On the Maxwellian distribution, symmetric form, and entropy conservation for the Euler equations

NASA Technical Reports Server (NTRS)

Deshpande, S. M.

1986-01-01

The Euler equations of gas dynamics have some very interesting properties in that the flux vector is a homogeneous function of the unknowns and the equations can be cast in symmetric hyperbolic form and satisfy the entropy conservation. The Euler equations are the moments of the Boltzmann equation of the kinetic theory of gases when the velocity distribution function is a Maxwellian. The present paper shows the relationship between the symmetrizability and the Maxwellian velocity distribution. The entropy conservation is in terms of the H-function, which is a slight modification of the H-function first introduced by Boltzmann in his famous H-theorem. In view of the H-theorem, it is suggested that the development of total H-diminishing (THD) numerical methods may be more profitable than the usual total variation diminishing (TVD) methods for obtaining wiggle-free solutions.

Protein domains of unknown function are essential in bacteria.

PubMed

Goodacre, Norman F; Gerloff, Dietlind L; Uetz, Peter

2013-12-31

More than 20% of all protein domains are currently annotated as "domains of unknown function" (DUFs). About 2,700 DUFs are found in bacteria compared with just over 1,500 in eukaryotes. Over 800 DUFs are shared between bacteria and eukaryotes, and about 300 of these are also present in archaea. A total of 2,786 bacterial Pfam domains even occur in animals, including 320 DUFs. Evolutionary conservation suggests that many of these DUFs are important. Here we show that 355 essential proteins in 16 model bacterial species contain 238 DUFs, most of which represent single-domain proteins, clearly establishing the biological essentiality of DUFs. We suggest that experimental research should focus on conserved and essential DUFs (eDUFs) for functional analysis given their important function and wide taxonomic distribution, including bacterial pathogens. The functional units of proteins are domains. Typically, each domain has a distinct structure and function. Genomes encode thousands of domains, and many of the domains have no known function (domains of unknown function [DUFs]). They are often ignored as of little relevance, given that many of them are found in only a few genomes. Here we show that many DUFs are essential DUFs (eDUFs) based on their presence in essential proteins. We also show that eDUFs are often essential even if they are found in relatively few genomes. However, in general, more common DUFs are more often essential than rare DUFs.

Point Pairing Method Based on the Principle of Material Frame Indifference for the Characterization of Unknown Space Objects using Non-Resolved Photometry Data

DTIC Science & Technology

2013-09-01

provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB...the satellite. The material constitutive laws of interest are the bidirectional reflectance distribution functions ( BRDF ) for diffuse and specular...solar panel can be related to each other using the BRDF definition. This creates a set of three independent equations and three unknowns, which can be

Identification of cloud fields by the nonparametric algorithm of pattern recognition from normalized video data recorded with the AVHRR instrument

NASA Astrophysics Data System (ADS)

Protasov, Konstantin T.; Pushkareva, Tatyana Y.; Artamonov, Evgeny S.

2002-02-01

The problem of cloud field recognition from the NOAA satellite data is urgent for solving not only meteorological problems but also for resource-ecological monitoring of the Earth's underlying surface associated with the detection of thunderstorm clouds, estimation of the liquid water content of clouds and the moisture of the soil, the degree of fire hazard, etc. To solve these problems, we used the AVHRR/NOAA video data that regularly displayed the situation in the territory. The complexity and extremely nonstationary character of problems to be solved call for the use of information of all spectral channels, mathematical apparatus of testing statistical hypotheses, and methods of pattern recognition and identification of the informative parameters. For a class of detection and pattern recognition problems, the average risk functional is a natural criterion for the quality and the information content of the synthesized decision rules. In this case, to solve efficiently the problem of identifying cloud field types, the informative parameters must be determined by minimization of this functional. Since the conditional probability density functions, representing mathematical models of stochastic patterns, are unknown, the problem of nonparametric reconstruction of distributions from the leaning samples arises. To this end, we used nonparametric estimates of distributions with the modified Epanechnikov kernel. The unknown parameters of these distributions were determined by minimization of the risk functional, which for the learning sample was substituted by the empirical risk. After the conditional probability density functions had been reconstructed for the examined hypotheses, a cloudiness type was identified using the Bayes decision rule.

Exact solutions for the selection-mutation equilibrium in the Crow-Kimura evolutionary model.

PubMed

Semenov, Yuri S; Novozhilov, Artem S

2015-08-01

We reformulate the eigenvalue problem for the selection-mutation equilibrium distribution in the case of a haploid asexually reproduced population in the form of an equation for an unknown probability generating function of this distribution. The special form of this equation in the infinite sequence limit allows us to obtain analytically the steady state distributions for a number of particular cases of the fitness landscape. The general approach is illustrated by examples; theoretical findings are compared with numerical calculations. Copyright © 2015. Published by Elsevier Inc.

Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics.

PubMed

Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam

2017-07-01

In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Application of quasi-distributions for solving inverse problems of neutron and {gamma}-ray transport

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

Pogosbekyan, L.R.; Lysov, D.A.

The considered inverse problems deal with the calculation of the unknown values of nuclear installations by means of the known (goal) functionals of neutron/{gamma}-ray distributions. The example of these problems might be the calculation of the automatic control rods position as function of neutron sensors reading, or the calculation of experimentally-corrected values of cross-sections, isotopes concentration, fuel enrichment via the measured functional. The authors have developed the new method to solve inverse problem. It finds flux density as quasi-solution of the particles conservation linear system adjointed to equalities for functionals. The method is more effective compared to the one basedmore » on the classical perturbation theory. It is suitable for vectorization and it can be used successfully in optimization codes.« less

Bayesian hierarchical functional data analysis via contaminated informative priors.

PubMed

Scarpa, Bruno; Dunson, David B

2009-09-01

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

ATTITUDE FILTERING ON SO(3)

NASA Technical Reports Server (NTRS)

Markley, F. Landis

2005-01-01

A new method is presented for the simultaneous estimation of the attitude of a spacecraft and an N-vector of bias parameters. This method uses a probability distribution function defined on the Cartesian product of SO(3), the group of rotation matrices, and the Euclidean space W N .The Fokker-Planck equation propagates the probability distribution function between measurements, and Bayes s formula incorporates measurement update information. This approach avoids all the issues of singular attitude representations or singular covariance matrices encountered in extended Kalman filters. In addition, the filter has a consistent initialization for a completely unknown initial attitude, owing to the fact that SO(3) is a compact space.

Eddington's demon: inferring galaxy mass functions and other distributions from uncertain data

NASA Astrophysics Data System (ADS)

Obreschkow, D.; Murray, S. G.; Robotham, A. S. G.; Westmeier, T.

2018-03-01

We present a general modified maximum likelihood (MML) method for inferring generative distribution functions from uncertain and biased data. The MML estimator is identical to, but easier and many orders of magnitude faster to compute than the solution of the exact Bayesian hierarchical modelling of all measurement errors. As a key application, this method can accurately recover the mass function (MF) of galaxies, while simultaneously dealing with observational uncertainties (Eddington bias), complex selection functions and unknown cosmic large-scale structure. The MML method is free of binning and natively accounts for small number statistics and non-detections. Its fast implementation in the R-package dftools is equally applicable to other objects, such as haloes, groups, and clusters, as well as observables other than mass. The formalism readily extends to multidimensional distribution functions, e.g. a Choloniewski function for the galaxy mass-angular momentum distribution, also handled by dftools. The code provides uncertainties and covariances for the fitted model parameters and approximate Bayesian evidences. We use numerous mock surveys to illustrate and test the MML method, as well as to emphasize the necessity of accounting for observational uncertainties in MFs of modern galaxy surveys.

Genome-wide survey of DNA-binding proteins in Arabidopsis thaliana: analysis of distribution and functions.

PubMed

Malhotra, Sony; Sowdhamini, Ramanathan

2013-08-01

The interaction of proteins with their respective DNA targets is known to control many high-fidelity cellular processes. Performing a comprehensive survey of the sequenced genomes for DNA-binding proteins (DBPs) will help in understanding their distribution and the associated functions in a particular genome. Availability of fully sequenced genome of Arabidopsis thaliana enables the review of distribution of DBPs in this model plant genome. We used profiles of both structure and sequence-based DNA-binding families, derived from PDB and PFam databases, to perform the survey. This resulted in 4471 proteins, identified as DNA-binding in Arabidopsis genome, which are distributed across 300 different PFam families. Apart from several plant-specific DNA-binding families, certain RING fingers and leucine zippers also had high representation. Our search protocol helped to assign DNA-binding property to several proteins that were previously marked as unknown, putative or hypothetical in function. The distribution of Arabidopsis genes having a role in plant DNA repair were particularly studied and noted for their functional mapping. The functions observed to be overrepresented in the plant genome harbour DNA-3-methyladenine glycosylase activity, alkylbase DNA N-glycosylase activity and DNA-(apurinic or apyrimidinic site) lyase activity, suggesting their role in specialized functions such as gene regulation and DNA repair.

On estimating the phase of periodic waveform in additive Gaussian noise, part 2

NASA Astrophysics Data System (ADS)

Rauch, L. L.

1984-11-01

Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.

On Estimating the Phase of Periodic Waveform in Additive Gaussian Noise, Part 2

NASA Technical Reports Server (NTRS)

Rauch, L. L.

1984-01-01

Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.

Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

PubMed

Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua

2016-11-14

In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.

[Clinical electro-ophthalmology at the Max Planck Institute of the Frankfurt University Ophthalmology Clinic 1970-1991].

PubMed

Lorenz, R; Baier, M; Eckl, G; Raile, A

1996-07-01

The survey shows the frequency and distribution of diseases evaluated by electroophthalmological methods. Patients with retinal diseases (51.2%) and those with diseases of the optic nerve (21.8%) were examined most frequently. In a high percentage these investigations lead to a clinically useful assessment: described as confirmation or exclusion of a clinical diagnosis, as establishing a possible differential diagnosis or clearing up formerly unknown aspects of a disease. In cases of hereditary retinal disorders only 11% remained unclear, with presumed optic neuritis only 6%. The importance of electroophthalmological investigations is there ability to assess functional deficits in the visual system especially in somehow more rare retinal and centrally located disorders, functional deficits of unknown origins or in general diseases including the visual system.

Distributed Adaptive Fuzzy Control for Nonlinear Multiagent Systems Via Sliding Mode Observers.

PubMed

Shen, Qikun; Shi, Peng; Shi, Yan

2016-12-01

In this paper, the problem of distributed adaptive fuzzy control is investigated for high-order uncertain nonlinear multiagent systems on directed graph with a fixed topology. It is assumed that only the outputs of each follower and its neighbors are available in the design of its distributed controllers. Equivalent output injection sliding mode observers are proposed for each follower to estimate the states of itself and its neighbors, and an observer-based distributed adaptive controller is designed for each follower to guarantee that it asymptotically synchronizes to a leader with tracking errors being semi-globally uniform ultimate bounded, in which fuzzy logic systems are utilized to approximate unknown functions. Based on algebraic graph theory and Lyapunov function approach, using Filippov-framework, the closed-loop system stability analysis is conducted. Finally, numerical simulations are provided to illustrate the effectiveness and potential of the developed design techniques.

Qualitative fusion technique based on information poor system and its application to factor analysis for vibration of rolling bearings

NASA Astrophysics Data System (ADS)

Xia, Xintao; Wang, Zhongyu

2008-10-01

For some methods of stability analysis of a system using statistics, it is difficult to resolve the problems of unknown probability distribution and small sample. Therefore, a novel method is proposed in this paper to resolve these problems. This method is independent of probability distribution, and is useful for small sample systems. After rearrangement of the original data series, the order difference and two polynomial membership functions are introduced to estimate the true value, the lower bound and the supper bound of the system using fuzzy-set theory. Then empirical distribution function is investigated to ensure confidence level above 95%, and the degree of similarity is presented to evaluate stability of the system. Cases of computer simulation investigate stable systems with various probability distribution, unstable systems with linear systematic errors and periodic systematic errors and some mixed systems. The method of analysis for systematic stability is approved.

Green's function of radial inhomogeneous spheres excited by internal sources.

PubMed

Zouros, Grigorios P; Kokkorakis, Gerassimos C

2011-01-01

Green's function in the interior of penetrable bodies with inhomogeneous compressibility by sources placed inside them is evaluated through a Schwinger-Lippmann volume integral equation. In the case of a radial inhomogeneous sphere, the radial part of the unknown Green's function can be expanded in a double Dini's series, which allows analytical evaluation of the involved cumbersome integrals. The simple case treated here can be extended to more difficult situations involving inhomogeneous density as well as to the corresponding electromagnetic or elastic problem. Finally, numerical results are given for various inhomogeneous compressibility distributions.

Measurement of distributions of temperature and wavelength-dependent emissivity of a laminar diffusion flame using hyper-spectral imaging technique

NASA Astrophysics Data System (ADS)

Liu, Huawei; Zheng, Shu; Zhou, Huaichun; Qi, Chaobo

2016-02-01

A generalized method to estimate a two-dimensional (2D) distribution of temperature and wavelength-dependent emissivity in a sooty flame with spectroscopic radiation intensities is proposed in this paper. The method adopts a Newton-type iterative method to solve the unknown coefficients in the polynomial relationship between the emissivity and the wavelength, as well as the unknown temperature. Polynomial functions with increasing order are examined, and final results are determined as the result converges. Numerical simulation on a fictitious flame with wavelength-dependent absorption coefficients shows a good performance with relative errors less than 0.5% in the average temperature. What’s more, a hyper-spectral imaging device is introduced to measure an ethylene/air laminar diffusion flame with the proposed method. The proper order for the polynomial function is selected to be 2, because every one order increase in the polynomial function will only bring in a temperature variation smaller than 20 K. For the ethylene laminar diffusion flame with 194 ml min-1 C2H4 and 284 L min-1 air studied in this paper, the 2D distribution of average temperature estimated along the line of sight is similar to, but smoother than that of the local temperature given in references, and the 2D distribution of emissivity shows a cumulative effect of the absorption coefficient along the line of sight. It also shows that emissivity of the flame decreases as the wavelength increases. The emissivity under wavelength 400 nm is about 2.5 times as much as that under wavelength 1000 nm for a typical line-of-sight in the flame, with the same trend for the absorption coefficient of soot varied with the wavelength.

Steady/unsteady aerodynamic analysis of wings at subsonic, sonic and supersonic Mach numbers using a 3D panel method

NASA Astrophysics Data System (ADS)

Cho, Jeonghyun; Han, Cheolheui; Cho, Leesang; Cho, Jinsoo

2003-08-01

This paper treats the kernel function of an integral equation that relates a known or prescribed upwash distribution to an unknown lift distribution for a finite wing. The pressure kernel functions of the singular integral equation are summarized for all speed range in the Laplace transform domain. The sonic kernel function has been reduced to a form, which can be conveniently evaluated as a finite limit from both the subsonic and supersonic sides when the Mach number tends to one. Several examples are solved including rectangular wings, swept wings, a supersonic transport wing and a harmonically oscillating wing. Present results are given with other numerical data, showing continuous results through the unit Mach number. Computed results are in good agreement with other numerical results.

Consistent description of kinetic equation with triangle anomaly

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

Pu Shi; Gao Jianhua; Wang Qun

2011-05-01

We provide a consistent description of the kinetic equation with a triangle anomaly which is compatible with the entropy principle of the second law of thermodynamics and the charge/energy-momentum conservation equations. In general an anomalous source term is necessary to ensure that the equations for the charge and energy-momentum conservation are satisfied and that the correction terms of distribution functions are compatible to these equations. The constraining equations from the entropy principle are derived for the anomaly-induced leading order corrections to the particle distribution functions. The correction terms can be determined for the minimum number of unknown coefficients in onemore » charge and two charge cases by solving the constraining equations.« less

Detecting fission from special nuclear material sources

DOEpatents

Rowland, Mark S [Alamo, CA; Snyderman, Neal J [Berkeley, CA

2012-06-05

A neutron detector system for discriminating fissile material from non-fissile material wherein a digital data acquisition unit collects data at high rate, and in real-time processes large volumes of data directly into information that a first responder can use to discriminate materials. The system comprises counting neutrons from the unknown source and detecting excess grouped neutrons to identify fission in the unknown source. The system includes a graphing component that displays the plot of the neutron distribution from the unknown source over a Poisson distribution and a plot of neutrons due to background or environmental sources. The system further includes a known neutron source placed in proximity to the unknown source to actively interrogate the unknown source in order to accentuate differences in neutron emission from the unknown source from Poisson distributions and/or environmental sources.

Reconstruction of phonon relaxation times from systems featuring interfaces with unknown properties

NASA Astrophysics Data System (ADS)

Forghani, Mojtaba; Hadjiconstantinou, Nicolas G.

2018-05-01

We present a method for reconstructing the phonon relaxation-time function τω=τ (ω ) (including polarization) and associated phonon free-path distribution from thermal spectroscopy data for systems featuring interfaces with unknown properties. Our method does not rely on the effective thermal-conductivity approximation or a particular physical model of the interface behavior. The reconstruction is formulated as an optimization problem in which the relaxation times are determined as functions of frequency by minimizing the discrepancy between the experimentally measured temperature profiles and solutions of the Boltzmann transport equation for the same system. Interface properties such as transmissivities are included as unknowns in the optimization; however, because for the thermal spectroscopy problems considered here the reconstruction is not very sensitive to the interface properties, the transmissivities are only approximately reconstructed and can be considered as byproducts of the calculation whose primary objective is the accurate determination of the relaxation times. The proposed method is validated using synthetic experimental data obtained from Monte Carlo solutions of the Boltzmann transport equation. The method is shown to remain robust in the presence of uncertainty (noise) in the measurement.

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Stochastic Inversion of 2D Magnetotelluric Data

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

Chen, Jinsong

2010-07-01

The algorithm is developed to invert 2D magnetotelluric (MT) data based on sharp boundary parametrization using a Bayesian framework. Within the algorithm, we consider the locations and the resistivity of regions formed by the interfaces are as unknowns. We use a parallel, adaptive finite-element algorithm to forward simulate frequency-domain MT responses of 2D conductivity structure. Those unknown parameters are spatially correlated and are described by a geostatistical model. The joint posterior probability distribution function is explored by Markov Chain Monte Carlo (MCMC) sampling methods. The developed stochastic model is effective for estimating the interface locations and resistivity. Most importantly, itmore » provides details uncertainty information on each unknown parameter. Hardware requirements: PC, Supercomputer, Multi-platform, Workstation; Software requirements C and Fortan; Operation Systems/version is Linux/Unix or Windows« less

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

PubMed

Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

2017-05-24

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

Distributed Decision Making in a Dynamic Network Environment

DTIC Science & Technology

1990-01-01

protocols, particularly when traffic arrival statistics are varying or unknown, and loads are high. Both nonpreemptive and preemptive repeat disciplines are...The simulation model allows general value functions, continuous time operation, and preemptive or nonpreemptive service. For reasons of tractability... nonpreemptive LIFO, (4) nonpreemptive LIFO with discarding, (5) nonpreemptive HOL, (6) nonpreemp- tive HOL with discarding, (7) preemptive repeat HOL, (8

Optical Characterization of Deep-Space Object Rotation States

DTIC Science & Technology

2014-09-01

surface bi-directional reflectance distribution function ( BRDF ), and then estimate the asteroid’s shape via a best-fit parameterized model . This hybrid...approach can be used because asteroid BRDFs are relatively well studied, but their shapes are generally unknown [17]. Asteroid shape models range...can be accomplished using a shape-dependent method that employs a model of the shape and reflectance characteristics of the object. Our analysis

A fast approach to designing airfoils from given pressure distribution in compressible flows

NASA Technical Reports Server (NTRS)

Daripa, Prabir

1987-01-01

A new inverse method for aerodynamic design of airfols is presented for subcritical flows. The pressure distribution in this method can be prescribed as a function of the arc length of the as-yet unknown body. This inverse problem is shown to be mathematically equivalent to solving only one nonlinear boundary value problem subject to known Dirichlet data on the boundary. The solution to this problem determines the airfoil, the freestream Mach number, and the upstream flow direction. The existence of a solution to a given pressure distribution is discussed. The method is easy to implement and extremely efficient. A series of results for which comparisons are made with the known airfoils is presented.

Statistical properties of two sine waves in Gaussian noise.

NASA Technical Reports Server (NTRS)

Esposito, R.; Wilson, L. R.

1973-01-01

A detailed study is presented of some statistical properties of a stochastic process that consists of the sum of two sine waves of unknown relative phase and a normal process. Since none of the statistics investigated seem to yield a closed-form expression, all the derivations are cast in a form that is particularly suitable for machine computation. Specifically, results are presented for the probability density function (pdf) of the envelope and the instantaneous value, the moments of these distributions, and the relative cumulative density function (cdf).

On the issues of probability distribution of GPS carrier phase observations

NASA Astrophysics Data System (ADS)

Luo, X.; Mayer, M.; Heck, B.

2009-04-01

In common practice the observables related to Global Positioning System (GPS) are assumed to follow a Gauss-Laplace normal distribution. Actually, full knowledge of the observables' distribution is not required for parameter estimation by means of the least-squares algorithm based on the functional relation between observations and unknown parameters as well as the associated variance-covariance matrix. However, the probability distribution of GPS observations plays a key role in procedures for quality control (e.g. outlier and cycle slips detection, ambiguity resolution) and in reliability-related assessments of the estimation results. Under non-ideal observation conditions with respect to the factors impacting GPS data quality, for example multipath effects and atmospheric delays, the validity of the normal distribution postulate of GPS observations is in doubt. This paper presents a detailed analysis of the distribution properties of GPS carrier phase observations using double difference residuals. For this purpose 1-Hz observation data from the permanent SAPOS

Intensive Versus Distributed Aphasia Therapy: A Nonrandomized, Parallel-Group, Dosage-Controlled Study.

PubMed

Dignam, Jade; Copland, David; McKinnon, Eril; Burfein, Penni; O'Brien, Kate; Farrell, Anna; Rodriguez, Amy D

2015-08-01

Most studies comparing different levels of aphasia treatment intensity have not controlled the dosage of therapy provided. Consequently, the true effect of treatment intensity in aphasia rehabilitation remains unknown. Aphasia Language Impairment and Functioning Therapy is an intensive, comprehensive aphasia program. We investigated the efficacy of a dosage-controlled trial of Aphasia Language Impairment and Functioning Therapy, when delivered in an intensive versus distributed therapy schedule, on communication outcomes in participants with chronic aphasia. Thirty-four adults with chronic, poststroke aphasia were recruited to participate in an intensive (n=16; 16 hours per week; 3 weeks) versus distributed (n=18; 6 hours per week; 8 weeks) therapy program. Treatment included 48 hours of impairment, functional, computer, and group-based aphasia therapy. Distributed therapy resulted in significantly greater improvements on the Boston Naming Test when compared with intensive therapy immediately post therapy (P=0.04) and at 1-month follow-up (P=0.002). We found comparable gains on measures of participants' communicative effectiveness, communication confidence, and communication-related quality of life for the intensive and distributed treatment conditions at post-therapy and 1-month follow-up. Aphasia Language Impairment and Functioning Therapy resulted in superior clinical outcomes on measures of language impairment when delivered in a distributed versus intensive schedule. The therapy progam had a positive effect on participants' functional communication and communication-related quality of life, regardless of treatment intensity. These findings contribute to our understanding of the effect of treatment intensity in aphasia rehabilitation and have important clinical implications for service delivery models. © 2015 American Heart Association, Inc.

Determination of the temperature distribution in a minichannel using ANSYS CFX and a procedure based on the Trefftz functions

NASA Astrophysics Data System (ADS)

Maciejewska, Beata; Błasiak, Sławomir; Piasecka, Magdalena

This work discusses the mathematical model for laminar-flow heat transfer in a minichannel. The boundary conditions in the form of temperature distributions on the outer sides of the channel walls were determined from experimental data. The data were collected from the experimental stand the essential part of which is a vertical minichannel 1.7 mm deep, 16 mm wide and 180 mm long, asymmetrically heated by a Haynes-230 alloy plate. Infrared thermography allowed determining temperature changes on the outer side of the minichannel walls. The problem was analysed numerically through either ANSYS CFX software or special calculation procedures based on the Finite Element Method and Trefftz functions in the thermal boundary layer. The Trefftz functions were used to construct the basis functions. Solutions to the governing differential equations were approximated with a linear combination of Trefftz-type basis functions. Unknown coefficients of the linear combination were calculated by minimising the functional. The results of the comparative analysis were represented in a graphical form and discussed.

Elevated red blood cell distribution width is associated with liver function tests in patients with primary hepatocellular carcinoma.

PubMed

Wei, Ting-Ting; Tang, Qing-Qin; Qin, Bao-Dong; Ma, Ning; Wang, Li-Li; Zhou, Lin; Zhong, Ren-Qian

2016-11-25

Red blood cell distribution width (RDW), a routinely tested parameter of the complete blood count (CBC), has been reported to be increased in various cancers and correlated with the patients' clinical characteristics. However, the significance of RDW in primary hepatocellular carcinoma (pHCC) is largely unknown. The aim of this study was to evaluate the associations between RDW and the clinical characteristics of pHCC patients. Medical records of 110 treatment-naive pHCC patients were retrospectively reviewed. Their clinical characteristics on admission, including RDW, liver function tests and tumor stage, were extracted, and their relationships were analyzed using Spearman correlation and Kruskal-Wallis test. Sixty-eight healthy individuals were set as controls. RDW was significantly increased in pHCC patients and correlated with the liver function tests. However, no correlation between RDW and tumor stage was found. RDW may be used to assess the liver function, but not the tumor stage in pHCC patients.

Drell-Yan production at small q T , transverse parton distributions and the collinear anomaly

NASA Astrophysics Data System (ADS)

Becher, Thomas; Neubert, Matthias

2011-06-01

Using methods from effective field theory, an exact all-order expression for the Drell-Yan cross section at small transverse momentum is derived directly in q T space, in which all large logarithms are resummed. The anomalous dimensions and matching coefficients necessary for resummation at NNLL order are given explicitly. The precise relation between our result and the Collins-Soper-Sterman formula is discussed, and as a by-product the previously unknown three-loop coefficient A (3) is obtained. The naive factorization of the cross section at small transverse momentum is broken by a collinear anomaly, which prevents a process-independent definition of x T -dependent parton distribution functions. A factorization theorem is derived for the product of two such functions, in which the dependence on the hard momentum transfer is separated out. The remainder factors into a product of two functions of longitudinal momentum variables and xT2, whose renormalization-group evolution is derived and solved in closed form. The matching of these functions at small x T onto standard parton distributions is calculated at O(αs), while their anomalous dimensions are known to three loops.

Toll-6 and Toll-7 function as neurotrophin receptors in the Drosophila melanogaster CNS.

PubMed

McIlroy, Graham; Foldi, Istvan; Aurikko, Jukka; Wentzell, Jill S; Lim, Mei Ann; Fenton, Janine C; Gay, Nicholas J; Hidalgo, Alicia

2013-09-01

Neurotrophin receptors corresponding to vertebrate Trk, p75(NTR) or Sortilin have not been identified in Drosophila, thus it is unknown how neurotrophism may be implemented in insects. Two Drosophila neurotrophins, DNT1 and DNT2, have nervous system functions, but their receptors are unknown. The Toll receptor superfamily has ancient evolutionary origins and a universal function in innate immunity. Here we show that Toll paralogs unrelated to the mammalian neurotrophin receptors function as neurotrophin receptors in fruit flies. Toll-6 and Toll-7 are expressed in the CNS throughout development and regulate locomotion, motor axon targeting and neuronal survival. DNT1 (also known as NT1 and spz2) and DNT2 (also known as NT2 and spz5) interact genetically with Toll-6 and Toll-7, and DNT1 and DNT2 bind to Toll-6 and Toll-7 promiscuously and are distributed in vivo in domains complementary to or overlapping with those of Toll-6 and Toll-7. We conclude that in fruit flies, Tolls are not only involved in development and immunity but also in neurotrophism, revealing an unforeseen relationship between the neurotrophin and Toll protein families.

Application of stochastic particle swarm optimization algorithm to determine the graded refractive index distribution in participating media

NASA Astrophysics Data System (ADS)

Wei, Lin-Yang; Qi, Hong; Ren, Ya-Tao; Ruan, Li-Ming

2016-11-01

Inverse estimation of the refractive index distribution in one-dimensional participating media with graded refractive index (GRI) is investigated. The forward radiative transfer problem is solved by the Chebyshev collocation spectral method. The stochastic particle swarm optimization (SPSO) algorithm is employed to retrieve three kinds of GRI distribution, i.e. the linear, sinusoidal and quadratic GRI distribution. The retrieval accuracy of GRI distribution with different wall emissivity, optical thickness, absorption coefficients and scattering coefficients are discussed thoroughly. To improve the retrieval accuracy of quadratic GRI distribution, a double-layer model is proposed to supply more measurement information. The influence of measurement errors upon the precision of estimated results is also investigated. Considering the GRI distribution is unknown beforehand in practice, a quadratic function is employed to retrieve the linear GRI by SPSO algorithm. All the results show that the SPSO algorithm is applicable to retrieve different GRI distributions in participating media accurately even with noisy data.

Microlens Masses from Astrometry and Parallax in Space-based Surveys: From Planets to Black Holes

NASA Astrophysics Data System (ADS)

Gould, Andrew; Yee, Jennifer C.

2014-03-01

We show that space-based microlensing experiments can recover lens masses and distances for a large fraction of all events (those with individual photometric errors <~ 0.01 mag) using a combination of one-dimensional microlens parallaxes and astrometric microlensing. This will provide a powerful probe of the mass distributions of planets, black holes, and neutron stars, the distribution of planets as a function of Galactic environment, and the velocity distributions of black holes and neutron stars. While systematics are in principle a significant concern, we show that it is possible to vet against all systematics (known and unknown) using single-epoch precursor observations with the Hubble Space Telescope roughly 10 years before the space mission.

Absolute nuclear material assay using count distribution (LAMBDA) space

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

Prasad, Mano K.; Snyderman, Neal J.; Rowland, Mark S.

A method of absolute nuclear material assay of an unknown source comprising counting neutrons from the unknown source and providing an absolute nuclear material assay utilizing a model to optimally compare to the measured count distributions. In one embodiment, the step of providing an absolute nuclear material assay comprises utilizing a random sampling of analytically computed fission chain distributions to generate a continuous time-evolving sequence of event-counts by spreading the fission chain distribution in time.

Absolute nuclear material assay using count distribution (LAMBDA) space

DOEpatents

Prasad, Manoj K [Pleasanton, CA; Snyderman, Neal J [Berkeley, CA; Rowland, Mark S [Alamo, CA

2012-06-05

A method of absolute nuclear material assay of an unknown source comprising counting neutrons from the unknown source and providing an absolute nuclear material assay utilizing a model to optimally compare to the measured count distributions. In one embodiment, the step of providing an absolute nuclear material assay comprises utilizing a random sampling of analytically computed fission chain distributions to generate a continuous time-evolving sequence of event-counts by spreading the fission chain distribution in time.

Age distribution patterns of human gene families: divergent for Gene Ontology categories and concordant between different subcellular localizations.

PubMed

Liu, Gangbiao; Zou, Yangyun; Cheng, Qiqun; Zeng, Yanwu; Gu, Xun; Su, Zhixi

2014-04-01

The age distribution of gene duplication events within the human genome exhibits two waves of duplications along with an ancient component. However, because of functional constraint differences, genes in different functional categories might show dissimilar retention patterns after duplication. It is known that genes in some functional categories are highly duplicated in the early stage of vertebrate evolution. However, the correlations of the age distribution pattern of gene duplication between the different functional categories are still unknown. To investigate this issue, we developed a robust pipeline to date the gene duplication events in the human genome. We successfully estimated about three-quarters of the duplication events within the human genome, along with the age distribution pattern in each Gene Ontology (GO) slim category. We found that some GO slim categories show different distribution patterns when compared to the whole genome. Further hierarchical clustering of the GO slim functional categories enabled grouping into two main clusters. We found that human genes located in the duplicated copy number variant regions, whose duplicate genes have not been fixed in the human population, were mainly enriched in the groups with a high proportion of recently duplicated genes. Moreover, we used a phylogenetic tree-based method to date the age of duplications in three signaling-related gene superfamilies: transcription factors, protein kinases and G-protein coupled receptors. These superfamilies were expressed in different subcellular localizations. They showed a similar age distribution as the signaling-related GO slim categories. We also compared the differences between the age distributions of gene duplications in multiple subcellular localizations. We found that the distribution patterns of the major subcellular localizations were similar to that of the whole genome. This study revealed the whole picture of the evolution patterns of gene functional categories in the human genome.

Mutational Analysis of Rab3 Function for Controlling Active Zone Protein Composition at the Drosophila Neuromuscular Junction

PubMed Central

Roche, John P.; Alsharif, Peter; Graf, Ethan R.

2015-01-01

At synapses, the release of neurotransmitter is regulated by molecular machinery that aggregates at specialized presynaptic release sites termed active zones. The complement of active zone proteins at each site is a determinant of release efficacy and can be remodeled to alter synapse function. The small GTPase Rab3 was previously identified as playing a novel role that controls the distribution of active zone proteins to individual release sites at the Drosophila neuromuscular junction. Rab3 has been extensively studied for its role in the synaptic vesicle cycle; however, the mechanism by which Rab3 controls active zone development remains unknown. To explore this mechanism, we conducted a mutational analysis to determine the molecular and structural requirements of Rab3 function at Drosophila synapses. We find that GTP-binding is required for Rab3 to traffick to synapses and distribute active zone components across release sites. Conversely, the hydrolytic activity of Rab3 is unnecessary for this function. Through a structure-function analysis we identify specific residues within the effector-binding switch regions that are required for Rab3 function and determine that membrane attachment is essential. Our findings suggest that Rab3 controls the distribution of active zone components via a vesicle docking mechanism that is consistent with standard Rab protein function. PMID:26317909

Phosphoinositide function in cytokinesis.

PubMed

Brill, Julie A; Wong, Raymond; Wilde, Andrew

2011-11-22

In systems as diverse as yeast, slime mold and animal cells, the levels and distribution of phosphatidylinositol phosphates (PIPs) must be strictly regulated for successful cell cleavage. The precise mechanism by which PIPs function in this process remains unknown. Recent experiments are beginning to shed light on the cellular pathways in which PIPs make key contributions during cytokinesis. In particular, PIPs promote proper actin cytoskeletal organization and direct membrane trafficking in dividing cells. Future research will uncover temporal and spatial regulation of the different PIPs, thus elucidating their role in cytoskeletal and membrane events that drive cell cleavage. Copyright © 2011 Elsevier Ltd. All rights reserved.

Model risk for European-style stock index options.

PubMed

Gençay, Ramazan; Gibson, Rajna

2007-01-01

In empirical modeling, there have been two strands for pricing in the options literature, namely the parametric and nonparametric models. Often, the support for the nonparametric methods is based on a benchmark such as the Black-Scholes (BS) model with constant volatility. In this paper, we study the stochastic volatility (SV) and stochastic volatility random jump (SVJ) models as parametric benchmarks against feedforward neural network (FNN) models, a class of neural network models. Our choice for FNN models is due to their well-studied universal approximation properties of an unknown function and its partial derivatives. Since the partial derivatives of an option pricing formula are risk pricing tools, an accurate estimation of the unknown option pricing function is essential for pricing and hedging. Our findings indicate that FNN models offer themselves as robust option pricing tools, over their sophisticated parametric counterparts in predictive settings. There are two routes to explain the superiority of FNN models over the parametric models in forecast settings. These are nonnormality of return distributions and adaptive learning.

A new modelling and identification scheme for time-delay systems with experimental investigation: a relay feedback approach

NASA Astrophysics Data System (ADS)

Pandey, Saurabh; Majhi, Somanath; Ghorai, Prasenjit

2017-07-01

In this paper, the conventional relay feedback test has been modified for modelling and identification of a class of real-time dynamical systems in terms of linear transfer function models with time-delay. An ideal relay and unknown systems are connected through a negative feedback loop to bring the sustained oscillatory output around the non-zero setpoint. Thereafter, the obtained limit cycle information is substituted in the derived mathematical equations for accurate identification of unknown plants in terms of overdamped, underdamped, critically damped second-order plus dead time and stable first-order plus dead time transfer function models. Typical examples from the literature are included for the validation of the proposed identification scheme through computer simulations. Subsequently, the comparisons between estimated model and true system are drawn through integral absolute error criterion and frequency response plots. Finally, the obtained output responses through simulations are verified experimentally on real-time liquid level control system using Yokogawa Distributed Control System CENTUM CS3000 set up.

A Proton-Cyclotron Wave Storm Generated by Unstable Proton Distribution Functions in the Solar Wind

NASA Technical Reports Server (NTRS)

Wicks, R. T.; Alexander, R. L.; Stevens, M.; Wilson, L. B., III; Moya, P. S.; Vinas, A.; Jian, L. K.; Roberts, D. A.; O’Modhrain, S.; Gilbert, J. A.;

Estimation of the diagnostic threshold accounting for decision costs and sampling uncertainty.

PubMed

Skaltsa, Konstantina; Jover, Lluís; Carrasco, Josep Lluís

2010-10-01

Medical diagnostic tests are used to classify subjects as non-diseased or diseased. The classification rule usually consists of classifying subjects using the values of a continuous marker that is dichotomised by means of a threshold. Here, the optimum threshold estimate is found by minimising a cost function that accounts for both decision costs and sampling uncertainty. The cost function is optimised either analytically in a normal distribution setting or empirically in a free-distribution setting when the underlying probability distributions of diseased and non-diseased subjects are unknown. Inference of the threshold estimates is based on approximate analytically standard errors and bootstrap-based approaches. The performance of the proposed methodology is assessed by means of a simulation study, and the sample size required for a given confidence interval precision and sample size ratio is also calculated. Finally, a case example based on previously published data concerning the diagnosis of Alzheimer's patients is provided in order to illustrate the procedure.

Inference of relativistic electron spectra from measurements of inverse Compton radiation

NASA Astrophysics Data System (ADS)

Craig, I. J. D.; Brown, J. C.

1980-07-01

The inference of relativistic electron spectra from spectral measurement of inverse Compton radiation is discussed for the case where the background photon spectrum is a Planck function. The problem is formulated in terms of an integral transform that relates the measured spectrum to the unknown electron distribution. A general inversion formula is used to provide a quantitative assessment of the information content of the spectral data. It is shown that the observations must generally be augmented by additional information if anything other than a rudimentary two or three parameter model of the source function is to be derived. It is also pointed out that since a similar equation governs the continuum spectra emitted by a distribution of black-body radiators, the analysis is relevant to the problem of stellar population synthesis from galactic spectra.

Predicting the Functional Impact of KCNQ1 Variants of Unknown Significance.

PubMed

Li, Bian; Mendenhall, Jeffrey L; Kroncke, Brett M; Taylor, Keenan C; Huang, Hui; Smith, Derek K; Vanoye, Carlos G; Blume, Jeffrey D; George, Alfred L; Sanders, Charles R; Meiler, Jens

2017-10-01

An emerging standard-of-care for long-QT syndrome uses clinical genetic testing to identify genetic variants of the KCNQ1 potassium channel. However, interpreting results from genetic testing is confounded by the presence of variants of unknown significance for which there is inadequate evidence of pathogenicity. In this study, we curated from the literature a high-quality set of 107 functionally characterized KCNQ1 variants. Based on this data set, we completed a detailed quantitative analysis on the sequence conservation patterns of subdomains of KCNQ1 and the distribution of pathogenic variants therein. We found that conserved subdomains generally are critical for channel function and are enriched with dysfunctional variants. Using this experimentally validated data set, we trained a neural network, designated Q1VarPred, specifically for predicting the functional impact of KCNQ1 variants of unknown significance. The estimated predictive performance of Q1VarPred in terms of Matthew's correlation coefficient and area under the receiver operating characteristic curve were 0.581 and 0.884, respectively, superior to the performance of 8 previous methods tested in parallel. Q1VarPred is publicly available as a web server at http://meilerlab.org/q1varpred. Although a plethora of tools are available for making pathogenicity predictions over a genome-wide scale, previous tools fail to perform in a robust manner when applied to KCNQ1. The contrasting and favorable results for Q1VarPred suggest a promising approach, where a machine-learning algorithm is tailored to a specific protein target and trained with a functionally validated data set to calibrate informatics tools. © 2017 American Heart Association, Inc.

cosmoabc: Likelihood-free inference for cosmology

NASA Astrophysics Data System (ADS)

Ishida, Emille E. O.; Vitenti, Sandro D. P.; Penna-Lima, Mariana; Trindade, Arlindo M.; Cisewski, Jessi; M.; de Souza, Rafael; Cameron, Ewan; Busti, Vinicius C.

2015-05-01

Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogs. cosmoabc is a Python Approximate Bayesian Computation (ABC) sampler featuring a Population Monte Carlo variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code can be coupled to an external simulator to allow incorporation of arbitrary distance and prior functions. When coupled with the numcosmo library, it has been used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function.

Comparative genomics approaches to understanding and manipulating plant metabolism.

PubMed

Bradbury, Louis M T; Niehaus, Tom D; Hanson, Andrew D

2013-04-01

Over 3000 genomes, including numerous plant genomes, are now sequenced. However, their annotation remains problematic as illustrated by the many conserved genes with no assigned function, vague annotations such as 'kinase', or even wrong ones. Around 40% of genes of unknown function that are conserved between plants and microbes are probably metabolic enzymes or transporters; finding functions for these genes is a major challenge. Comparative genomics has correctly predicted functions for many such genes by analyzing genomic context, and gene fusions, distributions and co-expression. Comparative genomics complements genetic and biochemical approaches to dissect metabolism, continues to increase in power and decrease in cost, and has a pivotal role in modeling and engineering by helping identify functions for all metabolic genes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.

PubMed

Neuwald, Andrew F; Altschul, Stephen F

2016-12-01

Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu).

The accumulation mechanism of the hypoxia imaging probe "FMISO" by imaging mass spectrometry: possible involvement of low-molecular metabolites.

PubMed

Masaki, Yukiko; Shimizu, Yoichi; Yoshioka, Takeshi; Tanaka, Yukari; Nishijima, Ken-Ichi; Zhao, Songji; Higashino, Kenichi; Sakamoto, Shingo; Numata, Yoshito; Yamaguchi, Yoshitaka; Tamaki, Nagara; Kuge, Yuji

2015-11-19

(18)F-fluoromisonidazole (FMISO) has been widely used as a hypoxia imaging probe for diagnostic positron emission tomography (PET). FMISO is believed to accumulate in hypoxic cells via covalent binding with macromolecules after reduction of its nitro group. However, its detailed accumulation mechanism remains unknown. Therefore, we investigated the chemical forms of FMISO and their distributions in tumours using imaging mass spectrometry (IMS), which visualises spatial distribution of chemical compositions based on molecular masses in tissue sections. Our radiochemical analysis revealed that most of the radioactivity in tumours existed as low-molecular-weight compounds with unknown chemical formulas, unlike observations made with conventional views, suggesting that the radioactivity distribution primarily reflected that of these unknown substances. The IMS analysis indicated that FMISO and its reductive metabolites were nonspecifically distributed in the tumour in patterns not corresponding to the radioactivity distribution. Our IMS search found an unknown low-molecular-weight metabolite whose distribution pattern corresponded to that of both the radioactivity and the hypoxia marker pimonidazole. This metabolite was identified as the glutathione conjugate of amino-FMISO. We showed that the glutathione conjugate of amino-FMISO is involved in FMISO accumulation in hypoxic tumour tissues, in addition to the conventional mechanism of FMISO covalent binding to macromolecules.

The Inverse Bagging Algorithm: Anomaly Detection by Inverse Bootstrap Aggregating

NASA Astrophysics Data System (ADS)

Vischia, Pietro; Dorigo, Tommaso

2017-03-01

For data sets populated by a very well modeled process and by another process of unknown probability density function (PDF), a desired feature when manipulating the fraction of the unknown process (either for enhancing it or suppressing it) consists in avoiding to modify the kinematic distributions of the well modeled one. A bootstrap technique is used to identify sub-samples rich in the well modeled process, and classify each event according to the frequency of it being part of such sub-samples. Comparisons with general MVA algorithms will be shown, as well as a study of the asymptotic properties of the method, making use of a public domain data set that models a typical search for new physics as performed at hadronic colliders such as the Large Hadron Collider (LHC).

A Measure Approximation for Distributionally Robust PDE-Constrained Optimization Problems

DOE PAGES

Kouri, Drew Philip

2017-12-19

In numerous applications, scientists and engineers acquire varied forms of data that partially characterize the inputs to an underlying physical system. This data is then used to inform decisions such as controls and designs. Consequently, it is critical that the resulting control or design is robust to the inherent uncertainties associated with the unknown probabilistic characterization of the model inputs. Here in this work, we consider optimal control and design problems constrained by partial differential equations with uncertain inputs. We do not assume a known probabilistic model for the inputs, but rather we formulate the problem as a distributionally robustmore » optimization problem where the outer minimization problem determines the control or design, while the inner maximization problem determines the worst-case probability measure that matches desired characteristics of the data. We analyze the inner maximization problem in the space of measures and introduce a novel measure approximation technique, based on the approximation of continuous functions, to discretize the unknown probability measure. Finally, we prove consistency of our approximated min-max problem and conclude with numerical results.« less

Simultaneous treatment of unspecified heteroskedastic model error distribution and mismeasured covariates for restricted moment models.

