

Are there functions for which Newton's method cycles for all non-trivial initial guesses? We construct and solve a differential equation whose solution is a real-valued function that two-cycles under Newton iteration. Higher-order cycles of Newton's method iterates are explored in the complex plane using complex powers of "x." We find a class of…

Spot auto-focusing and spot auto-stigmation methods with high-definition auto-correlation function in high-resolution TEM.

PubMed

Isakozawa, Shigeto; Fuse, Taishi; Amano, Junpei; Baba, Norio

2018-04-01

As alternatives to the diffractogram-based method in high-resolution transmission electron microscopy, a spot auto-focusing (AF) method and a spot auto-stigmation (AS) method are presented with a unique high-definition auto-correlation function (HD-ACF). The HD-ACF clearly resolves the ACF central peak region in small amorphous-thin-film images, reflecting the phase contrast transfer function. At a 300-k magnification for a 120-kV transmission electron microscope, the smallest areas used are 64 × 64 pixels (~3 nm2) for the AF and 256 × 256 pixels for the AS. A useful advantage of these methods is that the AF function has an allowable accuracy even for a low s/n (~1.0) image. A reference database on the defocus dependency of the HD-ACF by the pre-acquisition of through-focus amorphous-thin-film images must be prepared to use these methods. This can be very beneficial because the specimens are not limited to approximations of weak phase objects but can be extended to objects outside such approximations.

Probe measurements of the electron velocity distribution function in beams: Low-voltage beam discharge in helium

NASA Astrophysics Data System (ADS)

Sukhomlinov, V.; Mustafaev, A.; Timofeev, N.

2018-04-01

Previously developed methods based on the single-sided probe technique are altered and applied to measure the anisotropic angular spread and narrow energy distribution functions of charged particle (electron and ion) beams. The conventional method is not suitable for some configurations, such as low-voltage beam discharges, electron beams accelerated in near-wall and near-electrode layers, and vacuum electron beam sources. To determine the range of applicability of the proposed method, simple algebraic relationships between the charged particle energies and their angular distribution are obtained. The method is verified for the case of the collisionless mode of a low-voltage He beam discharge, where the traditional method for finding the electron distribution function with the help of a Legendre polynomial expansion is not applicable. This leads to the development of a physical model of the formation of the electron distribution function in a collisionless low-voltage He beam discharge. The results of a numerical calculation based on Monte Carlo simulations are in good agreement with the experimental data obtained using the new method.

An efficient and flexible Abel-inversion method for noisy data

NASA Astrophysics Data System (ADS)

Antokhin, Igor I.

2016-12-01

We propose an efficient and flexible method for solving the Abel integral equation of the first kind, frequently appearing in many fields of astrophysics, physics, chemistry, and applied sciences. This equation represents an ill-posed problem, thus solving it requires some kind of regularization. Our method is based on solving the equation on a so-called compact set of functions and/or using Tikhonov's regularization. A priori constraints on the unknown function, defining a compact set, are very loose and can be set using simple physical considerations. Tikhonov's regularization in itself does not require any explicit a priori constraints on the unknown function and can be used independently of such constraints or in combination with them. Various target degrees of smoothness of the unknown function may be set, as required by the problem at hand. The advantage of the method, apart from its flexibility, is that it gives uniform convergence of the approximate solution to the exact solution, as the errors of input data tend to zero. The method is illustrated on several simulated models with known solutions. An example of astrophysical application of the method is also given.

A Lagrange multiplier and Hopfield-type barrier function method for the traveling salesman problem.

PubMed

Dang, Chuangyin; Xu, Lei

2002-02-01

A Lagrange multiplier and Hopfield-type barrier function method is proposed for approximating a solution of the traveling salesman problem. The method is derived from applications of Lagrange multipliers and a Hopfield-type barrier function and attempts to produce a solution of high quality by generating a minimum point of a barrier problem for a sequence of descending values of the barrier parameter. For any given value of the barrier parameter, the method searches for a minimum point of the barrier problem in a feasible descent direction, which has a desired property that lower and upper bounds on variables are always satisfied automatically if the step length is a number between zero and one. At each iteration, the feasible descent direction is found by updating Lagrange multipliers with a globally convergent iterative procedure. For any given value of the barrier parameter, the method converges to a stationary point of the barrier problem without any condition on the objective function. Theoretical and numerical results show that the method seems more effective and efficient than the softassign algorithm.