PubMed

Garcia, Tanya P; Ma, Yanyuan

2017-10-01

We develop consistent and efficient estimation of parameters in general regression models with mismeasured covariates. We assume the model error and covariate distributions are unspecified, and the measurement error distribution is a general parametric distribution with unknown variance-covariance. We construct root- n consistent, asymptotically normal and locally efficient estimators using the semiparametric efficient score. We do not estimate any unknown distribution or model error heteroskedasticity. Instead, we form the estimator under possibly incorrect working distribution models for the model error, error-prone covariate, or both. Empirical results demonstrate robustness to different incorrect working models in homoscedastic and heteroskedastic models with error-prone covariates.

Reconstruction method for inversion problems in an acoustic tomography based temperature distribution measurement

NASA Astrophysics Data System (ADS)

Liu, Sha; Liu, Shi; Tong, Guowei

2017-11-01

In industrial areas, temperature distribution information provides a powerful data support for improving system efficiency, reducing pollutant emission, ensuring safety operation, etc. As a noninvasive measurement technology, acoustic tomography (AT) has been widely used to measure temperature distribution where the efficiency of the reconstruction algorithm is crucial for the reliability of the measurement results. Different from traditional reconstruction techniques, in this paper a two-phase reconstruction method is proposed to ameliorate the reconstruction accuracy (RA). In the first phase, the measurement domain is discretized by a coarse square grid to reduce the number of unknown variables to mitigate the ill-posed nature of the AT inverse problem. By taking into consideration the inaccuracy of the measured time-of-flight data, a new cost function is constructed to improve the robustness of the estimation, and a grey wolf optimizer is used to solve the proposed cost function to obtain the temperature distribution on the coarse grid. In the second phase, the Adaboost.RT based BP neural network algorithm is developed for predicting the temperature distribution on the refined grid in accordance with the temperature distribution data estimated in the first phase. Numerical simulations and experiment measurement results validate the superiority of the proposed reconstruction algorithm in improving the robustness and RA.

A novel astaxanthin-binding photooxidative stress-inducible aqueous carotenoprotein from a eukaryotic microalga isolated from asphalt in midsummer.

PubMed

Kawasaki, Shinji; Mizuguchi, Keisuke; Sato, Masaru; Kono, Tetsuya; Shimizu, Hirofumi

2013-07-01

Water-soluble orange carotenoid proteins (OCPs) that bind 3'-hydroxyechinenone are found in cyanobacteria, and are thought to play a key role in photoprotection. The distribution of OCPs in eukaryotes remains largely unknown. In this study, we identified a novel OCP that predominantly binds astaxanthin from a eukaryotic microalga, strain Ki-4, isolated from a dry surface of heated asphalt in midsummer. A purified astaxanthin-binding OCP, named AstaP, shows high solubility in water with an absorption peak at 484 nm, and possesses a heat-stable activity that quenches singlet oxygen. The deduced amino acid sequence of AstaP comprises an N-terminal hydrophobic signal peptide, fasciclin domains found in secreted and cell surface proteins, and N-linked glycosylation sites, the first example of a carotenoprotein among fasciclin family proteins. AstaP homologs of unknown function are distributed mainly in organisms from the hydrosphere, such as marine bacteria, cyanobacteria, sea anemone and eukaryotic microalgae; however, AstaP exhibits a unique extraordinarily high isoelectric point (pI) value among homologs. The gene encoding AstaP, as well as the AstaP peptide, is expressed abundantly under conditions of dehydration and salt stress in conjunction with high light exposure. As a unique aqueous carotenoprotein, AstaP will provide a novel function of OCPs in protection against extreme photooxidative stresses.

Absolute nuclear material assay

DOEpatents

Prasad, Manoj K [Pleasanton, CA; Snyderman, Neal J [Berkeley, CA; Rowland, Mark S [Alamo, CA

2012-05-15

A method of absolute nuclear material assay of an unknown source comprising counting neutrons from the unknown source and providing an absolute nuclear material assay utilizing a model to optimally compare to the measured count distributions. In one embodiment, the step of providing an absolute nuclear material assay comprises utilizing a random sampling of analytically computed fission chain distributions to generate a continuous time-evolving sequence of event-counts by spreading the fission chain distribution in time.

Absolute nuclear material assay

DOEpatents

Prasad, Manoj K [Pleasanton, CA; Snyderman, Neal J [Berkeley, CA; Rowland, Mark S [Alamo, CA

2010-07-13

A method of absolute nuclear material assay of an unknown source comprising counting neutrons from the unknown source and providing an absolute nuclear material assay utilizing a model to optimally compare to the measured count distributions. In one embodiment, the step of providing an absolute nuclear material assay comprises utilizing a random sampling of analytically computed fission chain distributions to generate a continuous time-evolving sequence of event-counts by spreading the fission chain distribution in time.

Network analysis in detection of early-stage mild cognitive impairment

NASA Astrophysics Data System (ADS)

Ni, Huangjing; Qin, Jiaolong; Zhou, Luping; Zhao, Zhigen; Wang, Jun; Hou, Fengzhen

2017-07-01

The detection and intervention for early-stage mild cognitive impairment (EMCI) is of vital importance However, the pathology of EMCI remains largely unknown, making it be challenge to the clinical diagnosis. In this paper, the resting-state functional magnetic resonance imaging (rs-fMRI) data derived from EMCI patients and normal controls are analyzed using the complex network theory. We construct the functional connectivity (FC) networks and employ the local false discovery rate approach to successfully detect the abnormal functional connectivities appeared in the EMCI patients. Our results demonstrate the abnormal functional connectivities have appeared in the EMCI patients, and the affected brain regions are mainly distributed in the frontal and temporal lobes In addition, to quantitatively characterize the statistical properties of FCs in the complex network, we herein employ the entropy of the degree distribution (EDD) index and some other well-established measures, i.e., clustering coefficient (CC) and the efficiency of graph (EG). Eventually, we found that the EDD index, better than the widely used CC and EG measures, may serve as an assistant and potential marker for the detection of EMCI.

Rheology of U-Shaped Granular Particles

NASA Astrophysics Data System (ADS)

Hill, Matthew; Franklin, Scott

We study the response of cylindrical samples of U-shaped granular particles (staples) to extensional loads. Samples elongate in discrete bursts (events) corresponding to particles rearranging and re-entangling. Previous research on samples of constant cross-sectional area found a Weibullian weakest-link theory could explain the distribution of yield points. We now vary the cross-sectional area, and find that the maximum yield pressure (force/area) is a function of particle number density and independent of area. The probability distribution function of important event characteristics -- the stress increase before an event and stress released during an event -- both fall of inversely with magnitude, reminiscent of avalanche dynamics. Fourier transforms of the fluctuating force (or stress) scales inversely with frequency, suggesting dry friction plays a role in the rearrangements. Finally, there is some evidence that dynamics are sensitive to the stiffness of the tensile testing machine, although an explanation for this behavior is unknown.

Phi Class of Glutathione S-transferase Gene Superfamily Widely Exists in Nonplant Taxonomic Groups.

PubMed

Munyampundu, Jean-Pierre; Xu, You-Ping; Cai, Xin-Zhong

2016-01-01

Glutathione S-transferases (GSTs) constitute a superfamily of enzymes involved in detoxification of noxious compounds and protection against oxidative damage. GST class Phi (GSTF), one of the important classes of plant GSTs, has long been considered as plant specific but was recently found in basidiomycete fungi. However, the range of nonplant taxonomic groups containing GSTFs remains unknown. In this study, the distribution and phylogenetic relationships of nonplant GSTFs were investigated. We identified GSTFs in ascomycete fungi, myxobacteria, and protists Naegleria gruberi and Aureococcus anophagefferens. GSTF occurrence in these bacteria and protists correlated with their genome sizes and habitats. While this link was missing across ascomycetes, the distribution and abundance of GSTFs among ascomycete genomes could be associated with their lifestyles to some extent. Sequence comparison, gene structure, and phylogenetic analyses indicated divergence among nonplant GSTFs, suggesting polyphyletic origins during evolution. Furthermore, in silico prediction of functional partners suggested functional diversification among nonplant GSTFs.

Estimation of two ordered mean residual lifetime functions.

PubMed

Ebrahimi, N

1993-06-01

In many statistical studies involving failure data, biometric mortality data, and actuarial data, mean residual lifetime (MRL) function is of prime importance. In this paper we introduce the problem of nonparametric estimation of a MRL function on an interval when this function is bounded from below by another such function (known or unknown) on that interval, and derive the corresponding two functional estimators. The first is to be used when there is a known bound, and the second when the bound is another MRL function to be estimated independently. Both estimators are obtained by truncating the empirical estimator discussed by Yang (1978, Annals of Statistics 6, 112-117). In the first case, it is truncated at a known bound; in the second, at a point somewhere between the two empirical estimates. Consistency of both estimators is proved, and a pointwise large-sample distribution theory of the first estimator is derived.

Distributed Containment Control for Multiple Unknown Second-Order Nonlinear Systems With Application to Networked Lagrangian Systems.

PubMed

Mei, Jie; Ren, Wei; Li, Bing; Ma, Guangfu

2015-09-01

In this paper, we consider the distributed containment control problem for multiagent systems with unknown nonlinear dynamics. More specifically, we focus on multiple second-order nonlinear systems and networked Lagrangian systems. We first study the distributed containment control problem for multiple second-order nonlinear systems with multiple dynamic leaders in the presence of unknown nonlinearities and external disturbances under a general directed graph that characterizes the interaction among the leaders and the followers. A distributed adaptive control algorithm with an adaptive gain design based on the approximation capability of neural networks is proposed. We present a necessary and sufficient condition on the directed graph such that the containment error can be reduced as small as desired. As a byproduct, the leaderless consensus problem is solved with asymptotical convergence. Because relative velocity measurements between neighbors are generally more difficult to obtain than relative position measurements, we then propose a distributed containment control algorithm without using neighbors' velocity information. A two-step Lyapunov-based method is used to study the convergence of the closed-loop system. Next, we apply the ideas to deal with the containment control problem for networked unknown Lagrangian systems under a general directed graph. All the proposed algorithms are distributed and can be implemented using only local measurements in the absence of communication. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.

A Class of Population Covariance Matrices in the Bootstrap Approach to Covariance Structure Analysis

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Hayashi, Kentaro; Yanagihara, Hirokazu

2007-01-01

Model evaluation in covariance structure analysis is critical before the results can be trusted. Due to finite sample sizes and unknown distributions of real data, existing conclusions regarding a particular statistic may not be applicable in practice. The bootstrap procedure automatically takes care of the unknown distribution and, for a given…

Prescribed performance distributed consensus control for nonlinear multi-agent systems with unknown dead-zone input

NASA Astrophysics Data System (ADS)

Cui, Guozeng; Xu, Shengyuan; Ma, Qian; Li, Yongmin; Zhang, Zhengqiang

2018-05-01

In this paper, the problem of prescribed performance distributed output consensus for higher-order non-affine nonlinear multi-agent systems with unknown dead-zone input is investigated. Fuzzy logical systems are utilised to identify the unknown nonlinearities. By introducing prescribed performance, the transient and steady performance of synchronisation errors are guaranteed. Based on Lyapunov stability theory and the dynamic surface control technique, a new distributed consensus algorithm for non-affine nonlinear multi-agent systems is proposed, which ensures cooperatively uniformly ultimately boundedness of all signals in the closed-loop systems and enables the output of each follower to synchronise with the leader within predefined bounded error. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

Understanding the brain through its spatial structure

NASA Astrophysics Data System (ADS)

Morrison, Will Zachary

The spatial location of cells in neural tissue can be easily extracted from many imaging modalities, but the information contained in spatial relationships between cells is seldom utilized. This is because of a lack of recognition of the importance of spatial relationships to some aspects of brain function, and the reflection in spatial statistics of other types of information. The mathematical tools necessary to describe spatial relationships are also unknown to many neuroscientists, and biologists in general. We analyze two cases, and show that spatial relationships can be used to understand the role of a particular type of cell, the astrocyte, in Alzheimer's disease, and that the geometry of axons in the brain's white matter sheds light on the process of establishing connectivity between areas of the brain. Astrocytes provide nutrients for neuronal metabolism, and regulate the chemical environment of the brain, activities that require manipulation of spatial distributions (of neurotransmitters, for example). We first show, through the use of a correlation function, that inter-astrocyte forces determine the size of independent regulatory domains in the cortex. By examining the spatial distribution of astrocytes in a mouse model of Alzheimer's Disease, we determine that astrocytes are not actively transported to fight the disease, as was previously thought. The paths axons take through the white matter determine which parts of the brain are connected, and how quickly signals are transmitted. The rules that determine these paths (i.e. shortest distance) are currently unknown. By measurement of axon orientation distributions using three-point correlation functions and the statistics of axon turning and branching, we reveal that axons are restricted to growth in three directions, like a taxicab traversing city blocks, albeit in three-dimensions. We show how geometric restrictions at the small scale are related to large-scale trajectories. Finally we discuss the implications of this finding for experimental and theoretical connectomics.

Diverticular Disease of the Colon: Neuromuscular Function Abnormalities.

PubMed

Bassotti, Gabrio; Villanacci, Vincenzo; Bernardini, Nunzia; Dore, Maria P

2016-10-01

Colonic diverticular disease is a frequent finding in daily clinical practice. However, its pathophysiological mechanisms are largely unknown. This condition is likely the result of several concomitant factors occurring together to cause anatomic and functional abnormalities, leading as a result to the outpouching of the colonic mucosa. A pivotal role seems to be played by an abnormal colonic neuromuscular function, as shown repeatedly in these patients, and by an altered visceral perception. There is recent evidence that these abnormalities might be related to the derangement of the enteric innervation, to an abnormal distribution of mucosal neuropeptides, and to low-grade mucosal inflammation. The latter might be responsible for the development of visceral hypersensitivity, often causing abdominal pain in a subset of these patients.

Estimation on nonlinear damping in second order distributed parameter systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Reich, Simeon; Rosen, I. G.

1989-01-01

An approximation and convergence theory for the identification of nonlinear damping in abstract wave equations is developed. It is assumed that the unknown dissipation mechanism to be identified can be described by a maximal monotone operator acting on the generalized velocity. The stiffness is assumed to be linear and symmetric. Functional analytic techniques are used to establish that solutions to a sequence of finite dimensional (Galerkin) approximating identification problems in some sense approximate a solution to the original infinite dimensional inverse problem.

A Study of Terrain Reductions, Density Anomalies and Geophysical Inversion Methods in Gravity Field Modelling

DTIC Science & Technology

1984-04-01

5.15) where a is a positive constant and 11 IIH the Hilbert space norm associated with the chosen covariance function K. The constant a is arbitrary...Density Anomalies 14 5. Unknown Densities - Geophysical Inversion 16 6. Density Modelling Using Rectangular Prisms 24 6.1 Space Domain 24 6.2 Frequency...theory: to calculate the gravity potential and its derivatives in space due to 6 • given density distributions. When the prime interest is in "external

The Viral and Eukaryotic Distribution of the Internal Ribosome Entry Site (IRES) and its Potential as an Anti-Viral Translation Target

DTIC Science & Technology

1998-12-16

Coxsackie A virus (CAV) Coxsackie B virus (CBV) Bovine enterovirus (BEV) Apbthoviruses Foot and mouth disease virus ( FMDV ) Cardioviruses Mengovirus...disease viruses ( FMDV ) contain a stretch ofpoly (C), of unknown function, located within the 5’ UTRs. To determine whether the 5’ UIR ofEMCV...human rhinovirus. Type 2 IRES elements are found in EMCV, TMEV, and FMDV . Type 3 IRES elements are found in hepatitis A virus. There is very little

Mapping cell surface adhesion by rotation tracking and adhesion footprinting

NASA Astrophysics Data System (ADS)

Li, Isaac T. S.; Ha, Taekjip; Chemla, Yann R.

2017-03-01

Rolling adhesion, in which cells passively roll along surfaces under shear flow, is a critical process involved in inflammatory responses and cancer metastasis. Surface adhesion properties regulated by adhesion receptors and membrane tethers are critical in understanding cell rolling behavior. Locally, adhesion molecules are distributed at the tips of membrane tethers. However, how functional adhesion properties are globally distributed on the individual cell’s surface is unknown. Here, we developed a label-free technique to determine the spatial distribution of adhesive properties on rolling cell surfaces. Using dark-field imaging and particle tracking, we extract the rotational motion of individual rolling cells. The rotational information allows us to construct an adhesion map along the contact circumference of a single cell. To complement this approach, we also developed a fluorescent adhesion footprint assay to record the molecular adhesion events from cell rolling. Applying the combination of the two methods on human promyelocytic leukemia cells, our results surprisingly reveal that adhesion is non-uniformly distributed in patches on the cell surfaces. Our label-free adhesion mapping methods are applicable to the variety of cell types that undergo rolling adhesion and provide a quantitative picture of cell surface adhesion at the functional and molecular level.

Topographic Distributions of Emergent Trees in Tropical Forests of the Osa Peninsula, Costa Rica

NASA Astrophysics Data System (ADS)

Balzotti, C.; Asner, G. P.; Taylor, P.; Cole, R. J.; Osborne, B. B.; Cleveland, C. C.; Porder, S.; Townsend, A. R.

2015-12-01

Tropical rainforests are reservoirs of terrestrial carbon and biodiversity. Large and often emergent trees store disproportionately large amounts of aboveground carbon and greatly influence the structure and functioning of tropical rainforests. Despite their importance, controls on the abundance and distribution of emergent trees are largely unknown across tropical landscapes. Conventional field approaches are limited in their ability to characterize patterns in emergent trees across vast landscapes with varying environmental conditions and floristic composition. Here we used a high-resolution light detection and ranging (LiDAR) sensor, aboard the Carnegie Airborne Observatory Airborne Taxonomic Mapping System (CAO-AToMS), to examine the abundance and distribution of tall emergent tree canopies (ETC) relative to surrounding tree canopies (STC), across the Osa Peninsula, a geologically and topographically diverse region of Costa Rica. The abundance of ETC was clearly influenced by fine-scale topographic variation, with distribution patterns that held across a variety of geologic substrates. Specifically, the density of ETC was much greater on lower slopes and in valleys, compared to upper slopes and ridges. Furthermore, using the CAO high-fidelity imaging spectrometer, ETC had a different spectral signature than that of the STC. Most notably, ETC had lower foliar N than STC, which was verified with an independent field survey of canopy leaf chemistry. The underlying mechanisms to explain the topographic-dependence of ETCs and linkages to canopy N are unknown, and remain an important area of research.

An offline approach for output-only Bayesian identification of stochastic nonlinear systems using unscented Kalman filtering

NASA Astrophysics Data System (ADS)

Erazo, Kalil; Nagarajaiah, Satish

2017-06-01

In this paper an offline approach for output-only Bayesian identification of stochastic nonlinear systems is presented. The approach is based on a re-parameterization of the joint posterior distribution of the parameters that define a postulated state-space stochastic model class. In the re-parameterization the state predictive distribution is included, marginalized, and estimated recursively in a state estimation step using an unscented Kalman filter, bypassing state augmentation as required by existing online methods. In applications expectations of functions of the parameters are of interest, which requires the evaluation of potentially high-dimensional integrals; Markov chain Monte Carlo is adopted to sample the posterior distribution and estimate the expectations. The proposed approach is suitable for nonlinear systems subjected to non-stationary inputs whose realization is unknown, and that are modeled as stochastic processes. Numerical verification and experimental validation examples illustrate the effectiveness and advantages of the approach, including: (i) an increased numerical stability with respect to augmented-state unscented Kalman filtering, avoiding divergence of the estimates when the forcing input is unmeasured; (ii) the ability to handle arbitrary prior and posterior distributions. The experimental validation of the approach is conducted using data from a large-scale structure tested on a shake table. It is shown that the approach is robust to inherent modeling errors in the description of the system and forcing input, providing accurate prediction of the dynamic response when the excitation history is unknown.

Superstatistical Energy Distributions of an Ion in an Ultracold Buffer Gas

NASA Astrophysics Data System (ADS)

Rouse, I.; Willitsch, S.

2017-04-01

An ion in a radio frequency ion trap interacting with a buffer gas of ultracold neutral atoms is a driven dynamical system which has been found to develop a nonthermal energy distribution with a power law tail. The exact analytical form of this distribution is unknown, but has often been represented empirically by q -exponential (Tsallis) functions. Based on the concepts of superstatistics, we introduce a framework for the statistical mechanics of an ion trapped in an rf field subject to collisions with a buffer gas. We derive analytic ion secular energy distributions from first principles both neglecting and including the effects of the thermal energy of the buffer gas. For a buffer gas with a finite temperature, we prove that Tsallis statistics emerges from the combination of a constant heating term and multiplicative energy fluctuations. We show that the resulting distributions essentially depend on experimentally controllable parameters paving the way for an accurate control of the statistical properties of ion-atom hybrid systems.

Polynomial probability distribution estimation using the method of moments

PubMed Central

Mattsson, Lars; Rydén, Jesper

2017-01-01

We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram–Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation. PMID:28394949

Polynomial probability distribution estimation using the method of moments.

PubMed

Munkhammar, Joakim; Mattsson, Lars; Rydén, Jesper

2017-01-01

We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram-Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation.

Comparative Metagenomics of Cellulose- and Poplar Hydrolysate-Degrading Microcosms from Gut Microflora of the Canadian Beaver (Castor canadensis) and North American Moose (Alces americanus) after Long-Term Enrichment

PubMed Central

Wong, Mabel T.; Wang, Weijun; Couturier, Marie; Razeq, Fakhria M.; Lombard, Vincent; Lapebie, Pascal; Edwards, Elizabeth A.; Terrapon, Nicolas; Henrissat, Bernard; Master, Emma R.

2017-01-01

To identify carbohydrate-active enzymes (CAZymes) that might be particularly relevant for wood fiber processing, we performed a comparative metagenomic analysis of digestive systems from Canadian beaver (Castor canadensis) and North American moose (Alces americanus) following 3 years of enrichment on either microcrystalline cellulose or poplar hydrolysate. In total, 9,386 genes encoding CAZymes and carbohydrate-binding modules (CBMs) were identified, with up to half predicted to originate from Firmicutes, Bacteroidetes, Chloroflexi, and Proteobacteria phyla, and up to 17% from unknown phyla. Both PCA and hierarchical cluster analysis distinguished the annotated glycoside hydrolase (GH) distributions identified herein, from those previously reported for grass-feeding mammals and herbivorous foragers. The CAZyme profile of moose rumen enrichments also differed from a recently reported moose rumen metagenome, most notably by the absence of GH13-appended dockerins. Consistent with substrate-driven convergence, CAZyme profiles from both poplar hydrolysate-fed cultures differed from cellulose-fed cultures, most notably by increased numbers of unique sequences belonging to families GH3, GH5, GH43, GH53, and CE1. Moreover, pairwise comparisons of moose rumen enrichments further revealed higher counts of GH127 and CE15 families in cultures fed with poplar hydrolysate. To expand our scope to lesser known carbohydrate-active proteins, we identified and compared multi-domain proteins comprising both a CBM and domain of unknown function (DUF) as well as proteins with unknown function within the 416 predicted polysaccharide utilization loci (PULs). Interestingly, DUF362, identified in iron–sulfur proteins, was consistently appended to CBM9; on the other hand, proteins with unknown function from PULs shared little identity unless from identical PULs. Overall, this study sheds new light on the lignocellulose degrading capabilities of microbes originating from digestive systems of mammals known for fiber-rich diets, and highlights the value of enrichment to select new CAZymes from metagenome sequences for future biochemical characterization. PMID:29326667

Predicting species distributions from checklist data using site-occupancy models

USGS Publications Warehouse

Kery, M.; Gardner, B.; Monnerat, C.

2010-01-01

Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent distribution, i.e. an unknown proportion of species distributions. That unknown proportion is equivalent to detectability. Imperfect detection in conventional species distribution models yields underestimates of the extent of distributions and covariate effects that are biased towards zero. In addition, patterns in detectability will erroneously be ascribed to species distributions. In contrast, site-occupancy models applied to replicated detection/non-detection data offer a powerful framework for making inferences about species distributions corrected for imperfect detection. The use of 'cheap' checklist data greatly enhances the scope of applications of this useful class of models. ?? 2010 Blackwell Publishing Ltd.

Structural and functional networks in complex systems with delay.

PubMed

Eguíluz, Víctor M; Pérez, Toni; Borge-Holthoefer, Javier; Arenas, Alex

2011-05-01

Functional networks of complex systems are obtained from the analysis of the temporal activity of their components, and are often used to infer their unknown underlying connectivity. We obtain the equations relating topology and function in a system of diffusively delay-coupled elements in complex networks. We solve exactly the resulting equations in motifs (directed structures of three nodes) and in directed networks. The mean-field solution for directed uncorrelated networks shows that the clusterization of the activity is dominated by the in-degree of the nodes, and that the locking frequency decreases with increasing average degree. We find that the exponent of a power law degree distribution of the structural topology γ is related to the exponent of the associated functional network as α=(2-γ)(-1) for γ<2. © 2011 American Physical Society

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

Fission meter and neutron detection using poisson distribution comparison

DOEpatents

Rowland, Mark S; Snyderman, Neal J

2014-11-18

A neutron detector system and method for discriminating fissile material from non-fissile material wherein a digital data acquisition unit collects data at high rate, and in real-time processes large volumes of data directly into information that a first responder can use to discriminate materials. The system comprises counting neutrons from the unknown source and detecting excess grouped neutrons to identify fission in the unknown source. Comparison of the observed neutron count distribution with a Poisson distribution is performed to distinguish fissile material from non-fissile material.

A flexible model for correlated medical costs, with application to medical expenditure panel survey data.

PubMed

Chen, Jinsong; Liu, Lei; Shih, Ya-Chen T; Zhang, Daowen; Severini, Thomas A

2016-03-15

We propose a flexible model for correlated medical cost data with several appealing features. First, the mean function is partially linear. Second, the distributional form for the response is not specified. Third, the covariance structure of correlated medical costs has a semiparametric form. We use extended generalized estimating equations to simultaneously estimate all parameters of interest. B-splines are used to estimate unknown functions, and a modification to Akaike information criterion is proposed for selecting knots in spline bases. We apply the model to correlated medical costs in the Medical Expenditure Panel Survey dataset. Simulation studies are conducted to assess the performance of our method. Copyright © 2015 John Wiley & Sons, Ltd.

Determination of the structural properties of the aqueous electrolyte LiCl6H 2 O at the supercooled state using the Reverse Monte Carlo (RMC) simulation

NASA Astrophysics Data System (ADS)

ZIANE, M.; HABCHI, M.; DEROUICHE, A.; MESLI, S. M.; BENZOUINE, F.; KOTBI, M.

2017-03-01

A structural study of an aqueous electrolyte whose experimental results are available. It is a solution of A structural study of an aqueous electrolyte whose experimental results are available. It is a solution LiCl6H 2 O type at supercooled state (162K) contrasted with pure water at room temperature by means of Partial Distribution Functions (PDF) issue from neutron scattering technique. The aqueous electrolyte solution of the chloride lithium LiCl presents interesting properties which is studied by different methods at different concentration and thermodynamical states: This system possesses the property to become a glass through a metastable supercooled state when the temperature decreases. Based on these partial functions, the Reverse Monte Carlo method (RMC) computes radial correlation functions which allow exploring a number of structural features of the system. The purpose of the RMC is to produce a consistent configuration with the experimental data. They are usually the most important in the limit of systematic errors (of unknown distribution).

A comparative study of single-leg ground reaction forces in running lizards.

PubMed

McElroy, Eric J; Wilson, Robbie; Biknevicius, Audrone R; Reilly, Stephen M

2014-03-01

The role of different limbs in supporting and propelling the body has been studied in many species with animals appearing to have either similarity in limb function or differential limb function. Differential hindlimb versus forelimb function has been proposed as a general feature of running with a sprawling posture and as benefiting sprawled postured animals by enhancing maneuvering and minimizing joint moments. Yet only a few species have been studied and thus the generality of differential limb function in running animals with sprawled postures is unknown. We measured the limb lengths of seven species of lizard and their single-limb three-dimensional ground reaction forces during high-speed running. We found that all species relied on the hindlimb for producing accelerative forces. Braking forces were forelimb dominated in four species and equally distributed between limbs in the other three. Vertical forces were dominated by the hindlimb in three species and equally distributed between the forelimb and hindlimb in the other four. Medial forces were dominated by the hindlimb in four species and equally distributed in the other three, with all Iguanians exhibiting hindlimb-biased medial forces. Relative hindlimb to forelimb length of each species was related to variation in hindlimb versus forelimb medial forces; species with relatively longer hindlimbs compared with forelimbs exhibited medial forces that were more biased towards the hindlimbs. These results suggest that the function of individual limbs in lizards varies across species with only a single general pattern (hindlimb-dominated accelerative force) being present.

Crystal structure of Bacillus subtilis YabJ, a purine regulatory protein and member of the highly conserved YjgF family

PubMed Central

Sinha, Sangita; Rappu, Pekka; Lange, S. C.; Mäntsälä, Pekka; Zalkin, Howard; Smith, Janet L.

1999-01-01

The yabJ gene in Bacillus subtilis is required for adenine-mediated repression of purine biosynthetic genes in vivo and codes for an acid-soluble, 14-kDa protein. The molecular mechanism of YabJ is unknown. YabJ is a member of a large, widely distributed family of proteins of unknown biochemical function. The 1.7-Å crystal structure of YabJ reveals a trimeric organization with extensive buried hydrophobic surface and an internal water-filled cavity. The most important finding in the structure is a deep, narrow cleft between subunits lined with nine side chains that are invariant among the 25 most similar homologs. This conserved site is proposed to be a binding or catalytic site for a ligand or substrate that is common to YabJ and other members of the YER057c/YjgF/UK114 family of proteins. PMID:10557275

Weakly Nonergodic Dynamics in the Gross-Pitaevskii Lattice

NASA Astrophysics Data System (ADS)

Mithun, Thudiyangal; Kati, Yagmur; Danieli, Carlo; Flach, Sergej

2018-05-01

The microcanonical Gross-Pitaevskii (also known as the semiclassical Bose-Hubbard) lattice model dynamics is characterized by a pair of energy and norm densities. The grand canonical Gibbs distribution fails to describe a part of the density space, due to the boundedness of its kinetic energy spectrum. We define Poincaré equilibrium manifolds and compute the statistics of microcanonical excursion times off them. The tails of the distribution functions quantify the proximity of the many-body dynamics to a weakly nonergodic phase, which occurs when the average excursion time is infinite. We find that a crossover to weakly nonergodic dynamics takes place inside the non-Gibbs phase, being unnoticed by the largest Lyapunov exponent. In the ergodic part of the non-Gibbs phase, the Gibbs distribution should be replaced by an unknown modified one. We relate our findings to the corresponding integrable limit, close to which the actions are interacting through a short range coupling network.

Schmallenberg virus non-structural protein NSm: Intracellular distribution and role of non-hydrophobic domains.

PubMed

Kraatz, Franziska; Wernike, Kerstin; Reiche, Sven; Aebischer, Andrea; Reimann, Ilona; Beer, Martin

2018-03-01

Schmallenberg virus (SBV) induces fetal malformation, abortions and stillbirth in ruminants. While the non-structural protein NSs is a major virulence factor, the biological function of NSm, the second non-structural protein which consists of three hydrophobic transmembrane (I, III, V) and two non-hydrophobic regions (II, IV), is still unknown. Here, a series of NSm mutants displaying deletions of nearly the entire NSm or of the non-hydrophobic domains was generated and the intracellular distribution of NSm was assessed. SBV-NSm is dispensable for the generation of infectious virus and mutants lacking domains II - V showed growth properties similar to the wild-type virus. In addition, a comparable intracellular distribution of SBV-NSm was observed in mammalian cells infected with domain II mutants or wild-type virus. In both cases, NSm co-localized with the glycoprotein Gc in the Golgi compartment. However, domain IV-deletion mutants showed an altered distribution pattern and no co-localization of NSm and Gc. Copyright © 2018 Elsevier Inc. All rights reserved.

Brain-wide Maps Reveal Stereotyped Cell-Type-Based Cortical Architecture and Subcortical Sexual Dimorphism.

PubMed

Kim, Yongsoo; Yang, Guangyu Robert; Pradhan, Kith; Venkataraju, Kannan Umadevi; Bota, Mihail; García Del Molino, Luis Carlos; Fitzgerald, Greg; Ram, Keerthi; He, Miao; Levine, Jesse Maurica; Mitra, Partha; Huang, Z Josh; Wang, Xiao-Jing; Osten, Pavel

2017-10-05

The stereotyped features of neuronal circuits are those most likely to explain the remarkable capacity of the brain to process information and govern behaviors, yet it has not been possible to comprehensively quantify neuronal distributions across animals or genders due to the size and complexity of the mammalian brain. Here we apply our quantitative brain-wide (qBrain) mapping platform to document the stereotyped distributions of mainly inhibitory cell types. We discover an unexpected cortical organizing principle: sensory-motor areas are dominated by output-modulating parvalbumin-positive interneurons, whereas association, including frontal, areas are dominated by input-modulating somatostatin-positive interneurons. Furthermore, we identify local cell type distributions with more cells in the female brain in 10 out of 11 sexually dimorphic subcortical areas, in contrast to the overall larger brains in males. The qBrain resource can be further mined to link stereotyped aspects of neuronal distributions to known and unknown functions of diverse brain regions. Copyright © 2017 Elsevier Inc. All rights reserved.

Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells.

PubMed

Recouvreux, Pierre; Sokolowski, Thomas R; Grammoustianou, Aristea; ten Wolde, Pieter Rein; Dogterom, Marileen

2016-02-16

Cell polarity refers to a functional spatial organization of proteins that is crucial for the control of essential cellular processes such as growth and division. To establish polarity, cells rely on elaborate regulation networks that control the distribution of proteins at the cell membrane. In fission yeast cells, a microtubule-dependent network has been identified that polarizes the distribution of signaling proteins that restricts growth to cell ends and targets the cytokinetic machinery to the middle of the cell. Although many molecular components have been shown to play a role in this network, it remains unknown which molecular functionalities are minimally required to establish a polarized protein distribution in this system. Here we show that a membrane-binding protein fragment, which distributes homogeneously in wild-type fission yeast cells, can be made to concentrate at cell ends by attaching it to a cytoplasmic microtubule end-binding protein. This concentration results in a polarized pattern of chimera proteins with a spatial extension that is very reminiscent of natural polarity patterns in fission yeast. However, chimera levels fluctuate in response to microtubule dynamics, and disruption of microtubules leads to disappearance of the pattern. Numerical simulations confirm that the combined functionality of membrane anchoring and microtubule tip affinity is in principle sufficient to create polarized patterns. Our chimera protein may thus represent a simple molecular functionality that is able to polarize the membrane, onto which additional layers of molecular complexity may be built to provide the temporal robustness that is typical of natural polarity patterns.

On the performance of the moment approximation for the numerical computation of fiber stress in turbulent channel flow

NASA Astrophysics Data System (ADS)

Gillissen, J. J. J.; Boersma, B. J.; Mortensen, P. H.; Andersson, H. I.

2007-03-01

Fiber-induced drag reduction can be studied in great detail by means of direct numerical simulation [J. S. Paschkewitz et al., J. Fluid Mech. 518, 281 (2004)]. To account for the effect of the fibers, the Navier-Stokes equations are supplemented by the fiber stress tensor, which depends on the distribution function of fiber orientation angles. We have computed this function in turbulent channel flow, by solving the Fokker-Planck equation numerically. The results are used to validate an approximate method for calculating fiber stress, in which the second moment of the orientation distribution is solved. Since the moment evolution equations contain higher-order moments, a closure relation is required to obtain as many equations as unknowns. We investigate the performance of the eigenvalue-based optimal fitted closure scheme [J. S. Cintra and C. L. Tucker, J. Rheol. 39, 1095 (1995)]. The closure-predicted stress and flow statistics in two-way coupled simulations are within 10% of the "exact" Fokker-Planck solution.

Phi Class of Glutathione S-transferase Gene Superfamily Widely Exists in Nonplant Taxonomic Groups

PubMed Central

Munyampundu, Jean-Pierre; Xu, You-Ping; Cai, Xin-Zhong

2016-01-01

Glutathione S-transferases (GSTs) constitute a superfamily of enzymes involved in detoxification of noxious compounds and protection against oxidative damage. GST class Phi (GSTF), one of the important classes of plant GSTs, has long been considered as plant specific but was recently found in basidiomycete fungi. However, the range of nonplant taxonomic groups containing GSTFs remains unknown. In this study, the distribution and phylogenetic relationships of nonplant GSTFs were investigated. We identified GSTFs in ascomycete fungi, myxobacteria, and protists Naegleria gruberi and Aureococcus anophagefferens. GSTF occurrence in these bacteria and protists correlated with their genome sizes and habitats. While this link was missing across ascomycetes, the distribution and abundance of GSTFs among ascomycete genomes could be associated with their lifestyles to some extent. Sequence comparison, gene structure, and phylogenetic analyses indicated divergence among nonplant GSTFs, suggesting polyphyletic origins during evolution. Furthermore, in silico prediction of functional partners suggested functional diversification among nonplant GSTFs. PMID:26884677

User's Manual: Routines for Radiative Heat Transfer and Thermometry

NASA Technical Reports Server (NTRS)

Risch, Timothy K.

2016-01-01

Determining the intensity and spectral distribution of radiation emanating from a heated surface has applications in many areas of science and engineering. Areas of research in which the quantification of spectral radiation is used routinely include thermal radiation heat transfer, infrared signature analysis, and radiation thermometry. In the analysis of radiation, it is helpful to be able to predict the radiative intensity and the spectral distribution of the emitted energy. Presented in this report is a set of routines written in Microsoft Visual Basic for Applications (VBA) (Microsoft Corporation, Redmond, Washington) and incorporating functions specific to Microsoft Excel (Microsoft Corporation, Redmond, Washington) that are useful for predicting the radiative behavior of heated surfaces. These routines include functions for calculating quantities of primary importance to engineers and scientists. In addition, the routines also provide the capability to use such information to determine surface temperatures from spectral intensities and for calculating the sensitivity of the surface temperature measurements to unknowns in the input parameters.

Choice of no-slip curved boundary condition for lattice Boltzmann simulations of high-Reynolds-number flows.

PubMed

Sanjeevi, Sathish K P; Zarghami, Ahad; Padding, Johan T

2018-04-01

Various curved no-slip boundary conditions available in literature improve the accuracy of lattice Boltzmann simulations compared to the traditional staircase approximation of curved geometries. Usually, the required unknown distribution functions emerging from the solid nodes are computed based on the known distribution functions using interpolation or extrapolation schemes. On using such curved boundary schemes, there will be mass loss or gain at each time step during the simulations, especially apparent at high Reynolds numbers, which is called mass leakage. Such an issue becomes severe in periodic flows, where the mass leakage accumulation would affect the computed flow fields over time. In this paper, we examine mass leakage of the most well-known curved boundary treatments for high-Reynolds-number flows. Apart from the existing schemes, we also test different forced mass conservation schemes and a constant density scheme. The capability of each scheme is investigated and, finally, recommendations for choosing a proper boundary condition scheme are given for stable and accurate simulations.

Choice of no-slip curved boundary condition for lattice Boltzmann simulations of high-Reynolds-number flows

NASA Astrophysics Data System (ADS)

Sanjeevi, Sathish K. P.; Zarghami, Ahad; Padding, Johan T.

2018-04-01

Various curved no-slip boundary conditions available in literature improve the accuracy of lattice Boltzmann simulations compared to the traditional staircase approximation of curved geometries. Usually, the required unknown distribution functions emerging from the solid nodes are computed based on the known distribution functions using interpolation or extrapolation schemes. On using such curved boundary schemes, there will be mass loss or gain at each time step during the simulations, especially apparent at high Reynolds numbers, which is called mass leakage. Such an issue becomes severe in periodic flows, where the mass leakage accumulation would affect the computed flow fields over time. In this paper, we examine mass leakage of the most well-known curved boundary treatments for high-Reynolds-number flows. Apart from the existing schemes, we also test different forced mass conservation schemes and a constant density scheme. The capability of each scheme is investigated and, finally, recommendations for choosing a proper boundary condition scheme are given for stable and accurate simulations.

A Statistical Treatment of Bioassay Pour Fractions

NASA Technical Reports Server (NTRS)

Barengoltz, Jack; Hughes, David W.

2014-01-01

The binomial probability distribution is used to treat the statistics of a microbiological sample that is split into two parts, with only one part evaluated for spore count. One wishes to estimate the total number of spores in the sample based on the counts obtained from the part that is evaluated (pour fraction). Formally, the binomial distribution is recharacterized as a function of the observed counts (successes), with the total number (trials) an unknown. The pour fraction is the probability of success per spore (trial). This distribution must be renormalized in terms of the total number. Finally, the new renormalized distribution is integrated and mathematically inverted to yield the maximum estimate of the total number as a function of a desired level of confidence ( P(

Prospects of second generation artificial intelligence tools in calibration of chemical sensors.

PubMed

Braibanti, Antonio; Rao, Rupenaguntla Sambasiva; Ramam, Veluri Anantha; Rao, Gollapalli Nageswara; Rao, Vaddadi Venkata Panakala

2005-05-01

Multivariate data driven calibration models with neural networks (NNs) are developed for binary (Cu++ and Ca++) and quaternary (K+, Ca++, NO3- and Cl-) ion-selective electrode (ISE) data. The response profiles of ISEs with concentrations are non-linear and sub-Nernstian. This task represents function approximation of multi-variate, multi-response, correlated, non-linear data with unknown noise structure i.e. multi-component calibration/prediction in chemometric parlance. Radial distribution function (RBF) and Fuzzy-ARTMAP-NN models implemented in the software packages, TRAJAN and Professional II, are employed for the calibration. The optimum NN models reported are based on residuals in concentration space. Being a data driven information technology, NN does not require a model, prior- or posterior- distribution of data or noise structure. Missing information, spikes or newer trends in different concentration ranges can be modeled through novelty detection. Two simulated data sets generated from mathematical functions are modeled as a function of number of data points and network parameters like number of neurons and nearest neighbors. The success of RBF and Fuzzy-ARTMAP-NNs to develop adequate calibration models for experimental data and function approximation models for more complex simulated data sets ensures AI2 (artificial intelligence, 2nd generation) as a promising technology in quantitation.

Reconstruction of Atmospheric Tracer Releases with Optimal Resolution Features: Concentration Data Assimilation

NASA Astrophysics Data System (ADS)

Singh, Sarvesh Kumar; Turbelin, Gregory; Issartel, Jean-Pierre; Kumar, Pramod; Feiz, Amir Ali

2015-04-01

The fast growing urbanization, industrialization and military developments increase the risk towards the human environment and ecology. This is realized in several past mortality incidents, for instance, Chernobyl nuclear explosion (Ukraine), Bhopal gas leak (India), Fukushima-Daichi radionuclide release (Japan), etc. To reduce the threat and exposure to the hazardous contaminants, a fast and preliminary identification of unknown releases is required by the responsible authorities for the emergency preparedness and air quality analysis. Often, an early detection of such contaminants is pursued by a distributed sensor network. However, identifying the origin and strength of unknown releases following the sensor reported concentrations is a challenging task. This requires an optimal strategy to integrate the measured concentrations with the predictions given by the atmospheric dispersion models. This is an inverse problem. The measured concentrations are insufficient and atmospheric dispersion models suffer from inaccuracy due to the lack of process understanding, turbulence uncertainties, etc. These lead to a loss of information in the reconstruction process and thus, affect the resolution, stability and uniqueness of the retrieved source. An additional well known issue is the numerical artifact arisen at the measurement locations due to the strong concentration gradient and dissipative nature of the concentration. Thus, assimilation techniques are desired which can lead to an optimal retrieval of the unknown releases. In general, this is facilitated within the Bayesian inference and optimization framework with a suitable choice of a priori information, regularization constraints, measurement and background error statistics. An inversion technique is introduced here for an optimal reconstruction of unknown releases using limited concentration measurements. This is based on adjoint representation of the source-receptor relationship and utilization of a weight function which exhibits a priori information about the unknown releases apparent to the monitoring network. The properties of the weight function provide an optimal data resolution and model resolution to the retrieved source estimates. The retrieved source estimates are proved theoretically to be stable against the random measurement errors and their reliability can be interpreted in terms of the distribution of the weight functions. Further, the same framework can be extended for the identification of the point type releases by utilizing the maximum of the retrieved source estimates. The inversion technique has been evaluated with the several diffusion experiments, like, Idaho low wind diffusion experiment (1974), IIT Delhi tracer experiment (1991), European Tracer Experiment (1994), Fusion Field Trials (2007), etc. In case of point release experiments, the source parameters are mostly retrieved close to the true source parameters with least error. Primarily, the proposed technique overcomes two major difficulties incurred in the source reconstruction: (i) The initialization of the source parameters as required by the optimization based techniques. The converged solution depends on their initialization. (ii) The statistical knowledge about the measurement and background errors as required by the Bayesian inference based techniques. These are hypothetically assumed in case of no prior knowledge.

Approximation-based adaptive tracking control of pure-feedback nonlinear systems with multiple unknown time-varying delays.

PubMed

Wang, Min; Ge, Shuzhi Sam; Hong, Keum-Shik

2010-11-01

This paper presents adaptive neural tracking control for a class of non-affine pure-feedback systems with multiple unknown state time-varying delays. To overcome the design difficulty from non-affine structure of pure-feedback system, mean value theorem is exploited to deduce affine appearance of state variables x(i) as virtual controls α(i), and of the actual control u. The separation technique is introduced to decompose unknown functions of all time-varying delayed states into a series of continuous functions of each delayed state. The novel Lyapunov-Krasovskii functionals are employed to compensate for the unknown functions of current delayed state, which is effectively free from any restriction on unknown time-delay functions and overcomes the circular construction of controller caused by the neural approximation of a function of u and [Formula: see text] . Novel continuous functions are introduced to overcome the design difficulty deduced from the use of one adaptive parameter. To achieve uniformly ultimate boundedness of all the signals in the closed-loop system and tracking performance, control gains are effectively modified as a dynamic form with a class of even function, which makes stability analysis be carried out at the present of multiple time-varying delays. Simulation studies are provided to demonstrate the effectiveness of the proposed scheme.

Existence conditions for unknown input functional observers

NASA Astrophysics Data System (ADS)

Fernando, T.; MacDougall, S.; Sreeram, V.; Trinh, H.

2013-01-01

This article presents necessary and sufficient conditions for the existence and design of an unknown input Functional observer. The existence of the observer can be verified by computing a nullspace of a known matrix and testing some matrix rank conditions. The existence of the observer does not require the satisfaction of the observer matching condition (i.e. Equation (16) in Hou and Muller 1992, 'Design of Observers for Linear Systems with Unknown Inputs', IEEE Transactions on Automatic Control, 37, 871-875), is not limited to estimating scalar functionals and allows for arbitrary pole placement. The proposed observer always exists when a state observer exists for the unknown input system, and furthermore, the proposed observer can exist even in some instances when an unknown input state observer does not exist.

A new statistical method for design and analyses of component tolerance

NASA Astrophysics Data System (ADS)

Movahedi, Mohammad Mehdi; Khounsiavash, Mohsen; Otadi, Mahmood; Mosleh, Maryam

2017-03-01

Tolerancing conducted by design engineers to meet customers' needs is a prerequisite for producing high-quality products. Engineers use handbooks to conduct tolerancing. While use of statistical methods for tolerancing is not something new, engineers often use known distributions, including the normal distribution. Yet, if the statistical distribution of the given variable is unknown, a new statistical method will be employed to design tolerance. In this paper, we use generalized lambda distribution for design and analyses component tolerance. We use percentile method (PM) to estimate the distribution parameters. The findings indicated that, when the distribution of the component data is unknown, the proposed method can be used to expedite the design of component tolerance. Moreover, in the case of assembled sets, more extensive tolerance for each component with the same target performance can be utilized.

An improved methodology of asymmetric flow field flow fractionation hyphenated with inductively coupled mass spectrometry for the determination of size distribution of gold nanoparticles in dietary supplements.

PubMed

Mudalige, Thilak K; Qu, Haiou; Linder, Sean W

2015-11-13

Engineered nanoparticles are available in large numbers of commercial products claiming various health benefits. Nanoparticle absorption, distribution, metabolism, excretion, and toxicity in a biological system are dependent on particle size, thus the determination of size and size distribution is essential for full characterization. Number based average size and size distribution is a major parameter for full characterization of the nanoparticle. In the case of polydispersed samples, large numbers of particles are needed to obtain accurate size distribution data. Herein, we report a rapid methodology, demonstrating improved nanoparticle recovery and excellent size resolution, for the characterization of gold nanoparticles in dietary supplements using asymmetric flow field flow fractionation coupled with visible absorption spectrometry and inductively coupled plasma mass spectrometry. A linear relationship between gold nanoparticle size and retention times was observed, and used for characterization of unknown samples. The particle size results from unknown samples were compared to results from traditional size analysis by transmission electron microscopy, and found to have less than a 5% deviation in size for unknown product over the size range from 7 to 30 nm. Published by Elsevier B.V.

Quantum key distribution with an unknown and untrusted source

NASA Astrophysics Data System (ADS)

Zhao, Yi; Qi, Bing; Lo, Hoi-Kwong

2008-05-01

The security of a standard bidirectional “plug-and-play” quantum key distribution (QKD) system has been an open question for a long time. This is mainly because its source is equivalently controlled by an eavesdropper, which means the source is unknown and untrusted. Qualitative discussion on this subject has been made previously. In this paper, we solve this question directly by presenting the quantitative security analysis on a general class of QKD protocols whose sources are unknown and untrusted. The securities of standard Bennett-Brassard 1984 protocol, weak+vacuum decoy state protocol, and one-decoy state protocol, with unknown and untrusted sources are rigorously proved. We derive rigorous lower bounds to the secure key generation rates of the above three protocols. Our numerical simulation results show that QKD with an untrusted source gives a key generation rate that is close to that with a trusted source.

Goals Set by Patients Using the ICF Model before Receiving Botulinum Injections and Their Relation to Spasticity Distribution

PubMed Central

Choi, Kevin; Peters, Jaclyn; Tri, Andrew; Chapman, Elizabeth; Sasaki, Ayako; Ismail, Farooq; Boulias, Chris; Reid, Shannon

2017-01-01

Purpose: Goal Attainment Scaling (GAS) is used to assess functional gains in response to treatment. Specific characteristics of the functional goals set by individuals receiving botulinum toxin type A (BoNTA) injections for spasticity management are unknown. The primary objectives of this study were to describe the characteristics of the goals set by patients before receiving BoNTA injections using the International Classification of Functioning, Disability and Health (ICF) and to determine whether the pattern of spasticity distribution affected the goals set. Methods: A cross-sectional retrospective chart review was carried out in an outpatient spasticity-management clinic in Toronto. A total of 176 patients with a variety of neurological lesions attended the clinic to receive BoNTA injections and completed GAS from December 2012 to December 2013. The main outcome measures were the characteristics of the goals set by the participants on the basis of ICF categories (body functions and structures, activity and participation) and the spasticity distribution using Modified Ashworth Scale scores. Results: Of the patients, 73% set activity and participation goals, and 27% set body functions and structures goals (p<0.05). In the activity and participation category, 30% of patients set moving and walking goals, 28% set self-care and dressing goals, and 12% set changing and maintaining body position goals. In the body functions and structures category, 18% set neuromuscular and movement-related goals, and 8% set pain goals. The ICF goal categories were not related to the patterns of spasticity (upper limb vs. lower limb or unilateral vs. bilateral spasticity) or type of upper motor neuron (UMN) lesion (p>0.05). Conclusion: Our results show that patients receiving BoNTA treatment set a higher percentage of activity and participation goals than body functions and structures goals. Goal classification was not affected by type of spasticity distribution or type of UMN disorder. PMID:28539691

Extracting DNA words based on the sequence features: non-uniform distribution and integrity.

PubMed

Li, Zhi; Cao, Hongyan; Cui, Yuehua; Zhang, Yanbo

2016-01-25

DNA sequence can be viewed as an unknown language with words as its functional units. Given that most sequence alignment algorithms such as the motif discovery algorithms depend on the quality of background information about sequences, it is necessary to develop an ab initio algorithm for extracting the "words" based only on the DNA sequences. We considered that non-uniform distribution and integrity were two important features of a word, based on which we developed an ab initio algorithm to extract "DNA words" that have potential functional meaning. A Kolmogorov-Smirnov test was used for consistency test of uniform distribution of DNA sequences, and the integrity was judged by the sequence and position alignment. Two random base sequences were adopted as negative control, and an English book was used as positive control to verify our algorithm. We applied our algorithm to the genomes of Saccharomyces cerevisiae and 10 strains of Escherichia coli to show the utility of the methods. The results provide strong evidences that the algorithm is a promising tool for ab initio building a DNA dictionary. Our method provides a fast way for large scale screening of important DNA elements and offers potential insights into the understanding of a genome.

A Unified Approach to Adaptive Neural Control for Nonlinear Discrete-Time Systems With Nonlinear Dead-Zone Input.

PubMed

Liu, Yan-Jun; Gao, Ying; Tong, Shaocheng; Chen, C L Philip

2016-01-01

In this paper, an effective adaptive control approach is constructed to stabilize a class of nonlinear discrete-time systems, which contain unknown functions, unknown dead-zone input, and unknown control direction. Different from linear dead zone, the dead zone, in this paper, is a kind of nonlinear dead zone. To overcome the noncausal problem, which leads to the control scheme infeasible, the systems can be transformed into a m -step-ahead predictor. Due to nonlinear dead-zone appearance, the transformed predictor still contains the nonaffine function. In addition, it is assumed that the gain function of dead-zone input and the control direction are unknown. These conditions bring about the difficulties and the complicacy in the controller design. Thus, the implicit function theorem is applied to deal with nonaffine dead-zone appearance, the problem caused by the unknown control direction can be resolved through applying the discrete Nussbaum gain, and the neural networks are used to approximate the unknown function. Based on the Lyapunov theory, all the signals of the resulting closed-loop system are proved to be semiglobal uniformly ultimately bounded. Moreover, the tracking error is proved to be regulated to a small neighborhood around zero. The feasibility of the proposed approach is demonstrated by a simulation example.

Hopping in the Crowd to Unveil Network Topology.

PubMed

Asllani, Malbor; Carletti, Timoteo; Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco

2018-04-13

We introduce a nonlinear operator to model diffusion on a complex undirected network under crowded conditions. We show that the asymptotic distribution of diffusing agents is a nonlinear function of the nodes' degree and saturates to a constant value for sufficiently large connectivities, at variance with standard diffusion in the absence of excluded-volume effects. Building on this observation, we define and solve an inverse problem, aimed at reconstructing the a priori unknown connectivity distribution. The method gathers all the necessary information by repeating a limited number of independent measurements of the asymptotic density at a single node, which can be chosen randomly. The technique is successfully tested against both synthetic and real data and is also shown to estimate with great accuracy the total number of nodes.

Hopping in the Crowd to Unveil Network Topology

NASA Astrophysics Data System (ADS)

Asllani, Malbor; Carletti, Timoteo; Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco

2018-04-01

We introduce a nonlinear operator to model diffusion on a complex undirected network under crowded conditions. We show that the asymptotic distribution of diffusing agents is a nonlinear function of the nodes' degree and saturates to a constant value for sufficiently large connectivities, at variance with standard diffusion in the absence of excluded-volume effects. Building on this observation, we define and solve an inverse problem, aimed at reconstructing the a priori unknown connectivity distribution. The method gathers all the necessary information by repeating a limited number of independent measurements of the asymptotic density at a single node, which can be chosen randomly. The technique is successfully tested against both synthetic and real data and is also shown to estimate with great accuracy the total number of nodes.

Proteins of unknown function in the Protein Data Bank (PDB): an inventory of true uncharacterized proteins and computational tools for their analysis.

PubMed

Nadzirin, Nurul; Firdaus-Raih, Mohd

2012-10-08

Proteins of uncharacterized functions form a large part of many of the currently available biological databases and this situation exists even in the Protein Data Bank (PDB). Our analysis of recent PDB data revealed that only 42.53% of PDB entries (1084 coordinate files) that were categorized under "unknown function" are true examples of proteins of unknown function at this point in time. The remainder 1465 entries also annotated as such appear to be able to have their annotations re-assessed, based on the availability of direct functional characterization experiments for the protein itself, or for homologous sequences or structures thus enabling computational function inference.

Dynamics of Geometrically Nonlinear Elastic Nonthin Anisotropic Shells of Variable Thickness

NASA Astrophysics Data System (ADS)

Marchuk, M. V.; Tuchapskii, R. I.

2017-11-01

A theory of dynamic elastic geometrically nonlinear deformation of nonthin anisotropic shells with variable thickness is constructed. Shells are assumed asymmetric about the reference surface. Functions are expanded into Legendre series. The basic equations are written in a coordinate system aligned with the lines of curvature of the reference surface. The equations of motion and appropriate boundary conditions are obtained using the Hamilton-Ostrogradsky variational principle. The change in metric across the thickness is taken into account. The theory assumes that the refinement process is regular and allows deriving equations including products of terms of Legendre series of unknown functions of arbitrary order. The behavior of a square metallic plate acted upon by a pressure pulse distributed over its face is studied.

Probabilistic Modeling of Aircraft Trajectories for Dynamic Separation Volumes

NASA Technical Reports Server (NTRS)

Lewis, Timothy A.

2016-01-01

With a proliferation of new and unconventional vehicles and operations expected in the future, the ab initio airspace design will require new approaches to trajectory prediction for separation assurance and other air traffic management functions. This paper presents an approach to probabilistic modeling of the trajectory of an aircraft when its intent is unknown. The approach uses a set of feature functions to constrain a maximum entropy probability distribution based on a set of observed aircraft trajectories. This model can be used to sample new aircraft trajectories to form an ensemble reflecting the variability in an aircraft's intent. The model learning process ensures that the variability in this ensemble reflects the behavior observed in the original data set. Computational examples are presented.

Benthic meiofaunal community response to the cascading effects of herbivory within an algal halo system of the Great Barrier Reef

PubMed Central

Hammill, Edward; Booth, David J.; Madin, Elizabeth M. P.; Hinchliffe, Charles; Harborne, Alastair R.; Lovelock, Catherine E.; Macreadie, Peter I.; Atwood, Trisha B.

2018-01-01

Benthic fauna play a crucial role in organic matter decomposition and nutrient cycling at the sediment-water boundary in aquatic ecosystems. In terrestrial systems, grazing herbivores have been shown to influence below-ground communities through alterations to plant distribution and composition, however whether similar cascading effects occur in aquatic systems is unknown. Here, we assess the relationship between benthic invertebrates and above-ground fish grazing across the ‘grazing halos’ of Heron Island lagoon, Australia. Grazing halos, which occur around patch reefs globally, are caused by removal of seagrass or benthic macroalgae by herbivorous fish that results in distinct bands of unvegetated sediments surrounding patch reefs. We found that benthic algal canopy height significantly increased with distance from patch reef, and that algal canopy height was positively correlated with the abundances of only one invertebrate taxon (Nematoda). Both sediment carbon to nitrogen ratios (C:N) and mean sediment particle size (μm) demonstrated a positive correlation with Nematoda and Arthropoda (predominantly copepod) abundances, respectively. These positive correlations indicate that environmental conditions are a major contributor to benthic invertebrate community distribution, acting on benthic communities in conjunction with the cascading effects of above-ground algal grazing. These results suggest that benthic communities, and the ecosystem functions they perform in this system, may be less responsive to changes in above-ground herbivorous processes than those previously studied in terrestrial systems. Understanding how above-ground organisms, and processes, affect their benthic invertebrate counterparts can shed light on how changes in aquatic communities may affect ecosystem function in previously unknown ways. PMID:29513746

Benthic meiofaunal community response to the cascading effects of herbivory within an algal halo system of the Great Barrier Reef.

PubMed

Ollivier, Quinn R; Hammill, Edward; Booth, David J; Madin, Elizabeth M P; Hinchliffe, Charles; Harborne, Alastair R; Lovelock, Catherine E; Macreadie, Peter I; Atwood, Trisha B

2018-01-01

Benthic fauna play a crucial role in organic matter decomposition and nutrient cycling at the sediment-water boundary in aquatic ecosystems. In terrestrial systems, grazing herbivores have been shown to influence below-ground communities through alterations to plant distribution and composition, however whether similar cascading effects occur in aquatic systems is unknown. Here, we assess the relationship between benthic invertebrates and above-ground fish grazing across the 'grazing halos' of Heron Island lagoon, Australia. Grazing halos, which occur around patch reefs globally, are caused by removal of seagrass or benthic macroalgae by herbivorous fish that results in distinct bands of unvegetated sediments surrounding patch reefs. We found that benthic algal canopy height significantly increased with distance from patch reef, and that algal canopy height was positively correlated with the abundances of only one invertebrate taxon (Nematoda). Both sediment carbon to nitrogen ratios (C:N) and mean sediment particle size (μm) demonstrated a positive correlation with Nematoda and Arthropoda (predominantly copepod) abundances, respectively. These positive correlations indicate that environmental conditions are a major contributor to benthic invertebrate community distribution, acting on benthic communities in conjunction with the cascading effects of above-ground algal grazing. These results suggest that benthic communities, and the ecosystem functions they perform in this system, may be less responsive to changes in above-ground herbivorous processes than those previously studied in terrestrial systems. Understanding how above-ground organisms, and processes, affect their benthic invertebrate counterparts can shed light on how changes in aquatic communities may affect ecosystem function in previously unknown ways.

A Robust Deconvolution Method based on Transdimensional Hierarchical Bayesian Inference

NASA Astrophysics Data System (ADS)

Kolb, J.; Lekic, V.

2012-12-01

Analysis of P-S and S-P conversions allows us to map receiver side crustal and lithospheric structure. This analysis often involves deconvolution of the parent wave field from the scattered wave field as a means of suppressing source-side complexity. A variety of deconvolution techniques exist including damped spectral division, Wiener filtering, iterative time-domain deconvolution, and the multitaper method. All of these techniques require estimates of noise characteristics as input parameters. We present a deconvolution method based on transdimensional Hierarchical Bayesian inference in which both noise magnitude and noise correlation are used as parameters in calculating the likelihood probability distribution. Because the noise for P-S and S-P conversion analysis in terms of receiver functions is a combination of both background noise - which is relatively easy to characterize - and signal-generated noise - which is much more difficult to quantify - we treat measurement errors as an known quantity, characterized by a probability density function whose mean and variance are model parameters. This transdimensional Hierarchical Bayesian approach has been successfully used previously in the inversion of receiver functions in terms of shear and compressional wave speeds of an unknown number of layers [1]. In our method we used a Markov chain Monte Carlo (MCMC) algorithm to find the receiver function that best fits the data while accurately assessing the noise parameters. In order to parameterize the receiver function we model the receiver function as an unknown number of Gaussians of unknown amplitude and width. The algorithm takes multiple steps before calculating the acceptance probability of a new model, in order to avoid getting trapped in local misfit minima. Using both observed and synthetic data, we show that the MCMC deconvolution method can accurately obtain a receiver function as well as an estimate of the noise parameters given the parent and daughter components. Furthermore, we demonstrate that this new approach is far less susceptible to generating spurious features even at high noise levels. Finally, the method yields not only the most-likely receiver function, but also quantifies its full uncertainty. [1] Bodin, T., M. Sambridge, H. Tkalčić, P. Arroucau, K. Gallagher, and N. Rawlinson (2012), Transdimensional inversion of receiver functions and surface wave dispersion, J. Geophys. Res., 117, B02301

Determination of the mass function of extra-galactic GMCs via NIR color maps. Testing the method in a disk-like geometry

NASA Astrophysics Data System (ADS)

Kainulainen, J.; Juvela, M.; Alves, J.

2007-06-01

The giant molecular clouds (GMCs) of external galaxies can be mapped with sub-arcsecond resolution using multiband observations in the near-infrared. However, the interpretation of the observed reddening and attenuation of light, and their transformation into physical quantities, is greatly hampered by the effects arising from the unknown geometry and the scattering of light by dust particles. We examine the relation between the observed near-infrared reddening and the column density of the dust clouds. In this paper we particularly assess the feasibility of deriving the mass function of GMCs from near-infrared color excess data. We perform Monte Carlo radiative transfer simulations with 3D models of stellar radiation and clumpy dust distributions. We include the scattered light in the models and calculate near-infrared color maps from the simulated data. The color maps are compared with the true line-of-sight density distributions of the models. We extract clumps from the color maps and compare the observed mass function to the true mass function. For the physical configuration chosen in this study, essentially a face-on geometry, the observed mass function is a non-trivial function of the true mass function with a large number of parameters affecting its exact form. The dynamical range of the observed mass function is confined to 103.5dots 105.5 M_⊙ regardless of the dynamical range of the true mass function. The color maps are more sensitive in detecting the high-mass end of the mass function, and on average the masses of clouds are underestimated by a factor of ˜ 10 depending on the parameters describing the dust distribution. A significant fraction of clouds is expected to remain undetected at all masses. The simulations show that the cloud mass function derived from JHK color excess data using simple foreground screening geometry cannot be regarded as a one-to-one tracer of the underlying mass function.

Observed, unknown distributions of clinical chemical quantities should be considered to be log-normal: a proposal.

PubMed

Haeckel, Rainer; Wosniok, Werner

2010-10-01

The distribution of many quantities in laboratory medicine are considered to be Gaussian if they are symmetric, although, theoretically, a Gaussian distribution is not plausible for quantities that can attain only non-negative values. If a distribution is skewed, further specification of the type is required, which may be difficult to provide. Skewed (non-Gaussian) distributions found in clinical chemistry usually show only moderately large positive skewness (e.g., log-normal- and χ(2) distribution). The degree of skewness depends on the magnitude of the empirical biological variation (CV(e)), as demonstrated using the log-normal distribution. A Gaussian distribution with a small CV(e) (e.g., for plasma sodium) is very similar to a log-normal distribution with the same CV(e). In contrast, a relatively large CV(e) (e.g., plasma aspartate aminotransferase) leads to distinct differences between a Gaussian and a log-normal distribution. If the type of an empirical distribution is unknown, it is proposed that a log-normal distribution be assumed in such cases. This avoids distributional assumptions that are not plausible and does not contradict the observation that distributions with small biological variation look very similar to a Gaussian distribution.

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

NASA Astrophysics Data System (ADS)

Izadi, Arman; Kimiagari, Ali mohammad

2014-01-01

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14% reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

NASA Astrophysics Data System (ADS)

Izadi, Arman; Kimiagari, Ali Mohammad

2014-05-01

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14 % reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

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.

Evolutionary analysis of the jacalin-related lectin family genes in 11 fishes.

PubMed

Cao, Jun; Lv, Yueqing

2016-09-01

Jacalin-related lectins are a type of carbohydrate-binding proteins, which are distributed across a wide variety of organisms and involved in some important biological processes. The evolution of this gene family in fishes is unknown. Here, 47 putative jacalin genes in 11 fish species were identified and divided into 4 groups through phylogenetic analysis. Conserved gene organization and motif distribution existed in each group, suggesting their functional conservation. Some fishes have eleven jacalin genes, while others have only one or zero gene in their genomes, suggesting dynamic changes in the number of jacalin genes during the evolution of fishes. Intragenic recombination played a key role in the evolution of jacalin genes. Synteny analyses of jacalin genes in some fishes implied conserved and dynamic evolution characteristics of this gene family and related genome segments. Moreover, a few functional divergence sites were identified within each group pairs. Divergent expression profiles of the zebra fish jacalin genes were further investigated in different stresses. The results provided a foundation for exploring the characterization of the jacalin genes in fishes and will offer insights for additional functional studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reducing Capacities and Distribution of Redox-Active Functional Groups in Low Molecular Weight Fractions of Humic Acids.

PubMed

Yang, Zhen; Kappler, Andreas; Jiang, Jie

2016-11-15

Humic substances (HS) are redox-active organic compounds with a broad spectrum of molecular sizes and reducing capacities, that is, number of electrons donated or accepted. However, it is unknown which role the distribution of redox-active functional groups in different molecule sizes plays for HS redox reactions in varying pore sizes microenvironments. We used dialysis experiments to separate bulk humic acids (HA) into low molecular weight fractions (LMWF) and retentate, for example, the remaining HA in the dialysis bag. LMWF accounted for only 2% of the total organic carbon content of the HA. However, their reducing capacities per gram of carbon were up to 33 times greater than either those of the bulk HA or the retentate. For a structural/mechanistic understanding of the high reducing capacity of the LMWF, we used fluorescence spectroscopy. We found that the LWMF showed significant fluorescence intensities for quinone-like functional groups, as indicated by the quinoid π-π* transition, that are probably responsible for the high reducing capacities. Therefore, the small-sized HS fraction can play a major role for redox transformation of metals or pollutants trapped in soil micropores (<2.5 nm diameter).

Joint Inversion of 1-Hz GPS Data and Strong Motion Records for the Rupture Process of the 2008 Iwate-Miyagi Nairiku Earthquake: Objectively Determining Relative Weighting

NASA Astrophysics Data System (ADS)

Wang, Z.; Kato, T.; Wang, Y.

2015-12-01

The spatiotemporal fault slip history of the 2008 Iwate-Miyagi Nairiku earthquake, Japan, is obtained by the joint inversion of 1-Hz GPS waveforms and near-field strong motion records. 1-Hz GPS data from GEONET is processed by GAMIT/GLOBK and then a low-pass filter of 0.05 Hz is applied. The ground surface strong motion records from stations of K-NET and Kik-Net are band-pass filtered for the range of 0.05 ~ 0.3 Hz and integrated once to obtain velocity. The joint inversion exploits a broader frequency band for near-field ground motions, which provides excellent constraints for both the detailed slip history and slip distribution. A fully Bayesian inversion method is performed to simultaneously and objectively determine the rupture model, the unknown relative weighting of multiple data sets and the unknown smoothing hyperparameters. The preferred rupture model is stable for different choices of velocity structure model and station distribution, with maximum slip of ~ 8.0 m and seismic moment of 2.9 × 1019 Nm (Mw 6.9). By comparison with the single inversion of strong motion records, the cumulative slip distribution of joint inversion shows sparser slip distribution with two slip asperities. One common slip asperity extends from the hypocenter southeastward to the ground surface of breakage; another slip asperity, which is unique for joint inversion contributed by 1-Hz GPS waveforms, appears in the deep part of fault where very few aftershocks are occurring. The differential moment rate function of joint and single inversions obviously indicates that rich high frequency waves are radiated in the first three seconds but few low frequency waves.

Shedding new light on opsin evolution

PubMed Central

Porter, Megan L.; Blasic, Joseph R.; Bok, Michael J.; Cameron, Evan G.; Pringle, Thomas; Cronin, Thomas W.; Robinson, Phyllis R.

2012-01-01

Opsin proteins are essential molecules in mediating the ability of animals to detect and use light for diverse biological functions. Therefore, understanding the evolutionary history of opsins is key to understanding the evolution of light detection and photoreception in animals. As genomic data have appeared and rapidly expanded in quantity, it has become possible to analyse opsins that functionally and histologically are less well characterized, and thus to examine opsin evolution strictly from a genetic perspective. We have incorporated these new data into a large-scale, genome-based analysis of opsin evolution. We use an extensive phylogeny of currently known opsin sequence diversity as a foundation for examining the evolutionary distributions of key functional features within the opsin clade. This new analysis illustrates the lability of opsin protein-expression patterns, site-specific functionality (i.e. counterion position) and G-protein binding interactions. Further, it demonstrates the limitations of current model organisms, and highlights the need for further characterization of many of the opsin sequence groups with unknown function. PMID:22012981

Photonic Programmable Tele-Cloning Network.

PubMed

Li, Wei; Chen, Ming-Cheng

2016-06-29

The concept of quantum teleportation allows an unknown quantum states to be broadcasted and processed in a distributed quantum network. The quantum information injected into the network can be diluted to distant multi-copies by quantum cloning and processed by arbitrary quantum logic gates which were programed in advance in the network quantum state. A quantum network combines simultaneously these fundamental quantum functions could lead to new intriguing applications. Here we propose a photonic programmable telecloning network based on a four-photon interferometer. The photonic network serves as quantum gate, quantum cloning and quantum teleportation and features experimental advantage of high brightness by photon recycling.

Bayesian methods for characterizing unknown parameters of material models

DOE PAGES

Emery, J. M.; Grigoriu, M. D.; Field Jr., R. V.

2016-02-04

A Bayesian framework is developed for characterizing the unknown parameters of probabilistic models for material properties. In this framework, the unknown parameters are viewed as random and described by their posterior distributions obtained from prior information and measurements of quantities of interest that are observable and depend on the unknown parameters. The proposed Bayesian method is applied to characterize an unknown spatial correlation of the conductivity field in the definition of a stochastic transport equation and to solve this equation by Monte Carlo simulation and stochastic reduced order models (SROMs). As a result, the Bayesian method is also employed tomore » characterize unknown parameters of material properties for laser welds from measurements of peak forces sustained by these welds.« less

Bayesian methods for characterizing unknown parameters of material models

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

Emery, J. M.; Grigoriu, M. D.; Field Jr., R. V.

A Bayesian framework is developed for characterizing the unknown parameters of probabilistic models for material properties. In this framework, the unknown parameters are viewed as random and described by their posterior distributions obtained from prior information and measurements of quantities of interest that are observable and depend on the unknown parameters. The proposed Bayesian method is applied to characterize an unknown spatial correlation of the conductivity field in the definition of a stochastic transport equation and to solve this equation by Monte Carlo simulation and stochastic reduced order models (SROMs). As a result, the Bayesian method is also employed tomore » characterize unknown parameters of material properties for laser welds from measurements of peak forces sustained by these welds.« less

Probabilistic Open Set Recognition

NASA Astrophysics Data System (ADS)

Jain, Lalit Prithviraj

Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary support vector machines. Building from the success of statistical EVT based recognition methods such as PI-SVM and W-SVM on the open set problem, we present a new general supervised learning algorithm for multi-class classification and multi-class open set recognition called the Extreme Value Local Basis (EVLB). The design of this algorithm is motivated by the observation that extrema from known negative class distributions are the closest negative points to any positive sample during training, and thus should be used to define the parameters of a probabilistic decision model. In the EVLB, the kernel distribution for each positive training sample is estimated via an EVT distribution fit over the distances to the separating hyperplane between positive training sample and closest negative samples, with a subset of the overall positive training data retained to form a probabilistic decision boundary. Using this subset as a frame of reference, the probability of a sample at test time decreases as it moves away from the positive class. Possessing this property, the EVLB is well-suited to open set recognition problems where samples from unknown or novel classes are encountered at test. Our experimental evaluation shows that the EVLB provides a substantial improvement in scalability compared to standard radial basis function kernel machines, as well as P I-SVM and W-SVM, with improved accuracy in many cases. We evaluate our algorithm on open set variations of the standard visual learning benchmarks, as well as with an open subset of classes from Caltech 256 and ImageNet. Our experiments show that PI-SVM, WSVM and EVLB provide significant advances over the previous state-of-the-art solutions for the same tasks.

Deducing Electron Properties from Hard X-Ray Observations

NASA Technical Reports Server (NTRS)

Kontar, E. P.; Brown, J. C.; Emslie, A. G.; Hajdas, W.; Holman, G. D.; Hurford, G. J.; Kasparova, J.; Mallik, P. C. V.; Massone, A. M.; McConnell, M. L.;

Quantum key distribution with an unknown and untrusted source

NASA Astrophysics Data System (ADS)

Zhao, Yi; Qi, Bing; Lo, Hoi-Kwong

2009-03-01

The security of a standard bi-directional ``plug & play'' quantum key distribution (QKD) system has been an open question for a long time. This is mainly because its source is equivalently controlled by an eavesdropper, which means the source is unknown and untrusted. Qualitative discussion on this subject has been made previously. In this paper, we present the first quantitative security analysis on a general class of QKD protocols whose sources are unknown and untrusted. The securities of standard BB84 protocol, weak+vacuum decoy state protocol, and one-decoy decoy state protocol, with unknown and untrusted sources are rigorously proved. We derive rigorous lower bounds to the secure key generation rates of the above three protocols. Our numerical simulation results show that QKD with an untrusted source gives a key generation rate that is close to that with a trusted source. Our work is published in [1]. [4pt] [1] Y. Zhao, B. Qi, and H.-K. Lo, Phys. Rev. A, 77:052327 (2008).

Uncertainty Analysis via Failure Domain Characterization: Unrestricted Requirement Functions

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2011-01-01

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. The methods developed herein, which are based on nonlinear constrained optimization, are applicable to requirement functions whose functional dependency on the uncertainty is arbitrary and whose explicit form may even be unknown. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the assumed uncertainty model (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

Cognitive tutoring induces widespread neuroplasticity and remediates brain function in children with mathematical learning disabilities.

PubMed

Iuculano, Teresa; Rosenberg-Lee, Miriam; Richardson, Jennifer; Tenison, Caitlin; Fuchs, Lynn; Supekar, Kaustubh; Menon, Vinod

2015-09-30

Competency with numbers is essential in today's society; yet, up to 20% of children exhibit moderate to severe mathematical learning disabilities (MLD). Behavioural intervention can be effective, but the neurobiological mechanisms underlying successful intervention are unknown. Here we demonstrate that eight weeks of 1:1 cognitive tutoring not only remediates poor performance in children with MLD, but also induces widespread changes in brain activity. Neuroplasticity manifests as normalization of aberrant functional responses in a distributed network of parietal, prefrontal and ventral temporal-occipital areas that support successful numerical problem solving, and is correlated with performance gains. Remarkably, machine learning algorithms show that brain activity patterns in children with MLD are significantly discriminable from neurotypical peers before, but not after, tutoring, suggesting that behavioural gains are not due to compensatory mechanisms. Our study identifies functional brain mechanisms underlying effective intervention in children with MLD and provides novel metrics for assessing response to intervention.

CLUH couples mitochondrial distribution to the energetic and metabolic status.

PubMed

Wakim, Jamal; Goudenege, David; Perrot, Rodolphe; Gueguen, Naig; Desquiret-Dumas, Valerie; Chao de la Barca, Juan Manuel; Dalla Rosa, Ilaria; Manero, Florence; Le Mao, Morgane; Chupin, Stephanie; Chevrollier, Arnaud; Procaccio, Vincent; Bonneau, Dominique; Logan, David C; Reynier, Pascal; Lenaers, Guy; Khiati, Salim

2017-06-01

Mitochondrial dynamics and distribution are critical for supplying ATP in response to energy demand. CLUH is a protein involved in mitochondrial distribution whose dysfunction leads to mitochondrial clustering, the metabolic consequences of which remain unknown. To gain insight into the role of CLUH on mitochondrial energy production and cellular metabolism, we have generated CLUH-knockout cells using CRISPR/Cas9. Mitochondrial clustering was associated with a smaller cell size and with decreased abundance of respiratory complexes, resulting in oxidative phosphorylation (OXPHOS) defects. This energetic impairment was found to be due to the alteration of mitochondrial translation and to a metabolic shift towards glucose dependency. Metabolomic profiling by mass spectroscopy revealed an increase in the concentration of some amino acids, indicating a dysfunctional Krebs cycle, and increased palmitoylcarnitine concentration, indicating an alteration of fatty acid oxidation, and a dramatic decrease in the concentrations of phosphatidylcholine and sphingomyeline, consistent with the decreased cell size. Taken together, our study establishes a clear function for CLUH in coupling mitochondrial distribution to the control of cell energetic and metabolic status. © 2017. Published by The Company of Biologists Ltd.

Genome-wide association studies of obesity and metabolic syndrome.

PubMed

Fall, Tove; Ingelsson, Erik

2014-01-25

Until just a few years ago, the genetic determinants of obesity and metabolic syndrome were largely unknown, with the exception of a few forms of monogenic extreme obesity. Since genome-wide association studies (GWAS) became available, large advances have been made. The first single nucleotide polymorphism robustly associated with increased body mass index (BMI) was in 2007 mapped to a gene with for the time unknown function. This gene, now known as fat mass and obesity associated (FTO) has been repeatedly replicated in several ethnicities and is affecting obesity by regulating appetite. Since the first report from a GWAS of obesity, an increasing number of markers have been shown to be associated with BMI, other measures of obesity or fat distribution and metabolic syndrome. This systematic review of obesity GWAS will summarize genome-wide significant findings for obesity and metabolic syndrome and briefly give a few suggestions of what is to be expected in the next few years. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Kumaraswamy autoregressive moving average models for double bounded environmental data

NASA Astrophysics Data System (ADS)

Bayer, Fábio Mariano; Bayer, Débora Missio; Pumi, Guilherme

2017-12-01

In this paper we introduce the Kumaraswamy autoregressive moving average models (KARMA), which is a dynamic class of models for time series taking values in the double bounded interval (a,b) following the Kumaraswamy distribution. The Kumaraswamy family of distribution is widely applied in many areas, especially hydrology and related fields. Classical examples are time series representing rates and proportions observed over time. In the proposed KARMA model, the median is modeled by a dynamic structure containing autoregressive and moving average terms, time-varying regressors, unknown parameters and a link function. We introduce the new class of models and discuss conditional maximum likelihood estimation, hypothesis testing inference, diagnostic analysis and forecasting. In particular, we provide closed-form expressions for the conditional score vector and conditional Fisher information matrix. An application to environmental real data is presented and discussed.

How much to trust the senses: Likelihood learning

PubMed Central

Sato, Yoshiyuki; Kording, Konrad P.

2014-01-01

Our brain often needs to estimate unknown variables from imperfect information. Our knowledge about the statistical distributions of quantities in our environment (called priors) and currently available information from sensory inputs (called likelihood) are the basis of all Bayesian models of perception and action. While we know that priors are learned, most studies of prior-likelihood integration simply assume that subjects know about the likelihood. However, as the quality of sensory inputs change over time, we also need to learn about new likelihoods. Here, we show that human subjects readily learn the distribution of visual cues (likelihood function) in a way that can be predicted by models of statistically optimal learning. Using a likelihood that depended on color context, we found that a learned likelihood generalized to new priors. Thus, we conclude that subjects learn about likelihood. PMID:25398975

Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency

PubMed Central

Abu Bakr, Muhammad; Lee, Sukhan

2017-01-01

The paradigm of multisensor data fusion has been evolved from a centralized architecture to a decentralized or distributed architecture along with the advancement in sensor and communication technologies. These days, distributed state estimation and data fusion has been widely explored in diverse fields of engineering and control due to its superior performance over the centralized one in terms of flexibility, robustness to failure and cost effectiveness in infrastructure and communication. However, distributed multisensor data fusion is not without technical challenges to overcome: namely, dealing with cross-correlation and inconsistency among state estimates and sensor data. In this paper, we review the key theories and methodologies of distributed multisensor data fusion available to date with a specific focus on handling unknown correlation and data inconsistency. We aim at providing readers with a unifying view out of individual theories and methodologies by presenting a formal analysis of their implications. Finally, several directions of future research are highlighted. PMID:29077035

Confronting the catalytic dark matter encoded by sequenced genomes

PubMed Central

Ellens, Kenneth W.; Christian, Nils; Singh, Charandeep; Satagopam, Venkata P.

2017-01-01

Abstract The post-genomic era has provided researchers with a deluge of protein sequences. However, a significant fraction of the proteins encoded by sequenced genomes remains without an identified function. Here, we aim at determining how many enzymes of uncertain or unknown function are still present in the Saccharomyces cerevisiae and human proteomes. Using information available in the Swiss-Prot, BRENDA and KEGG databases in combination with a Hidden Markov Model-based method, we estimate that >600 yeast and 2000 human proteins (>30% of their proteins of unknown function) are enzymes whose precise function(s) remain(s) to be determined. This illustrates the impressive scale of the ‘unknown enzyme problem’. We extensively review classical biochemical as well as more recent systematic experimental and computational approaches that can be used to support enzyme function discovery research. Finally, we discuss the possible roles of the elusive catalysts in light of recent developments in the fields of enzymology and metabolism as well as the significance of the unknown enzyme problem in the context of metabolic modeling, metabolic engineering and rare disease research. PMID:29059321

Post-glacial redistribution and shifts in productivity of giant kelp forests

PubMed Central

Graham, Michael H.; Kinlan, Brian P.; Grosberg, Richard K.

2010-01-01

Quaternary glacial–interglacial cycles create lasting biogeographic, demographic and genetic effects on ecosystems, yet the ecological effects of ice ages on benthic marine communities are unknown. We analysed long-term datasets to develop a niche-based model of southern Californian giant kelp (Macrocystis pyrifera) forest distribution as a function of oceanography and geomorphology, and synthesized palaeo-oceanographic records to show that late Quaternary climate change probably drove high millennial variability in the distribution and productivity of this foundation species. Our predictions suggest that kelp forest biomass increased up to threefold from the glacial maximum to the mid-Holocene, then rapidly declined by 40–70 per cent to present levels. The peak in kelp forest productivity would have coincided with the earliest coastal archaeological sites in the New World. Similar late Quaternary changes in kelp forest distribution and productivity probably occurred in coastal upwelling systems along active continental margins worldwide, which would have resulted in complex shifts in the relative productivity of terrestrial and marine components of coastal ecosystems. PMID:19846450

Survivorship analysis when cure is a possibility: a Monte Carlo study.

PubMed

Goldman, A I

1984-01-01

Parametric survivorship analyses of clinical trials commonly involves the assumption of a hazard function constant with time. When the empirical curve obviously levels off, one can modify the hazard function model by use of a Gompertz or Weibull distribution with hazard decreasing over time. Some cancer treatments are thought to cure some patients within a short time of initiation. Then, instead of all patients having the same hazard, decreasing over time, a biologically more appropriate model assumes that an unknown proportion (1 - pi) have constant high risk whereas the remaining proportion (pi) have essentially no risk. This paper discusses the maximum likelihood estimation of pi and the power curves of the likelihood ratio test. Monte Carlo studies provide results for a variety of simulated trials; empirical data illustrate the methods.

Minimal-Approximation-Based Decentralized Backstepping Control of Interconnected Time-Delay Systems.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2016-12-01

A decentralized adaptive backstepping control design using minimal function approximators is proposed for nonlinear large-scale systems with unknown unmatched time-varying delayed interactions and unknown backlash-like hysteresis nonlinearities. Compared with existing decentralized backstepping methods, the contribution of this paper is to design a simple local control law for each subsystem, consisting of an actual control with one adaptive function approximator, without requiring the use of multiple function approximators and regardless of the order of each subsystem. The virtual controllers for each subsystem are used as intermediate signals for designing a local actual control at the last step. For each subsystem, a lumped unknown function including the unknown nonlinear terms and the hysteresis nonlinearities is derived at the last step and is estimated by one function approximator. Thus, the proposed approach only uses one function approximator to implement each local controller, while existing decentralized backstepping control methods require the number of function approximators equal to the order of each subsystem and a calculation of virtual controllers to implement each local actual controller. The stability of the total controlled closed-loop system is analyzed using the Lyapunov stability theorem.

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

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

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

Joint Bayesian Estimation of Quasar Continua and the Lyα Forest Flux Probability Distribution Function

NASA Astrophysics Data System (ADS)

Eilers, Anna-Christina; Hennawi, Joseph F.; Lee, Khee-Gan

2017-08-01

We present a new Bayesian algorithm making use of Markov Chain Monte Carlo sampling that allows us to simultaneously estimate the unknown continuum level of each quasar in an ensemble of high-resolution spectra, as well as their common probability distribution function (PDF) for the transmitted Lyα forest flux. This fully automated PDF regulated continuum fitting method models the unknown quasar continuum with a linear principal component analysis (PCA) basis, with the PCA coefficients treated as nuisance parameters. The method allows one to estimate parameters governing the thermal state of the intergalactic medium (IGM), such as the slope of the temperature-density relation γ -1, while marginalizing out continuum uncertainties in a fully Bayesian way. Using realistic mock quasar spectra created from a simplified semi-numerical model of the IGM, we show that this method recovers the underlying quasar continua to a precision of ≃ 7 % and ≃ 10 % at z = 3 and z = 5, respectively. Given the number of principal component spectra, this is comparable to the underlying accuracy of the PCA model itself. Most importantly, we show that we can achieve a nearly unbiased estimate of the slope γ -1 of the IGM temperature-density relation with a precision of +/- 8.6 % at z = 3 and +/- 6.1 % at z = 5, for an ensemble of ten mock high-resolution quasar spectra. Applying this method to real quasar spectra and comparing to a more realistic IGM model from hydrodynamical simulations would enable precise measurements of the thermal and cosmological parameters governing the IGM, albeit with somewhat larger uncertainties, given the increased flexibility of the model.

Genome-Wide Association Study of the Genetic Determinants of Emphysema Distribution.

PubMed

Boueiz, Adel; Lutz, Sharon M; Cho, Michael H; Hersh, Craig P; Bowler, Russell P; Washko, George R; Halper-Stromberg, Eitan; Bakke, Per; Gulsvik, Amund; Laird, Nan M; Beaty, Terri H; Coxson, Harvey O; Crapo, James D; Silverman, Edwin K; Castaldi, Peter J; DeMeo, Dawn L

2017-03-15

Emphysema has considerable variability in the severity and distribution of parenchymal destruction throughout the lungs. Upper lobe-predominant emphysema has emerged as an important predictor of response to lung volume reduction surgery. Yet, aside from alpha-1 antitrypsin deficiency, the genetic determinants of emphysema distribution remain largely unknown. To identify the genetic influences of emphysema distribution in non-alpha-1 antitrypsin-deficient smokers. A total of 11,532 subjects with complete genotype and computed tomography densitometry data in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]; non-Hispanic white and African American), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), and GenKOLS (Genetics of Chronic Obstructive Lung Disease) studies were analyzed. Two computed tomography scan emphysema distribution measures (difference between upper-third and lower-third emphysema; ratio of upper-third to lower-third emphysema) were tested for genetic associations in all study subjects. Separate analyses in each study population were followed by a fixed effect metaanalysis. Single-nucleotide polymorphism-, gene-, and pathway-based approaches were used. In silico functional evaluation was also performed. We identified five loci associated with emphysema distribution at genome-wide significance. These loci included two previously reported associations with COPD susceptibility (4q31 near HHIP and 15q25 near CHRNA5) and three new associations near SOWAHB, TRAPPC9, and KIAA1462. Gene set analysis and in silico functional evaluation revealed pathways and cell types that may potentially contribute to the pathogenesis of emphysema distribution. This multicohort genome-wide association study identified new genomic loci associated with differential emphysematous destruction throughout the lungs. These findings may point to new biologic pathways on which to expand diagnostic and therapeutic approaches in chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764).

Nonparametric density estimation and optimal bandwidth selection for protein unfolding and unbinding data

NASA Astrophysics Data System (ADS)

Bura, E.; Zhmurov, A.; Barsegov, V.

2009-01-01

Dynamic force spectroscopy and steered molecular simulations have become powerful tools for analyzing the mechanical properties of proteins, and the strength of protein-protein complexes and aggregates. Probability density functions of the unfolding forces and unfolding times for proteins, and rupture forces and bond lifetimes for protein-protein complexes allow quantification of the forced unfolding and unbinding transitions, and mapping the biomolecular free energy landscape. The inference of the unknown probability distribution functions from the experimental and simulated forced unfolding and unbinding data, as well as the assessment of analytically tractable models of the protein unfolding and unbinding requires the use of a bandwidth. The choice of this quantity is typically subjective as it draws heavily on the investigator's intuition and past experience. We describe several approaches for selecting the "optimal bandwidth" for nonparametric density estimators, such as the traditionally used histogram and the more advanced kernel density estimators. The performance of these methods is tested on unimodal and multimodal skewed, long-tailed distributed data, as typically observed in force spectroscopy experiments and in molecular pulling simulations. The results of these studies can serve as a guideline for selecting the optimal bandwidth to resolve the underlying distributions from the forced unfolding and unbinding data for proteins.