Optimization of removal function in computer controlled optical surfacing

NASA Astrophysics Data System (ADS)

Chen, Xi; Guo, Peiji; Ren, Jianfeng

2010-10-01

The technical principle of computer controlled optical surfacing (CCOS) and the common method of optimizing removal function that is used in CCOS are introduced in this paper. A new optimizing method time-sharing synthesis of removal function is proposed to solve problems of the removal function being far away from Gaussian type and slow approaching of the removal function error that encountered in the mode of planet motion or translation-rotation. Detailed time-sharing synthesis of using six removal functions is discussed. For a given region on the workpiece, six positions are selected as the centers of the removal function; polishing tool controlled by the executive system of CCOS revolves around each centre to complete a cycle in proper order. The overall removal function obtained by the time-sharing process is the ratio of total material removal in six cycles to time duration of the six cycles, which depends on the arrangement and distribution of the six removal functions. Simulations on the synthesized overall removal functions under two different modes of motion, i.e., planet motion and translation-rotation are performed from which the optimized combination of tool parameters and distribution of time-sharing synthesis removal functions are obtained. The evaluation function when optimizing is determined by an approaching factor which is defined as the ratio of the material removal within the area of half of the polishing tool coverage from the polishing center to the total material removal within the full polishing tool coverage area. After optimization, it is found that the optimized removal function obtained by time-sharing synthesis is closer to the ideal Gaussian type removal function than those by the traditional methods. The time-sharing synthesis method of the removal function provides an efficient way to increase the convergence speed of the surface error in CCOS for the fabrication of aspheric optical surfaces, and to reduce the intermediate- and high-frequency error.

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.

The assessment of function. Part II: clinical perspective of a javelin thrower with low back and groin pain

PubMed Central

Reiman, Michael P; Manske, Robert C

2012-01-01

Assessment of an individual’s functional ability can be complex. This assessment should also be individualized and adaptable to changes in functional status. In the first article of this series, we operationally defined function, discussed the construct of function, examined the evidence as it relates to assessment methods of various aspects of function, and explored the multi-dimensional nature of the concept of function. In this case report, we aim to demonstrate the utilization of a multi-dimensional assessment method (functional performance testing) as it relates to a high-level athlete presenting with pain in the low back and groin. It is our intent to demonstrate how the clinician should continually adapt their assessment dependent on the current functional abilities of the patients. PMID:23633887

A Dynamic Time Warping based covariance function for Gaussian Processes signature identification

NASA Astrophysics Data System (ADS)

Silversides, Katherine L.; Melkumyan, Arman

2016-11-01

Modelling stratiform deposits requires a detailed knowledge of the stratigraphic boundaries. In Banded Iron Formation (BIF) hosted ores of the Hamersley Group in Western Australia these boundaries are often identified using marker shales. Both Gaussian Processes (GP) and Dynamic Time Warping (DTW) have been previously proposed as methods to automatically identify marker shales in natural gamma logs. However, each method has different advantages and disadvantages. We propose a DTW based covariance function for the GP that combines the flexibility of the DTW with the probabilistic framework of the GP. The three methods are tested and compared on their ability to identify two natural gamma signatures from a Marra Mamba type iron ore deposit. These tests show that while all three methods can identify boundaries, the GP with the DTW covariance function combines and balances the strengths and weaknesses of the individual methods. This method identifies more positive signatures than the GP with the standard covariance function, and has a higher accuracy for identified signatures than the DTW. The combined method can handle larger variations in the signature without requiring multiple libraries, has a probabilistic output and does not require manual cut-off selections.

A New High-Order Spectral Difference Method for Simulating Viscous Flows on Unstructured Grids with Mixed Elements

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

Li, Mao; Qiu, Zihua; Liang, Chunlei

In the present study, a new spectral difference (SD) method is developed for viscous flows on meshes with a mixture of triangular and quadrilateral elements. The standard SD method for triangular elements, which employs Lagrangian interpolating functions for fluxes, is not stable when the designed accuracy of spatial discretization is third-order or higher. Unlike the standard SD method, the method examined here uses vector interpolating functions in the Raviart-Thomas (RT) spaces to construct continuous flux functions on reference elements. Studies have been performed for 2D wave equation and Euler equa- tions. Our present results demonstrated that the SDRT method ismore » stable and high-order accurate for a number of test problems by using triangular-, quadrilateral-, and mixed- element meshes.« less

Analysis of corner cracks at hole by a 3-D weight function method with stresses from finite element method

NASA Technical Reports Server (NTRS)

Zhao, W.; Newman, J. C., Jr.; Sutton, M. A.; Wu, X. R.; Shivakumar, K. N.

1995-01-01

Stress intensity factors for quarter-elliptical corner cracks emanating from a circular hole are determined using a 3-D weight function method combined with a 3-D finite element method. The 3-D finite element method is used to analyze uncracked configuration and provide stress distribution in the region where crack is to occur. Using this stress distribution as input, the 3-D weight function method is used to determine stress intensity factors. Three different loading conditions, i.e. remote tension, remote bending and wedge loading, are considered for a wide range in geometrical parameters. The significance in using 3-D uncracked stress distribution and the difference between single and double corner cracks are studied. Typical crack opening displacements are also provided. Comparisons are made with solutions available in the literature.