A Core Regulatory Pathway Controlling Rice Tiller Angle Mediated by the LAZY1-dependent Asymmetric Distribution of Auxin.

PubMed

Zhang, Ning; Yu, Hong; Yu, Hao; Cai, Yueyue; Huang, Linzhou; Xu, Cao; Xiong, Guosheng; Meng, Xiangbing; Wang, Jiyao; Chen, Haofeng; Liu, Guifu; Jing, Yanhui; Yuan, Yundong; Liang, Yan; Li, Shujia; Smith, Steven M; Li, Jiayang; Wang, Yonghong

2018-06-18

Tiller angle in cereals is a key shoot architecture trait that strongly influences grain yield. Studies in rice (Oryza sativa L.) have implicated shoot gravitropism in the regulation of tiller angle. However, the functional link between shoot gravitropism and tiller angle is unknown. Here, we conducted a large-scale transcriptome analysis of rice shoots in response to gravistimulation and identified two new nodes of a shoot gravitropism regulatory gene network that also controls rice tiller angle. We demonstrate that HEAT STRESS TRANSCRIPTION FACTOR 2D (HSFA2D) is an upstream positive regulator of the LAZY1-mediated asymmetric auxin distribution pathway. We also show that two functionally redundant transcription factor genes, WUSCHEL RELATED HOMEOBOX6 (WOX6) and WOX11, are expressed asymmetrically in response to auxin to connect gravitropism responses with the control of rice tiller angle. These findings define upstream and downstream genetic components that link shoot gravitropism, asymmetric auxin distribution, and rice tiller angle. The results highlight the power of the high-temporal-resolution RNA-seq dataset, and its use to explore further genetic components controlling tiller angle. Collectively these approaches will identify genes to improve grain yields by facilitating the optimization of plant architecture. © 2018 American Society of Plant Biologists. All rights reserved.

Distribution dynamics and functional importance of NHERF1 in regulation of Mrp-2 trafficking in hepatocytes.

PubMed

Karvar, Serhan; Suda, Jo; Zhu, Lixin; Rockey, Don C

2014-10-15

Na(+)/H(+) exchanger regulatory factor 1 (NHERF1) is a multifunctional scaffolding protein that interacts with receptors and ion transporters in its PDZ domains and with the ezrin-radixin-moesin (ERM) family of proteins in its COOH terminus. The role of NHERF1 in hepatocyte function remains largely unknown. We examine the distribution and physiological significance of NHERF1 and multidrug resistance-associated protein 2 (Mrp-2) in hepatocytes. A WT radixin binding site mutant (F355R) and NHERF1 PDZ1 and PDZ2 domain adenoviral mutant constructs were tagged with yellow fluorescent protein and expressed in polarized hepatocytes to study localization and function of NHERF1. Cellular distribution of NHERF1 and radixin was visualized by fluorescence microscopy. A 5-chloromethylfluorescein diacetate (CMFDA) assay was used to characterize Mrp-2 function. Similar to Mrp-2, WT NHERF1 and the NHERF1 PDZ2 deletion mutant were localized to the canalicular membrane. In contrast, the radixin binding site mutant (F355R) and the NHERF1 PDZ1 deletion mutant, which interacts poorly with Mrp-2, were rarely associated with the canalicular membrane. Knockdown of NHERF1 led to dramatically impaired CMFDA secretory response. Use of CMFDA showed that the NHERF1 PDZ1 and F355R mutants were devoid of a secretory response, while WT NHERF1-infected cells exhibited increased secretion of glutathione-methylfluorescein. The data indicate that NHERF1 interacts with Mrp-2 via the PDZ1 domain of NHERF1 and, furthermore, that NHERF1 is essential for maintaining the localization and function of Mrp-2. Copyright © 2014 the American Physiological Society.

Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations

PubMed Central

Araya, Carlos L.; Cenik, Can; Reuter, Jason A.; Kiss, Gert; Pande, Vijay S.; Snyder, Michael P.; Greenleaf, William J.

2015-01-01

Cancer sequencing studies have primarily identified cancer-driver genes by the accumulation of protein-altering mutations. An improved method would be annotation-independent, sensitive to unknown distributions of functions within proteins, and inclusive of non-coding drivers. We employed density-based clustering methods in 21 tumor types to detect variably-sized significantly mutated regions (SMRs). SMRs reveal recurrent alterations across a spectrum of coding and non-coding elements, including transcription factor binding sites and untranslated regions mutated in up to ∼15% of specific tumor types. SMRs reveal spatial clustering of mutations at molecular domains and interfaces, often with associated changes in signaling. Mutation frequencies in SMRs demonstrate that distinct protein regions are differentially mutated among tumor types, as exemplified by a linker region of PIK3CA in which biophysical simulations suggest mutations affect regulatory interactions. The functional diversity of SMRs underscores both the varied mechanisms of oncogenic misregulation and the advantage of functionally-agnostic driver identification. PMID:26691984

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

An approximate solution for interlaminar stresses in laminated composites: Applied mechanics program

NASA Technical Reports Server (NTRS)

Rose, Cheryl A.; Herakovich, Carl T.

1992-01-01

An approximate solution for interlaminar stresses in finite width, laminated composites subjected to uniform extensional, and bending loads is presented. The solution is based upon the principle of minimum complementary energy and an assumed, statically admissible stress state, derived by considering local material mismatch effects and global equilibrium requirements. The stresses in each layer are approximated by polynomial functions of the thickness coordinate, multiplied by combinations of exponential functions of the in-plane coordinate, expressed in terms of fourteen unknown decay parameters. Imposing the stationary condition of the laminate complementary energy with respect to the unknown variables yields a system of fourteen non-linear algebraic equations for the parameters. Newton's method is implemented to solve this system. Once the parameters are known, the stresses can be easily determined at any point in the laminate. Results are presented for through-thickness and interlaminar stress distributions for angle-ply, cross-ply (symmetric and unsymmetric laminates), and quasi-isotropic laminates subjected to uniform extension and bending. It is shown that the solution compares well with existing finite element solutions and represents an improved approximate solution for interlaminar stresses, primarily at interfaces where global equilibrium is satisfied by the in-plane stresses, but large local mismatch in properties requires the presence of interlaminar stresses.

4. VIEW NORTHEAST, radar tower (unknown function), prime search radar ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

4. VIEW NORTHEAST, radar tower (unknown function), prime search radar tower, emergency power building, and height finder radar tower - Fort Custer Military Reservation, P-67 Radar Station, .25 mile north of Dickman Road, east of Clark Road, Battle Creek, Calhoun County, MI

On the joint bimodality of temperature and moisture near stratocumulus cloud tops

NASA Technical Reports Server (NTRS)

Randall, D. A.

1983-01-01

The observed distributions of the thermodynamic variables near stratocumulus top are highly bimodal. Two simple models of sub-grid fractional cloudiness motivated by this observed bimodality are examined. In both models, certain low order moments of two independent, moist-conservative thermodynamic variables are assumed to be known. The first model is based on the assumption of two discrete populations of parcels: a warm-day population and a cool-moist population. If only the first and second moments are assumed to be known, the number of unknowns exceeds the number of independent equations. If the third moments are assumed to be known as well, the number of independent equations exceeds the number of unknowns. The second model is based on the assumption of a continuous joint bimodal distribution of parcels, obtained as the weighted sum of two binormal distributions. For this model, the third moments are used to obtain 9 independent nonlinear algebraic equations in 11 unknowns. Two additional equations are needed to determine the covariance within the two subpopulations. In case these two internal covariance vanish, the system of equations can be solved analytically.

Abundance and functional diversity of riboswitches in microbial communities

PubMed Central

Kazanov, Marat D; Vitreschak, Alexey G; Gelfand, Mikhail S

2007-01-01

Background Several recently completed large-scale enviromental sequencing projects produced a large amount of genetic information about microbial communities ('metagenomes') which is not biased towards cultured organisms. It is a good source for estimation of the abundance of genes and regulatory structures in both known and unknown members of microbial communities. In this study we consider the distribution of RNA regulatory structures, riboswitches, in the Sargasso Sea, Minnesota Soil and Whale Falls metagenomes. Results Over three hundred riboswitches were found in about 2 Gbp metagenome DNA sequences. The abundabce of riboswitches in metagenomes was highest for the TPP, B12 and GCVT riboswitches; the S-box, RFN, YKKC/YXKD, YYBP/YKOY regulatory elements showed lower but significant abundance, while the LYS, G-box, GLMS and YKOK riboswitches were rare. Regions downstream of identified riboswitches were scanned for open reading frames. Comparative analysis of identified ORFs revealed new riboswitch-regulated functions for several classes of riboswitches. In particular, we have observed phosphoserine aminotransferase serC (COG1932) and malate synthase glcB (COG2225) to be regulated by the glycine (GCVT) riboswitch; fatty acid desaturase ole1 (COG1398), by the cobalamin (B12) riboswitch; 5-methylthioribose-1-phosphate isomerase ykrS (COG0182), by the SAM-riboswitch. We also identified conserved riboswitches upstream of genes of unknown function: thiamine (TPP), cobalamine (B12), and glycine (GCVT, upstream of genes from COG4198). Conclusion This study demonstrates applicability of bioinformatics to the analysis of RNA regulatory structures in metagenomes. PMID:17908319

A comparison between Gauss-Newton and Markov chain Monte Carlo basedmethods for inverting spectral induced polarization data for Cole-Coleparameters

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

Chen, Jinsong; Kemna, Andreas; Hubbard, Susan S.

2008-05-15

We develop a Bayesian model to invert spectral induced polarization (SIP) data for Cole-Cole parameters using Markov chain Monte Carlo (MCMC) sampling methods. We compare the performance of the MCMC based stochastic method with an iterative Gauss-Newton based deterministic method for Cole-Cole parameter estimation through inversion of synthetic and laboratory SIP data. The Gauss-Newton based method can provide an optimal solution for given objective functions under constraints, but the obtained optimal solution generally depends on the choice of initial values and the estimated uncertainty information is often inaccurate or insufficient. In contrast, the MCMC based inversion method provides extensive globalmore » information on unknown parameters, such as the marginal probability distribution functions, from which we can obtain better estimates and tighter uncertainty bounds of the parameters than with the deterministic method. Additionally, the results obtained with the MCMC method are independent of the choice of initial values. Because the MCMC based method does not explicitly offer single optimal solution for given objective functions, the deterministic and stochastic methods can complement each other. For example, the stochastic method can first be used to obtain the means of the unknown parameters by starting from an arbitrary set of initial values and the deterministic method can then be initiated using the means as starting values to obtain the optimal estimates of the Cole-Cole parameters.« less

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

NASA Technical Reports Server (NTRS)

Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

2002-01-01

The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 x g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies.

Photonic Programmable Tele-Cloning Network

PubMed Central

Li, Wei; Chen, Ming-Cheng

2016-01-01

The concept of quantum teleportation allows an unknown quantum states to be broadcasted and processed in a distributed quantum network. The quantum information injected into the network can be diluted to distant multi-copies by quantum cloning and processed by arbitrary quantum logic gates which were programed in advance in the network quantum state. A quantum network combines simultaneously these fundamental quantum functions could lead to new intriguing applications. Here we propose a photonic programmable telecloning network based on a four-photon interferometer. The photonic network serves as quantum gate, quantum cloning and quantum teleportation and features experimental advantage of high brightness by photon recycling. PMID:27353838

Upstream mononucleotide A-repeats play a cis-regulatory role in mammals through the DICER1 and Ago proteins.

PubMed

Aporntewan, Chatchawit; Pin-on, Piyapat; Chaiyaratana, Nachol; Pongpanich, Monnat; Boonyaratanakornkit, Viroj; Mutirangura, Apiwat

2013-10-01

A-repeats are the simplest form of tandem repeats and are found ubiquitously throughout genomes. These mononucleotide repeats have been widely believed to be non-functional 'junk' DNA. However, studies in yeasts suggest that A-repeats play crucial biological functions, and their role in humans remains largely unknown. Here, we showed a non-random pattern of distribution of sense A- and T-repeats within 20 kb around transcription start sites (TSSs) in the human genome. Different distributions of these repeats are observed upstream and downstream of TSSs. Sense A-repeats are enriched upstream, whereas sense T-repeats are enriched downstream of TSSs. This enrichment directly correlates with repeat size. Genes with different functions contain different lengths of repeats. In humans, tissue-specific genes are enriched for short repeats of <10 bp, whereas housekeeping genes are enriched for long repeats of ≥10 bp. We demonstrated that DICER1 and Argonaute proteins are required for the cis-regulatory role of A-repeats. Moreover, in the presence of a synthetic polymer that mimics an A-repeat, protein binding to A-repeats was blocked, resulting in a dramatic change in the expression of genes containing upstream A-repeats. Our findings suggest a length-dependent cis-regulatory function of A-repeats and that Argonaute proteins serve as trans-acting factors, binding to A-repeats.

Altered Expression of ZO-1 and ZO-2 in Sertoli Cells and Loss of Blood-Testis Barrier Integrity in Testicular Carcinoma In Situ1

PubMed Central

Fink, Cornelia; Weigel, Roswitha; Hembes, Tanja; Lauke-Wettwer, Heidrun; Kliesch, Sabine; Bergmann, Martin; Brehm, Ralph H

2006-01-01

Abstract Carcinoma in situ (CIS) is the noninvasive precursor of most human testicular germ cell tumors. In normal seminiferous epithelium, specialized tight junctions between Sertoli cells constitute the major component of the blood-testis barrier. Sertoli cells associated with CIS exhibit impaired maturation status, but their functional significance remains unknown. The aim was to determine whether the blood-testis barrier is morphologically and/or functionally altered. We investigated the expression and distribution pattern of the tight junction proteins zonula occludens (ZO) 1 and 2 in normal seminiferous tubules compared to tubules showing CIS. In normal tubules, ZO-1 and ZO-2 immunostaining was observed at the blood-testis barrier region of adjacent Sertoli cells. Within CIS tubules, ZO-1 and ZO-2 immunoreactivity was reduced at the blood-testis barrier region, but spread to stain the Sertoli cell cytoplasm. Western blot analysis confirmed ZO-1 and ZO-2, and their respective mRNA were shown by RT-PCR. Additionally, we assessed the functional integrity of the blood-testis barrier by lanthanum tracer study. Lanthanum permeated tight junctions in CIS tubules, indicating disruption of the blood-testis barrier. In conclusion, Sertoli cells associated with CIS show an altered distribution of ZO-1 and ZO-2 and lose their blood-testis barrier function. PMID:17217619

Real-time strategy game training: emergence of a cognitive flexibility trait.

PubMed

Glass, Brian D; Maddox, W Todd; Love, Bradley C

2013-01-01

Training in action video games can increase the speed of perceptual processing. However, it is unknown whether video-game training can lead to broad-based changes in higher-level competencies such as cognitive flexibility, a core and neurally distributed component of cognition. To determine whether video gaming can enhance cognitive flexibility and, if so, why these changes occur, the current study compares two versions of a real-time strategy (RTS) game. Using a meta-analytic Bayes factor approach, we found that the gaming condition that emphasized maintenance and rapid switching between multiple information and action sources led to a large increase in cognitive flexibility as measured by a wide array of non-video gaming tasks. Theoretically, the results suggest that the distributed brain networks supporting cognitive flexibility can be tuned by engrossing video game experience that stresses maintenance and rapid manipulation of multiple information sources. Practically, these results suggest avenues for increasing cognitive function.

The topography of mutational processes in breast cancer genomes.

PubMed

Morganella, Sandro; Alexandrov, Ludmil B; Glodzik, Dominik; Zou, Xueqing; Davies, Helen; Staaf, Johan; Sieuwerts, Anieta M; Brinkman, Arie B; Martin, Sancha; Ramakrishna, Manasa; Butler, Adam; Kim, Hyung-Yong; Borg, Åke; Sotiriou, Christos; Futreal, P Andrew; Campbell, Peter J; Span, Paul N; Van Laere, Steven; Lakhani, Sunil R; Eyfjord, Jorunn E; Thompson, Alastair M; Stunnenberg, Hendrik G; van de Vijver, Marc J; Martens, John W M; Børresen-Dale, Anne-Lise; Richardson, Andrea L; Kong, Gu; Thomas, Gilles; Sale, Julian; Rada, Cristina; Stratton, Michael R; Birney, Ewan; Nik-Zainal, Serena

2016-05-02

Somatic mutations in human cancers show unevenness in genomic distribution that correlate with aspects of genome structure and function. These mutations are, however, generated by multiple mutational processes operating through the cellular lineage between the fertilized egg and the cancer cell, each composed of specific DNA damage and repair components and leaving its own characteristic mutational signature on the genome. Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, here we show that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription, DNA replication and chromatin organization. This signature-based approach permits visualization of the genomic distribution of mutational processes associated with APOBEC enzymes, mismatch repair deficiency and homologous recombinational repair deficiency, as well as mutational processes of unknown aetiology. Furthermore, it highlights mechanistic insights including a putative replication-dependent mechanism of APOBEC-related mutagenesis.

Real-Time Strategy Game Training: Emergence of a Cognitive Flexibility Trait

PubMed Central

Glass, Brian D.; Maddox, W. Todd; Love, Bradley C.

2013-01-01

Training in action video games can increase the speed of perceptual processing. However, it is unknown whether video-game training can lead to broad-based changes in higher-level competencies such as cognitive flexibility, a core and neurally distributed component of cognition. To determine whether video gaming can enhance cognitive flexibility and, if so, why these changes occur, the current study compares two versions of a real-time strategy (RTS) game. Using a meta-analytic Bayes factor approach, we found that the gaming condition that emphasized maintenance and rapid switching between multiple information and action sources led to a large increase in cognitive flexibility as measured by a wide array of non-video gaming tasks. Theoretically, the results suggest that the distributed brain networks supporting cognitive flexibility can be tuned by engrossing video game experience that stresses maintenance and rapid manipulation of multiple information sources. Practically, these results suggest avenues for increasing cognitive function. PMID:23950921

Differential depth distribution of microbial function and putative symbionts through sediment-hosted aquifers in the deep terrestrial subsurface

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

Probst, Alexander J.; Ladd, Bethany; Jarett, Jessica K.

An enormous diversity of previously unknown bacteria and archaea has been discovered recently, yet their functional capacities and distributions in the terrestrial subsurface remain uncertain. Here, we continually sampled a CO 2-driven geyser (Colorado Plateau, Utah, USA) over its 5-day eruption cycle to test the hypothesis that stratified, sandstone-hosted aquifers sampled over three phases of the eruption cycle have microbial communities that differ both in membership and function. Genome-resolved metagenomics, single-cell genomics and geochemical analyses confirmed this hypothesis and linked microorganisms to groundwater compositions from different depths. Autotrophic Candidatus “Altiarchaeum sp.” and phylogenetically deep-branching nanoarchaea dominate the deepest groundwater. Amore » nanoarchaeon with limited metabolic capacity is inferred to be a potential symbiont of the Ca. “Altiarchaeum”. Candidate Phyla Radiation bacteria are also present in the deepest groundwater and they are relatively abundant in water from intermediate depths. During the recovery phase of the geyser, microaerophilic Fe- and S-oxidizers have high in situ genome replication rates. Autotrophic Sulfurimonas sustained by aerobic sulfide oxidation and with the capacity for N 2 fixation dominate the shallow aquifer. Overall, 104 different phylum-level lineages are present in water from these subsurface environments, with uncultivated archaea and bacteria partitioned to the deeper subsurface.« less

Three-dimensional inverse problem of geometrical optics: a mathematical comparison between Fermat's principle and the eikonal equation.

PubMed

Borghero, Francesco; Demontis, Francesco

2016-09-01

In the framework of geometrical optics, we consider the following inverse problem: given a two-parameter family of curves (congruence) (i.e., f(x,y,z)=c₁,g(x,y,z)=c₂), construct the refractive-index distribution function n=n(x,y,z) of a 3D continuous transparent inhomogeneous isotropic medium, allowing for the creation of the given congruence as a family of monochromatic light rays. We solve this problem by following two different procedures: 1. By applying Fermat's principle, we establish a system of two first-order linear nonhomogeneous PDEs in the unique unknown function n=n(x,y,z) relating the assigned congruence of rays with all possible refractive-index profiles compatible with this family. Moreover, we furnish analytical proof that the family of rays must be a normal congruence. 2. By applying the eikonal equation, we establish a second system of two first-order linear homogeneous PDEs whose solutions give the equation S(x,y,z)=const. of the geometric wavefronts and, consequently, all pertinent refractive-index distribution functions n=n(x,y,z). Finally, we make a comparison between the two procedures described above, discussing appropriate examples having exact solutions.

Differential depth distribution of microbial function and putative symbionts through sediment-hosted aquifers in the deep terrestrial subsurface

DOE PAGES

Probst, Alexander J.; Ladd, Bethany; Jarett, Jessica K.; ...

2018-01-29

An enormous diversity of previously unknown bacteria and archaea has been discovered recently, yet their functional capacities and distributions in the terrestrial subsurface remain uncertain. Here, we continually sampled a CO 2-driven geyser (Colorado Plateau, Utah, USA) over its 5-day eruption cycle to test the hypothesis that stratified, sandstone-hosted aquifers sampled over three phases of the eruption cycle have microbial communities that differ both in membership and function. Genome-resolved metagenomics, single-cell genomics and geochemical analyses confirmed this hypothesis and linked microorganisms to groundwater compositions from different depths. Autotrophic Candidatus “Altiarchaeum sp.” and phylogenetically deep-branching nanoarchaea dominate the deepest groundwater. Amore » nanoarchaeon with limited metabolic capacity is inferred to be a potential symbiont of the Ca. “Altiarchaeum”. Candidate Phyla Radiation bacteria are also present in the deepest groundwater and they are relatively abundant in water from intermediate depths. During the recovery phase of the geyser, microaerophilic Fe- and S-oxidizers have high in situ genome replication rates. Autotrophic Sulfurimonas sustained by aerobic sulfide oxidation and with the capacity for N 2 fixation dominate the shallow aquifer. Overall, 104 different phylum-level lineages are present in water from these subsurface environments, with uncultivated archaea and bacteria partitioned to the deeper subsurface.« less

From Intensity Profile to Surface Normal: Photometric Stereo for Unknown Light Sources and Isotropic Reflectances.

PubMed

Lu, Feng; Matsushita, Yasuyuki; Sato, Imari; Okabe, Takahiro; Sato, Yoichi

2015-10-01

We propose an uncalibrated photometric stereo method that works with general and unknown isotropic reflectances. Our method uses a pixel intensity profile, which is a sequence of radiance intensities recorded at a pixel under unknown varying directional illumination. We show that for general isotropic materials and uniformly distributed light directions, the geodesic distance between intensity profiles is linearly related to the angular difference of their corresponding surface normals, and that the intensity distribution of the intensity profile reveals reflectance properties. Based on these observations, we develop two methods for surface normal estimation; one for a general setting that uses only the recorded intensity profiles, the other for the case where a BRDF database is available while the exact BRDF of the target scene is still unknown. Quantitative and qualitative evaluations are conducted using both synthetic and real-world scenes, which show the state-of-the-art accuracy of smaller than 10 degree without using reference data and 5 degree with reference data for all 100 materials in MERL database.

MRI-based, wireless determination of the transfer function of a linear implant: Introduction of the transfer matrix.

PubMed

Tokaya, Janot P; Raaijmakers, Alexander J E; Luijten, Peter R; van den Berg, Cornelis A T

2018-04-24

We introduce the transfer matrix (TM) that makes MR-based wireless determination of transfer functions (TFs) possible. TFs are implant specific measures for RF-safety assessment of linear implants. The TF relates an incident tangential electric field on an implant to a scattered electric field at its tip that generally governs local heating. The TM extends this concept and relates an incident tangential electric field to a current distribution in the implant therewith characterizing the RF response along the entire implant. The TM is exploited to measure TFs with MRI without hardware alterations. A model of rightward and leftward propagating attenuated waves undergoing multiple reflections is used to derive an analytical expression for the TM. This allows parameterization of the TM of generic implants, e.g., (partially) insulated single wires, in a homogeneous medium in a few unknowns that simultaneously describe the TF. These unknowns can be determined with MRI making it possible to measure the TM and, therefore, also the TF. The TM is able to predict an induced current due to an incident electric field and can be accurately parameterized with a limited number of unknowns. Using this description the TF is determined accurately (with a Pearson correlation coefficient R ≥ 0.9 between measurements and simulations) from MRI acquisitions. The TM enables measuring of TFs with MRI of the tested generic implant models. The MR-based method does not need hardware alterations and is wireless hence making TF determination in more realistic scenarios conceivable. © 2018 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

A unifying view of synchronization for data assimilation in complex nonlinear networks

NASA Astrophysics Data System (ADS)

Abarbanel, Henry D. I.; Shirman, Sasha; Breen, Daniel; Kadakia, Nirag; Rey, Daniel; Armstrong, Eve; Margoliash, Daniel

2017-12-01

Networks of nonlinear systems contain unknown parameters and dynamical degrees of freedom that may not be observable with existing instruments. From observable state variables, we want to estimate the connectivity of a model of such a network and determine the full state of the model at the termination of a temporal observation window during which measurements transfer information to a model of the network. The model state at the termination of a measurement window acts as an initial condition for predicting the future behavior of the network. This allows the validation (or invalidation) of the model as a representation of the dynamical processes producing the observations. Once the model has been tested against new data, it may be utilized as a predictor of responses to innovative stimuli or forcing. We describe a general framework for the tasks involved in the "inverse" problem of determining properties of a model built to represent measured output from physical, biological, or other processes when the measurements are noisy, the model has errors, and the state of the model is unknown when measurements begin. This framework is called statistical data assimilation and is the best one can do in estimating model properties through the use of the conditional probability distributions of the model state variables, conditioned on observations. There is a very broad arena of applications of the methods described. These include numerical weather prediction, properties of nonlinear electrical circuitry, and determining the biophysical properties of functional networks of neurons. Illustrative examples will be given of (1) estimating the connectivity among neurons with known dynamics in a network of unknown connectivity, and (2) estimating the biophysical properties of individual neurons in vitro taken from a functional network underlying vocalization in songbirds.

Universality of optimal measurements

NASA Astrophysics Data System (ADS)

Tarrach, Rolf; Vidal, Guifré

1999-11-01

We present optimal and minimal measurements on identical copies of an unknown state of a quantum bit when the quality of measuring strategies is quantified with the gain of information (Kullback-or mutual information-of probability distributions). We also show that the maximal gain of information occurs, among isotropic priors, when the state is known to be pure. Universality of optimal measurements follows from our results: using the fidelity or the gain of information, two different figures of merits, leads to exactly the same conclusions for isotropic distributions. We finally investigate the optimal capacity of N copies of an unknown state as a quantum channel of information.

Optimal minimal measurements of mixed states

NASA Astrophysics Data System (ADS)

Vidal, G.; Latorre, J. I.; Pascual, P.; Tarrach, R.

1999-07-01

The optimal and minimal measuring strategy is obtained for a two-state system prepared in a mixed state with a probability given by any isotropic a priori distribution. We explicitly construct the specific optimal and minimal generalized measurements, which turn out to be independent of the a priori probability distribution, obtaining the best guesses for the unknown state as well as a closed expression for the maximal mean-average fidelity. We do this for up to three copies of the unknown state in a way that leads to the generalization to any number of copies, which we then present and prove.

Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

PubMed

Chen, Mou; Tao, Gang

2016-08-01

In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.

Consistent Parameter and Transfer Function Estimation using Context Free Grammars

NASA Astrophysics Data System (ADS)

Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten

2017-04-01

This contribution presents a method for the inference of transfer functions for rainfall-runoff models. Here, transfer functions are defined as parametrized (functional) relationships between a set of spatial predictors (e.g. elevation, slope or soil texture) and model parameters. They are ultimately used for estimation of consistent, spatially distributed model parameters from a limited amount of lumped global parameters. Additionally, they provide a straightforward method for parameter extrapolation from one set of basins to another and can even be used to derive parameterizations for multi-scale models [see: Samaniego et al., 2010]. Yet, currently an actual knowledge of the transfer functions is often implicitly assumed. As a matter of fact, for most cases these hypothesized transfer functions can rarely be measured and often remain unknown. Therefore, this contribution presents a general method for the concurrent estimation of the structure of transfer functions and their respective (global) parameters. Note, that by consequence an estimation of the distributed parameters of the rainfall-runoff model is also undertaken. The method combines two steps to achieve this. The first generates different possible transfer functions. The second then estimates the respective global transfer function parameters. The structural estimation of the transfer functions is based on the context free grammar concept. Chomsky first introduced context free grammars in linguistics [Chomsky, 1956]. Since then, they have been widely applied in computer science. But, to the knowledge of the authors, they have so far not been used in hydrology. Therefore, the contribution gives an introduction to context free grammars and shows how they can be constructed and used for the structural inference of transfer functions. This is enabled by new methods from evolutionary computation, such as grammatical evolution [O'Neill, 2001], which make it possible to exploit the constructed grammar as a search space for equations. The parametrization of the transfer functions is then achieved through a second optimization routine. The contribution explores different aspects of the described procedure through a set of experiments. These experiments can be divided into three categories: (1) The inference of transfer functions from directly measurable parameters; (2) The estimation of global parameters for given transfer functions from runoff data; and (3) The estimation of sets of completely unknown transfer functions from runoff data. The conducted tests reveal different potentials and limits of the procedure. In concrete it is shown that example (1) and (2) work remarkably well. Example (3) is much more dependent on the setup. In general, it can be said that in that case much more data is needed to derive transfer function estimations, even for simple models and setups. References: - Chomsky, N. (1956): Three Models for the Description of Language. IT IRETr. 2(3), p 113-124 - O'Neil, M. (2001): Grammatical Evolution. IEEE ToEC, Vol.5, No. 4 - Samaniego, L.; Kumar, R.; Attinger, S. (2010): Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. WWR, Vol. 46, W05523, doi:10.1029/2008WR007327

Computer program determines exact two-sided tolerance limits for normal distributions

NASA Technical Reports Server (NTRS)

Friedman, H. A.; Webb, S. R.

1968-01-01

Computer program determines by numerical integration the exact statistical two-sided tolerance limits, when the proportion between the limits is at least a specified number. The program is limited to situations in which the underlying probability distribution for the population sampled is the normal distribution with unknown mean and variance.

Distributed Synchronization Control of Multiagent Systems With Unknown Nonlinearities.

PubMed

Su, Shize; Lin, Zongli; Garcia, Alfredo

2016-01-01

This paper revisits the distributed adaptive control problem for synchronization of multiagent systems where the dynamics of the agents are nonlinear, nonidentical, unknown, and subject to external disturbances. Two communication topologies, represented, respectively, by a fixed strongly-connected directed graph and by a switching connected undirected graph, are considered. Under both of these communication topologies, we use distributed neural networks to approximate the uncertain dynamics. Decentralized adaptive control protocols are then constructed to solve the cooperative tracker problem, the problem of synchronization of all follower agents to a leader agent. In particular, we show that, under the proposed decentralized control protocols, the synchronization errors are ultimately bounded, and their ultimate bounds can be reduced arbitrarily by choosing the control parameter appropriately. Simulation study verifies the effectiveness of our proposed protocols.

Iterative optimizing quantization method for reconstructing three-dimensional images from a limited number of views

DOEpatents

Lee, Heung-Rae

1997-01-01

A three-dimensional image reconstruction method comprises treating the object of interest as a group of elements with a size that is determined by the resolution of the projection data, e.g., as determined by the size of each pixel. One of the projections is used as a reference projection. A fictitious object is arbitrarily defined that is constrained by such reference projection. The method modifies the known structure of the fictitious object by comparing and optimizing its four projections to those of the unknown structure of the real object and continues to iterate until the optimization is limited by the residual sum of background noise. The method is composed of several sub-processes that acquire four projections from the real data and the fictitious object: generate an arbitrary distribution to define the fictitious object, optimize the four projections, generate a new distribution for the fictitious object, and enhance the reconstructed image. The sub-process for the acquisition of the four projections from the input real data is simply the function of acquiring the four projections from the data of the transmitted intensity. The transmitted intensity represents the density distribution, that is, the distribution of absorption coefficients through the object.

Bayesian assessment of uncertainty in aerosol size distributions and index of refraction retrieved from multiwavelength lidar measurements.

PubMed

Herman, Benjamin R; Gross, Barry; Moshary, Fred; Ahmed, Samir

2008-04-01

We investigate the assessment of uncertainty in the inference of aerosol size distributions from backscatter and extinction measurements that can be obtained from a modern elastic/Raman lidar system with a Nd:YAG laser transmitter. To calculate the uncertainty, an analytic formula for the correlated probability density function (PDF) describing the error for an optical coefficient ratio is derived based on a normally distributed fractional error in the optical coefficients. Assuming a monomodal lognormal particle size distribution of spherical, homogeneous particles with a known index of refraction, we compare the assessment of uncertainty using a more conventional forward Monte Carlo method with that obtained from a Bayesian posterior PDF assuming a uniform prior PDF and show that substantial differences between the two methods exist. In addition, we use the posterior PDF formalism, which was extended to include an unknown refractive index, to find credible sets for a variety of optical measurement scenarios. We find the uncertainty is greatly reduced with the addition of suitable extinction measurements in contrast to the inclusion of extra backscatter coefficients, which we show to have a minimal effect and strengthens similar observations based on numerical regularization methods.

Probabilistic graphs as a conceptual and computational tool in hydrology and water management

NASA Astrophysics Data System (ADS)

Schoups, Gerrit

2014-05-01

Originally developed in the fields of machine learning and artificial intelligence, probabilistic graphs constitute a general framework for modeling complex systems in the presence of uncertainty. The framework consists of three components: 1. Representation of the model as a graph (or network), with nodes depicting random variables in the model (e.g. parameters, states, etc), which are joined together by factors. Factors are local probabilistic or deterministic relations between subsets of variables, which, when multiplied together, yield the joint distribution over all variables. 2. Consistent use of probability theory for quantifying uncertainty, relying on basic rules of probability for assimilating data into the model and expressing unknown variables as a function of observations (via the posterior distribution). 3. Efficient, distributed approximation of the posterior distribution using general-purpose algorithms that exploit model structure encoded in the graph. These attributes make probabilistic graphs potentially useful as a conceptual and computational tool in hydrology and water management (and beyond). Conceptually, they can provide a common framework for existing and new probabilistic modeling approaches (e.g. by drawing inspiration from other fields of application), while computationally they can make probabilistic inference feasible in larger hydrological models. The presentation explores, via examples, some of these benefits.

Fast Radio Bursts’ Recipes for the Distributions of Dispersion Measures, Flux Densities, and Fluences

NASA Astrophysics Data System (ADS)

Niino, Yuu

2018-05-01

We investigate how the statistical properties of dispersion measure (DM) and apparent flux density/fluence of (nonrepeating) fast radio bursts (FRBs) are determined by unknown cosmic rate density history [ρ FRB(z)] and luminosity function (LF) of the transient events. We predict the distributions of DMs, flux densities, and fluences of FRBs taking account of the variation of the receiver efficiency within its beam, using analytical models of ρ FRB(z) and LF. Comparing the predictions with the observations, we show that the cumulative distribution of apparent fluences suggests that FRBs originate at cosmological distances and ρ FRB increases with redshift resembling the cosmic star formation history (CSFH). We also show that an LF model with a bright-end cutoff at log10 L ν (erg s‑1 Hz‑1) ∼ 34 are favored to reproduce the observed DM distribution if ρ FRB(z) ∝ CSFH, although the statistical significance of the constraints obtained with the current size of the observed sample is not high. Finally, we find that the correlation between DM and flux density of FRBs is potentially a powerful tool to distinguish whether FRBs are at cosmological distances or in the local universe more robustly with future observations.

Learning Unknown Event Models

DTIC Science & Technology

2014-07-01

Intelligence (www.aaai.org). All rights reserved. knowledge engineering, but it is often impractical due to high environment variance, or unknown events...distribution unlimited 13. SUPPLEMENTARY NOTES In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence , 27-31 July 2014...autonomy for responding to unexpected events in strategy simulations. Computational Intelligence , 29(2), 187-206. Leake, D. B. (1991), Goal-based

Adaptive sliding control of non-autonomous active suspension systems with time-varying loadings

NASA Astrophysics Data System (ADS)

Chen, Po-Chang; Huang, An-Chyau

2005-04-01

An adaptive sliding controller is proposed in this paper for controlling a non-autonomous quarter-car suspension system with time-varying loadings. The bound of the car-body loading is assumed to be available. Then, the reference coordinate is placed at the static position under the nominal loading so that the system dynamic equation is derived. Due to spring nonlinearities, the system property becomes asymmetric after coordinate transformation. Besides, in practical cases, system parameters are not easy to be obtained precisely for controller design. Therefore, in this paper, system uncertainties are lumped into two unknown time-varying functions. Since the variation bound of one of the unknown functions is not available, conventional adaptive schemes and robust designs are not applicable. To deal with this problem, the function approximation technique is employed to represent the unknown function as a finite combination of basis functions. The Lyapunov direct method can thus be used to find adaptive laws for updating coefficients in the approximating series and to prove stability of the closed-loop system. Since the position and velocity measurements of the unsprung mass are lumped into the unknown function, there is no need to install sensors on the axle and wheel assembly in the actual implementation. Simulation results are presented to show the performance of the proposed strategy.

Altered Cortical Swallowing Processing in Patients with Functional Dysphagia: A Preliminary Study

PubMed Central

Wollbrink, Andreas; Warnecke, Tobias; Winkels, Martin; Pantev, Christo; Dziewas, Rainer

2014-01-01

Objective Current neuroimaging research on functional disturbances provides growing evidence for objective neuronal correlates of allegedly psychogenic symptoms, thereby shifting the disease concept from a psychological towards a neurobiological model. Functional dysphagia is such a rare condition, whose pathogenetic mechanism is largely unknown. In the absence of any organic reason for a patient's persistent swallowing complaints, sensorimotor processing abnormalities involving central neural pathways constitute a potential etiology. Methods In this pilot study we measured cortical swallow-related activation in 5 patients diagnosed with functional dysphagia and a matched group of healthy subjects applying magnetoencephalography. Source localization of cortical activation was done with synthetic aperture magnetometry. To test for significant differences in cortical swallowing processing between groups, a non-parametric permutation test was afterwards performed on individual source localization maps. Results Swallowing task performance was comparable between groups. In relation to control subjects, in whom activation was symmetrically distributed in rostro-medial parts of the sensorimotor cortices of both hemispheres, patients showed prominent activation of the right insula, dorsolateral prefrontal cortex and lateral premotor, motor as well as inferolateral parietal cortex. Furthermore, activation was markedly reduced in the left medial primary sensory cortex as well as right medial sensorimotor cortex and adjacent supplementary motor area (p<0.01). Conclusions Functional dysphagia - a condition with assumed normal brain function - seems to be associated with distinctive changes of the swallow-related cortical activation pattern. Alterations may reflect exaggerated activation of a widely distributed vigilance, self-monitoring and salience rating network that interferes with down-stream deglutition sensorimotor control. PMID:24586948

MUSIC-type imaging of small perfectly conducting cracks with an unknown frequency

NASA Astrophysics Data System (ADS)

Park, Won-Kwang

2015-09-01

MUltiple SIgnal Classification (MUSIC) is a famous non-iterative detection algorithm in inverse scattering problems. However, when the applied frequency is unknown, inaccurate locations are identified via MUSIC. This fact has been confirmed through numerical simulations. However, the reason behind this phenomenon has not been investigated theoretically. Motivated by this fact, we identify the structure of MUSIC-type imaging functionals with unknown frequency, by establishing a relationship with Bessel functions of order zero of the first kind. Through this, we can explain why inaccurate results appear.

Ambient Noise Interferometry and Surface Wave Array Tomography: Promises and Problems

NASA Astrophysics Data System (ADS)

van der Hilst, R. D.; Yao, H.; de Hoop, M. V.; Campman, X.; Solna, K.

2008-12-01

In the late 1990ies most seismologists would have frowned at the possibility of doing high-resolution surface wave tomography with noise instead of with signal associated with ballistic source-receiver propagation. Some may still do, but surface wave tomography with Green's functions estimated through ambient noise interferometry ('sourceless tomography') has transformed from a curiosity into one of the (almost) standard tools for analysis of data from dense seismograph arrays. Indeed, spectacular applications of ambient noise surface wave tomography have recently been published. For example, application to data from arrays in SE Tibet revealed structures in the crust beneath the Tibetan plateau that could not be resolved by traditional tomography (Yao et al., GJI, 2006, 2008). While the approach is conceptually simple, in application the proverbial devil is in the detail. Full reconstruction of the Green's function requires that the wavefields used are diffusive and that ambient noise energy is evenly distributed in the spatial dimensions of interest. In the field, these conditions are not usually met, and (frequency dependent) non-uniformity of the noise sources may lead to incomplete reconstruction of the Green's function. Furthermore, ambient noise distributions can be time-dependent, and seasonal variations have been documented. Naive use of empirical Green's functions may produce (unknown) bias in the tomographic models. The degrading effect on EGFs of the directionality of noise distribution forms particular challenges for applications beyond isotropic surface wave inversions, such as inversions for (azimuthal) anisotropy and attempts to use higher modes (or body waves). Incomplete Green's function reconstruction can (probably) not be prevented, but it may be possible to reduce the problem and - at least - understand the degree of incomplete reconstruction and prevent it from degrading the tomographic model. We will present examples of Rayleigh wave inversions and discuss strategies to mitigate effects of incomplete Green's function reconstruction on tomographic images.

Finding undetected protein associations in cell signaling by belief propagation.

PubMed

Bailly-Bechet, M; Borgs, C; Braunstein, A; Chayes, J; Dagkessamanskaia, A; François, J-M; Zecchina, R

2011-01-11

External information propagates in the cell mainly through signaling cascades and transcriptional activation, allowing it to react to a wide spectrum of environmental changes. High-throughput experiments identify numerous molecular components of such cascades that may, however, interact through unknown partners. Some of them may be detected using data coming from the integration of a protein-protein interaction network and mRNA expression profiles. This inference problem can be mapped onto the problem of finding appropriate optimal connected subgraphs of a network defined by these datasets. The optimization procedure turns out to be computationally intractable in general. Here we present a new distributed algorithm for this task, inspired from statistical physics, and apply this scheme to alpha factor and drug perturbations data in yeast. We identify the role of the COS8 protein, a member of a gene family of previously unknown function, and validate the results by genetic experiments. The algorithm we present is specially suited for very large datasets, can run in parallel, and can be adapted to other problems in systems biology. On renowned benchmarks it outperforms other algorithms in the field.

Interaction of HSP20 with a viral RdRp changes its sub-cellular localization and distribution pattern in plants.

PubMed

Li, Jing; Xiang, Cong-Ying; Yang, Jian; Chen, Jian-Ping; Zhang, Heng-Mu

2015-09-11

Small heat shock proteins (sHSPs) perform a fundamental role in protecting cells against a wide array of stresses but their biological function during viral infection remains unknown. Rice stripe virus (RSV) causes a severe disease of rice in Eastern Asia. OsHSP20 and its homologue (NbHSP20) were used as baits in yeast two-hybrid (YTH) assays to screen an RSV cDNA library and were found to interact with the viral RNA-dependent RNA polymerase (RdRp) of RSV. Interactions were confirmed by pull-down and BiFC assays. Further analysis showed that the N-terminus (residues 1-296) of the RdRp was crucial for the interaction between the HSP20s and viral RdRp and responsible for the alteration of the sub-cellular localization and distribution pattern of HSP20s in protoplasts of rice and epidermal cells of Nicotiana benthamiana. This is the first report that a plant virus or a viral protein alters the expression pattern or sub-cellular distribution of sHSPs.

Ants regulate colony spatial organization using multiple chemical road-signs

PubMed Central

Heyman, Yael; Shental, Noam; Brandis, Alexander; Hefetz, Abraham; Feinerman, Ofer

2017-01-01

Communication provides the basis for social life. In ant colonies, the prevalence of local, often chemically mediated, interactions introduces strong links between communication networks and the spatial distribution of ants. It is, however, unknown how ants identify and maintain nest chambers with distinct functions. Here, we combine individual tracking, chemical analysis and machine learning to decipher the chemical signatures present on multiple nest surfaces. We present evidence for several distinct chemical ‘road-signs' that guide the ants' movements within the dark nest. These chemical signatures can be used to classify nest chambers with different functional roles. Using behavioural manipulations, we demonstrate that at least three of these chemical signatures are functionally meaningful and allow ants from different task groups to identify their specific nest destinations, thus facilitating colony coordination and stabilization. The use of multiple chemicals that assist spatiotemporal guidance, segregation and pattern formation is abundant in multi-cellular organisms. Here, we provide a rare example for the use of these principles in the ant colony. PMID:28569746

Cognitive tutoring induces widespread neuroplasticity and remediates brain function in children with mathematical learning disabilities

PubMed Central

Iuculano, Teresa; Rosenberg-Lee, Miriam; Richardson, Jennifer; Tenison, Caitlin; Fuchs, Lynn; Supekar, Kaustubh; Menon, Vinod

2015-01-01

Competency with numbers is essential in today's society; yet, up to 20% of children exhibit moderate to severe mathematical learning disabilities (MLD). Behavioural intervention can be effective, but the neurobiological mechanisms underlying successful intervention are unknown. Here we demonstrate that eight weeks of 1:1 cognitive tutoring not only remediates poor performance in children with MLD, but also induces widespread changes in brain activity. Neuroplasticity manifests as normalization of aberrant functional responses in a distributed network of parietal, prefrontal and ventral temporal–occipital areas that support successful numerical problem solving, and is correlated with performance gains. Remarkably, machine learning algorithms show that brain activity patterns in children with MLD are significantly discriminable from neurotypical peers before, but not after, tutoring, suggesting that behavioural gains are not due to compensatory mechanisms. Our study identifies functional brain mechanisms underlying effective intervention in children with MLD and provides novel metrics for assessing response to intervention. PMID:26419418

This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms--theory and practice.

PubMed

Harmany, Zachary T; Marcia, Roummel F; Willett, Rebecca M

2012-03-01

Observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Gaussian noise model, and instead require a Poisson noise model. As a result, accurate reconstruction of a spatially or temporally distributed phenomenon (f*) from Poisson data (y) cannot be effectively accomplished by minimizing a conventional penalized least-squares objective function. The problem addressed in this paper is the estimation of f* from y in an inverse problem setting, where the number of unknowns may potentially be larger than the number of observations and f* admits sparse approximation. The optimization formulation considered in this paper uses a penalized negative Poisson log-likelihood objective function with nonnegativity constraints (since Poisson intensities are naturally nonnegative). In particular, the proposed approach incorporates key ideas of using separable quadratic approximations to the objective function at each iteration and penalization terms related to l1 norms of coefficient vectors, total variation seminorms, and partition-based multiscale estimation methods.

COSMOABC: Likelihood-free inference via Population Monte Carlo Approximate Bayesian Computation

NASA Astrophysics Data System (ADS)

Ishida, E. E. O.; Vitenti, S. D. P.; Penna-Lima, M.; Cisewski, J.; de Souza, R. S.; Trindade, A. M. M.; Cameron, E.; Busti, V. C.; COIN Collaboration

2015-11-01

Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogues. Here we present COSMOABC, a Python ABC sampler featuring a Population Monte Carlo variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code is very flexible and can be easily coupled to an external simulator, while allowing to incorporate arbitrary distance and prior functions. As an example of practical application, we coupled COSMOABC with the NUMCOSMO library and demonstrate how it can be used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function. COSMOABC is published under the GPLv3 license on PyPI and GitHub and documentation is available at http://goo.gl/SmB8EX.

Shared neural circuits for mentalizing about the self and others.

PubMed

Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

2010-07-01

Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

Ants regulate colony spatial organization using multiple chemical road-signs.

PubMed

Heyman, Yael; Shental, Noam; Brandis, Alexander; Hefetz, Abraham; Feinerman, Ofer

2017-06-01

Communication provides the basis for social life. In ant colonies, the prevalence of local, often chemically mediated, interactions introduces strong links between communication networks and the spatial distribution of ants. It is, however, unknown how ants identify and maintain nest chambers with distinct functions. Here, we combine individual tracking, chemical analysis and machine learning to decipher the chemical signatures present on multiple nest surfaces. We present evidence for several distinct chemical 'road-signs' that guide the ants' movements within the dark nest. These chemical signatures can be used to classify nest chambers with different functional roles. Using behavioural manipulations, we demonstrate that at least three of these chemical signatures are functionally meaningful and allow ants from different task groups to identify their specific nest destinations, thus facilitating colony coordination and stabilization. The use of multiple chemicals that assist spatiotemporal guidance, segregation and pattern formation is abundant in multi-cellular organisms. Here, we provide a rare example for the use of these principles in the ant colony.

Distinct Cellular and Subcellular Distributions of G Protein-Coupled Receptor Kinase and Arrestin Isoforms in the Striatum

PubMed Central

Bychkov, Evgeny; Zurkovsky, Lilia; Garret, Mika B.; Ahmed, Mohamed R.; Gurevich, Eugenia V.

2012-01-01

G protein-coupled receptor kinases (GRKs) and arrestins mediate desensitization of G protein-coupled receptors (GPCR). Arrestins also mediate G protein-independent signaling via GPCRs. Since GRK and arrestins demonstrate no strict receptor specificity, their functions in the brain may depend on their cellular complement, expression level, and subcellular targeting. However, cellular expression and subcellular distribution of GRKs and arrestins in the brain is largely unknown. We show that GRK isoforms GRK2 and GRK5 are similarly expressed in direct and indirect pathway neurons in the rat striatum. Arrestin-2 and arrestin-3 are also expressed in neurons of both pathways. Cholinergic interneurons are enriched in GRK2, arrestin-3, and GRK5. Parvalbumin-positive interneurons express more of GRK2 and less of arrestin-2 than medium spiny neurons. The GRK5 subcellular distribution in the human striatal neurons is altered by its phosphorylation: unphosphorylated enzyme preferentially localizes to synaptic membranes, whereas phosphorylated GRK5 is found in plasma membrane and cytosolic fractions. Both GRK isoforms are abundant in the nucleus of human striatal neurons, whereas the proportion of both arrestins in the nucleus was equally low. However, overall higher expression of arrestin-2 yields high enough concentration in the nucleus to mediate nuclear functions. These data suggest cell type- and subcellular compartment-dependent differences in GRK/arrestin-mediated desensitization and signaling. PMID:23139825

Distinct cellular and subcellular distributions of G protein-coupled receptor kinase and arrestin isoforms in the striatum.

PubMed

Bychkov, Evgeny; Zurkovsky, Lilia; Garret, Mika B; Ahmed, Mohamed R; Gurevich, Eugenia V

2012-01-01

G protein-coupled receptor kinases (GRKs) and arrestins mediate desensitization of G protein-coupled receptors (GPCR). Arrestins also mediate G protein-independent signaling via GPCRs. Since GRK and arrestins demonstrate no strict receptor specificity, their functions in the brain may depend on their cellular complement, expression level, and subcellular targeting. However, cellular expression and subcellular distribution of GRKs and arrestins in the brain is largely unknown. We show that GRK isoforms GRK2 and GRK5 are similarly expressed in direct and indirect pathway neurons in the rat striatum. Arrestin-2 and arrestin-3 are also expressed in neurons of both pathways. Cholinergic interneurons are enriched in GRK2, arrestin-3, and GRK5. Parvalbumin-positive interneurons express more of GRK2 and less of arrestin-2 than medium spiny neurons. The GRK5 subcellular distribution in the human striatal neurons is altered by its phosphorylation: unphosphorylated enzyme preferentially localizes to synaptic membranes, whereas phosphorylated GRK5 is found in plasma membrane and cytosolic fractions. Both GRK isoforms are abundant in the nucleus of human striatal neurons, whereas the proportion of both arrestins in the nucleus was equally low. However, overall higher expression of arrestin-2 yields high enough concentration in the nucleus to mediate nuclear functions. These data suggest cell type- and subcellular compartment-dependent differences in GRK/arrestin-mediated desensitization and signaling.

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

Uozumi, Naoki; Matsumoto, Hotaru; Saitoh, Hisato, E-mail: hisa@kumamoto-u.ac.jp

The amino-nucleoside antibiotic, puromycin, acts by covalently linking to elongating polypeptide chains on ribosomes to generate prematurely terminated immature polypeptides. The trafficking of puromycin-conjugated (puromycylated) immature polypeptides within cell has, however, remained elusive. In this study, using O-propargyl-puromycin (OP-Puro), the distribution of puromycylated polypeptides was assessed in HeLa cells by click chemistry. Under standard culture conditions, OP-Puro signals were detected in the cytoplasm and nucleus with the highest concentrations in the nucleolus. Intriguingly, when proteasome activities were aborted using MG132, OP-Puro signals began to accumulate at promyelocytic leukemia nuclear bodies (PML-NBs) in addition to the nucleolus. We also found promiscuousmore » association of OP-Puro signals with SUMO-2/3 and ubiquitin at PML-NBs, but not at the nucleolus, during abortive proteasome activities. This study reveals a previously unknown distribution of OP-Puro that argues for a nuclear function in regulating immature protein homeostasis. -- Highlights: •Click chemistry detects O-propargyl-puromycin (OP-Puro) signals in the nucleus. •OP-Puro accumulates at PML-NBs during abortive proteasome activities. •SUMO and ubiquitin are promiscuously associated with OP-Puro at PML-NBs. •The nucleus may function in immature protein homeostasis.« less

PLEMT: A NOVEL PSEUDOLIKELIHOOD BASED EM TEST FOR HOMOGENEITY IN GENERALIZED EXPONENTIAL TILT MIXTURE MODELS.

PubMed

Hong, Chuan; Chen, Yong; Ning, Yang; Wang, Shuang; Wu, Hao; Carroll, Raymond J

2017-01-01

Motivated by analyses of DNA methylation data, we propose a semiparametric mixture model, namely the generalized exponential tilt mixture model, to account for heterogeneity between differentially methylated and non-differentially methylated subjects in the cancer group, and capture the differences in higher order moments (e.g. mean and variance) between subjects in cancer and normal groups. A pairwise pseudolikelihood is constructed to eliminate the unknown nuisance function. To circumvent boundary and non-identifiability problems as in parametric mixture models, we modify the pseudolikelihood by adding a penalty function. In addition, the test with simple asymptotic distribution has computational advantages compared with permutation-based test for high-dimensional genetic or epigenetic data. We propose a pseudolikelihood based expectation-maximization test, and show the proposed test follows a simple chi-squared limiting distribution. Simulation studies show that the proposed test controls Type I errors well and has better power compared to several current tests. In particular, the proposed test outperforms the commonly used tests under all simulation settings considered, especially when there are variance differences between two groups. The proposed test is applied to a real data set to identify differentially methylated sites between ovarian cancer subjects and normal subjects.

Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

PubMed Central

Nessler, Bernhard; Pfeiffer, Michael; Buesing, Lars; Maass, Wolfgang

2013-01-01

The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) of synaptic weights generates and maintains their computational function, are unknown. Preceding work has shown that soft winner-take-all (WTA) circuits, where pyramidal neurons inhibit each other via interneurons, are a common motif of cortical microcircuits. We show through theoretical analysis and computer simulations that Bayesian computation is induced in these network motifs through STDP in combination with activity-dependent changes in the excitability of neurons. The fundamental components of this emergent Bayesian computation are priors that result from adaptation of neuronal excitability and implicit generative models for hidden causes that are created in the synaptic weights through STDP. In fact, a surprising result is that STDP is able to approximate a powerful principle for fitting such implicit generative models to high-dimensional spike inputs: Expectation Maximization. Our results suggest that the experimentally observed spontaneous activity and trial-to-trial variability of cortical neurons are essential features of their information processing capability, since their functional role is to represent probability distributions rather than static neural codes. Furthermore it suggests networks of Bayesian computation modules as a new model for distributed information processing in the cortex. PMID:23633941

Nature, nurture and evolution of intra-species variation in mosquito arbovirus transmission competence.

PubMed

Tabachnick, Walter J

2013-01-11

Mosquitoes vary in their competence or ability to transmit arthropod-borne viruses (arboviruses). Many arboviruses cause disease in humans and animals. Identifying the environmental and genetic causes of variation in mosquito competence for arboviruses is one of the great challenges in public health. Progress identifying genetic (nature) and environmental (nurture) factors influencing mosquito competence for arboviruses is reviewed. There is great complexity in the various traits that comprise mosquito competence. The complex interactions between environmental and genetic factors controlling these traits and the factors shaping variation in Nature are largely unknown. The norms of reaction of specific genes influencing competence, their distributions in natural populations and the effects of genetic polymorphism on phenotypic variation need to be determined. Mechanisms influencing competence are not likely due to natural selection because of the direct effects of the arbovirus on mosquito fitness. More likely the traits for mosquito competence for arboviruses are the effects of adaptations for other functions of these competence mechanisms. Determining these other functions is essential to understand the evolution and distributions of competence for arboviruses. This information is needed to assess risk from mosquito-borne disease, predict new mosquito-arbovirus systems, and provide novel strategies to mitigate mosquito-borne arbovirus transmission.

The Area Coverage of Geophysical Fields as a Function of Sensor Field-of View

NASA Technical Reports Server (NTRS)

Key, Jeffrey R.

1994-01-01

In many remote sensing studies of geophysical fields such as clouds, land cover, or sea ice characteristics, the fractional area coverage of the field in an image is estimated as the proportion of pixels that have the characteristic of interest (i.e., are part of the field) as determined by some thresholding operation. The effect of sensor field-of-view on this estimate is examined by modeling the unknown distribution of subpixel area fraction with the beta distribution, whose two parameters depend upon the true fractional area coverage, the pixel size, and the spatial structure of the geophysical field. Since it is often not possible to relate digital number, reflectance, or temperature to subpixel area fraction, the statistical models described are used to determine the effect of pixel size and thresholding operations on the estimate of area fraction for hypothetical geophysical fields. Examples are given for simulated cumuliform clouds and linear openings in sea ice, whose spatial structures are described by an exponential autocovariance function. It is shown that the rate and direction of change in total area fraction with changing pixel size depends on the true area fraction, the spatial structure, and the thresholding operation used.

Distributed subterranean exploration and mapping with teams of UAVs

NASA Astrophysics Data System (ADS)

Rogers, John G.; Sherrill, Ryan E.; Schang, Arthur; Meadows, Shava L.; Cox, Eric P.; Byrne, Brendan; Baran, David G.; Curtis, J. Willard; Brink, Kevin M.

2017-05-01

Teams of small autonomous UAVs can be used to map and explore unknown environments which are inaccessible to teams of human operators in humanitarian assistance and disaster relief efforts (HA/DR). In addition to HA/DR applications, teams of small autonomous UAVs can enhance Warfighter capabilities and provide operational stand-off for military operations such as cordon and search, counter-WMD, and other intelligence, surveillance, and reconnaissance (ISR) operations. This paper will present a hardware platform and software architecture to enable distributed teams of heterogeneous UAVs to navigate, explore, and coordinate their activities to accomplish a search task in a previously unknown environment.

Pulsar statistics and their interpretations

NASA Technical Reports Server (NTRS)

Arnett, W. D.; Lerche, I.

1981-01-01

It is shown that a lack of knowledge concerning interstellar electron density, the true spatial distribution of pulsars, the radio luminosity source distribution of pulsars, the real ages and real aging rates of pulsars, the beaming factor (and other unknown factors causing the known sample of about 350 pulsars to be incomplete to an unknown degree) is sufficient to cause a minimum uncertainty of a factor of 20 in any attempt to determine pulsar birth or death rates in the Galaxy. It is suggested that this uncertainty must impact on suggestions that the pulsar rates can be used to constrain possible scenarios for neutron star formation and stellar evolution in general.

Distinct Domains of CheA Confer Unique Functions in Chemotaxis and Cell Length in Azospirillum brasilense Sp7.

PubMed

Gullett, Jessica M; Bible, Amber; Alexandre, Gladys

2017-07-01

Chemotaxis is the movement of cells in response to gradients of diverse chemical cues. Motile bacteria utilize a conserved chemotaxis signal transduction system to bias their motility and navigate through a gradient. A central regulator of chemotaxis is the histidine kinase CheA. This cytoplasmic protein interacts with membrane-bound receptors, which assemble into large polar arrays, to propagate the signal. In the alphaproteobacterium Azospirillum brasilense , Che1 controls transient increases in swimming speed during chemotaxis, but it also biases the cell length at division. However, the exact underlying molecular mechanisms for Che1-dependent control of multiple cellular behaviors are not known. Here, we identify specific domains of the CheA1 histidine kinase implicated in modulating each of these functions. We show that CheA1 is produced in two isoforms: a membrane-anchored isoform produced as a fusion with a conserved seven-transmembrane domain of unknown function (TMX) at the N terminus and a soluble isoform similar to prototypical CheA. Site-directed and deletion mutagenesis combined with behavioral assays confirm the role of CheA1 in chemotaxis and implicate the TMX domain in mediating changes in cell length. Fluorescence microscopy further reveals that the membrane-anchored isoform is distributed around the cell surface while the soluble isoform localizes at the cell poles. Together, the data provide a mechanism for the role of Che1 in controlling multiple unrelated cellular behaviors via acquisition of a new domain in CheA1 and production of distinct functional isoforms. IMPORTANCE Chemotaxis provides a significant competitive advantage to bacteria in the environment, and this function has been transferred laterally multiple times, with evidence of functional divergence in different genomic contexts. The molecular principles that underlie functional diversification of chemotaxis in various genomic contexts are unknown. Here, we provide a molecular mechanism by which a single CheA protein controls two unrelated functions: chemotaxis and cell length. Acquisition of this multifunctionality is seemingly a recent evolutionary event. The findings illustrate a mechanism by which chemotaxis function may be co-opted to regulate additional cellular functions. Copyright © 2017 American Society for Microbiology.

Distinct Domains of CheA Confer Unique Functions in Chemotaxis and Cell Length in Azospirillum brasilense Sp7

PubMed Central

Gullett, Jessica M.

2017-01-01

ABSTRACT Chemotaxis is the movement of cells in response to gradients of diverse chemical cues. Motile bacteria utilize a conserved chemotaxis signal transduction system to bias their motility and navigate through a gradient. A central regulator of chemotaxis is the histidine kinase CheA. This cytoplasmic protein interacts with membrane-bound receptors, which assemble into large polar arrays, to propagate the signal. In the alphaproteobacterium Azospirillum brasilense, Che1 controls transient increases in swimming speed during chemotaxis, but it also biases the cell length at division. However, the exact underlying molecular mechanisms for Che1-dependent control of multiple cellular behaviors are not known. Here, we identify specific domains of the CheA1 histidine kinase implicated in modulating each of these functions. We show that CheA1 is produced in two isoforms: a membrane-anchored isoform produced as a fusion with a conserved seven-transmembrane domain of unknown function (TMX) at the N terminus and a soluble isoform similar to prototypical CheA. Site-directed and deletion mutagenesis combined with behavioral assays confirm the role of CheA1 in chemotaxis and implicate the TMX domain in mediating changes in cell length. Fluorescence microscopy further reveals that the membrane-anchored isoform is distributed around the cell surface while the soluble isoform localizes at the cell poles. Together, the data provide a mechanism for the role of Che1 in controlling multiple unrelated cellular behaviors via acquisition of a new domain in CheA1 and production of distinct functional isoforms. IMPORTANCE Chemotaxis provides a significant competitive advantage to bacteria in the environment, and this function has been transferred laterally multiple times, with evidence of functional divergence in different genomic contexts. The molecular principles that underlie functional diversification of chemotaxis in various genomic contexts are unknown. Here, we provide a molecular mechanism by which a single CheA protein controls two unrelated functions: chemotaxis and cell length. Acquisition of this multifunctionality is seemingly a recent evolutionary event. The findings illustrate a mechanism by which chemotaxis function may be co-opted to regulate additional cellular functions. PMID:28416707

Integrative and conjugative elements and their hosts: composition, distribution and organization

PubMed Central

Touchon, Marie; Rocha, Eduardo P. C.

2017-01-01

Abstract Conjugation of single-stranded DNA drives horizontal gene transfer between bacteria and was widely studied in conjugative plasmids. The organization and function of integrative and conjugative elements (ICE), even if they are more abundant, was only studied in a few model systems. Comparative genomics of ICE has been precluded by the difficulty in finding and delimiting these elements. Here, we present the results of a method that circumvents these problems by requiring only the identification of the conjugation genes and the species’ pan-genome. We delimited 200 ICEs and this allowed the first large-scale characterization of these elements. We quantified the presence in ICEs of a wide set of functions associated with the biology of mobile genetic elements, including some that are typically associated with plasmids, such as partition and replication. Protein sequence similarity networks and phylogenetic analyses revealed that ICEs are structured in functional modules. Integrases and conjugation systems have different evolutionary histories, even if the gene repertoires of ICEs can be grouped in function of conjugation types. Our characterization of the composition and organization of ICEs paves the way for future functional and evolutionary analyses of their cargo genes, composed of a majority of unknown function genes. PMID:28911112

Maximization of Learning Speed in the Motor Cortex Due to Neuronal Redundancy

PubMed Central

Takiyama, Ken; Okada, Masato

2012-01-01

Many redundancies play functional roles in motor control and motor learning. For example, kinematic and muscle redundancies contribute to stabilizing posture and impedance control, respectively. Another redundancy is the number of neurons themselves; there are overwhelmingly more neurons than muscles, and many combinations of neural activation can generate identical muscle activity. The functional roles of this neuronal redundancy remains unknown. Analysis of a redundant neural network model makes it possible to investigate these functional roles while varying the number of model neurons and holding constant the number of output units. Our analysis reveals that learning speed reaches its maximum value if and only if the model includes sufficient neuronal redundancy. This analytical result does not depend on whether the distribution of the preferred direction is uniform or a skewed bimodal, both of which have been reported in neurophysiological studies. Neuronal redundancy maximizes learning speed, even if the neural network model includes recurrent connections, a nonlinear activation function, or nonlinear muscle units. Furthermore, our results do not rely on the shape of the generalization function. The results of this study suggest that one of the functional roles of neuronal redundancy is to maximize learning speed. PMID:22253586

Spatial Distribution of Small Water Body Types across Indiana Ecoregions

EPA Science Inventory

Due to their large numbers and biogeochemical activity, small water bodies (SWB), such as ponds and wetlands, can have substantial cumulative effects on hydrologic, biogeochemical, and biological processes; yet the spatial distributions of various SWB types are often unknown. Usi...

A new polytopic approach for the unknown input functional observer design

NASA Astrophysics Data System (ADS)

Bezzaoucha, Souad; Voos, Holger; Darouach, Mohamed

2018-03-01

In this paper, a constructive procedure to design Functional Unknown Input Observers for nonlinear continuous time systems is proposed under the Polytopic Takagi-Sugeno framework. An equivalent representation for the nonlinear model is achieved using the sector nonlinearity transformation. Applying the Lyapunov theory and the ? attenuation, linear matrix inequalities conditions are deduced which are solved for feasibility to obtain the observer design matrices. To cope with the effect of unknown inputs, classical approach of decoupling the unknown input for the linear case is used. Both algebraic and solver-based solutions are proposed (relaxed conditions). Necessary and sufficient conditions for the existence of the functional polytopic observer are given. For both approaches, the general and particular cases (measurable premise variables, full state estimation with full and reduced order cases) are considered and it is shown that the proposed conditions correspond to the one presented for standard linear case. To illustrate the proposed theoretical results, detailed numerical simulations are presented for a Quadrotor Aerial Robots Landing and a Waste Water Treatment Plant. Both systems are highly nonlinear and represented in a T-S polytopic form with unmeasurable premise variables and unknown inputs.

Testing the Hypothesis of a Homoscedastic Error Term in Simple, Nonparametric Regression

ERIC Educational Resources Information Center

Wilcox, Rand R.

2006-01-01

Consider the nonparametric regression model Y = m(X)+ [tau](X)[epsilon], where X and [epsilon] are independent random variables, [epsilon] has a median of zero and variance [sigma][squared], [tau] is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated…

Efficient Learning Algorithms with Limited Information

ERIC Educational Resources Information Center

De, Anindya

2013-01-01

The thesis explores efficient learning algorithms in settings which are more restrictive than the PAC model of learning (Valiant) in one of the following two senses: (i) The learning algorithm has a very weak access to the unknown function, as in, it does not get labeled samples for the unknown function (ii) The error guarantee required from the…

Analysis of the Prefoldin Gene Family in 14 Plant Species

PubMed Central

Cao, Jun

2016-01-01

Prefoldin is a hexameric molecular chaperone complex present in all eukaryotes and archaea. The evolution of this gene family in plants is unknown. Here, I identified 140 prefoldin genes in 14 plant species. These prefoldin proteins were divided into nine groups through phylogenetic analysis. Highly conserved gene organization and motif distribution exist in each prefoldin group, implying their functional conservation. I also observed the segmental duplication of maize prefoldin gene family. Moreover, a few functional divergence sites were identified within each group pairs. Functional network analyses identified 78 co-expressed genes, and most of them were involved in carrying, binding and kinase activity. Divergent expression profiles of the maize prefoldin genes were further investigated in different tissues and development periods and under auxin and some abiotic stresses. I also found a few cis-elements responding to abiotic stress and phytohormone in the upstream sequences of the maize prefoldin genes. The results provided a foundation for exploring the characterization of the prefoldin genes in plants and will offer insights for additional functional studies. PMID:27014333

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

Novel Occurrence of Uncommon Polyamines in Higher Plants 1

PubMed Central

Kuehn, Glenn D.; Rodriguez-Garay, Benjamin; Bagga, Suman; Phillips, Gregory C.

1990-01-01

Diamines and polyamines are ubiquitous components of living cells, and apparently are involved in numerous cellular and physiological processes. Certain “uncommon” polyamines have limited distribution in nature and have been associated primarily with organisms adapted to extreme environments, although the precise function of these polyamines in such organisms is unknown. This article summarizes current knowledge regarding the occurrence in higher plants of the uncommon polyamines related to and including norspermidine and norspermine. A putative biosynthetic pathway to account for the occurrences of these uncommon polyamines in higher plants is presented, with a summary of the supporting evidence indicating the existence of the requisite enzymatic activities in alfalfa, Medicago sativa L. PMID:16667862

A method for determining electrophoretic and electroosmotic mobilities using AC and DC electric field particle displacements.

PubMed

Oddy, M H; Santiago, J G

2004-01-01

We have developed a method for measuring the electrophoretic mobility of submicrometer, fluorescently labeled particles and the electroosmotic mobility of a microchannel. We derive explicit expressions for the unknown electrophoretic and the electroosmotic mobilities as a function of particle displacements resulting from alternating current (AC) and direct current (DC) applied electric fields. Images of particle displacements are captured using an epifluorescent microscope and a CCD camera. A custom image-processing code was developed to determine image streak lengths associated with AC measurements, and a custom particle tracking velocimetry (PTV) code was devised to determine DC particle displacements. Statistical analysis was applied to relate mobility estimates to measured particle displacement distributions.

Highly Decorated Lignins in Leaf Tissues of the Canary Island Date Palm Phoenix canariensis1[OPEN

PubMed Central

Bartuce, Allison; Free, Heather C.A.; Smith, Bronwen G.

2017-01-01

The cell walls of leaf base tissues of the Canary Island date palm (Phoenix canariensis) contain lignins with the most complex compositions described to date. The lignin composition varies by tissue region and is derived from traditional monolignols (ML) along with an unprecedented range of ML conjugates: ML-acetate, ML-benzoate, ML-p-hydroxybenzoate, ML-vanillate, ML-p-coumarate, and ML-ferulate. The specific functions of such complex lignin compositions are unknown. However, the distribution of the ML conjugates varies depending on the tissue region, indicating that they may play specific roles in the cell walls of these tissues and/or in the plant’s defense system. PMID:28894022

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

Swenson, Joel M.; Colmenares, Serafin U.; Strom, Amy R.

Heterochromatin is enriched for specific epigenetic factors including Heterochromatin Protein 1a (HP1a), and is essential for many organismal functions. To elucidate heterochromatin organization and regulation, we purified Drosophila melanogaster HP1a interactors, and performed a genome-wide RNAi screen to identify genes that impact HP1a levels or localization. The majority of the over four hundred putative HP1a interactors and regulators identified were previously unknown. We found that 13 of 16 tested candidates (83%) are required for gene silencing, providing a substantial increase in the number of identified components that impact heterochromatin properties. Surprisingly, image analysis revealed that although some HP1a interactors andmore » regulators are broadly distributed within the heterochromatin domain, most localize to discrete subdomains that display dynamic localization patterns during the cell cycle. We conclude that heterochromatin composition and architecture is more spatially complex and dynamic than previously suggested, and propose that a network of subdomains regulates diverse heterochromatin functions.« less

Human brain networks function in connectome-specific harmonic waves.

PubMed

Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

2016-01-21

A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call 'connectome harmonics', oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory-inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation-inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.

Therapeutic Effects of Caloric Stimulation and Optokinetic Stimulation on Hemispatial Neglect

PubMed Central

Moon, SY; Lee, BH

2006-01-01

Hemispatial neglect refers to a cognitive disorder in which patients with unilateral brain injury cannot recognize or respond to stimuli located in the contralesional hemispace. Hemispatial neglect in stroke patients is an important predictor for poor functional outcome. Therefore, there is a need for effective treatment for this condition. A number of interventions for hemispatial neglect have been proposed, although an approach resulting in persistent improvement is not available. Of these interventions, our review is focused on caloric stimulation and optokinetic stimulation. These lateralized or direction-specific stimulations of peripheral sensory systems can temporarily improve hemispatial neglect. According to recent functional MRI and PET studies, this improvement might result from the partial (re)activation of a distributed, multisensory vestibular network in the lesioned hemisphere, which is a part of a system that codes ego-centered space. However, much remain unknown regarding exact signal timing and directional selectivity of the network. PMID:20396481

Early efforts in modeling the incubation period of infectious diseases with an acute course of illness.

PubMed

Nishiura, Hiroshi

2007-05-11

The incubation period of infectious diseases, the time from infection with a microorganism to onset of disease, is directly relevant to prevention and control. Since explicit models of the incubation period enhance our understanding of the spread of disease, previous classic studies were revisited, focusing on the modeling methods employed and paying particular attention to relatively unknown historical efforts. The earliest study on the incubation period of pandemic influenza was published in 1919, providing estimates of the incubation period of Spanish flu using the daily incidence on ships departing from several ports in Australia. Although the study explicitly dealt with an unknown time of exposure, the assumed periods of exposure, which had an equal probability of infection, were too long, and thus, likely resulted in slight underestimates of the incubation period. After the suggestion that the incubation period follows lognormal distribution, Japanese epidemiologists extended this assumption to estimates of the time of exposure during a point source outbreak. Although the reason why the incubation period of acute infectious diseases tends to reveal a right-skewed distribution has been explored several times, the validity of the lognormal assumption is yet to be fully clarified. At present, various different distributions are assumed, and the lack of validity in assuming lognormal distribution is particularly apparent in the case of slowly progressing diseases. The present paper indicates that (1) analysis using well-defined short periods of exposure with appropriate statistical methods is critical when the exact time of exposure is unknown, and (2) when assuming a specific distribution for the incubation period, comparisons using different distributions are needed in addition to estimations using different datasets, analyses of the determinants of incubation period, and an understanding of the underlying disease mechanisms.

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

Methodological approaches for using synchrotron X-ray fluorescence (SXRF) imaging as a tool in ionomics: Examples from Arabidopsis thaliana

PubMed Central

Hindt, Maria; Socha, Amanda L.; Zuber, Hélène

2013-01-01

Here we present approaches for using multi-elemental imaging (specifically synchrotron X-ray fluorescence microscopy, SXRF) in ionomics, with examples using the model plant Arabidopsis thaliana. The complexity of each approach depends on the amount of a priori information available for the gene and/or phenotype being studied. Three approaches are outlined, which apply to experimental situations where a gene of interest has been identified but has an unknown phenotype (Phenotyping), an unidentified gene is associated with a known phenotype (Gene Cloning) and finally, a Screening approach, where both gene and phenotype are unknown. These approaches make use of open-access, online databases with which plant molecular genetics researchers working in the model plant Arabidopsis will be familiar, in particular the Ionomics Hub and online transcriptomic databases such as the Arabidopsis eFP browser. The approaches and examples we describe are based on the assumption that altering the expression of ion transporters can result in changes in elemental distribution. We provide methodological details on using elemental imaging to aid or accelerate gene functional characterization by narrowing down the search for candidate genes to the tissues in which elemental distributions are altered. We use synchrotron X-ray microprobes as a technique of choice, which can now be used to image all parts of an Arabidopsis plant in a hydrated state. We present elemental images of leaves, stem, root, siliques and germinating hypocotyls. PMID:23912758

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

PubMed Central

Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

2002-01-01

The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 × g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies. PMID:12370447

Expressed sequence tags from poplar wood tissues--a comparative analysis from multiple libraries.

PubMed

Déjardin, A; Leplé, J-C; Lesage-Descauses, M-C; Costa, G; Pilate, G

2004-01-01

Xylogenesis involves successive developmental processes--cambial division, cell expansion and differentiation, cell death--each occurring along a gradient from the cambium to the pith of the stem. Taking advantage of the high level of organisation of wood tissues, we isolated cambial zone (CZ), differentiating xylem (DX) and mature xylem (MX) from both tension wood (TW) and opposite wood (OW) of bent poplars. Four different cDNA libraries were then constructed and used to generate 10,062 EST, reflecting the genes expressed in the different wood tissues. For the most abundant clusters, the EST distributions were compared between libraries in order to identify genes specific or over-represented at some specific developmental stages. They clearly showed a developmental shift between CZ and DX, whereas there is a continuity of development between DX and MX. CZ was mainly characterized by clusters of genes involved in cell cycle, protein synthesis and fate. Interestingly, two clusters with no assigned function were found specific to the cambial zone. In DX and MX, clusters were mostly involved in methylation of lignin precursors and microtubule cytoskeleton. In addition, in DX, EST from TW and OW were compared: five clusters of arabinogalactan proteins, one for sucrose synthase and one for fructokinase were specific or over-represented in TW. Moreover, a putative transcription factor and a cluster of unknown function were also identified in DX-TW. The informative comparison of multiple libraries prepared from wood tissues led to the identification of genes--some with still unknown functions--putatively involved in xylogenesis and tension wood formation.

Chemokine-Dependent pH Elevation at the Cell Front Sustains Polarity in Directionally Migrating Zebrafish Germ Cells.

PubMed

Tarbashevich, Katsiaryna; Reichman-Fried, Michal; Grimaldi, Cecilia; Raz, Erez

2015-04-20

Directional cell migration requires cell polarization with respect to the distribution of the guidance cue. Cell polarization often includes asymmetric distribution of response components as well as elements of the motility machinery. Importantly, the function and regulation of most of these molecules are known to be pH dependent. Intracellular pH gradients were shown to occur in certain cells migrating in vitro, but the functional relevance of such gradients for cell migration and for the response to directional cues, particularly in the intact organism, is currently unknown. In this study, we find that primordial germ cells migrating in the context of the developing embryo respond to the graded distribution of the chemokine Cxcl12 by establishing elevated intracellular pH at the cell front. We provide insight into the mechanisms by which a polar pH distribution contributes to efficient cell migration. Specifically, we show that Carbonic Anhydrase 15b, an enzyme controlling the pH in many cell types, including metastatic cancer cells, is expressed in migrating germ cells and is crucial for establishing and maintaining an asymmetric pH distribution within them. Reducing the level of the protein and thereby erasing the pH elevation at the cell front resulted in abnormal cell migration and impaired arrival at the target. The basis for the disrupted migration is found in the stringent requirement for pH conditions in the cell for regulating contractility, for the polarization of Rac1 activity, and hence for the formation of actin-rich structures at the leading edge of the migrating cells. Copyright © 2015 Elsevier Ltd. All rights reserved.

A fuzzy adaptive network approach to parameter estimation in cases where independent variables come from an exponential distribution

NASA Astrophysics Data System (ADS)

Dalkilic, Turkan Erbay; Apaydin, Aysen

2009-11-01

In a regression analysis, it is assumed that the observations come from a single class in a data cluster and the simple functional relationship between the dependent and independent variables can be expressed using the general model; Y=f(X)+[epsilon]. However; a data cluster may consist of a combination of observations that have different distributions that are derived from different clusters. When faced with issues of estimating a regression model for fuzzy inputs that have been derived from different distributions, this regression model has been termed the [`]switching regression model' and it is expressed with . Here li indicates the class number of each independent variable and p is indicative of the number of independent variables [J.R. Jang, ANFIS: Adaptive-network-based fuzzy inference system, IEEE Transaction on Systems, Man and Cybernetics 23 (3) (1993) 665-685; M. Michel, Fuzzy clustering and switching regression models using ambiguity and distance rejects, Fuzzy Sets and Systems 122 (2001) 363-399; E.Q. Richard, A new approach to estimating switching regressions, Journal of the American Statistical Association 67 (338) (1972) 306-310]. In this study, adaptive networks have been used to construct a model that has been formed by gathering obtained models. There are methods that suggest the class numbers of independent variables heuristically. Alternatively, in defining the optimal class number of independent variables, the use of suggested validity criterion for fuzzy clustering has been aimed. In the case that independent variables have an exponential distribution, an algorithm has been suggested for defining the unknown parameter of the switching regression model and for obtaining the estimated values after obtaining an optimal membership function, which is suitable for exponential distribution.

Integrated survival analysis using an event-time approach in a Bayesian framework

USGS Publications Warehouse

Walsh, Daniel P.; Dreitz, VJ; Heisey, Dennis M.

2015-01-01

Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

Integrated survival analysis using an event-time approach in a Bayesian framework.

PubMed

Walsh, Daniel P; Dreitz, Victoria J; Heisey, Dennis M

2015-02-01

Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

A deterministic global optimization using smooth diagonal auxiliary functions

NASA Astrophysics Data System (ADS)

Sergeyev, Yaroslav D.; Kvasov, Dmitri E.

2015-04-01

In many practical decision-making problems it happens that functions involved in optimization process are black-box with unknown analytical representations and hard to evaluate. In this paper, a global optimization problem is considered where both the goal function f (x) and its gradient f‧ (x) are black-box functions. It is supposed that f‧ (x) satisfies the Lipschitz condition over the search hyperinterval with an unknown Lipschitz constant K. A new deterministic 'Divide-the-Best' algorithm based on efficient diagonal partitions and smooth auxiliary functions is proposed in its basic version, its convergence conditions are studied and numerical experiments executed on eight hundred test functions are presented.

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

PubMed

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.

Distributed weighted least-squares estimation with fast convergence for large-scale systems☆

PubMed Central

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods. PMID:25641976

Clustering redshift distributions for the Dark Energy Survey

NASA Astrophysics Data System (ADS)

Helsby, Jennifer

Accurate determination of photometric redshifts and their errors is critical for large scale structure and weak lensing studies for constraining cosmology from deep, wide imaging surveys. Current photometric redshift methods suffer from bias and scatter due to incomplete training sets. Exploiting the clustering between a sample of galaxies for which we have spectroscopic redshifts and a sample of galaxies for which the redshifts are unknown can allow us to reconstruct the true redshift distribution of the unknown sample. Here we use this method in both simulations and early data from the Dark Energy Survey (DES) to determine the true redshift distributions of galaxies in photometric redshift bins. We find that cross-correlating with the spectroscopic samples currently used for training provides a useful test of photometric redshifts and provides reliable estimates of the true redshift distribution in a photometric redshift bin. We discuss the use of the cross-correlation method in validating template- or learning-based approaches to redshift estimation and its future use in Stage IV surveys.

Functional Characterization and Signaling Systems of Corazonin and Red Pigment Concentrating Hormone in the Green Shore Crab, Carcinus maenas

PubMed Central

Alexander, Jodi L.; Oliphant, Andrew; Wilcockson, David C.; Audsley, Neil; Down, Rachel E.; Lafont, Rene; Webster, Simon G.

2018-01-01

Neuropeptides play a central role as neurotransmitters, neuromodulators and hormones in orchestrating arthropod physiology. The post-genomic surge in identified neuropeptides and their putative receptors has not been matched by functional characterization of ligand-receptor pairs. Indeed, until very recently no G protein-coupled receptors (GPCRs) had been functionally defined in any crustacean. Here we explore the structurally-related, functionally-diverse gonadotropin-releasing hormone paralogs, corazonin (CRZ) and red-pigment concentrating hormone (RPCH) and their G-protein coupled receptors (GPCRs) in the crab, Carcinus maenas. Using aequorin luminescence to measure in vitro Ca2+ mobilization we demonstrated receptor-ligand pairings of CRZ and RPCH. CRZR-activated cell signaling in a dose-dependent manner (EC50 0.75 nM) and comparative studies with insect CRZ peptides suggest that the C-terminus of this peptide is important in receptor-ligand interaction. RPCH interacted with RPCHR with extremely high sensitivity (EC50 20 pM). Neither receptor bound GnRH, nor the AKH/CRZ-related peptide. Transcript distributions of both receptors indicate that CRZR expression was, unexpectedly, restricted to the Y-organs (YO). Application of CRZ peptide to YO had no effect on ecdysteroid biosynthesis, excepting a modest stimulation in early post-molt. CRZ had no effect on heart activity, blood glucose levels, lipid mobilization or pigment distribution in chromatophores, a scenario that reflected the distribution of its mRNA. Apart from the well-known activity of RPCH as a chromatophorotropin, it also indirectly elicited hyperglycemia (which was eyestalk-dependent). RPCHR mRNA was also expressed in the ovary, indicating possible roles in reproduction. The anatomy of CRZ and RPCH neurons in the nervous system is described in detail by immunohistochemistry and in situ hybridization. Each peptide has extensive but non-overlapping distribution in the CNS, and neuroanatomy suggests that both are possibly released from the post-commissural organs. This study is one of the first to deorphanize a GPCR in a crustacean and to provide evidence for hitherto unknown and diverse functions of these evolutionarily-related neuropeptides. PMID:29379412

Genome-Wide Association Study of the Genetic Determinants of Emphysema Distribution

PubMed Central

Boueiz, Adel; Lutz, Sharon M.; Cho, Michael H.; Hersh, Craig P.; Bowler, Russell P.; Washko, George R.; Halper-Stromberg, Eitan; Bakke, Per; Gulsvik, Amund; Laird, Nan M.; Beaty, Terri H.; Coxson, Harvey O.; Crapo, James D.; Silverman, Edwin K.; Castaldi, Peter J.

2017-01-01

Rationale: Emphysema has considerable variability in the severity and distribution of parenchymal destruction throughout the lungs. Upper lobe–predominant emphysema has emerged as an important predictor of response to lung volume reduction surgery. Yet, aside from alpha-1 antitrypsin deficiency, the genetic determinants of emphysema distribution remain largely unknown. Objectives: To identify the genetic influences of emphysema distribution in non–alpha-1 antitrypsin–deficient smokers. Methods: A total of 11,532 subjects with complete genotype and computed tomography densitometry data in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]; non-Hispanic white and African American), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), and GenKOLS (Genetics of Chronic Obstructive Lung Disease) studies were analyzed. Two computed tomography scan emphysema distribution measures (difference between upper-third and lower-third emphysema; ratio of upper-third to lower-third emphysema) were tested for genetic associations in all study subjects. Separate analyses in each study population were followed by a fixed effect metaanalysis. Single-nucleotide polymorphism–, gene-, and pathway-based approaches were used. In silico functional evaluation was also performed. Measurements and Main Results: We identified five loci associated with emphysema distribution at genome-wide significance. These loci included two previously reported associations with COPD susceptibility (4q31 near HHIP and 15q25 near CHRNA5) and three new associations near SOWAHB, TRAPPC9, and KIAA1462. Gene set analysis and in silico functional evaluation revealed pathways and cell types that may potentially contribute to the pathogenesis of emphysema distribution. Conclusions: This multicohort genome-wide association study identified new genomic loci associated with differential emphysematous destruction throughout the lungs. These findings may point to new biologic pathways on which to expand diagnostic and therapeutic approaches in chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764). PMID:27669027

Decreased Functional Brain Connectivity in Adolescents with Internet Addiction

PubMed Central

Hong, Soon-Beom; Zalesky, Andrew; Cocchi, Luca; Fornito, Alex; Choi, Eun-Jung; Kim, Ho-Hyun; Suh, Jeong-Eun; Kim, Chang-Dai; Kim, Jae-Won; Yi, Soon-Hyung

2013-01-01

Background Internet addiction has become increasingly recognized as a mental disorder, though its neurobiological basis is unknown. This study used functional neuroimaging to investigate whole-brain functional connectivity in adolescents diagnosed with internet addiction. Based on neurobiological changes seen in other addiction related disorders, it was predicted that connectivity disruptions in adolescents with internet addiction would be most prominent in cortico-striatal circuitry. Methods Participants were 12 adolescents diagnosed with internet addiction and 11 healthy comparison subjects. Resting-state functional magnetic resonance images were acquired, and group differences in brain functional connectivity were analyzed using the network-based statistic. We also analyzed network topology, testing for between-group differences in key graph-based network measures. Results Adolescents with internet addiction showed reduced functional connectivity spanning a distributed network. The majority of impaired connections involved cortico-subcortical circuits (∼24% with prefrontal and ∼27% with parietal cortex). Bilateral putamen was the most extensively involved subcortical brain region. No between-group difference was observed in network topological measures, including the clustering coefficient, characteristic path length, or the small-worldness ratio. Conclusions Internet addiction is associated with a widespread and significant decrease of functional connectivity in cortico-striatal circuits, in the absence of global changes in brain functional network topology. PMID:23451272

SEM with Missing Data and Unknown Population Distributions Using Two-Stage ML: Theory and Its Application

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Lu, Laura

2008-01-01

This article provides the theory and application of the 2-stage maximum likelihood (ML) procedure for structural equation modeling (SEM) with missing data. The validity of this procedure does not require the assumption of a normally distributed population. When the population is normally distributed and all missing data are missing at random…

Proteins of Unknown Biochemical Function: A Persistent Problem and a Roadmap to Help Overcome It.

PubMed

Niehaus, Thomas D; Thamm, Antje M K; de Crécy-Lagard, Valérie; Hanson, Andrew D

2015-11-01

The number of sequenced genomes is rapidly increasing, but functional annotation of the genes in these genomes lags far behind. Even in Arabidopsis (Arabidopsis thaliana), only approximately 40% of enzyme- and transporter-encoding genes have credible functional annotations, and this number is even lower in nonmodel plants. Functional characterization of unknown genes is a challenge, but various databases (e.g. for protein localization and coexpression) can be mined to provide clues. If homologous microbial genes exist-and about one-half the genes encoding unknown enzymes and transporters in Arabidopsis have microbial homologs-cross-kingdom comparative genomics can powerfully complement plant-based data. Multiple lines of evidence can strengthen predictions and warrant experimental characterization. In some cases, relatively quick tests in genetically tractable microbes can determine whether a prediction merits biochemical validation, which is costly and demands specialized skills. © 2015 American Society of Plant Biologists. All Rights Reserved.