Complex Correlation Kohn-T Method of Calculating Total and Elastic Cross Sections. Part 1; Electron-Hydrogen Elastic Scattering

NASA Technical Reports Server (NTRS)

Bhatia, A. K.; Temkin, A.; Fisher, Richard R. (Technical Monitor)

2001-01-01

We report on the first part of a study of electron-hydrogen scattering, using a method which allows for the ab initio calculation of total and elastic cross sections at higher energies. In its general form the method uses complex 'radial' correlation functions, in a (Kohn) T-matrix formalism. The titled method, abbreviated Complex Correlation Kohn T (CCKT) method, is reviewed, in the context of electron-hydrogen scattering, including the derivation of the equation for the (complex) scattering function, and the extraction of the scattering information from the latter. The calculation reported here is restricted to S-waves in the elastic region, where the correlation functions can be taken, without loss of generality, to be real. Phase shifts are calculated using Hylleraas-type correlation functions with up to 95 terms. Results are rigorous lower bounds; they are in general agreement with those of Schwartz, but they are more accurate and outside his error bounds at a couple of energies,

Designing scalable product families by the radial basis function-high-dimensional model representation metamodelling technique

NASA Astrophysics Data System (ADS)

Pirmoradi, Zhila; Haji Hajikolaei, Kambiz; Wang, G. Gary

2015-10-01

Product family design is cost-efficient for achieving the best trade-off between commonalization and diversification. However, for computationally intensive design functions which are viewed as black boxes, the family design would be challenging. A two-stage platform configuration method with generalized commonality is proposed for a scale-based family with unknown platform configuration. Unconventional sensitivity analysis and information on variation in the individual variants' optimal design are used for platform configuration design. Metamodelling is employed to provide the sensitivity and variable correlation information, leading to significant savings in function calls. A family of universal electric motors is designed for product performance and the efficiency of this method is studied. The impact of the employed parameters is also analysed. Then, the proposed method is modified for obtaining higher commonality. The proposed method is shown to yield design solutions with better objective function values, allowable performance loss and higher commonality than the previously developed methods in the literature.

Computing wave functions in multichannel collisions with non-local potentials using the R-matrix method

NASA Astrophysics Data System (ADS)

Bonitati, Joey; Slimmer, Ben; Li, Weichuan; Potel, Gregory; Nunes, Filomena

2017-09-01

The calculable form of the R-matrix method has been previously shown to be a useful tool in approximately solving the Schrodinger equation in nuclear scattering problems. We use this technique combined with the Gauss quadrature for the Lagrange-mesh method to efficiently solve for the wave functions of projectile nuclei in low energy collisions (1-100 MeV) involving an arbitrary number of channels. We include the local Woods-Saxon potential, the non-local potential of Perey and Buck, a Coulomb potential, and a coupling potential to computationally solve for the wave function of two nuclei at short distances. Object oriented programming is used to increase modularity, and parallel programming techniques are introduced to reduce computation time. We conclude that the R-matrix method is an effective method to predict the wave functions of nuclei in scattering problems involving both multiple channels and non-local potentials. Michigan State University iCER ACRES REU.

Residues with similar hexagon neighborhoods share similar side-chain conformations.

PubMed

Li, Shuai Cheng; Bu, Dongbo; Li, Ming

2012-01-01

We present in this study a new approach to code protein side-chain conformations into hexagon substructures. Classical side-chain packing methods consist of two steps: first, side-chain conformations, known as rotamers, are extracted from known protein structures as candidates for each residue; second, a searching method along with an energy function is used to resolve conflicts among residues and to optimize the combinations of side chain conformations for all residues. These methods benefit from the fact that the number of possible side-chain conformations is limited, and the rotamer candidates are readily extracted; however, these methods also suffer from the inaccuracy of energy functions. Inspired by threading and Ab Initio approaches to protein structure prediction, we propose to use hexagon substructures to implicitly capture subtle issues of energy functions. Our initial results indicate that even without guidance from an energy function, hexagon structures alone can capture side-chain conformations at an accuracy of 83.8 percent, higher than 82.6 percent by the state-of-art side-chain packing methods.

Density-functional expansion methods: Grand challenges.

PubMed

Giese, Timothy J; York, Darrin M

2012-03-01

We discuss the source of errors in semiempirical density functional expansion (VE) methods. In particular, we show that VE methods are capable of well-reproducing their standard Kohn-Sham density functional method counterparts, but suffer from large errors upon using one or more of these approximations: the limited size of the atomic orbital basis, the Slater monopole auxiliary basis description of the response density, and the one- and two-body treatment of the core-Hamiltonian matrix elements. In the process of discussing these approximations and highlighting their symptoms, we introduce a new model that supplements the second-order density-functional tight-binding model with a self-consistent charge-dependent chemical potential equalization correction; we review our recently reported method for generalizing the auxiliary basis description of the atomic orbital response density; and we decompose the first-order potential into a summation of additive atomic components and many-body corrections, and from this examination, we provide new insights and preliminary results that motivate and inspire new approximate treatments of the core-Hamiltonian.