Development of autonomous grasping and navigating robot

NASA Astrophysics Data System (ADS)

Kudoh, Hiroyuki; Fujimoto, Keisuke; Nakayama, Yasuichi

2015-01-01

The ability to find and grasp target items in an unknown environment is important for working robots. We developed an autonomous navigating and grasping robot. The operations are locating a requested item, moving to where the item is placed, finding the item on a shelf or table, and picking the item up from the shelf or the table. To achieve these operations, we designed the robot with three functions: an autonomous navigating function that generates a map and a route in an unknown environment, an item position recognizing function, and a grasping function. We tested this robot in an unknown environment. It achieved a series of operations: moving to a destination, recognizing the positions of items on a shelf, picking up an item, placing it on a cart with its hand, and returning to the starting location. The results of this experiment show the applicability of reducing the workforce with robots.

Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints.

PubMed

Chen, Weisheng

2009-07-01

This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh(.) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.

Probabilistic and deterministic aspects of linear estimation in geodesy. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Dermanis, A.

1976-01-01

Recent advances in observational techniques related to geodetic work (VLBI, laser ranging) make it imperative that more consideration should be given to modeling problems. Uncertainties in the effect of atmospheric refraction, polar motion and precession-nutation parameters, cannot be dispensed with in the context of centimeter level geodesy. Even physical processes that have generally been previously altogether neglected (station motions) must now be taken into consideration. The problem of modeling functions of time or space, or at least their values at observation points (epochs) is explored. When the nature of the function to be modeled is unknown. The need to include a limited number of terms and to a priori decide upon a specific form may result in a representation which fails to sufficiently approximate the unknown function. An alternative approach of increasing application is the modeling of unknown functions as stochastic processes.

Climate Controls AM Fungal Distributions from Global to Local Scales

NASA Astrophysics Data System (ADS)

Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

2016-12-01

Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal composition and root colonization, with weaker influences of plant identity and soil nutrients. These two studies across scales suggest prevailing effects of climate on AM fungal distributions. Thus, incorporating climate when forecasting future ranges of AM fungi will enhance predictions of AM fungal abundance and associated ecosystem functions.

Prompt Neutron Spectrometry for Identification of SNM in Unknown Shielding Configurations: FY16 ONR YIP Final Report

DTIC Science & Technology

2016-05-31

UMKC-YIP-TR-2016 May 2016 Technical Report Prompt Neutron Spectrometry for Identification of SNM in Unknown Shielding...University of Missouri – Kansas City MSND: Micro-structured Neutron Detector HRM: Handheld Radiation Monitor PHS: Pulse Height Spectrum ANI: Active... Neutron Interrogation Distribution Statement A 6 Administrative Information and Acknowledgements Members of the University of Missouri

Distributions of the Kullback-Leibler divergence with applications.

PubMed

Belov, Dmitry I; Armstrong, Ronald D

2011-05-01

The Kullback-Leibler divergence (KLD) is a widely used method for measuring the fit of two distributions. In general, the distribution of the KLD is unknown. Under reasonable assumptions, common in psychometrics, the distribution of the KLD is shown to be asymptotically distributed as a scaled (non-central) chi-square with one degree of freedom or a scaled (doubly non-central) F. Applications of the KLD for detecting heterogeneous response data are discussed with particular emphasis on test security. © The British Psychological Society.

Radarclinometry: Bootstrapping the radar reflectance function from the image pixel-signal frequency distribution and an altimetry profile

USGS Publications Warehouse

Wildey, R.L.

1988-01-01

A method is derived for determining the dependence of radar backscatter on incidence angle that is applicable to the region corresponding to a particular radar image. The method is based on enforcing mathematical consistency between the frequency distribution of the image's pixel signals (histogram of DN values with suitable normalizations) and a one-dimensional frequency distribution of slope component, as might be obtained from a radar or laser altimetry profile in or near the area imaged. In order to achieve a unique solution, the auxiliary assumption is made that the two-dimensional frequency distribution of slope is isotropic. The backscatter is not derived in absolute units. The method is developed in such a way as to separate the reflectance function from the pixel-signal transfer characteristic. However, these two sources of variation are distinguishable only on the basis of a weak dependence on the azimuthal component of slope; therefore such an approach can be expected to be ill-conditioned unless the revision of the transfer characteristic is limited to the determination of an additive instrumental background level. The altimetry profile does not have to be registered in the image, and the statistical nature of the approach minimizes pixel noise effects and the effects of a disparity between the resolutions of the image and the altimetry profile, except in the wings of the distribution where low-number statistics preclude accuracy anyway. The problem of dealing with unknown slope components perpendicular to the profiling traverse, which besets the one-to-one comparison between individual slope components and pixel-signal values, disappears in the present approach. In order to test the resulting algorithm, an artificial radar image was generated from the digitized topographic map of the Lake Champlain West quadrangle in the Adirondack Mountains, U.S.A., using an arbitrarily selected reflectance function. From the same map, a one-dimensional frequency distribution of slope component was extracted. The algorithm recaptured the original reflectance function to the degree that, for the central 90% of the data, the discrepancy translates to a RMS slope error of 0.1 ???. For the central 99% of the data, the maximum error translates to 1 ???; at the absolute extremes of the data the error grows to 6 ???. ?? 1988 Kluwer Academic Publishers.

Tight junction-associated MARVEL proteins marveld3, tricellulin, and occludin have distinct but overlapping functions.

PubMed

Raleigh, David R; Marchiando, Amanda M; Zhang, Yong; Shen, Le; Sasaki, Hiroyuki; Wang, Yingmin; Long, Manyuan; Turner, Jerrold R

2010-04-01

In vitro studies have demonstrated that occludin and tricellulin are important for tight junction barrier function, but in vivo data suggest that loss of these proteins can be overcome. The presence of a heretofore unknown, yet related, protein could explain these observations. Here, we report marvelD3, a novel tight junction protein that, like occludin and tricellulin, contains a conserved four-transmembrane MARVEL (MAL and related proteins for vesicle trafficking and membrane link) domain. Phylogenetic tree reconstruction; analysis of RNA and protein tissue distribution; immunofluorescent and electron microscopic examination of subcellular localization; characterization of intracellular trafficking, protein interactions, dynamic behavior, and siRNA knockdown effects; and description of remodeling after in vivo immune activation show that marvelD3, occludin, and tricellulin have distinct but overlapping functions at the tight junction. Although marvelD3 is able to partially compensate for occludin or tricellulin loss, it cannot fully restore function. We conclude that marvelD3, occludin, and tricellulin define the tight junction-associated MARVEL protein family. The data further suggest that these proteins are best considered as a group with both redundant and unique contributions to epithelial function and tight junction regulation.

The emission function of ground-based light sources: State of the art and research challenges

NASA Astrophysics Data System (ADS)

Solano Lamphar, Héctor Antonio

2018-05-01

To understand the night sky radiance generated by the light emissions of urbanised areas, different researchers are currently proposing various theoretical approaches. The distribution of the radiant intensity as a function of the zenith angle is one of the most unknown properties on modelling skyglow. This is due to the collective effects of the artificial radiation emitted from the ground-based light sources. The emission function is a key property in characterising the sky brightness under arbitrary conditions, therefore it is required by modellers, environmental engineers, urban planners, light pollution researchers, and experimentalists who study the diffuse light of the night sky. As a matter of course, the emission function considers the public lighting system, which is in fact the main generator of the skyglow. Still, another class of light-emitting devices are gaining importance since their overuse and the urban sprawl of recent years. This paper will address the importance of the emission function in modelling skyglow and the factors involved in its characterization. On this subject, the author's intention is to organise, integrate, and evaluate previously published research in order to state the progress of current research toward clarifying this topic.

Neural network consistent empirical physical formula construction for density functional theory based nonlinear vibrational absorbance and intensity of 6-choloronicotinic acid molecule

NASA Astrophysics Data System (ADS)

Yildiz, Nihat; Karabacak, Mehmet; Kurt, Mustafa; Akkoyun, Serkan

2012-05-01

Being directly related to the electric charge distributions in a molecule, the vibrational spectra intensities are both experimentally and theoretically important physical quantities. However, these intensities are inherently highly nonlinear and of complex pattern. Therefore, in particular for unknown detailed spatial molecular structures, it is difficult to make ab initio intensity calculations to compare with new experimental data. In this respect, we very recently initiated entirely novel layered feedforward neural network (LFNN) approach to construct empirical physical formulas (EPFs) for density functional theory (DFT) vibrational spectra of some molecules. In this paper, as a new and far improved contribution to our novel molecular vibrational spectra LFNN-EPF approach, we constructed LFFN-EPFs for absorbances and intensities of 6-choloronicotinic acid (6-CNA) molecule. The 6-CNA data, borrowed from our previous study, was entirely different and much larger than the vibrational intensity data of our formerly used LFNN-EPF molecules. In line with our another previous work which theoretically proved the LFNN relevance to EPFs, although the 6-CNA DFT absorbance and intensity were inherently highly nonlinear and sharply fluctuating in character, still the optimally constructed train set LFFN-EPFs very successfully fitted the absorbances and intensities. Moreover, test set (i.e. yet-to-be measured experimental data) LFNN-EPFs consistently and successfully predicted the absorbance and intensity data. This simply means that the physical law embedded in the 6-CNA vibrational data was successfully extracted by the LFNN-EPFs. In conclusion, these vibrational LFNN-EPFs are of explicit form. Therefore, by various suitable operations of mathematical analysis, they can be used to estimate the electronic charge distributions of the unknown molecule of the significant complexity. Additionally, these estimations can be combined with those of theoretical DFT atomic polar tensor calculations to contribute to the identification of the molecule.

Neural network consistent empirical physical formula construction for density functional theory based nonlinear vibrational absorbance and intensity of 6-choloronicotinic acid molecule.

PubMed

Yildiz, Nihat; Karabacak, Mehmet; Kurt, Mustafa; Akkoyun, Serkan

2012-05-01

Being directly related to the electric charge distributions in a molecule, the vibrational spectra intensities are both experimentally and theoretically important physical quantities. However, these intensities are inherently highly nonlinear and of complex pattern. Therefore, in particular for unknown detailed spatial molecular structures, it is difficult to make ab initio intensity calculations to compare with new experimental data. In this respect, we very recently initiated entirely novel layered feedforward neural network (LFNN) approach to construct empirical physical formulas (EPFs) for density functional theory (DFT) vibrational spectra of some molecules. In this paper, as a new and far improved contribution to our novel molecular vibrational spectra LFNN-EPF approach, we constructed LFFN-EPFs for absorbances and intensities of 6-choloronicotinic acid (6-CNA) molecule. The 6-CNA data, borrowed from our previous study, was entirely different and much larger than the vibrational intensity data of our formerly used LFNN-EPF molecules. In line with our another previous work which theoretically proved the LFNN relevance to EPFs, although the 6-CNA DFT absorbance and intensity were inherently highly nonlinear and sharply fluctuating in character, still the optimally constructed train set LFFN-EPFs very successfully fitted the absorbances and intensities. Moreover, test set (i.e. yet-to-be measured experimental data) LFNN-EPFs consistently and successfully predicted the absorbance and intensity data. This simply means that the physical law embedded in the 6-CNA vibrational data was successfully extracted by the LFNN-EPFs. In conclusion, these vibrational LFNN-EPFs are of explicit form. Therefore, by various suitable operations of mathematical analysis, they can be used to estimate the electronic charge distributions of the unknown molecule of the significant complexity. Additionally, these estimations can be combined with those of theoretical DFT atomic polar tensor calculations to contribute to the identification of the molecule. Copyright © 2012 Elsevier B.V. All rights reserved.

Adaptive iterative learning control of a class of nonlinear time-delay systems with unknown backlash-like hysteresis input and control direction.

PubMed

Wei, Jianming; Zhang, Youan; Sun, Meimei; Geng, Baoliang

2017-09-01

This paper presents an adaptive iterative learning control scheme for a class of nonlinear systems with unknown time-varying delays and control direction preceded by unknown nonlinear backlash-like hysteresis. Boundary layer function is introduced to construct an auxiliary error variable, which relaxes the identical initial condition assumption of iterative learning control. For the controller design, integral Lyapunov function candidate is used, which avoids the possible singularity problem by introducing hyperbolic tangent funciton. After compensating for uncertainties with time-varying delays by combining appropriate Lyapunov-Krasovskii function with Young's inequality, an adaptive iterative learning control scheme is designed through neural approximation technique and Nussbaum function method. On the basis of the hyperbolic tangent function's characteristics, the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function (CEF) in two cases, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Distributed control system for parallel-connected DC boost converters

DOEpatents

Goldsmith, Steven

2017-08-15

The disclosed invention is a distributed control system for operating a DC bus fed by disparate DC power sources that service a known or unknown load. The voltage sources vary in v-i characteristics and have time-varying, maximum supply capacities. Each source is connected to the bus via a boost converter, which may have different dynamic characteristics and power transfer capacities, but are controlled through PWM. The invention tracks the time-varying power sources and apportions their power contribution while maintaining the DC bus voltage within the specifications. A central digital controller solves the steady-state system for the optimal duty cycle settings that achieve a desired power supply apportionment scheme for a known or predictable DC load. A distributed networked control system is derived from the central system that utilizes communications among controllers to compute a shared estimate of the unknown time-varying load through shared bus current measurements and bus voltage measurements.

The topography of mutational processes in breast cancer genomes

DOE PAGES

Morganella, Sandro; Alexandrov, Ludmil B.; Glodzik, Dominik; ...

2016-01-01

Somatic mutations in human cancers show unevenness in genomic distribution that correlate with aspects of genome structure and function. These mutations are, however, generated by multiple mutational processes operating through the cellular lineage between the fertilized egg and the cancer cell, each composed of specific DNA damage and repair components and leaving its own characteristic mutational signature on the genome. Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, here we show that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription,more » DNA replication and chromatin organization. This signature-based approach permits visualization of the genomic distribution of mutational processes associated with APOBEC enzymes, mismatch repair deficiency and homologous recombinational repair deficiency, as well as mutational processes of unknown aetiology. Lastly, it highlights mechanistic insights including a putative replication-dependent mechanism of APOBEC-related mutagenesis.« less

What causes the spatial heterogeneity of bacterial flora in the intestine of zebrafish larvae?

PubMed

Yang, Jinyou; Shimogonya, Yuji; Ishikawa, Takuji

2018-06-07

Microbial flora in the intestine has been thoroughly investigated, as it plays an important role in the health of the host. Jemielita et al. (2014) showed experimentally that Aeromonas bacteria in the intestine of zebrafish larvae have a heterogeneous spatial distribution. Although bacterial aggregation is important biologically and clinically, there is no mathematical model describing the phenomenon and its mechanism remains largely unknown. In this study, we developed a computational model to describe the heterogeneous distribution of bacteria in the intestine of zebrafish larvae. The results showed that biological taxis could cause the bacterial aggregation. Intestinal peristalsis had the effect of reducing bacterial aggregation through mixing function. Using a scaling argument, we showed that the taxis velocity of bacteria must be larger than the sum of the diffusive velocity and background bulk flow velocity to induce bacterial aggregation. Our model and findings will be useful to further the scientific understanding of intestinal microbial flora. Copyright © 2018 Elsevier Ltd. All rights reserved.

Estimating distributions with increasing failure rate in an imperfect repair model.

PubMed

Kvam, Paul H; Singh, Harshinder; Whitaker, Lyn R

2002-03-01

A failed system is repaired minimally if after failure, it is restored to the working condition of an identical system of the same age. We extend the nonparametric maximum likelihood estimator (MLE) of a system's lifetime distribution function to test units that are known to have an increasing failure rate. Such items comprise a significant portion of working components in industry. The order-restricted MLE is shown to be consistent. Similar results hold for the Brown-Proschan imperfect repair model, which dictates that a failed component is repaired perfectly with some unknown probability, and is otherwise repaired minimally. The estimators derived are motivated and illustrated by failure data in the nuclear industry. Failure times for groups of emergency diesel generators and motor-driven pumps are analyzed using the order-restricted methods. The order-restricted estimators are consistent and show distinct differences from the ordinary MLEs. Simulation results suggest significant improvement in reliability estimation is available in many cases when component failure data exhibit the IFR property.

Mapping Brain Metals to Evaluate Therapies for Neurodegenerative Disease

PubMed Central

Popescu, Bogdan Florin Gh; Nichol, Helen

2013-01-01

The brain is rich in metals and has a high metabolic rate, making it acutely vulnerable to the toxic effects of endogenously produced free radicals. The abundant metals, iron and copper, transfer single electrons as they cycle between their reduced (Fe2+, Cu1+) and oxidized (Fe3+, Cu2+) states making them powerful catalysts of reactive oxygen species (ROS) production. Even redox inert zinc, if present in excess, can trigger ROS production indirectly by altering mitochondrial function. While metal chelators seem to improve the clinical outcome of several neurodegenerative diseases, their mechanisms of action remain obscure and the effects of long-term use are largely unknown. Most chelators are not specific to a single metal and could alter the distribution of multiple metals in the brain, leading to unexpected consequences over the long-term. We show here how X-ray fluorescence will be a valuable tool to examine the effect of chelators on the distribution and amount of metals in the brain. PMID:20553312

Statistical modeling of optical attenuation measurements in continental fog conditions

NASA Astrophysics Data System (ADS)

Khan, Muhammad Saeed; Amin, Muhammad; Awan, Muhammad Saleem; Minhas, Abid Ali; Saleem, Jawad; Khan, Rahimdad

2017-03-01

Free-space optics is an innovative technology that uses atmosphere as a propagation medium to provide higher data rates. These links are heavily affected by atmospheric channel mainly because of fog and clouds that act to scatter and even block the modulated beam of light from reaching the receiver end, hence imposing severe attenuation. A comprehensive statistical study of the fog effects and deep physical understanding of the fog phenomena are very important for suggesting improvements (reliability and efficiency) in such communication systems. In this regard, 6-months real-time measured fog attenuation data are considered and statistically investigated. A detailed statistical analysis related to each fog event for that period is presented; the best probability density functions are selected on the basis of Akaike information criterion, while the estimates of unknown parameters are computed by maximum likelihood estimation technique. The results show that most fog attenuation events follow normal mixture distribution and some follow the Weibull distribution.

SYNTHESIS OF NOVEL ALL-DIELECTRIC GRATING FILTERS USING GENETIC ALGORITHMS

NASA Technical Reports Server (NTRS)

Zuffada, Cinzia; Cwik, Tom; Ditchman, Christopher

1997-01-01

We are concerned with the design of inhomogeneous, all dielectric (lossless) periodic structures which act as filters. Dielectric filters made as stacks of inhomogeneous gratings and layers of materials are being used in optical technology, but are not common at microwave frequencies. The problem is then finding the periodic cell's geometric configuration and permittivity values which correspond to a specified reflectivity/transmittivity response as a function of frequency/illumination angle. This type of design can be thought of as an inverse-source problem, since it entails finding a distribution of sources which produce fields (or quantities derived from them) of given characteristics. Electromagnetic sources (electric and magnetic current densities) in a volume are related to the outside fields by a well known linear integral equation. Additionally, the sources are related to the fields inside the volume by a constitutive equation, involving the material properties. Then, the relationship linking the fields outside the source region to those inside is non-linear, in terms of material properties such as permittivity, permeability and conductivity. The solution of the non-linear inverse problem is cast here as a combination of two linear steps, by explicitly introducing the electromagnetic sources in the computational volume as a set of unknowns in addition to the material unknowns. This allows to solve for material parameters and related electric fields in the source volume which are consistent with Maxwell's equations. Solutions are obtained iteratively by decoupling the two steps. First, we invert for the permittivity only in the minimization of a cost function and second, given the materials, we find the corresponding electric fields through direct solution of the integral equation in the source volume. The sources thus computed are used to generate the far fields and the synthesized triter response. The cost function is obtained by calculating the deviation between the synthesized value of reflectivity/transmittivity and the desired one. Solution geometries for the periodic cell are sought as gratings (ensembles of columns of different heights and widths), or combinations of homogeneous layers of different dielectric materials and gratings. Hence the explicit unknowns of the inversion step are the material permittivities and the relative boundaries separating homogeneous parcels of the periodic cell.

VISUALIZATION OF TISSUE DISTRIBUTION AND METABOLISM OF BENZO[A]PYRENE IN EARLY EMBRYONIC MEDAKA (ORYZIAS LATIPES)

EPA Science Inventory

Fish early life stages are highly sensitive to exposure to persistent bioaccumulative toxicants (PBTs). The factors that contribute to this are unknown, but may include the distribution of PBTs to sensitive tissues during critical stages of development. Multiphoton laser scannin...

Spatial probability models of fire in the desert grasslands of the southwestern USA

USDA-ARS?s Scientific Manuscript database

Fire is an important driver of ecological processes in semiarid environments; however, the role of fire in desert grasslands of the Southwestern US is controversial and the regional fire distribution is largely unknown. We characterized the spatial distribution of fire in the desert grassland region...

Analytic Approximations to the Free Boundary and Multi-dimensional Problems in Financial Derivatives Pricing

NASA Astrophysics Data System (ADS)

Lau, Chun Sing

This thesis studies two types of problems in financial derivatives pricing. The first type is the free boundary problem, which can be formulated as a partial differential equation (PDE) subject to a set of free boundary condition. Although the functional form of the free boundary condition is given explicitly, the location of the free boundary is unknown and can only be determined implicitly by imposing continuity conditions on the solution. Two specific problems are studied in details, namely the valuation of fixed-rate mortgages and CEV American options. The second type is the multi-dimensional problem, which involves multiple correlated stochastic variables and their governing PDE. One typical problem we focus on is the valuation of basket-spread options, whose underlying asset prices are driven by correlated geometric Brownian motions (GBMs). Analytic approximate solutions are derived for each of these three problems. For each of the two free boundary problems, we propose a parametric moving boundary to approximate the unknown free boundary, so that the original problem transforms into a moving boundary problem which can be solved analytically. The governing parameter of the moving boundary is determined by imposing the first derivative continuity condition on the solution. The analytic form of the solution allows the price and the hedging parameters to be computed very efficiently. When compared against the benchmark finite-difference method, the computational time is significantly reduced without compromising the accuracy. The multi-stage scheme further allows the approximate results to systematically converge to the benchmark results as one recasts the moving boundary into a piecewise smooth continuous function. For the multi-dimensional problem, we generalize the Kirk (1995) approximate two-asset spread option formula to the case of multi-asset basket-spread option. Since the final formula is in closed form, all the hedging parameters can also be derived in closed form. Numerical examples demonstrate that the pricing and hedging errors are in general less than 1% relative to the benchmark prices obtained by numerical integration or Monte Carlo simulation. By exploiting an explicit relationship between the option price and the underlying probability distribution, we further derive an approximate distribution function for the general basket-spread variable. It can be used to approximate the transition probability distribution of any linear combination of correlated GBMs. Finally, an implicit perturbation is applied to reduce the pricing errors by factors of up to 100. When compared against the existing methods, the basket-spread option formula coupled with the implicit perturbation turns out to be one of the most robust and accurate approximation methods.

A Non-linear Geodetic Data Inversion Using ABIC for Slip Distribution on a Fault With an Unknown dip Angle

NASA Astrophysics Data System (ADS)

Fukahata, Y.; Wright, T. J.

2006-12-01

We developed a method of geodetic data inversion for slip distribution on a fault with an unknown dip angle. When fault geometry is unknown, the problem of geodetic data inversion is non-linear. A common strategy for obtaining slip distribution is to first determine the fault geometry by minimizing the square misfit under the assumption of a uniform slip on a rectangular fault, and then apply the usual linear inversion technique to estimate a slip distribution on the determined fault. It is not guaranteed, however, that the fault determined under the assumption of a uniform slip gives the best fault geometry for a spatially variable slip distribution. In addition, in obtaining a uniform slip fault model, we have to simultaneously determine the values of the nine mutually dependent parameters, which is a highly non-linear, complicated process. Although the inverse problem is non-linear for cases with unknown fault geometries, the non-linearity of the problems is actually weak, when we can assume the fault surface to be flat. In particular, when a clear fault trace is observed on the EarthOs surface after an earthquake, we can precisely estimate the strike and the location of the fault. In this case only the dip angle has large ambiguity. In geodetic data inversion we usually need to introduce smoothness constraints in order to compromise reciprocal requirements for model resolution and estimation errors in a natural way. Strictly speaking, the inverse problem with smoothness constraints is also non-linear, even if the fault geometry is known. The non-linearity has been dissolved by introducing AkaikeOs Bayesian Information Criterion (ABIC), with which the optimal value of the relative weight of observed data to smoothness constraints is objectively determined. In this study, using ABIC in determining the optimal dip angle, we dissolved the non-linearity of the inverse problem. We applied the method to the InSAR data of the 1995 Dinar, Turkey earthquake and obtained a much shallower dip angle than before.

Conformation Types of Ubiquitin [M+8H]8+ Ions from Water:Methanol Solutions: Evidence for the N and A States in Aqueous Solution

PubMed Central

Shi, Huilin; Pierson, Nicholas A.; Valentine, Stephen J.; Clemmer, David E.

2012-01-01

Ion mobility and mass spectrometry measurements are used to examine the gas-phase populations of [M+8H]8+ ubiquitin ions formed upon electrospraying 20 different solutions: from 100:0 to 5:95 water:methanol that are maintained at pH = 2.0. Over this range of solution conditions, mobility distributions for the +8 charge state show substantial variations. Here we develop a model that treats the combined measurements as one data set. By varying the relative abundances of a discrete set of conformation types, it is possible to represent distributions obtained from any solution. For solutions that favor the well-known A-state ubiquitin, it is possible to represent the gas-phase distributions with seven conformation types. Aqueous conditions that favor the native structure require four more structural types to represent the distribution. This analysis provides the first direct evidence for trace amounts of the A state under native conditions. The method of analysis presented here should help illuminate how solution populations evolve into new gas-phase structures as solvent is removed. Evidence for trace quantities of previously unknown states under native solution conditions may provide insight about the relationship of dynamics to protein function as well as misfolding and aggregation phenomena. PMID:22315998

Iterative optimizing quantization method for reconstructing three-dimensional images from a limited number of views

DOEpatents

Lee, H.R.

1997-11-18

A three-dimensional image reconstruction method comprises treating the object of interest as a group of elements with a size that is determined by the resolution of the projection data, e.g., as determined by the size of each pixel. One of the projections is used as a reference projection. A fictitious object is arbitrarily defined that is constrained by such reference projection. The method modifies the known structure of the fictitious object by comparing and optimizing its four projections to those of the unknown structure of the real object and continues to iterate until the optimization is limited by the residual sum of background noise. The method is composed of several sub-processes that acquire four projections from the real data and the fictitious object: generate an arbitrary distribution to define the fictitious object, optimize the four projections, generate a new distribution for the fictitious object, and enhance the reconstructed image. The sub-process for the acquisition of the four projections from the input real data is simply the function of acquiring the four projections from the data of the transmitted intensity. The transmitted intensity represents the density distribution, that is, the distribution of absorption coefficients through the object. 5 figs.

Effect of reaction-step-size noise on the switching dynamics of stochastic populations

NASA Astrophysics Data System (ADS)

Be'er, Shay; Heller-Algazi, Metar; Assaf, Michael

2016-05-01

In genetic circuits, when the messenger RNA lifetime is short compared to the cell cycle, proteins are produced in geometrically distributed bursts, which greatly affects the cellular switching dynamics between different metastable phenotypic states. Motivated by this scenario, we study a general problem of switching or escape in stochastic populations, where influx of particles occurs in groups or bursts, sampled from an arbitrary distribution. The fact that the step size of the influx reaction is a priori unknown and, in general, may fluctuate in time with a given correlation time and statistics, introduces an additional nondemographic reaction-step-size noise into the system. Employing the probability-generating function technique in conjunction with Hamiltonian formulation, we are able to map the problem in the leading order onto solving a stationary Hamilton-Jacobi equation. We show that compared to the "usual case" of single-step influx, bursty influx exponentially decreases the population's mean escape time from its long-lived metastable state. In particular, close to bifurcation we find a simple analytical expression for the mean escape time which solely depends on the mean and variance of the burst-size distribution. Our results are demonstrated on several realistic distributions and compare well with numerical Monte Carlo simulations.

Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations

PubMed Central

Good, Benjamin H.; Rouzine, Igor M.; Balick, Daniel J.; Hallatschek, Oskar; Desai, Michael M.

2012-01-01

When large asexual populations adapt, competition between simultaneously segregating mutations slows the rate of adaptation and restricts the set of mutations that eventually fix. This phenomenon of interference arises from competition between mutations of different strengths as well as competition between mutations that arise on different fitness backgrounds. Previous work has explored each of these effects in isolation, but the way they combine to influence the dynamics of adaptation remains largely unknown. Here, we describe a theoretical model to treat both aspects of interference in large populations. We calculate the rate of adaptation and the distribution of fixed mutational effects accumulated by the population. We focus particular attention on the case when the effects of beneficial mutations are exponentially distributed, as well as on a more general class of exponential-like distributions. In both cases, we show that the rate of adaptation and the influence of genetic background on the fixation of new mutants is equivalent to an effective model with a single selection coefficient and rescaled mutation rate, and we explicitly calculate these effective parameters. We find that the effective selection coefficient exactly coincides with the most common fixed mutational effect. This equivalence leads to an intuitive picture of the relative importance of different types of interference effects, which can shift dramatically as a function of the population size, mutation rate, and the underlying distribution of fitness effects. PMID:22371564

The Human Thalamus Is an Integrative Hub for Functional Brain Networks

PubMed Central

Bertolero, Maxwell A.

2017-01-01

The thalamus is globally connected with distributed cortical regions, yet the functional significance of this extensive thalamocortical connectivity remains largely unknown. By performing graph-theoretic analyses on thalamocortical functional connectivity data collected from human participants, we found that most thalamic subdivisions display network properties that are capable of integrating multimodal information across diverse cortical functional networks. From a meta-analysis of a large dataset of functional brain-imaging experiments, we further found that the thalamus is involved in multiple cognitive functions. Finally, we found that focal thalamic lesions in humans have widespread distal effects, disrupting the modular organization of cortical functional networks. This converging evidence suggests that the human thalamus is a critical hub region that could integrate diverse information being processed throughout the cerebral cortex as well as maintain the modular structure of cortical functional networks. SIGNIFICANCE STATEMENT The thalamus is traditionally viewed as a passive relay station of information from sensory organs or subcortical structures to the cortex. However, the thalamus has extensive connections with the entire cerebral cortex, which can also serve to integrate information processing between cortical regions. In this study, we demonstrate that multiple thalamic subdivisions display network properties that are capable of integrating information across multiple functional brain networks. Moreover, the thalamus is engaged by tasks requiring multiple cognitive functions. These findings support the idea that the thalamus is involved in integrating information across cortical networks. PMID:28450543

Off-Policy Actor-Critic Structure for Optimal Control of Unknown Systems With Disturbances.

PubMed

Song, Ruizhuo; Lewis, Frank L; Wei, Qinglai; Zhang, Huaguang

2016-05-01

An optimal control method is developed for unknown continuous-time systems with unknown disturbances in this paper. The integral reinforcement learning (IRL) algorithm is presented to obtain the iterative control. Off-policy learning is used to allow the dynamics to be completely unknown. Neural networks are used to construct critic and action networks. It is shown that if there are unknown disturbances, off-policy IRL may not converge or may be biased. For reducing the influence of unknown disturbances, a disturbances compensation controller is added. It is proven that the weight errors are uniformly ultimately bounded based on Lyapunov techniques. Convergence of the Hamiltonian function is also proven. The simulation study demonstrates the effectiveness of the proposed optimal control method for unknown systems with disturbances.

ShiftNMFk 1.2

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

Alexandrov, Boian S.; Vesselinov, Velimir V.; Stanev, Valentin

The ShiftNMFk1.2 code, or as we call it, GreenNMFk, represents a hybrid algorithm combining unsupervised adaptive machine learning and Green's function inverse method. GreenNMFk allows an efficient and high performance de-mixing and feature extraction of a multitude of nonnegative signals that change their shape propagating through the medium. The signals are mixed and recorded by a network of uncorrelated sensors. The code couples Non-negative Matrix Factorization (NMF) and inverse-analysis Green's functions method. GreenNMF synergistically performs decomposition of the recorded mixtures, finds the number of the unknown sources and uses the Green's function of the governing partial differential equation to identifymore » the unknown sources and their charecteristics. GreenNMF can be applied directly to any problem controlled by a known partial-differential parabolic equation where mixtures of an unknown number of sources are measured at multiple locations. Full GreenNMFk method is a subject LANL U.S. Patent application S133364.000 August, 2017. The ShiftNMFk 1.2 version here is a toy version of this method that can work with a limited number of unknown sources (4 or less).« less

Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints.

PubMed

Li, Da-Peng; Li, Dong-Juan; Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip

2017-10-01

This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.

Microtubule Actin Cross-Linking Factor 1 Regulates Cardiomyocyte Microtubule Distribution and Adaptation to Hemodynamic Overload

PubMed Central

Kwak, Dongmin; Wang, Huan; Liu, Xiaoyu; Hu, Xinli; Bache, Robert J.; Chen, Yingjie

2013-01-01

Aberrant cardiomyocyte microtubule growth is a feature of pressure overload induced cardiac hypertrophy believed to contribute to left ventricular (LV) dysfunction. Microtubule Actin Cross-linking Factor 1 (MACF1/Acf7) is a 600 kd spectraplakin that stabilizes and guides microtubule growth along actin filaments. MACF1 is expressed in the heart, but its impact on cardiac microtubules, and how this influences cardiac structure, function, and adaptation to hemodynamic overload is unknown. Here we used inducible cardiac-specific MACF1 knockout mice (MACF1 KO) to determine the impact of MACF1 on cardiac microtubules and adaptation to pressure overload (transverse aortic constriction (TAC).In adult mouse hearts, MACF1 expression was low under basal conditions, but increased significantly in response to TAC. While MACF1 KO had no observable effect on heart size or function under basal conditions, MACF1 KO exacerbated TAC induced LV hypertrophy, LV dilation and contractile dysfunction. Interestingly, subcellular fractionation of ventricular lysates revealed that MACF1 KO altered microtubule distribution in response to TAC, so that more tubulin was associated with the cell membrane fraction. Moreover, TAC induced microtubule redistribution into this cell membrane fraction in both WT and MACF1 KO mice correlated strikingly with the level of contractile dysfunction (r2 = 0.786, p<.001). MACF1 disruption also resulted in reduction of membrane caveolin 3 levels, and increased levels of membrane PKCα and β1 integrin after TAC, suggesting MACF1 function is important for spatial regulation of several physiologically relevant signaling proteins during hypertrophy. Together, these data identify for the first time, a role for MACF1 in cardiomyocyte microtubule distribution and in adaptation to hemodynamic overload. PMID:24086300

Microtubule Actin Cross-linking Factor 1 regulates cardiomyocyte microtubule distribution and adaptation to hemodynamic overload.

PubMed

Fassett, John T; Xu, Xin; Kwak, Dongmin; Wang, Huan; Liu, Xiaoyu; Hu, Xinli; Bache, Robert J; Chen, Yingjie

2013-01-01

Aberrant cardiomyocyte microtubule growth is a feature of pressure overload induced cardiac hypertrophy believed to contribute to left ventricular (LV) dysfunction. Microtubule Actin Cross-linking Factor 1 (MACF1/Acf7) is a 600 kd spectraplakin that stabilizes and guides microtubule growth along actin filaments. MACF1 is expressed in the heart, but its impact on cardiac microtubules, and how this influences cardiac structure, function, and adaptation to hemodynamic overload is unknown. Here we used inducible cardiac-specific MACF1 knockout mice (MACF1 KO) to determine the impact of MACF1 on cardiac microtubules and adaptation to pressure overload (transverse aortic constriction (TAC).In adult mouse hearts, MACF1 expression was low under basal conditions, but increased significantly in response to TAC. While MACF1 KO had no observable effect on heart size or function under basal conditions, MACF1 KO exacerbated TAC induced LV hypertrophy, LV dilation and contractile dysfunction. Interestingly, subcellular fractionation of ventricular lysates revealed that MACF1 KO altered microtubule distribution in response to TAC, so that more tubulin was associated with the cell membrane fraction. Moreover, TAC induced microtubule redistribution into this cell membrane fraction in both WT and MACF1 KO mice correlated strikingly with the level of contractile dysfunction (r(2) = 0.786, p<.001). MACF1 disruption also resulted in reduction of membrane caveolin 3 levels, and increased levels of membrane PKCα and β1 integrin after TAC, suggesting MACF1 function is important for spatial regulation of several physiologically relevant signaling proteins during hypertrophy. Together, these data identify for the first time, a role for MACF1 in cardiomyocyte microtubule distribution and in adaptation to hemodynamic overload.

Multiple polypeptides immunologically related to beta-poly(L-malate) hydrolase (polymalatase) in the plasmodium of the slime mold Physarum polycephalum.

PubMed

Karl, M; Holler, E

1998-01-15

Plasmodia of Physarum polycephalum contain large amounts of the cell-type-specific polyanion beta-poly(L-malate) and of a corresponding specific hydrolase (polymalatase), both expressed in the plasmodial form of the organism. We have partially purified polymalatase, the preparation consisting of several polypeptides, which could not be separated without destroying the hydrolase activity. Polypeptides of 68 kDa and 97 kDa were identified as polymalatases. Both were glycosylated, the 68-kDa form giving rise to a 54-kDa form when deglycosylated, and the 97-kDa form giving rise to an 88-kDa polypeptide that was indistinguishable from an 88-kDa inactive species also contained in the enzyme preparation. Antisera against each of these proteins were used to detect the intracellular distribution of the proteins. We found that the antisera crossreacted with the three proteins and, furthermore, with a multiplicity of polypeptides ubiquitously distributed over the plasmodium. Results of a two-dimensional non-denaturing in the first dimension and SDS-denaturing polyacrylamide gel electrophoresis in the second dimension suggested that the proteins were derived from a 200-kDa 'precursor' protein by proteolytic fragmentation. Polymalatase activity could be generated from a high molecular-mass precursor. According to several pieces of evidence, the proteolytic nicking occurred within plasmodia. The fragments were sticky and gave rise to preferred sizes of nicked macromolecules. The observed multiplicity varied as a function of the age of the cultures. The cellular distribution and the intracellular pH value were not compatible with an in situ polymalatase activity and suggested other, presently unknown, function(s) such as in the transportation of beta-poly(L-malate) from the nucleus to the culture medium.

The effects of Strongylus vulgaris parasitism on eosinophil distribution and accumulation in equine large intestinal mucosa.

PubMed

Rötting, A K; Freeman, D E; Constable, P D; Moore, R M; Eurell, J C; Wallig, M A; Hubert, J D

2008-06-01

Eosinophilic granulocytes have been associated with parasite or immune-mediated diseases, but their functions in other disease processes remain unclear. Cause and timing of eosinophil migration into the equine gastrointestinal mucosa are also unknown. To determine the effects of intestinal parasitism on eosinophils in equine large intestinal mucosa. Large intestinal mucosal samples were collected from horses and ponies (n = 16) from the general veterinary hospital population, ponies (n = 3) raised in a parasite-free environment, ponies experimentally infected with 500 infective Strongylus vulgaris larvae and treated with a proprietary anthelmintic drug (n = 14), and a similar group of ponies (n = 7) that received no anthelmintic treatment. Total eosinophil counts and eosinophil distribution in the mucosa were determined by histological examination. A mixed model analysis was performed and appropriate Bonferroni adjusted P values used for each family of comparisons. P<0.05 was considered significant. There was no difference in large intestinal mucosal eosinophil counts and eosinophil distribution between ponies infected with S. vulgaris and those raised in a parasite-free environment. Experimental infection with S. vulgaris, with or without subsequent anthelmintic treatment, did not change eosinophil counts, and counts were similar to those for horses from the general population. Migration of eosinophils to the equine large intestinal mucosa appears to be independent of exposure to parasites. Large intestinal mucosal eosinophils may have more functions in addition to their role in defence against parasites.

Ethnicity and lipoprotein(a) polymorphism in Native Mexican populations.

PubMed

Cardoso-Saldaña, G; De La Peña-Díaz, A; Zamora-González, J; Gomez-Ortega, R; Posadas-Romero, C; Izaguirre-Avila, R; Malvido-Miranda, E; Morales-Anduaga, M E; Anglés-Cano, E

2006-01-01

Lp(a) is a lipoparticle of unknown function mainly present in primates and humans. It consists of a low-density lipoprotein and apo(a), a polymorphic glycoprotein. Apo(a) shares sequence homology and fibrin binding with plasminogen, inhibiting its fibrinolytic properties. Lp(a) is considered a link between atherosclerosis and thrombosis. Marked inter-ethnic differences in Lp(a) concentration related to the genetic polymorphism of apo(a) have been reported in several populations. The study examined the structural and functional features of Lp(a) in three Native Mexican populations (Mayos, Mazahuas and Mayas) and in Mestizo subjects. We determined the plasma concentration of Lp(a) by immunonephelometry, apo(a) isoforms by Western blot, Lp(a) fibrin binding by immuno-enzymatic assay and short tandem repeat (STR) polymorphic marker genetic analysis by capillary electrophoresis. Mestizos presented the less skewed distribution and the highest median Lp(a) concentration (13.25 mg dL(-1)) relative to Mazahuas (8.2 mg dL(-1)), Mayas (8.25 mg dL(-1)) and Mayos (6.5 mg dL(-1)). Phenotype distribution was different in Mayas and Mazahuas as compared with the Mestizo group. The higher Lp(a) fibrin-binding capacity was found in the Maya population. There was an inverse relationship between the size of apo(a) polymorphs and both Lp(a) levels and Lp(a) fibrin binding. There is evidence of significative differences in Lp(a) plasma concentration and phenotype distribution in the Native Mexican and the Mestizo group.

Ethnicity and lipoprotein(a) polymorphism in Native Mexican populations

PubMed Central

Cardoso-Saldaña, Guillermo; De La Peña-Díaz, Aurora; Zamora-González, José; Gomez-Ortega, Rocio; Posadas-Romero, Carlos; Izaguirre-Avila, Raul; Malvido-Miranda, Elsa; Morales-Anduaga, Maria Elena; Angles-Cano, Eduardo

2006-01-01

Background Lp(a) is a lipoparticle of unknown function mainly present in primates and humans. It consists of a low-density lipoprotein and apo(a), a polymorphic glycoprotein. Apo(a) shares sequence homology and fibrin-binding with plasminogen inhibiting its fibrinolytic properties. Lp(a) is considered a link between atherosclerosis and thrombosis. Marked inter-ethnic differences in Lp(a) concentration related to the genetic polymorphism of apo(a), have been reported in several populations. Aim To study the structural and functional features of Lp(a) in three Native Mexican populations (Mayos, Mazahuas and Mayas) and in Mestizo subjects. Methods We determined the plasma concentration of Lp(a) by immunonephelometry, apo(a) isoforms by Western blot, Lp(a) fibrin-binding by immuno-enzymatic assay and STR polymorphic markers genetic analysis by capillary electrophoresis. Results Mestizos presented the less skewed distribution and the highest median Lp(a) concentration (13.25 mg/dL) relative to Mazahuas (8.2 mg/dL), Mayas (8.25 mg/dL) and Mayos (6.5 mg/dL). Phenotype distribution was different in Mayas and Mazahuas as compared to the Mestizo group. The higher Lp(a) fibrin-binding capacity was found in the Maya population. There was an inverse relationship between the size of apo(a) polymorphs and both Lp(a) levels and Lp(a) fibrin binding. Conclusion There is evidence of significative differences in Lp(a) plasma concentration and phenotype distribution in Native Mexican and the Mestizo group. PMID:16684693

A preference for mathematical processing outweighs the selectivity for Arabic numbers in the inferior temporal gyrus.

PubMed

Grotheer, Mareike; Jeska, Brianna; Grill-Spector, Kalanit

2018-03-28

A region in the posterior inferior temporal gyrus (ITG), referred to as the number form area (NFA, here ITG-numbers) has been implicated in the visual processing of Arabic numbers. However, it is unknown if this region is specifically involved in the visual encoding of Arabic numbers per se or in mathematical processing more broadly. Using functional magnetic resonance imaging (fMRI) during experiments that systematically vary tasks and stimuli, we find that mathematical processing, not preference to Arabic numbers, consistently drives both mean and distributed responses in the posterior ITG. While we replicated findings of higher responses in ITG-numbers to numbers than other visual stimuli during a 1-back task, this preference to numbers was abolished when participants engaged in mathematical processing. In contrast, an ITG region (ITG-math) that showed higher responses during an adding task vs. other tasks maintained this preference for mathematical processing across a wide range of stimuli including numbers, number/letter morphs, hands, and dice. Analysis of distributed responses across an anatomically-defined posterior ITG expanse further revealed that mathematical task but not Arabic number form can be successfully and consistently decoded from these distributed responses. Together, our findings suggest that the function of neuronal regions in the posterior ITG goes beyond the specific visual processing of Arabic numbers. We hypothesize that they ascribe numerical content to the visual input, irrespective of the format of the stimulus. Copyright © 2018 Elsevier Inc. All rights reserved.

Solving differential equations with unknown constitutive relations as recurrent neural networks

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

Hagge, Tobias J.; Stinis, Panagiotis; Yeung, Enoch H.

We solve a system of ordinary differential equations with an unknown functional form of a sink (reaction rate) term. We assume that the measurements (time series) of state variables are partially available, and use a recurrent neural network to “learn” the reaction rate from this data. This is achieved by including discretized ordinary differential equations as part of a recurrent neural network training problem. We extend TensorFlow’s recurrent neural network architecture to create a simple but scalable and effective solver for the unknown functions, and apply it to a fedbatch bioreactor simulation problem. Use of techniques from recent deep learningmore » literature enables training of functions with behavior manifesting over thousands of time steps. Our networks are structurally similar to recurrent neural networks, but differ in purpose, and require modified training strategies.« less

A robust H∞-tracking design for uncertain Takagi-Sugeno fuzzy systems with unknown premise variables using descriptor redundancy approach

NASA Astrophysics Data System (ADS)

Hassan Asemani, Mohammad; Johari Majd, Vahid

2015-12-01

This paper addresses a robust H∞ fuzzy observer-based tracking design problem for uncertain Takagi-Sugeno fuzzy systems with external disturbances. To have a practical observer-based controller, the premise variables of the system are assumed to be not measurable in general, which leads to a more complex design process. The tracker is synthesised based on a fuzzy Lyapunov function approach and non-parallel distributed compensation (non-PDC) scheme. Using the descriptor redundancy approach, the robust stability conditions are derived in the form of strict linear matrix inequalities (LMIs) even in the presence of uncertainties in the system, input, and output matrices simultaneously. Numerical simulations are provided to show the effectiveness of the proposed method.

Modified interferometric imaging condition for reverse-time migration

NASA Astrophysics Data System (ADS)

Guo, Xue-Bao; Liu, Hong; Shi, Ying

2018-01-01

For reverse-time migration, high-resolution imaging mainly depends on the accuracy of the velocity model and the imaging condition. In practice, however, the small-scale components of the velocity model cannot be estimated by tomographical methods; therefore, the wavefields are not accurately reconstructed from the background velocity, and the imaging process will generate artefacts. Some of the noise is due to cross-correlation of unrelated seismic events. Interferometric imaging condition suppresses imaging noise very effectively, especially the unknown random disturbance of the small-scale part. The conventional interferometric imaging condition is extended in this study to obtain a new imaging condition based on the pseudo-Wigner distribution function (WDF). Numerical examples show that the modified interferometric imaging condition improves imaging precision.

"Who" is saying "what"? Brain-based decoding of human voice and speech.

PubMed

Formisano, Elia; De Martino, Federico; Bonte, Milene; Goebel, Rainer

2008-11-07

Can we decipher speech content ("what" is being said) and speaker identity ("who" is saying it) from observations of brain activity of a listener? Here, we combine functional magnetic resonance imaging with a data-mining algorithm and retrieve what and whom a person is listening to from the neural fingerprints that speech and voice signals elicit in the listener's auditory cortex. These cortical fingerprints are spatially distributed and insensitive to acoustic variations of the input so as to permit the brain-based recognition of learned speech from unknown speakers and of learned voices from previously unheard utterances. Our findings unravel the detailed cortical layout and computational properties of the neural populations at the basis of human speech recognition and speaker identification.

Live-cell and super-resolution imaging reveal that the distribution of wall-associated protein A is correlated with the cell chain integrity of Streptococcus mutans.

PubMed

Li, Y; Liu, Z; Zhang, Y; Su, Q P; Xue, B; Shao, S; Zhu, Y; Xu, X; Wei, S; Sun, Y

2015-10-01

Streptococcus mutans is a primary pathogen responsible for dental caries. It has an outstanding ability to form biofilm, which is vital for virulence. Previous studies have shown that knockout of Wall-associated protein A (WapA) affects cell chain and biofilm formation of S. mutans. As a surface protein, the distribution of WapA remains unknown, but it is important to understand the mechanism underlying the function of WapA. This study applied the fluorescence protein mCherry as a reporter gene to characterize the dynamic distribution of WapA in S. mutans via time-lapse and super-resolution fluorescence imaging. The results revealed interesting subcellular distribution patterns of WapA in single, dividing and long chains of S. mutans cells. It appears at the middle of the cell and moves to the poles as the cell grows and divides. In a cell chain, after each round of cell division, such dynamic relocation results in WapA distribution at the previous cell division sites, resulting in a pattern where WapA is located at the boundary of two adjacent cell pairs. This WapA distribution pattern corresponds to the breaking segmentation of wapA deletion cell chains. The dynamic relocation of WapA through the cell cycle increases our understanding of the mechanism of WapA in maintaining cell chain integrity and biofilm formation. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

Terai, Tsuyoshi; Takahashi, Jun; Itoh, Yoichi, E-mail: tsuyoshi.terai@nao.ac.jp

Main-belt asteroids have been continuously colliding with one another since they were formed. Their size distribution is primarily determined by the size dependence of asteroid strength against catastrophic impacts. The strength scaling law as a function of body size could depend on collision velocity, but the relationship remains unknown, especially under hypervelocity collisions comparable to 10 km s{sup –1}. We present a wide-field imaging survey at an ecliptic latitude of about 25° for investigating the size distribution of small main-belt asteroids that have highly inclined orbits. The analysis technique allowing for efficient asteroid detections and high-accuracy photometric measurements provides sufficientmore » sample data to estimate the size distribution of sub-kilometer asteroids with inclinations larger than 14°. The best-fit power-law slopes of the cumulative size distribution are 1.25 ± 0.03 in the diameter range of 0.6-1.0 km and 1.84 ± 0.27 in 1.0-3.0 km. We provide a simple size distribution model that takes into consideration the oscillations of the power-law slope due to the transition from the gravity-scaled regime to the strength-scaled regime. We find that the high-inclination population has a shallow slope of the primary components of the size distribution compared to the low-inclination populations. The asteroid population exposed to hypervelocity impacts undergoes collisional processes where large bodies have a higher disruptive strength and longer lifespan relative to tiny bodies than the ecliptic asteroids.« less

Location error uncertainties - an advanced using of probabilistic inverse theory

NASA Astrophysics Data System (ADS)

Debski, Wojciech

2016-04-01

The spatial location of sources of seismic waves is one of the first tasks when transient waves from natural (uncontrolled) sources are analyzed in many branches of physics, including seismology, oceanology, to name a few. Source activity and its spatial variability in time, the geometry of recording network, the complexity and heterogeneity of wave velocity distribution are all factors influencing the performance of location algorithms and accuracy of the achieved results. While estimating of the earthquake foci location is relatively simple a quantitative estimation of the location accuracy is really a challenging task even if the probabilistic inverse method is used because it requires knowledge of statistics of observational, modelling, and apriori uncertainties. In this presentation we addressed this task when statistics of observational and/or modeling errors are unknown. This common situation requires introduction of apriori constraints on the likelihood (misfit) function which significantly influence the estimated errors. Based on the results of an analysis of 120 seismic events from the Rudna copper mine operating in southwestern Poland we illustrate an approach based on an analysis of Shanon's entropy calculated for the aposteriori distribution. We show that this meta-characteristic of the aposteriori distribution carries some information on uncertainties of the solution found.

Hierarchical Probabilistic Inference of Cosmic Shear

NASA Astrophysics Data System (ADS)

Schneider, Michael D.; Hogg, David W.; Marshall, Philip J.; Dawson, William A.; Meyers, Joshua; Bard, Deborah J.; Lang, Dustin

2015-07-01

Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.

Bayesian source tracking via focalization and marginalization in an uncertain Mediterranean Sea environment.

PubMed

Dosso, Stan E; Wilmut, Michael J; Nielsen, Peter L

2010-07-01

This paper applies Bayesian source tracking in an uncertain environment to Mediterranean Sea data, and investigates the resulting tracks and track uncertainties as a function of data information content (number of data time-segments, number of frequencies, and signal-to-noise ratio) and of prior information (environmental uncertainties and source-velocity constraints). To track low-level sources, acoustic data recorded for multiple time segments (corresponding to multiple source positions along the track) are inverted simultaneously. Environmental uncertainty is addressed by including unknown water-column and seabed properties as nuisance parameters in an augmented inversion. Two approaches are considered: Focalization-tracking maximizes the posterior probability density (PPD) over the unknown source and environmental parameters. Marginalization-tracking integrates the PPD over environmental parameters to obtain a sequence of joint marginal probability distributions over source coordinates, from which the most-probable track and track uncertainties can be extracted. Both approaches apply track constraints on the maximum allowable vertical and radial source velocity. The two approaches are applied for towed-source acoustic data recorded at a vertical line array at a shallow-water test site in the Mediterranean Sea where previous geoacoustic studies have been carried out.

Nonholonomic Ofject Tracking with Optical Sensors and Ofject Recognition Feedback

NASA Technical Reports Server (NTRS)

Goddard, R. E.; Hadaegh, F.

1994-01-01

Robotic controllers frequently operate under constraints. Often, the constraints are imperfectly or completely unknown. In this paper, the Lagrangian dynamics of a planar robot arm are expressed as a function of a globally unknown consraint.

Integrative and conjugative elements and their hosts: composition, distribution and organization.

PubMed

Cury, Jean; Touchon, Marie; Rocha, Eduardo P C

2017-09-06

Conjugation of single-stranded DNA drives horizontal gene transfer between bacteria and was widely studied in conjugative plasmids. The organization and function of integrative and conjugative elements (ICE), even if they are more abundant, was only studied in a few model systems. Comparative genomics of ICE has been precluded by the difficulty in finding and delimiting these elements. Here, we present the results of a method that circumvents these problems by requiring only the identification of the conjugation genes and the species' pan-genome. We delimited 200 ICEs and this allowed the first large-scale characterization of these elements. We quantified the presence in ICEs of a wide set of functions associated with the biology of mobile genetic elements, including some that are typically associated with plasmids, such as partition and replication. Protein sequence similarity networks and phylogenetic analyses revealed that ICEs are structured in functional modules. Integrases and conjugation systems have different evolutionary histories, even if the gene repertoires of ICEs can be grouped in function of conjugation types. Our characterization of the composition and organization of ICEs paves the way for future functional and evolutionary analyses of their cargo genes, composed of a majority of unknown function genes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

NASA Astrophysics Data System (ADS)

Fort, G.; Jourdain, B.; Lelièvre, T.; Stoltz, G.

2018-04-01

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang-Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

An Applied Physicist Does Econometrics

NASA Astrophysics Data System (ADS)

Taff, L. G.

2010-02-01

The biggest problem those attempting to understand econometric data, via modeling, have is that economics has no F = ma. Without a theoretical underpinning, econometricians have no way to build a good model to fit observations to. Physicists do, and when F = ma failed, we knew it. Still desiring to comprehend econometric data, applied economists turn to mis-applying probability theory---especially with regard to the assumptions concerning random errors---and choosing extremely simplistic analytical formulations of inter-relationships. This introduces model bias to an unknown degree. An applied physicist, used to having to match observations to a numerical or analytical model with a firm theoretical basis, modify the model, re-perform the analysis, and then know why, and when, to delete ``outliers'', is at a considerable advantage when quantitatively analyzing econometric data. I treat two cases. One is to determine the household density distribution of total assets, annual income, age, level of education, race, and marital status. Each of these ``independent'' variables is highly correlated with every other but only current annual income and level of education follow a linear relationship. The other is to discover the functional dependence of total assets on the distribution of assets: total assets has an amazingly tight power law dependence on a quadratic function of portfolio composition. Who knew? )

Nature, Nurture and Evolution of Intra-Species Variation in Mosquito Arbovirus Transmission Competence

PubMed Central

Tabachnick, Walter J.

2013-01-01

Mosquitoes vary in their competence or ability to transmit arthropod-borne viruses (arboviruses). Many arboviruses cause disease in humans and animals. Identifying the environmental and genetic causes of variation in mosquito competence for arboviruses is one of the great challenges in public health. Progress identifying genetic (nature) and environmental (nurture) factors influencing mosquito competence for arboviruses is reviewed. There is great complexity in the various traits that comprise mosquito competence. The complex interactions between environmental and genetic factors controlling these traits and the factors shaping variation in Nature are largely unknown. The norms of reaction of specific genes influencing competence, their distributions in natural populations and the effects of genetic polymorphism on phenotypic variation need to be determined. Mechanisms influencing competence are not likely due to natural selection because of the direct effects of the arbovirus on mosquito fitness. More likely the traits for mosquito competence for arboviruses are the effects of adaptations for other functions of these competence mechanisms. Determining these other functions is essential to understand the evolution and distributions of competence for arboviruses. This information is needed to assess risk from mosquito-borne disease, predict new mosquito-arbovirus systems, and provide novel strategies to mitigate mosquito-borne arbovirus transmission. PMID:23343982

Changing pattern of the subcellular distribution of erythroblast macrophage protein (Emp) during macrophage differentiation.

PubMed

Soni, Shivani; Bala, Shashi; Kumar, Ajay; Hanspal, Manjit

2007-01-01

Erythroblast macrophage protein (Emp) mediates the attachment of erythroid cells to macrophages and is required for normal differentiation of both cell lineages. In erythroid cells, Emp is believed to be involved in nuclear extrusion, however, its role in macrophage differentiation is unknown. Information on the changes in the expression level and subcellular distribution of Emp in differentiating macrophages is essential for understanding the function of Emp. Macrophages of varying maturity were examined by immunofluorescence microscopy and biochemical methods. Our data show that Emp is expressed in all stages of maturation, but its localization pattern changes dramatically during maturation: in immature macrophages, a substantial fraction of Emp is associated with the nuclear matrix, whereas in more mature cells, Emp is expressed largely at cell surface. Pulse-chase experiments show that nascent Emp migrates intracellularly from the cytoplasm to the plasma membrane more efficiently in mature macrophages than in immature cells. Incubation of erythroid cells with macrophages in culture shows that erythroid cells attach to mature macrophages but not to immature macrophage precursors. Together, our data show that the temporal and spatial expression of Emp correlates with its role in erythroblastic island formation and suggest that Emp may be involved in multiple cellular functions.

*CHANGING PATTERN OF THE SUBCELLULAR DISTRIBUTION OF ERYTHROBLAST MACROPHAGE PROTEIN (EMP) DURING MACROPHAGE DIFFERENTIATION

PubMed Central

Soni, Shivani; Bala, Shashi; Kumar, Ajay; Hanspal, Manjit

2007-01-01

Erythroblast macrophage protein (Emp), mediates the attachment of erythroid cells to macrophages, and is required for normal differentiation of both cell lineages. In erythroid cells Emp is believed to be involved in nuclear extrusion however, its role in macrophage differentiation is unknown. Information on the changes in the expression level and subcellular distribution of Emp in differentiating macrophages is essential for understanding the function of Emp. Macrophages of varying maturity were examined by immunofluorescence microscopy and biochemical methods. Our data shows that Emp is expressed in all stages of maturation, but its localization pattern changes dramatically during maturation: in immature macrophages, a substantial fraction of Emp is associated with the nuclear matrix, whereas in more mature cells, Emp is expressed largely at cell surface. Pulse-chase experiments show that nascent Emp migrates intracellularly from the cytoplasm to the plasma membrane more efficiently in mature macrophages than in immature cells. Incubation of erythroid cells with macrophages in culture show that erythroid cells attach to mature macrophages but not to immature macrophage precursors. Together, our data shows that the temporal and spatial expression of Emp correlates with its role in erythroblastic island formation, and suggests that Emp may be involved in multiple cellular functions. PMID:17071116

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

Bianchi type I in f(T) gravitational theories

NASA Astrophysics Data System (ADS)

M, I. Wanas; G, G. L. Nashed; O, A. Ibrahim

2016-05-01

A tetrad field that is homogeneous and anisotropic which contains two unknown functions A(t) and B(t) of cosmic time is applied to the field equations of f (T), where T is the torsion scalar, T = T μ νρ S μ νρ . We calculate the equation of continuity and rewrite it as a product of two brackets, the first is a function of f (T) and the second is a function of the two unknowns A(t) and B(t). We use two different relations between the two unknown functions A(t) and B(t) in the second bracket to solve it. Both of these relations give constant scalar torsion and solutions coincide with the de Sitter one. So, another assumption related to the contents of the matter fields is postulated. This assumption enables us to drive a solution with a non-constant value of the scalar torsion and a form of f (T) which represents ΛCDM. Project supported by the Egyptian Ministry of Scientific Research (Project No. 24-2-12).

Recent human history governs global ant invasion dynamics

Treesearch

Cleo Bertelsmeier; Sébastien Ollier; Andrew Liebhold; Laurent Keller

2017-01-01

Human trade and travel are breaking down biogeographic barriers, resulting in shifts in the geographical distribution of organisms, yet it remains largely unknown whether different alien species generally follow similar spatiotemporal colonization patterns and how such patterns are driven by trends in global trade. Here, we analyse the global distribution of 241 alien...

Distributed Learning Enhances Relational Memory Consolidation

ERIC Educational Resources Information Center

Litman, Leib; Davachi, Lila

2008-01-01

It has long been known that distributed learning (DL) provides a mnemonic advantage over massed learning (ML). However, the underlying mechanisms that drive this robust mnemonic effect remain largely unknown. In two experiments, we show that DL across a 24 hr interval does not enhance immediate memory performance but instead slows the rate of…

Functional specialization in nucleotide sugar transporters occurred through differentiation of the gene cluster EamA (DUF6) before the radiation of Viridiplantae

PubMed Central

2011-01-01

Background The drug/metabolite transporter superfamily comprises a diversity of protein domain families with multiple functions including transport of nucleotide sugars. Drug/metabolite transporter domains are contained in both solute carrier families 30, 35 and 39 proteins as well as in acyl-malonyl condensing enzyme proteins. In this paper, we present an evolutionary analysis of nucleotide sugar transporters in relation to the entire superfamily of drug/metabolite transporters that considers crucial intra-protein duplication events that have shaped the transporters. We use a method that combines the strengths of hidden Markov models and maximum likelihood to find relationships between drug/metabolite transporter families, and branches within families. Results We present evidence that the triose-phosphate transporters, domain unknown function 914, uracil-diphosphate glucose-N-acetylglucosamine, and nucleotide sugar transporter families have evolved from a domain duplication event before the radiation of Viridiplantae in the EamA family (previously called domain unknown function 6). We identify previously unknown branches in the solute carrier 30, 35 and 39 protein families that emerged simultaneously as key physiological developments after the radiation of Viridiplantae, including the "35C/E" branch of EamA, which formed in the lineage of T. adhaerens (Animalia). We identify a second cluster of DMTs, called the domain unknown function 1632 cluster, which has non-cytosolic N- and C-termini, and thus appears to have been formed from a different domain duplication event. We identify a previously uncharacterized motif, G-X(6)-G, which is overrepresented in the fifth transmembrane helix of C-terminal domains. We present evidence that the family called fatty acid elongases are homologous to transporters, not enzymes as had previously been thought. Conclusions The nucleotide sugar transporters families were formed through differentiation of the gene cluster EamA (domain unknown function 6) before Viridiplantae, showing for the first time the significance of EamA. PMID:21569384

Force-independent distribution of correlated neural inputs to hand muscles during three-digit grasping.

PubMed

Poston, Brach; Danna-Dos Santos, Alessander; Jesunathadas, Mark; Hamm, Thomas M; Santello, Marco

2010-08-01

The ability to modulate digit forces during grasping relies on the coordination of multiple hand muscles. Because many muscles innervate each digit, the CNS can potentially choose from a large number of muscle coordination patterns to generate a given digit force. Studies of single-digit force production tasks have revealed that the electromyographic (EMG) activity scales uniformly across all muscles as a function of digit force. However, the extent to which this finding applies to the coordination of forces across multiple digits is unknown. We addressed this question by asking subjects (n = 8) to exert isometric forces using a three-digit grip (thumb, index, and middle fingers) that allowed for the quantification of hand muscle coordination within and across digits as a function of grasp force (5, 20, 40, 60, and 80% maximal voluntary force). We recorded EMG from 12 muscles (6 extrinsic and 6 intrinsic) of the three digits. Hand muscle coordination patterns were quantified in the amplitude and frequency domains (EMG-EMG coherence). EMG amplitude scaled uniformly across all hand muscles as a function of grasp force (muscle x force interaction: P = 0.997; cosines of angle between muscle activation pattern vector pairs: 0.897-0.997). Similarly, EMG-EMG coherence was not significantly affected by force (P = 0.324). However, coherence was stronger across extrinsic than that across intrinsic muscle pairs (P = 0.0039). These findings indicate that the distribution of neural drive to multiple hand muscles is force independent and may reflect the anatomical properties or functional roles of hand muscle groups.

Active zone protein Bassoon co-localizes with presynaptic calcium channel, modifies channel function, and recovers from aging related loss by exercise.

PubMed

Nishimune, Hiroshi; Numata, Tomohiro; Chen, Jie; Aoki, Yudai; Wang, Yonghong; Starr, Miranda P; Mori, Yasuo; Stanford, John A

2012-01-01

The P/Q-type voltage-dependent calcium channels (VDCCs) are essential for synaptic transmission at adult mammalian neuromuscular junctions (NMJs); however, the subsynaptic location of VDCCs relative to active zones in rodent NMJs, and the functional modification of VDCCs by the interaction with active zone protein Bassoon remain unknown. Here, we show that P/Q-type VDCCs distribute in a punctate pattern within the NMJ presynaptic terminals and align in three dimensions with Bassoon. This distribution pattern of P/Q-type VDCCs and Bassoon in NMJs is consistent with our previous study demonstrating the binding of VDCCs and Bassoon. In addition, we now show that the interaction between P/Q-type VDCCs and Bassoon significantly suppressed the inactivation property of P/Q-type VDCCs, suggesting that the Ca(2+) influx may be augmented by Bassoon for efficient synaptic transmission at NMJs. However, presynaptic Bassoon level was significantly attenuated in aged rat NMJs, which suggests an attenuation of VDCC function due to a lack of this interaction between VDCC and Bassoon. Importantly, the decreased Bassoon level in aged NMJs was ameliorated by isometric strength training of muscles for two months. The training increased Bassoon immunoreactivity in NMJs without affecting synapse size. These results demonstrated that the P/Q-type VDCCs preferentially accumulate at NMJ active zones and play essential role in synaptic transmission in conjunction with the active zone protein Bassoon. This molecular mechanism becomes impaired by aging, which suggests altered synaptic function in aged NMJs. However, Bassoon level in aged NMJs can be improved by muscle exercise.

Age-dependent changes in prefrontal intrinsic connectivity

PubMed Central

Zhou, Xin; Zhu, Dantong; Katsuki, Fumi; Qi, Xue-Lian; Lees, Cynthia J.; Bennett, Allyson J.; Salinas, Emilio; Stanford, Terrence R.; Constantinidis, Christos

2014-01-01

The prefrontal cortex continues to mature after puberty and into early adulthood, mirroring the time course of maturation of cognitive abilities. However, the way in which prefrontal activity changes during peri- and postpubertal cortical maturation is largely unknown. To address this question, we evaluated the developmental stage of peripubertal rhesus monkeys with a series of morphometric, hormonal, and radiographic measures, and conducted behavioral and neurophysiological tests as the monkeys performed working memory tasks. We compared firing rate and the strength of intrinsic functional connectivity between neurons in peripubertal vs. adult monkeys. Notably, analyses of spike train cross-correlations demonstrated that the average magnitude of functional connections measured between neurons was lower overall in the prefrontal cortex of peripubertal monkeys compared with adults. The difference resulted because negative functional connections (indicative of inhibitory interactions) were stronger and more prevalent in peripubertal compared with adult monkeys, whereas the positive connections showed similar distributions in the two groups. Our results identify changes in the intrinsic connectivity of prefrontal neurons, particularly that mediated by inhibition, as a possible substrate for peri- and postpubertal advances in cognitive capacity. PMID:24567390

The schizophrenia risk gene product miR-137 alters presynaptic plasticity

PubMed Central

Siegert, Sandra; Seo, Jinsoo; Kwon, Ester J.; Rudenko, Andrii; Cho, Sukhee; Wang, Wenyuan; Flood, Zachary; Martorell, Anthony J.; Ericsson, Maria; Mungenast, Alison E.; Tsai, Li-Huei

2015-01-01

Non-coding variants in the human MIR137 gene locus increase schizophrenia risk at a genome-wide significance level. However, the functional consequence of these risk alleles is unknown. Here, we examined induced human neurons harboring the minor alleles of four disease-associated single nucleotide polymorphisms (SNPs) in MIR137, and observed increased MIR137 levels compared to major allele-carrying cells. We found that miR-137 gain-of-function causes downregulation of the presynaptic target genes, Complexin-1 (Cplx1), Nsf, and Synaptotagmin-1 (Syt1), leading to impaired vesicle release. In vivo, miR-137 gain-of-function results in changes in synaptic vesicle pool distribution, impaired mossy fiber-LTP induction and deficits in hippocampus-dependent learning and memory. By sequestering endogenous miR-137, we were able to ameliorate the synaptic phenotypes. Moreover, reinstatement of Syt1 expression partially restored synaptic plasticity, demonstrating the importance of Syt1 as a miR-137 target. Our data provide new insight into the mechanism by which miR-137 dysregulation can impair synaptic plasticity in the hippocampus. PMID:26005852

Leader-follower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation.

PubMed

Sun, Zhijian; Zhang, Guoqing; Lu, Yu; Zhang, Weidong

2018-01-01

This paper studies the leader-follower formation control of underactuated surface vehicles with model uncertainties and environmental disturbances. A parameter estimation and upper bound estimation based sliding mode control scheme is proposed to solve the problem of the unknown plant parameters and environmental disturbances. For each of these leader-follower formation systems, the dynamic equations of position and attitude are analyzed using coordinate transformation with the aid of the backstepping technique. All the variables are guaranteed to be uniformly ultimately bounded stable in the closed-loop system, which is proven by the distribution design Lyapunov function synthesis. The main advantages of this approach are that: first, parameter estimation based sliding mode control can enhance the robustness of the closed-loop system in presence of model uncertainties and environmental disturbances; second, a continuous function is developed to replace the signum function in the design of sliding mode scheme, which devotes to reduce the chattering of the control system. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram; Kiremidjian, Anne S.

2012-04-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method for the cases where the post-damage feature distribution is unknown a priori. This algorithm extracts features from structural vibration data using time-series analysis and then declares damage using the change point detection method. The change point detection method asymptotically minimizes detection delay for a given false alarm rate. The conventional method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori. Therefore, our algorithm estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using multiple sets of simulated data and a set of experimental data collected from a four-story steel special moment-resisting frame. Our algorithm was able to estimate the post-damage distribution consistently and resulted in detection delays only a few seconds longer than the delays from the conventional method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

An empirical description of the dispersion of 5th and 95th percentiles in worldwide anthropometric data applied to estimating accommodation with unknown correlation values.

PubMed

Albin, Thomas J; Vink, Peter

2015-01-01

Anthropometric data are assumed to have a Gaussian (Normal) distribution, but if non-Gaussian, accommodation estimates are affected. When data are limited, users may choose to combine anthropometric elements by Combining Percentiles (CP) (adding or subtracting), despite known adverse effects. This study examined whether global anthropometric data are Gaussian distributed. It compared the Median Correlation Method (MCM) of combining anthropometric elements with unknown correlations to CP to determine if MCM provides better estimates of percentile values and accommodation. Percentile values of 604 male and female anthropometric data drawn from seven countries worldwide were expressed as standard scores. The standard scores were tested to determine if they were consistent with a Gaussian distribution. Empirical multipliers for determining percentile values were developed.In a test case, five anthropometric elements descriptive of seating were combined in addition and subtraction models. Percentile values were estimated for each model by CP, MCM with Gaussian distributed data, or MCM with empirically distributed data. The 5th and 95th percentile values of a dataset of global anthropometric data are shown to be asymmetrically distributed. MCM with empirical multipliers gave more accurate estimates of 5th and 95th percentiles values. Anthropometric data are not Gaussian distributed. The MCM method is more accurate than adding or subtracting percentiles.

Batch Tests To Determine Activity Distribution and Kinetic Parameters for Acetate Utilization in Expanded-Bed Anaerobic Reactors

PubMed Central

Fox, Peter; Suidan, Makram T.

1990-01-01

Batch tests to measure maximum acetate utilization rates were used to determine the distribution of acetate utilizers in expanded-bed sand and expanded-bed granular activated carbon (GAC) reactors. The reactors were fed a mixture of acetate and 3-ethylphenol, and they contained the same predominant aceticlastic methanogen, Methanothrix sp. Batch tests were performed both on the entire reactor contents and with media removed from the reactors. Results indicated that activity was evenly distributed within the GAC reactors, whereas in the sand reactor a sludge blanket on top of the sand bed contained approximately 50% of the activity. The Monod half-velocity constant (Ks) for the acetate-utilizing methanogens in two expanded-bed GAC reactors was searched for by combining steady-state results with batch test data. All parameters necessary to develop a model with Monod kinetics were experimentally determined except for Ks. However, Ks was a function of the effluent 3-ethylphenol concentration, and batch test results demonstrated that maximum acetate utilization rates were not a function of the effluent 3-ethylphenol concentration. Addition of a competitive inhibition term into the Monod expression predicted the dependence of Ks on the effluent 3-ethylphenol concentration. A two-parameter search determined a Ks of 8.99 mg of acetate per liter and a Ki of 2.41 mg of 3-ethylphenol per liter. Model predictions were in agreement with experimental observations for all effluent 3-ethylphenol concentrations. Batch tests measured the activity for a specific substrate and determined the distribution of activity in the reactor. The use of steady-state data in conjunction with batch test results reduced the number of unknown kinetic parameters and thereby reduced the uncertainty in the results and the assumptions made. PMID:16348175

Batch tests to determine activity distribution and kinetic parameters for acetate utilization in expanded-bed anaerobic reactors.

PubMed

Fox, P; Suidan, M T

1990-04-01

Batch tests to measure maximum acetate utilization rates were used to determine the distribution of acetate utilizers in expanded-bed sand and expanded-bed granular activated carbon (GAC) reactors. The reactors were fed a mixture of acetate and 3-ethylphenol, and they contained the same predominant aceticlastic methanogen, Methanothrix sp. Batch tests were performed both on the entire reactor contents and with media removed from the reactors. Results indicated that activity was evenly distributed within the GAC reactors, whereas in the sand reactor a sludge blanket on top of the sand bed contained approximately 50% of the activity. The Monod half-velocity constant (K(s)) for the acetate-utilizing methanogens in two expanded-bed GAC reactors was searched for by combining steady-state results with batch test data. All parameters necessary to develop a model with Monod kinetics were experimentally determined except for K(s). However, K(s) was a function of the effluent 3-ethylphenol concentration, and batch test results demonstrated that maximum acetate utilization rates were not a function of the effluent 3-ethylphenol concentration. Addition of a competitive inhibition term into the Monod expression predicted the dependence of K(s) on the effluent 3-ethylphenol concentration. A two-parameter search determined a K(s) of 8.99 mg of acetate per liter and a K(i) of 2.41 mg of 3-ethylphenol per liter. Model predictions were in agreement with experimental observations for all effluent 3-ethylphenol concentrations. Batch tests measured the activity for a specific substrate and determined the distribution of activity in the reactor. The use of steady-state data in conjunction with batch test results reduced the number of unknown kinetic parameters and thereby reduced the uncertainty in the results and the assumptions made.

A generalised age- and phase-structured model of human tumour cell populations both unperturbed and exposed to a range of cancer therapies.

PubMed

Basse, Britta; Ubezio, Paolo

2007-07-01

We develop a general mathematical model for a population of cells differentiated by their position within the cell division cycle. A system of partial differential equations governs the kinetics of cell densities in certain phases of the cell division cycle dependent on time t (hours) and an age-like variable tau (hours) describing the time since arrival in a particular phase of the cell division cycle. Transition rate functions control the transfer of cells between phases. We first obtain a theoretical solution on the infinite domain -infinity < t < infinity. We then assume that age distributions at time t=0 are known and write our solution in terms of these age distributions on t=0. In practice, of course, these age distributions are unknown. All is not lost, however, because a cell line before treatment usually lies in a state of asynchronous balanced growth where the proportion of cells in each phase of the cell cycle remain constant. We assume that an unperturbed cell line has four distinct phases and that the rate of transition between phases is constant within a short period of observation ('short' relative to the whole history of the tumour growth) and we show that under certain conditions, this is equivalent to exponential growth or decline. We can then gain expressions for the age distributions. So, in short, our approach is to assume that we have an unperturbed cell line on t

Evaluation of a Class of Simple and Effective Uncertainty Methods for Sparse Samples of Random Variables and Functions

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

Romero, Vicente; Bonney, Matthew; Schroeder, Benjamin

When very few samples of a random quantity are available from a source distribution of unknown shape, it is usually not possible to accurately infer the exact distribution from which the data samples come. Under-estimation of important quantities such as response variance and failure probabilities can result. For many engineering purposes, including design and risk analysis, we attempt to avoid under-estimation with a strategy to conservatively estimate (bound) these types of quantities -- without being overly conservative -- when only a few samples of a random quantity are available from model predictions or replicate experiments. This report examines a classmore » of related sparse-data uncertainty representation and inference approaches that are relatively simple, inexpensive, and effective. Tradeoffs between the methods' conservatism, reliability, and risk versus number of data samples (cost) are quantified with multi-attribute metrics use d to assess method performance for conservative estimation of two representative quantities: central 95% of response; and 10 -4 probability of exceeding a response threshold in a tail of the distribution. Each method's performance is characterized with 10,000 random trials on a large number of diverse and challenging distributions. The best method and number of samples to use in a given circumstance depends on the uncertainty quantity to be estimated, the PDF character, and the desired reliability of bounding the true value. On the basis of this large data base and study, a strategy is proposed for selecting the method and number of samples for attaining reasonable credibility levels in bounding these types of quantities when sparse samples of random variables or functions are available from experiments or simulations.« less

Functional diversity of soil invertebrates: a potential tool to explain N2O emission?

NASA Astrophysics Data System (ADS)

Lubbers, Ingrid; De Deyn, Gerlinde; Drake, Harold; Hunger, Sindy; Oppermann, Timo; van Groenigen, Jan Willem

2017-04-01

Soil biota play a crucial role in the mineralization of nutrients from organic material. However, they can thereby increase emissions of the potent greenhouse gas nitrous oxide (N2O). Our current lack of understanding of the factors controlling N2O production and emission is impeding the development of effective mitigation strategies. It is the challenge to control N2O emissions from production systems without reducing crop yield, and diversity of soil fauna may play a key role. A high functional diversity of soil invertebrates is known to stimulate nitrogen mineralization and thereby plant growth, however, it is unknown whether a high functional diversity of soil invertebrates can concurrently diminish N2O emissions. We hypothesized that increased functional diversity of soil invertebrates reduces faunal-induced N2O emissions by facilitating more complete denitrification through (i) stimulating the activity of denitrifying microbes, and (ii) affecting the distribution of micro and macro pores, creating more anaerobic reaction sites. Using state-of-the-art X-ray tomography and next-generation sequencing, we studied effects of functional diversity on soil structural properties and the diversity of the microbial community (16S rRNA genes and 16S rRNA), and linked these to soil N2O emissions. In a 120-day study we found that the functional composition of the soil invertebrate community determined N2O emissions: earthworm activity was key to faunal-induced N2O emissions (a 32-fold increase after 120 days, P<0.001). No proof was found to explain faunal-induced N2O emissions through differences in stimulated microbial activity. On the other hand, soil structural properties (mean pore size, pore size distribution) were found to be radically altered by earthworm activity. We conclude that the presence of a few functional groups (ecosystem engineers) is more important than overall increased functional diversity in explaining faunal-affected N2O emissions.

Functional transient receptor potential vanilloid 1 and transient receptor potential vanilloid 4 channels along different segments of the renal vasculature.

PubMed

Chen, L; Kaßmann, M; Sendeski, M; Tsvetkov, D; Marko, L; Michalick, L; Riehle, M; Liedtke, W B; Kuebler, W M; Harteneck, C; Tepel, M; Patzak, A; Gollasch, M

2015-02-01

Transient receptor potential vanilloid 1 (TRPV1) and vanilloid 4 (TRPV4) cation channels have been recently identified to promote endothelium-dependent relaxation of mouse mesenteric arteries. However, the role of TRPV1 and TRPV4 in the renal vasculature is largely unknown. We hypothesized that TRPV1/4 plays a role in endothelium-dependent vasodilation of renal blood vessels. We studied the distribution of functional TRPV1/4 along different segments of the renal vasculature. Mesenteric arteries were studied as control vessels. The TRPV1 agonist capsaicin relaxed mouse mesenteric arteries with an EC50 of 25 nm, but large mouse renal arteries or rat descending vasa recta only at >100-fold higher concentrations. The vasodilatory effect of capsaicin in the low-nanomolar concentration range was endothelium-dependent and absent in vessels of Trpv1 -/- mice. The TRPV4 agonist GSK1016790A relaxed large conducting renal arteries, mesenteric arteries and vasa recta with EC50 of 18, 63 nm and ~10 nm respectively. These effects were endothelium-dependent and inhibited by a TRPV4 antagonist, AB159908 (10 μm). Capsaicin and GSK1016790A produced vascular dilation in isolated mouse perfused kidneys with EC50 of 23 and 3 nm respectively. The capsaicin effects were largely reduced in Trpv1 -/- kidneys, and the effects of GSK1016790A were inhibited in Trpv4 -/- kidneys. Our results demonstrate that two TRPV channels have unique sites of vasoregulatory function in the kidney with functional TRPV1 having a narrow, discrete distribution in the resistance vasculature and TRPV4 having more universal, widespread distribution along different vascular segments. We suggest that TRPV1/4 channels are potent therapeutic targets for site-specific vasodilation in the kidney. © 2014 Scandinavian Physiological Society. Published by John Wiley & Sons Ltd.

Evolution of tonoplast P-ATPase transporters involved in vacuolar acidification.

PubMed

Li, Yanbang; Provenzano, Sofia; Bliek, Mattijs; Spelt, Cornelis; Appelhagen, Ingo; Machado de Faria, Laura; Verweij, Walter; Schubert, Andrea; Sagasser, Martin; Seidel, Thorsten; Weisshaar, Bernd; Koes, Ronald; Quattrocchio, Francesca

2016-08-01

Petunia mutants (Petunia hybrida) with blue flowers defined a novel vacuolar proton pump consisting of two interacting P-ATPases, PH1 and PH5, that hyper-acidify the vacuoles of petal cells. PH5 is similar to plasma membrane H(+) P3A -ATPase, whereas PH1 is the only known eukaryoticP3B -ATPase. As there were no indications that this tonoplast pump is widespread in plants, we investigated the distribution and evolution of PH1 and PH5. We combined database mining and phylogenetic and synteny analyses of PH1- and PH5-like proteins from all kingdoms with functional analyses (mutant complementation and intracellular localization) of homologs from diverse angiosperms. We identified functional PH1 and PH5 homologs in divergent angiosperms. PH5 homologs evolved from plasma membrane P3A -ATPases, acquiring an N-terminal tonoplast-sorting sequence and new cellular function before angiosperms appeared. PH1 is widespread among seed plants and related proteins are found in some groups of bacteria and fungi and in one moss, but is absent in most algae, suggesting that its evolution involved several cases of gene loss and possibly horizontal transfer events. The distribution of PH1 and PH5 in the plant kingdom suggests that vacuolar acidification by P-ATPases appeared in gymnosperms before flowers. This implies that, next to flower color determination, vacuolar hyper-acidification is required for yet unknown processes. © 2016 European Union. New Phytologist © 2016 New Phytologist Trust.

Drosophila glypican Dally-like acts in FGF-receiving cells to modulate FGF signaling during tracheal morphogenesis

PubMed Central

Yan, Dong; Lin, Xinhua

2007-01-01

Summary Previous studies in Drosophila have shown that heparan sulfate proteoglycans (HSPGs) are involved in both breathless (btl)- and heartless (htl)-mediated FGF signaling during embryogenesis. However, the mechanism(s) by which HSPGs control Btl and Htl signaling is unknown. Here we show that dally-like (dlp, a Drosophila glypican) mutant embryos exhibit severe defects in tracheal morphogenesis and show a reduction in btl-mediated FGF signaling activity. However, htl-dependent mesodermal cell migration is not affected in dlp mutant embryos. Furthermore, expression of Dlp, but not other Drosophila HSPGs, can restore effectively the tracheal morphogenesis in dlp embryos. Rescue experiments in dlp embryos demonstrate that Dlp functions only in Bnl/FGF receiving cells in a cell-autonomous manner, but is not essential for Bnl/FGF expression cells. To further dissect the mechanism(s) of Dlp in Btl signaling, we analyzed the role of Dlp in Btl-mediated air sac tracheoblast formation in wing discs. Mosaic analysis experiments show that removal of HSPG activity in FGF-producing or other surrounding cells does not affect tracheoblasts migration, while HSPG mutant tracheoblast cells fail to receive FGF signaling. Together, our results argue strongly that HSPGs regulate Btl signaling exclusively in FGF-receiving cells as co-receptors, but are not essential for the secretion and distribution of the FGF ligand. This mechanism is distinct from HSPG functions in morphogen distribution, and is likely a general paradigm for HSPG functions in FGF signaling in Drosophila. PMID:17959166

A new family of β-helix proteins with similarities to the polysaccharide lyases

DOE PAGES

Close, Devin W.; D'Angelo, Sara; Bradbury, Andrew R. M.

2014-09-27

Microorganisms that degrade biomass produce diverse assortments of carbohydrate-active enzymes and binding modules. Despite tremendous advances in the genomic sequencing of these organisms, many genes do not have an ascribed function owing to low sequence identity to genes that have been annotated. Consequently, biochemical and structural characterization of genes with unknown function is required to complement the rapidly growing pool of genomic sequencing data. A protein with previously unknown function (Cthe_2159) was recently isolated in a genome-wide screen using phage display to identify cellulose-binding protein domains from the biomass-degrading bacterium Clostridium thermocellum. Here, the crystal structure of Cthe_2159 is presentedmore » and it is shown that it is a unique right-handed parallel β-helix protein. Despite very low sequence identity to known β-helix or carbohydrate-active proteins, Cthe_2159 displays structural features that are very similar to those of polysaccharide lyase (PL) families 1, 3, 6 and 9. Cthe_2159 is conserved across bacteria and some archaea and is a member of the domain of unknown function family DUF4353. This suggests that Cthe_2159 is the first representative of a previously unknown family of cellulose and/or acid-sugar binding β-helix proteins that share structural similarities with PLs. More importantly, these results demonstrate how functional annotation by biochemical and structural analysis remains a critical tool in the characterization of new gene products.« less

A new family of β-helix proteins with similarities to the polysaccharide lyases

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

Close, Devin W.; D'Angelo, Sara; Bradbury, Andrew R. M.

Microorganisms that degrade biomass produce diverse assortments of carbohydrate-active enzymes and binding modules. Despite tremendous advances in the genomic sequencing of these organisms, many genes do not have an ascribed function owing to low sequence identity to genes that have been annotated. Consequently, biochemical and structural characterization of genes with unknown function is required to complement the rapidly growing pool of genomic sequencing data. A protein with previously unknown function (Cthe_2159) was recently isolated in a genome-wide screen using phage display to identify cellulose-binding protein domains from the biomass-degrading bacterium Clostridium thermocellum. Here, the crystal structure of Cthe_2159 is presentedmore » and it is shown that it is a unique right-handed parallel β-helix protein. Despite very low sequence identity to known β-helix or carbohydrate-active proteins, Cthe_2159 displays structural features that are very similar to those of polysaccharide lyase (PL) families 1, 3, 6 and 9. Cthe_2159 is conserved across bacteria and some archaea and is a member of the domain of unknown function family DUF4353. This suggests that Cthe_2159 is the first representative of a previously unknown family of cellulose and/or acid-sugar binding β-helix proteins that share structural similarities with PLs. More importantly, these results demonstrate how functional annotation by biochemical and structural analysis remains a critical tool in the characterization of new gene products.« less

Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

PubMed

Li, Yongming; Tong, Shaocheng

The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.

Particles decorated by an ionizable thermoresponsive polymer brush in water: experiments and self-consistent field modeling.

PubMed

Alves, S P C; Pinheiro, J P; Farinha, J P S; Leermakers, F A M

2014-03-20

We have synthesized anionic multistimuli responsive core-shell polymer nanoparticles with low size dispersity composed of glassy poly(methyl methacrylate) (PMMA) cores of ca. 40 nm radius and poly(N-isopropylacrylamide) (PNIPAM) anionic brush-like shells with methacrylic acid comonomers. Using dynamic light scattering, we observed a volume phase transition upon an increase in temperature and this response was pH and ionic strength dependent. Already at room temperature we observed a pronounced polyelectrolyte effect, that is, a shift of the apparent pKa extracted from the degree of dissociation of the acids as a function of the pH. The multiresponsive behavior of the hydrophobic polyelectrolyte brush has been modeled using the Scheutjens-Fleer self-consistent field (SF-SCF) approach. Using a phenomenological relation between the Flory-Huggins χ parameter and the temperature, we confront the predicted change in the brush height with the observed change of the hydrodynamic radius and degree of dissociation and obtain estimates for the average chain lengths (number of Kuhn segments) of the corona chains, the grafting density and charge density distributions. The theory reveals a rich internal structure of the hydrophobic polyelectrolyte brush, especially near the collapse transition, where we find a microphase segregated structure. Considering this complexity, it is fair to state that the theoretical predictions follow the experimental data semiquantitatively, and it is attractive to attribute the observed disparity between theory and experiments to the unknown polydispersity of the chains, the unknown distribution of the charges, or other experimental complications. More likely, however, the deviations point to significant problems of the mean field theory, which focuses solely on the radial distributions and ignores the possibility of the formation of lateral (local) inhomogeneities in partially collapsed polyelectrolyte brushes. We argue that the PNIPAM brush at room temperature is already behaving nonideally.

Expression Patterns and Subcellular Localization of Carbonic Anhydrases Are Developmentally Regulated during Tooth Formation

PubMed Central

Reibring, Claes-Göran; El Shahawy, Maha; Hallberg, Kristina; Kannius-Janson, Marie; Nilsson, Jeanette; Parkkila, Seppo; Sly, William S.; Waheed, Abdul; Linde, Anders; Gritli-Linde, Amel

2014-01-01

Carbonic anhydrases (CAs) play fundamental roles in several physiological events, and emerging evidence points at their involvement in an array of disorders, including cancer. The expression of CAs in the different cells of teeth is unknown, let alone their expression patterns during odontogenesis. As a first step towards understanding the role of CAs during odontogenesis, we used immunohistochemistry, histochemistry and in situ hybridization to reveal hitherto unknown dynamic distribution patterns of eight CAs in mice. The most salient findings include expression of CAII/Car2 not only in maturation-stage ameloblasts (MA) but also in the papillary layer, dental papilla mesenchyme, odontoblasts and the epithelial rests of Malassez. We uncovered that the latter form lace-like networks around incisors; hitherto these have been known to occur only in molars. All CAs studied were produced by MA, however CAIV, CAIX and CARPXI proteins were distinctly enriched in the ruffled membrane of the ruffled MA but exhibited a homogeneous distribution in smooth-ended MA. While CAIV, CAVI/Car6, CAIX, CARPXI and CAXIV were produced by all odontoblasts, CAIII distribution displayed a striking asymmetry, in that it was virtually confined to odontoblasts in the root of molars and root analog of incisors. Remarkably, from initiation until near completion of odontogenesis and in several other tissues, CAXIII localized mainly in intracellular punctae/vesicles that we show to overlap with LAMP-1- and LAMP-2-positive vesicles, suggesting that CAXIII localizes within lysosomes. We showed that expression of CAs in developing teeth is not confined to cells involved in biomineralization, pointing at their participation in other biological events. Finally, we uncovered novel sites of CA expression, including the developing brain and eye, the olfactory epithelium, melanoblasts, tongue, notochord, nucleus pulposus and sebaceous glands. Our study provides important information for future single or multiple gene targeting strategies aiming at deciphering the function of CAs during odontogenesis. PMID:24789143

Genome-wide enrichment analysis between endometriosis and obesity-related traits reveals novel susceptibility loci

PubMed Central

Rahmioglu, Nilufer; Macgregor, Stuart; Drong, Alexander W.; Hedman, Åsa K.; Harris, Holly R.; Randall, Joshua C.; Prokopenko, Inga; Nyholt, Dale R.; Morris, Andrew P.; Montgomery, Grant W.; Missmer, Stacey A.; Lindgren, Cecilia M.; Zondervan, Krina T.

2015-01-01

Endometriosis is a chronic inflammatory condition in women that results in pelvic pain and subfertility, and has been associated with decreased body mass index (BMI). Genetic variants contributing to the heritable component have started to emerge from genome-wide association studies (GWAS), although the majority remain unknown. Unexpectedly, we observed an intergenic locus on 7p15.2 that was genome-wide significantly associated with both endometriosis and fat distribution (waist-to-hip ratio adjusted for BMI; WHRadjBMI) in an independent meta-GWAS of European ancestry individuals. This led us to investigate the potential overlap in genetic variants underlying the aetiology of endometriosis, WHRadjBMI and BMI using GWAS data. Our analyses demonstrated significant enrichment of common variants between fat distribution and endometriosis (P = 3.7 × 10−3), which was stronger when we restricted the investigation to more severe (Stage B) cases (P = 4.5 × 10−4). However, no genetic enrichment was observed between endometriosis and BMI (P = 0.79). In addition to 7p15.2, we identify four more variants with statistically significant evidence of involvement in both endometriosis and WHRadjBMI (in/near KIFAP3, CAB39L, WNT4, GRB14); two of these, KIFAP3 and CAB39L, are novel associations for both traits. KIFAP3, WNT4 and 7p15.2 are associated with the WNT signalling pathway; formal pathway analysis confirmed a statistically significant (P = 6.41 × 10−4) overrepresentation of shared associations in developmental processes/WNT signalling between the two traits. Our results demonstrate an example of potential biological pleiotropy that was hitherto unknown, and represent an opportunity for functional follow-up of loci and further cross-phenotype comparisons to assess how fat distribution and endometriosis pathogenesis research fields can inform each other. PMID:25296917

Using an APOS Framework to Understand Teachers' Responses to Questions on the Normal Distribution

ERIC Educational Resources Information Center

Bansilal, Sarah

2014-01-01

This study is an exploration of teachers' engagement with concepts embedded in the normal distribution. The participants were a group of 290 in-service teachers enrolled in a teacher development program. The research instrument was an assessment task that can be described as an "unknown percentage" problem, which required the application…

The polyomavirus BK agnoprotein co-localizes with lipid droplets

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

Unterstab, Gunhild; Gosert, Rainer; Leuenberger, David

Agnoprotein encoded by human polyomavirus BK (BKV) is a late cytoplasmic protein of 66 amino acids (aa) of unknown function. Immunofluorescence microscopy revealed a fine granular and a vesicular distribution in donut-like structures. Using BKV(Dunlop)-infected or agnoprotein-transfected cells, we investigated agnoprotein co-localization with subcellular structures. We found that agnoprotein co-localizes with lipid droplets (LD) in primary human renal tubular epithelial cells as well as in other cells supporting BKV replication in vitro (UTA, Vero cells). Using agnoprotein-enhanced green fluorescent protein (EGFP) fusion constructs, we demonstrate that agnoprotein aa 20-42 are required for targeting LD, whereas aa 1-20 or aa 42-66more » were not. Agnoprotein aa 22-40 are predicted to form an amphipathic helix, and mutations A25D and F39E, disrupting its hydrophobic domain, prevented LD targeting. However, changing the phosphorylation site serine-11 to alanine or aspartic acid did not alter LD co-localization. Our findings provide new clues to unravel agnoprotein function.« less

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

Kim, A.; Avakian, H.; Burkert, V.

The target and double spin asymmetries of the exclusive pseudoscalar channel e→p→→epπ0 were measured for the first time in the deep-inelastic regime using a longitudinally polarized 5.9 GeV electron beam and a longitudinally polarized proton target at Jefferson Lab with the CEBAF Large Acceptance Spectrometer (CLAS). The data were collected over a large kinematic phase space and divided into 110 four-dimensional bins of Q2, xB, -t and Φ. Large values of asymmetry moments clearly indicate a substantial contribution to the polarized structure functions from transverse virtual photon amplitudes. The interpretation of experimental data in terms of generalized parton distributions (GPDs)more » provides the first insight on the chiral-odd GPDs H˜T and ET, and complement previous measurements of unpolarized structure functions sensitive to the GPDs HT and E¯T. These data provide a crucial input for parametrizations of essentially unknown chiral-odd GPDs and will strongly influence existing theoretical calculations based on the handbag formalism.« less

Preserved cognitive functions with age are determined by domain-dependent shifts in network responsivity

PubMed Central

Samu, Dávid; Campbell, Karen L.; Tsvetanov, Kamen A.; Shafto, Meredith A.; Brayne, Carol; Bullmore, Edward T.; Calder, Andrew C.; Cusack, Rhodri; Dalgleish, Tim; Duncan, John; Henson, Richard N.; Matthews, Fiona E.; Marslen-Wilson, William D.; Rowe, James B.; Cheung, Teresa; Davis, Simon; Geerligs, Linda; Kievit, Rogier; McCarrey, Anna; Mustafa, Abdur; Price, Darren; Taylor, Jason R.; Treder, Matthias; van Belle, Janna; Williams, Nitin; Bates, Lauren; Emery, Tina; Erzinçlioglu, Sharon; Gadie, Andrew; Gerbase, Sofia; Georgieva, Stanimira; Hanley, Claire; Parkin, Beth; Troy, David; Auer, Tibor; Correia, Marta; Gao, Lu; Green, Emma; Henriques, Rafael; Allen, Jodie; Amery, Gillian; Amunts, Liana; Barcroft, Anne; Castle, Amanda; Dias, Cheryl; Dowrick, Jonathan; Fair, Melissa; Fisher, Hayley; Goulding, Anna; Grewal, Adarsh; Hale, Geoff; Hilton, Andrew; Johnson, Frances; Johnston, Patricia; Kavanagh-Williamson, Thea; Kwasniewska, Magdalena; McMinn, Alison; Norman, Kim; Penrose, Jessica; Roby, Fiona; Rowland, Diane; Sargeant, John; Squire, Maggie; Stevens, Beth; Stoddart, Aldabra; Stone, Cheryl; Thompson, Tracy; Yazlik, Ozlem; Barnes, Dan; Dixon, Marie; Hillman, Jaya; Mitchell, Joanne; Villis, Laura; Tyler, Lorraine K.

2017-01-01

Healthy ageing has disparate effects on different cognitive domains. The neural basis of these differences, however, is largely unknown. We investigated this question by using Independent Components Analysis to obtain functional brain components from 98 healthy participants aged 23–87 years from the population-based Cam-CAN cohort. Participants performed two cognitive tasks that show age-related decrease (fluid intelligence and object naming) and a syntactic comprehension task that shows age-related preservation. We report that activation of task-positive neural components predicts inter-individual differences in performance in each task across the adult lifespan. Furthermore, only the two tasks that show performance declines with age show age-related decreases in task-positive activation of neural components and decreasing default mode (DM) suppression. Our results suggest that distributed, multi-component brain responsivity supports cognition across the adult lifespan, and the maintenance of this, along with maintained DM deactivation, characterizes successful ageing and may explain differential ageing trajectories across cognitive domains. PMID:28480894

The composition and organization of Drosophila heterochromatin are heterogeneous and dynamic

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

Swenson, Joel M.; Colmenares, Serafin U.; Strom, Amy R.

Heterochromatin is enriched for specific epigenetic factors including Heterochromatin Protein 1a (HP1a), and is essential for many organismal functions. To elucidate heterochromatin organization and regulation, we purified Drosophila melanogaster HP1a interactors, and performed a genome-wide RNAi screen to identify genes that impact HP1a levels or localization. The majority of the over four hundred putative HP1a interactors and regulators identified were previously unknown. We found that 13 of 16 tested candidates (83%) are required for gene silencing, providing a substantial increase in the number of identified components that impact heterochromatin properties. Surprisingly, image analysis revealed that although some HP1a interactors andmore » regulators are broadly distributed within the heterochromatin domain, most localize to discrete subdomains that display dynamic localization patterns during the cell cycle. We conclude that heterochromatin composition and architecture is more spatially complex and dynamic than previously suggested, and propose that a network of subdomains regulates diverse heterochromatin functions.« less

The composition and organization of Drosophila heterochromatin are heterogeneous and dynamic

DOE PAGES

Swenson, Joel M.; Colmenares, Serafin U.; Strom, Amy R.; ...

2016-08-11

Heterochromatin is enriched for specific epigenetic factors including Heterochromatin Protein 1a (HP1a), and is essential for many organismal functions. To elucidate heterochromatin organization and regulation, we purified Drosophila melanogaster HP1a interactors, and performed a genome-wide RNAi screen to identify genes that impact HP1a levels or localization. The majority of the over four hundred putative HP1a interactors and regulators identified were previously unknown. We found that 13 of 16 tested candidates (83%) are required for gene silencing, providing a substantial increase in the number of identified components that impact heterochromatin properties. Surprisingly, image analysis revealed that although some HP1a interactors andmore » regulators are broadly distributed within the heterochromatin domain, most localize to discrete subdomains that display dynamic localization patterns during the cell cycle. We conclude that heterochromatin composition and architecture is more spatially complex and dynamic than previously suggested, and propose that a network of subdomains regulates diverse heterochromatin functions.« less

The Tölz Temporal Topography Study: mapping the visual field across the life span. Part I: the topography of light detection and temporal-information processing.

PubMed

Poggel, Dorothe A; Treutwein, Bernhard; Calmanti, Claudia; Strasburger, Hans

2012-08-01

Temporal performance parameters vary across the visual field. Their topographical distributions relative to each other and relative to basic visual performance measures and their relative change over the life span are unknown. Our goal was to characterize the topography and age-related change of temporal performance. We acquired visual field maps in 95 healthy participants (age: 10-90 years): perimetric thresholds, double-pulse resolution (DPR), reaction times (RTs), and letter contrast thresholds. DPR and perimetric thresholds increased with eccentricity and age; the periphery showed a more pronounced age-related increase than the center. RT increased only slightly and uniformly with eccentricity. It remained almost constant up to the age of 60, a marked change occurring only above 80. Overall, age was a poor predictor of functionality. Performance decline could be explained only in part by the aging of the retina and optic media. In Part II, we therefore examine higher visual and cognitive functions.

Regulation of branching dynamics by axon-intrinsic asymmetries in Tyrosine Kinase Receptor signaling

PubMed Central

Zschätzsch, Marlen; Oliva, Carlos; Langen, Marion; De Geest, Natalie; Özel, Mehmet Neset; Williamson, W Ryan; Lemon, William C; Soldano, Alessia; Munck, Sebastian; Hiesinger, P Robin; Sanchez-Soriano, Natalia; Hassan, Bassem A

2014-01-01

Axonal branching allows a neuron to connect to several targets, increasing neuronal circuit complexity. While axonal branching is well described, the mechanisms that control it remain largely unknown. We find that in the Drosophila CNS branches develop through a process of excessive growth followed by pruning. In vivo high-resolution live imaging of developing brains as well as loss and gain of function experiments show that activation of Epidermal Growth Factor Receptor (EGFR) is necessary for branch dynamics and the final branching pattern. Live imaging also reveals that intrinsic asymmetry in EGFR localization regulates the balance between dynamic and static filopodia. Elimination of signaling asymmetry by either loss or gain of EGFR function results in reduced dynamics leading to excessive branch formation. In summary, we propose that the dynamic process of axon branch development is mediated by differential local distribution of signaling receptors. DOI: http://dx.doi.org/10.7554/eLife.01699.001 PMID:24755286

Preserved cognitive functions with age are determined by domain-dependent shifts in network responsivity.

PubMed

Samu, Dávid; Campbell, Karen L; Tsvetanov, Kamen A; Shafto, Meredith A; Tyler, Lorraine K

2017-05-08

Healthy ageing has disparate effects on different cognitive domains. The neural basis of these differences, however, is largely unknown. We investigated this question by using Independent Components Analysis to obtain functional brain components from 98 healthy participants aged 23-87 years from the population-based Cam-CAN cohort. Participants performed two cognitive tasks that show age-related decrease (fluid intelligence and object naming) and a syntactic comprehension task that shows age-related preservation. We report that activation of task-positive neural components predicts inter-individual differences in performance in each task across the adult lifespan. Furthermore, only the two tasks that show performance declines with age show age-related decreases in task-positive activation of neural components and decreasing default mode (DM) suppression. Our results suggest that distributed, multi-component brain responsivity supports cognition across the adult lifespan, and the maintenance of this, along with maintained DM deactivation, characterizes successful ageing and may explain differential ageing trajectories across cognitive domains.

Laminin γ3 plays an important role in retinal lamination, photoreceptor organisation and ganglion cell differentiation.

PubMed

Dorgau, Birthe; Felemban, Majed; Sharpe, Alexander; Bauer, Roman; Hallam, Dean; Steel, David H; Lindsay, Susan; Mellough, Carla; Lako, Majlinda

2018-05-23

Laminins are heterotrimeric glycoproteins of the extracellular matrix. Eleven different laminin chains have been identified in vertebrates. They are ubiquitously expressed in the human body, with a distinct tissue distribution. Laminin expression in neural retina and their functional role during human retinogenesis is still unknown. This study investigated the laminin expression in human developing and adult retina, showing laminin α1, α5, β1, β2 and γ1 to be predominantly expressed in Bruch's membrane and the inner limiting membrane. Laminin-332 and laminin γ3 expression were mainly observed in the neural retina during retinal histogenesis. These expression patterns were largely conserved in pluripotent stem cell-derived retinal organoids. Blocking of laminin γ3 function in retinal organoids resulted in the disruption of laminar organisation and synapse formation, the loss of photoreceptor organisation and retinal ganglion cells. Our data demonstrate a unique temporal and spatial expression for laminins and reveal a novel role for laminin γ3 during human retinogenesis.

Concordance measure and discriminatory accuracy in transformation cure models.

PubMed

Zhang, Yilong; Shao, Yongzhao

2018-01-01

Many populations of early-stage cancer patients have non-negligible latent cure fractions that can be modeled using transformation cure models. However, there is a lack of statistical metrics to evaluate prognostic utility of biomarkers in this context due to the challenges associated with unknown cure status and heavy censorship. In this article, we develop general concordance measures as evaluation metrics for the discriminatory accuracy of transformation cure models including the so-called promotion time cure models and mixture cure models. We introduce explicit formulas for the consistent estimates of the concordance measures, and show that their asymptotically normal distributions do not depend on the unknown censoring distribution. The estimates work for both parametric and semiparametric transformation models as well as transformation cure models. Numerical feasibility of the estimates and their robustness to the censoring distributions are illustrated via simulation studies and demonstrated using a melanoma data set. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Comparative methylomics between domesticated and wild silkworms implies possible epigenetic influences on silkworm domestication

PubMed Central

2013-01-01

Background In contrast to wild species, which have typically evolved phenotypes over long periods of natural selection, domesticates rapidly gained human-preferred agronomic traits in a relatively short-time frame via artificial selection. Under domesticated conditions, many traits can be observed that cannot only be due to environmental alteration. In the case of silkworms, aside from genetic divergence, whether epigenetic divergence played a role in domestication is an unanswered question. The silkworm is still an enigma in that it has two DNA methyltransferases (DNMT1 and DNMT2) but their functionality is unknown. Even in particular the functionality of the widely distributed DNMT1 remains unknown in insects in general. Results By embryonic RNA interference, we reveal that knockdown of silkworm Dnmt1 caused decreased hatchability, providing the first direct experimental evidence of functional significance of insect Dnmt1. In the light of this fact and those that DNA methylation is correlated with gene expression in silkworms and some agronomic traits in domesticated organisms are not stable, we comprehensively compare silk gland methylomes of 3 domesticated (Bombyx mori) and 4 wild (Bombyx mandarina) silkworms to identify differentially methylated genes between the two. We observed 2-fold more differentiated methylated cytosinces (mCs) in domesticated silkworms as compared to their wild counterparts, suggesting a trend of increasing DNA methylation during domestication. Further study of more domesticated and wild silkworms narrowed down the domesticates’ epimutations, and we were able to identify a number of differential genes. One such gene showing demethyaltion in domesticates correspondently displays lower gene expression, and more interestingly, has experienced selective sweep. A methylation-increased gene seems to result in higher expression in domesticates and the function of its Drosophila homolog was previously found to be essential for cell volume regulation, indicating a possible correlation with the enlargement of silk glands in domesticated silkworms. Conclusions Our results imply epigenetic influences at work during domestication, which gives insight into long time historical controversies regarding acquired inheritance. PMID:24059350

Functional annotation from the genome sequence of the giant panda.

PubMed

Huo, Tong; Zhang, Yinjie; Lin, Jianping

2012-08-01

The giant panda is one of the most critically endangered species due to the fragmentation and loss of its habitat. Studying the functions of proteins in this animal, especially specific trait-related proteins, is therefore necessary to protect the species. In this work, the functions of these proteins were investigated using the genome sequence of the giant panda. Data on 21,001 proteins and their functions were stored in the Giant Panda Protein Database, in which the proteins were divided into two groups: 20,179 proteins whose functions can be predicted by GeneScan formed the known-function group, whereas 822 proteins whose functions cannot be predicted by GeneScan comprised the unknown-function group. For the known-function group, we further classified the proteins by molecular function, biological process, cellular component, and tissue specificity. For the unknown-function group, we developed a strategy in which the proteins were filtered by cross-Blast to identify panda-specific proteins under the assumption that proteins related to the panda-specific traits in the unknown-function group exist. After this filtering procedure, we identified 32 proteins (2 of which are membrane proteins) specific to the giant panda genome as compared against the dog and horse genomes. Based on their amino acid sequences, these 32 proteins were further analyzed by functional classification using SVM-Prot, motif prediction using MyHits, and interacting protein prediction using the Database of Interacting Proteins. Nineteen proteins were predicted to be zinc-binding proteins, thus affecting the activities of nucleic acids. The 32 panda-specific proteins will be further investigated by structural and functional analysis.

Teleportation of a 3-dimensional GHZ State

NASA Astrophysics Data System (ADS)

Cao, Hai-Jing; Wang, Huai-Sheng; Li, Peng-Fei; Song, He-Shan

2012-05-01

The process of teleportation of a completely unknown 3-dimensional GHZ state is considered. Three maximally entangled 3-dimensional Bell states function as quantum channel in the scheme. This teleportation scheme can be directly generalized to teleport an unknown d-dimensional GHZ state.

Notes on SAW Tag Interrogation Techniques

NASA Technical Reports Server (NTRS)

Barton, Richard J.

2010-01-01

We consider the problem of interrogating a single SAW RFID tag with a known ID and known range in the presence of multiple interfering tags under the following assumptions: (1) The RF propagation environment is well approximated as a simple delay channel with geometric power-decay constant alpha >/= 2. (2) The interfering tag IDs are unknown but well approximated as independent, identically distributed random samples from a probability distribution of tag ID waveforms with known second-order properties, and the tag of interest is drawn independently from the same distribution. (3) The ranges of the interfering tags are unknown but well approximated as independent, identically distributed realizations of a random variable rho with a known probability distribution f(sub rho) , and the tag ranges are independent of the tag ID waveforms. In particular, we model the tag waveforms as random impulse responses from a wide-sense-stationary, uncorrelated-scattering (WSSUS) fading channel with known bandwidth and scattering function. A brief discussion of the properties of such channels and the notation used to describe them in this document is given in the Appendix. Under these assumptions, we derive the expression for the output signal-to-noise ratio (SNR) for an arbitrary combination of transmitted interrogation signal and linear receiver filter. Based on this expression, we derive the optimal interrogator configuration (i.e., transmitted signal/receiver filter combination) in the two extreme noise/interference regimes, i.e., noise-limited and interference-limited, under the additional assumption that the coherence bandwidth of the tags is much smaller than the total tag bandwidth. Finally, we evaluate the performance of both optimal interrogators over a broad range of operating scenarios using both numerical simulation based on the assumed model and Monte Carlo simulation based on a small sample of measured tag waveforms. The performance evaluation results not only provide guidelines for proper interrogator design, but also provide some insight on the validity of the assumed signal model. It should be noted that the assumption that the impulse response of the tag of interest is known precisely implies that the temperature and range of the tag are also known precisely, which is generally not the case in practice. However, analyzing interrogator performance under this simplifying assumption is much more straightforward and still provides a great deal of insight into the nature of the problem.

Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples

PubMed Central

Kim, Bernard Y.; Huber, Christian D.; Lohmueller, Kirk E.

2017-01-01

The distribution of fitness effects (DFE) has considerable importance in population genetics. To date, estimates of the DFE come from studies using a small number of individuals. Thus, estimates of the proportion of moderately to strongly deleterious new mutations may be unreliable because such variants are unlikely to be segregating in the data. Additionally, the true functional form of the DFE is unknown, and estimates of the DFE differ significantly between studies. Here we present a flexible and computationally tractable method, called Fit∂a∂i, to estimate the DFE of new mutations using the site frequency spectrum from a large number of individuals. We apply our approach to the frequency spectrum of 1300 Europeans from the Exome Sequencing Project ESP6400 data set, 1298 Danes from the LuCamp data set, and 432 Europeans from the 1000 Genomes Project to estimate the DFE of deleterious nonsynonymous mutations. We infer significantly fewer (0.38–0.84 fold) strongly deleterious mutations with selection coefficient |s| > 0.01 and more (1.24–1.43 fold) weakly deleterious mutations with selection coefficient |s| < 0.001 compared to previous estimates. Furthermore, a DFE that is a mixture distribution of a point mass at neutrality plus a gamma distribution fits better than a gamma distribution in two of the three data sets. Our results suggest that nearly neutral forces play a larger role in human evolution than previously thought. PMID:28249985

Distributions of observed death tolls govern sensitivity to human fatalities

PubMed Central

Olivola, Christopher Y.; Sagara, Namika

2009-01-01

How we react to humanitarian crises, epidemics, and other tragic events involving the loss of human lives depends largely on the extent to which we are moved by the size of their associated death tolls. Many studies have demonstrated that people generally exhibit a diminishing sensitivity to the number of human fatalities and, equivalently, a preference for risky (vs. sure) alternatives in decisions under risk involving human losses. However, the reason for this tendency remains unknown. Here we show that the distributions of event-related death tolls that people observe govern their evaluations of, and risk preferences concerning, human fatalities. In particular, we show that our diminishing sensitivity to human fatalities follows from the fact that these death tolls are approximately power-law distributed. We further show that, by manipulating the distribution of mortality-related events that people observe, we can alter their risk preferences in decisions involving fatalities. Finally, we show that the tendency to be risk-seeking in mortality-related decisions is lower in countries in which high-mortality events are more frequently observed. Our results support a model of magnitude evaluation based on memory sampling and relative judgment. This model departs from the utility-based approaches typically encountered in psychology and economics in that it does not rely on stable, underlying value representations to explain valuation and choice, or on choice behavior to derive value functions. Instead, preferences concerning human fatalities emerge spontaneously from the distributions of sampled events and the relative nature of the evaluation process. PMID:20018778

Sparse graph regularization for robust crop mapping using hyperspectral remotely sensed imagery with very few in situ data

NASA Astrophysics Data System (ADS)

Xue, Zhaohui; Du, Peijun; Li, Jun; Su, Hongjun

2017-02-01

The generally limited availability of training data relative to the usually high data dimension pose a great challenge to accurate classification of hyperspectral imagery, especially for identifying crops characterized with highly correlated spectra. However, traditional parametric classification models are problematic due to the need of non-singular class-specific covariance matrices. In this research, a novel sparse graph regularization (SGR) method is presented, aiming at robust crop mapping using hyperspectral imagery with very few in situ data. The core of SGR lies in propagating labels from known data to unknown, which is triggered by: (1) the fraction matrix generated for the large unknown data by using an effective sparse representation algorithm with respect to the few training data serving as the dictionary; (2) the prediction function estimated for the few training data by formulating a regularization model based on sparse graph. Then, the labels of large unknown data can be obtained by maximizing the posterior probability distribution based on the two ingredients. SGR is more discriminative, data-adaptive, robust to noise, and efficient, which is unique with regard to previously proposed approaches and has high potentials in discriminating crops, especially when facing insufficient training data and high-dimensional spectral space. The study area is located at Zhangye basin in the middle reaches of Heihe watershed, Gansu, China, where eight crop types were mapped with Compact Airborne Spectrographic Imager (CASI) and Shortwave Infrared Airborne Spectrogrpahic Imager (SASI) hyperspectral data. Experimental results demonstrate that the proposed method significantly outperforms other traditional and state-of-the-art methods.

A Modified Goodness-of-Fit Test for the Lognormal Distribution with Unknown Scale and Location Parameters.

DTIC Science & Technology

1986-12-01

Force and other branches of the military are placing an increased emphasis on system reliablity and maintainability. In studying current systems ...used in the research of proposed systems , by predicting MTTF and MTTR of the new parts and thus, predict the reliability of those parts. The statistics...effectiveness of new systems . Aitchison’s book on the lognormal distribution, printed and used by Cambridge University, highlighted the distributions

Modeling the Solar Dust Environment at 9.5 Solar Radii: Revealing Radiance Trends with MESSENGER Star Tracker Data

NASA Astrophysics Data System (ADS)

Strong, S. B.; Strikwerda, T.; Lario, D.; Raouafi, N.; Decker, R.

2010-12-01

The main components of interplanetary dust are created through destruction, erosion, and collision of asteroids and comets (e.g. Mann et al. 2006). Solar radiation forces distribute these interplanetary dust particles throughout the solar system. The percent contribution of these source particulates to the net interplanetary dust distribution can reveal information about solar nebula conditions, within which these objects are formed. In the absence of observational data (e.g. Helios, Pioneer), specifically at distances less than 0.3 AU, the precise dust distributions remain unknown and limited to 1 AU extrapolative models (e.g. Mann et al. 2003). We have developed a model suitable for the investigation of scattered dust and electron irradiance incident on a sensor for distances inward of 1 AU. The model utilizes the Grün et al. (1985) and Mann et al. (2004) dust distribution theory combined with Mie theory and Thomson electron scattering to determine the magnitude of solar irradiance scattered towards an optical sensor as a function of helio-ecliptic latitude and longitude. MESSENGER star tracker observations (launch to 2010) of the ambient celestial background combined with Helios data (Lienert et al. 1982) reveal trends in support of the model predictions. This analysis further emphasizes the need to characterize the inner solar system dust environment in anticipation of near-Solar missions.

Normal Distribution of CD8+ T-Cell-Derived ELISPOT Counts within Replicates Justifies the Reliance on Parametric Statistics for Identifying Positive Responses.

PubMed

Karulin, Alexey Y; Caspell, Richard; Dittrich, Marcus; Lehmann, Paul V

2015-03-02

Accurate assessment of positive ELISPOT responses for low frequencies of antigen-specific T-cells is controversial. In particular, it is still unknown whether ELISPOT counts within replicate wells follow a theoretical distribution function, and thus whether high power parametric statistics can be used to discriminate between positive and negative wells. We studied experimental distributions of spot counts for up to 120 replicate wells of IFN-γ production by CD8+ T-cell responding to EBV LMP2A (426 - 434) peptide in human PBMC. The cells were tested in serial dilutions covering a wide range of average spot counts per condition, from just a few to hundreds of spots per well. Statistical analysis of the data using diagnostic Q-Q plots and the Shapiro-Wilk normality test showed that in the entire dynamic range of ELISPOT spot counts within replicate wells followed a normal distribution. This result implies that the Student t-Test and ANOVA are suited to identify positive responses. We also show experimentally that borderline responses can be reliably detected by involving more replicate wells, plating higher numbers of PBMC, addition of IL-7, or a combination of these. Furthermore, we have experimentally verified that the number of replicates needed for detection of weak responses can be calculated using parametric statistics.

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.

The structure of the cyanobactin domain of unknown function from PatG in the patellamide gene cluster

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

Mann, Greg; Koehnke, Jesko; Bent, Andrew F.

The highly conserved domain of unknown function in the cyanobactin superfamily has a novel fold. The protein does not appear to bind the most plausible substrates, leaving questions as to its role. Patellamides are members of the cyanobactin family of ribosomally synthesized and post-translationally modified cyclic peptide natural products, many of which, including some patellamides, are biologically active. A detailed mechanistic understanding of the biosynthetic pathway would enable the construction of a biotechnological ‘toolkit’ to make novel analogues of patellamides that are not found in nature. All but two of the protein domains involved in patellamide biosynthesis have been characterized.more » The two domains of unknown function (DUFs) are homologous to each other and are found at the C-termini of the multi-domain proteins PatA and PatG. The domain sequence is found in all cyanobactin-biosynthetic pathways characterized to date, implying a functional role in cyanobactin biosynthesis. Here, the crystal structure of the PatG DUF domain is reported and its binding interactions with plausible substrates are investigated.« less

Singular values behaviour optimization in the diagnosis of feed misalignments in radioastronomical reflectors

NASA Astrophysics Data System (ADS)

Capozzoli, Amedeo; Curcio, Claudio; Liseno, Angelo; Savarese, Salvatore; Schipani, Pietro

2016-07-01

The communication presents an innovative method for the diagnosis of reflector antennas in radio astronomical applications. The approach is based on the optimization of the number and the distribution of the far field sampling points exploited to retrieve the antenna status in terms of feed misalignments, this to drastically reduce the time length of the measurement process and minimize the effects of variable environmental conditions and simplifying the tracking process of the source. The feed misplacement is modeled in terms of an aberration function of the aperture field. The relationship between the unknowns and the far field pattern samples is linearized thanks to a Principal Component Analysis. The number and the position of the field samples are then determined by optimizing the Singular Values behaviour of the relevant operator.

Schlieren Cinematography of Current Driven Plasma Jet Dynamics

NASA Astrophysics Data System (ADS)

Loebner, Keith; Underwood, Thomas; Cappelli, Mark

2016-10-01

Schlieren cinematography of a pulsed plasma deflagration jet is presented and analyzed. An ultra-high frame rate CMOS camera coupled to a Z-type laser Schlieren apparatus is used to obtain flow-field refractometry data for the continuous flow Z-pinch formed within the plasma deflagration jet. The 10 MHz frame rate for 256 consecutive frames provides high temporal resolution, enabling turbulent fluctuations and plasma instabilities to be visualized over the course of a single pulse (20 μs). The Schlieren signal is radiometrically calibrated to obtain a two dimensional mapping of the refraction angle of the axisymmetric pinch plasma, and this mapping is then Abel inverted to derive the plasma density distribution as a function radius, axial coordinate, and time. Analyses of previously unknown discharge characteristics and comparisons with prior work are discussed.

Observation of Turbulent Intermittency Scaling with Magnetic Helicity in an MHD Plasma Wind Tunnel

NASA Astrophysics Data System (ADS)

Schaffner, D. A.; Wan, A.; Brown, M. R.

2014-04-01

The intermittency in turbulent magnetic field fluctuations has been observed to scale with the amount of magnetic helicity injected into a laboratory plasma. An unstable spheromak injected into the MHD wind tunnel of the Swarthmore Spheromak Experiment displays turbulent magnetic and plasma fluctuations as it relaxes into a Taylor state. The level of intermittency of this turbulence is determined by finding the flatness of the probability distribution function of increments for magnetic pickup coil fluctuations B˙(t). The intermittency increases with the injected helicity, but spectral indices are unaffected by this variation. While evidence is provided which supports the hypothesis that current sheets and reconnection sites are related to the generation of this intermittent signal, the true nature of the observed intermittency remains unknown.

Adaptive Neural Networks Prescribed Performance Control Design for Switched Interconnected Uncertain Nonlinear Systems.

PubMed

Li, Yongming; Tong, Shaocheng

2017-06-28

In this paper, an adaptive neural networks (NNs)-based decentralized control scheme with the prescribed performance is proposed for uncertain switched nonstrict-feedback interconnected nonlinear systems. It is assumed that nonlinear interconnected terms and nonlinear functions of the concerned systems are unknown, and also the switching signals are unknown and arbitrary. A linear state estimator is constructed to solve the problem of unmeasured states. The NNs are employed to approximate unknown interconnected terms and nonlinear functions. A new output feedback decentralized control scheme is developed by using the adaptive backstepping design technique. The control design problem of nonlinear interconnected switched systems with unknown switching signals can be solved by the proposed scheme, and only a tuning parameter is needed for each subsystem. The proposed scheme can ensure that all variables of the control systems are semi-globally uniformly ultimately bounded and the tracking errors converge to a small residual set with the prescribed performance bound. The effectiveness of the proposed control approach is verified by some simulation results.

The Protein Interactome of Mycobacteriophage Giles Predicts Functions for Unknown Proteins.

PubMed

Mehla, Jitender; Dedrick, Rebekah M; Caufield, J Harry; Siefring, Rachel; Mair, Megan; Johnson, Allison; Hatfull, Graham F; Uetz, Peter

2015-08-01

Mycobacteriophages are viruses that infect mycobacterial hosts and are prevalent in the environment. Nearly 700 mycobacteriophage genomes have been completely sequenced, revealing considerable diversity and genetic novelty. Here, we have determined the protein complement of mycobacteriophage Giles by mass spectrometry and mapped its genome-wide protein interactome to help elucidate the roles of its 77 predicted proteins, 50% of which have no known function. About 22,000 individual yeast two-hybrid (Y2H) tests with four different Y2H vectors, followed by filtering and retest screens, resulted in 324 reproducible protein-protein interactions, including 171 (136 nonredundant) high-confidence interactions. The complete set of high-confidence interactions among Giles proteins reveals new mechanistic details and predicts functions for unknown proteins. The Giles interactome is the first for any mycobacteriophage and one of just five known phage interactomes so far. Our results will help in understanding mycobacteriophage biology and aid in development of new genetic and therapeutic tools to understand Mycobacterium tuberculosis. Mycobacterium tuberculosis causes over 9 million new cases of tuberculosis each year. Mycobacteriophages, viruses of mycobacterial hosts, hold considerable potential to understand phage diversity, evolution, and mycobacterial biology, aiding in the development of therapeutic tools to control mycobacterial infections. The mycobacteriophage Giles protein-protein interaction network allows us to predict functions for unknown proteins and shed light on major biological processes in phage biology. For example, Giles gp76, a protein of unknown function, is found to associate with phage packaging and maturation. The functions of mycobacteriophage-derived proteins may suggest novel therapeutic approaches for tuberculosis. Our ORFeome clone set of Giles proteins and the interactome data will be useful resources for phage interactomics. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

A note on the blind deconvolution of multiple sparse signals from unknown subspaces

NASA Astrophysics Data System (ADS)

Cosse, Augustin

2017-08-01

This note studies the recovery of multiple sparse signals, xn ∈ ℝL, n = 1, . . . , N, from the knowledge of their convolution with an unknown point spread function h ∈ ℝL. When the point spread function is known to be nonzero, |h[k]| > 0, this blind deconvolution problem can be relaxed into a linear, ill-posed inverse problem in the vector concatenating the unknown inputs xn together with the inverse of the filter, d ∈ ℝL where d[k] := 1/h[k]. When prior information is given on the input subspaces, the resulting overdetermined linear system can be solved efficiently via least squares (see Ling et al. 20161). When no information is given on those subspaces, and the inputs are only known to be sparse, it still remains possible to recover these inputs along with the filter by considering an additional l1 penalty. This note certifies exact recovery of both the unknown PSF and unknown sparse inputs, from the knowledge of their convolutions, as soon as the number of inputs N and the dimension of each input, L , satisfy L ≳ N and N ≳ T2max, up to log factors. Here Tmax = maxn{Tn} and Tn, n = 1, . . . , N denote the supports of the inputs xn. Our proof system combines the recent results on blind deconvolution via least squares to certify invertibility of the linear map encoding the convolutions, with the construction of a dual certificate following the structure first suggested in Candés et al. 2007.2 Unlike in these papers, however, it is not possible to rely on the norm ||(A*TAT)-1|| to certify recovery. We instead use a combination of the Schur Complement and Neumann series to compute an expression for the inverse (A*TAT)-1. Given this expression, it is possible to show that the poorly scaled blocks in (A*TAT)-1 are multiplied by the better scaled ones or vanish in the construction of the certificate. Recovery is certified with high probablility on the choice of the supports and distribution of the signs of each input xn on the support. The paper follows the line of previous work by Wang et al. 20163 where the authors guarantee recovery for subgaussian × Bernoulli inputs satisfying 𝔼xn|k| ∈ [1/10, 1] as soon as N ≳ L. Examples of applications include seismic imaging with unknown source or marine seismic data deghosting, magnetic resonance autocalibration or multiple channel estimation in communication. Numerical experiments are provided along with a discussion on the sample complexity tightness.

Photocopy of photograph. Photographer unknown. Poster from the World War ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Photocopy of photograph. Photographer unknown. Poster from the World War II period. During drives to encourage purchase of war bonds, posters featuring female shipyard workers were widely distributed purchasers were allowed one vote for each bond bought. Votes were cast and the woman who got the most votes was named "War Bond Girl." The contest was won by Kay McGinty, 4th row, 2nd column. - Naval Base Philadelphia-Philadelphia Naval Shipyard, League Island, Philadelphia, Philadelphia County, PA

The importance of data quality for generating reliable distribution models for rare, elusive, and cryptic species

Treesearch

Keith B. Aubry; Catherine M. Raley; Kevin S. McKelvey

2017-01-01

The availability of spatially referenced environmental data and species occurrence records in online databases enable practitioners to easily generate species distribution models (SDMs) for a broad array of taxa. Such databases often include occurrence records of unknown reliability, yet little information is available on the influence of data quality on SDMs generated...

Design of Genetic Algorithms for Topology Control of Unmanned Vehicles

DTIC Science & Technology

2010-01-01

decentralised topology control mechanism distributed among active running software agents to achieve a uniform spread of terrestrial unmanned vehicles...14. ABSTRACT We present genetic algorithms (GAs) as a decentralised topology control mechanism distributed among active running software agents to...inspired topology control algorithm. The topology control of UVs using a decentralised solution over an unknown geographical terrain is a challenging

Coaching the exploration and exploitation in active learning for interactive video retrieval.

PubMed

Wei, Xiao-Yong; Yang, Zhen-Qun

2013-03-01

Conventional active learning approaches for interactive video/image retrieval usually assume the query distribution is unknown, as it is difficult to estimate with only a limited number of labeled instances available. Thus, it is easy to put the system in a dilemma whether to explore the feature space in uncertain areas for a better understanding of the query distribution or to harvest in certain areas for more relevant instances. In this paper, we propose a novel approach called coached active learning that makes the query distribution predictable through training and, therefore, avoids the risk of searching on a completely unknown space. The estimated distribution, which provides a more global view of the feature space, can be used to schedule not only the timing but also the step sizes of the exploration and the exploitation in a principled way. The results of the experiments on a large-scale data set from TRECVID 2005-2009 validate the efficiency and effectiveness of our approach, which demonstrates an encouraging performance when facing domain-shift, outperforms eight conventional active learning methods, and shows superiority to six state-of-the-art interactive video retrieval systems.

Estimating the periodic components of a biomedical signal through inverse problem modelling and Bayesian inference with sparsity enforcing prior

NASA Astrophysics Data System (ADS)

Dumitru, Mircea; Djafari, Ali-Mohammad

2015-01-01

The recent developments in chronobiology need a periodic components variation analysis for the signals expressing the biological rhythms. A precise estimation of the periodic components vector is required. The classical approaches, based on FFT methods, are inefficient considering the particularities of the data (short length). In this paper we propose a new method, using the sparsity prior information (reduced number of non-zero values components). The considered law is the Student-t distribution, viewed as a marginal distribution of a Infinite Gaussian Scale Mixture (IGSM) defined via a hidden variable representing the inverse variances and modelled as a Gamma Distribution. The hyperparameters are modelled using the conjugate priors, i.e. using Inverse Gamma Distributions. The expression of the joint posterior law of the unknown periodic components vector, hidden variables and hyperparameters is obtained and then the unknowns are estimated via Joint Maximum A Posteriori (JMAP) and Posterior Mean (PM). For the PM estimator, the expression of the posterior law is approximated by a separable one, via the Bayesian Variational Approximation (BVA), using the Kullback-Leibler (KL) divergence. Finally we show the results on synthetic data in cancer treatment applications.

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Applications

NASA Technical Reports Server (NTRS)

Phan, Minh Q.

1998-01-01

This report describes a nonlinear mapping technique where the unknown static or dynamic system is approximated by a sum of dimensionally increasing functions (one-dimensional curves, two-dimensional surfaces, etc.). These lower dimensional functions are synthesized from a set of multi-resolution basis functions, where the resolutions specify the level of details at which the nonlinear system is approximated. The basis functions also cause the parameter estimation step to become linear. This feature is taken advantage of to derive a systematic procedure to determine and eliminate basis functions that are less significant for the particular system under identification. The number of unknown parameters that must be estimated is thus reduced and compact models obtained. The lower dimensional functions (identified curves and surfaces) permit a kind of "visualization" into the complexity of the nonlinearity itself.

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Application

NASA Technical Reports Server (NTRS)

Phan, Minh Q.

1997-01-01

This report describes a nonlinear mapping technique where the unknown static or dynamic system is approximated by a sum of dimensionally increasing functions (one-dimensional curves, two-dimensional surfaces, etc.). These lower dimensional functions are synthesized from a set of multi-resolution basis functions, where the resolutions specify the level of details at which the nonlinear system is approximated. The basis functions also cause the parameter estimation step to become linear. This feature is taken advantage of to derive a systematic procedure to determine and eliminate basis functions that are less significant for the particular system under identification. The number of unknown parameters that must be estimated is thus reduced and compact models obtained. The lower dimensional functions (identified curves and surfaces) permit a kind of "visualization" into the complexity of the nonlinearity itself.

5. VIEW EAST, height finder radar towers, radar tower (unknown ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

5. VIEW EAST, height finder radar towers, radar tower (unknown function), prime search radar tower, operations building, and central heating plant - Fort Custer Military Reservation, P-67 Radar Station, .25 mile north of Dickman Road, east of Clark Road, Battle Creek, Calhoun County, MI

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

NASA Astrophysics Data System (ADS)

Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.

2018-03-01

Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

Investigating physical field effects on the size-dependent dynamic behavior of inhomogeneous nanoscale plates

NASA Astrophysics Data System (ADS)

Ebrahimi, Farzad; Reza Barati, Mohammad

2017-02-01

This article investigates the thermo-mechanical vibration frequencies of magneto-electro-thermo-elastic functionally graded (METE-FG) nanoplates in the framework of refined four-unknown shear deformation plate theory. The present nanoplate is subjected to various kinds of thermal loads with uniform, linear and nonlinear distributions. The nonlinear distribution is considered as heat conduction and sinusoidal temperature rise. The present refined theory captures the influences of shear deformations without the need for shear correction factors. Thermo-magneto-electro-elastic coefficients of the FG nanoplate vary gradually along the thickness according to the power-law form. The scale coefficient is taken into consideration implementing the nonlocal elasticity of Eringen. The governing equations are derived through Hamilton's principle and are solved analytically. The frequency response is compared with those of previously published data. The obtained results are presented for the thermo-mechanical vibrations of the FG nanobeams to investigate the effects of material graduation, nonlocal parameter, mode number, slenderness ratio and thermal loading in detail. The present study is associated to aerospace, mechanical and nuclear engineering structures which are under thermal loads.

Towards a cosmic-ray mass-composition study at Tunka Radio Extension

NASA Astrophysics Data System (ADS)

Kostunin, D.; Bezyazeekov, P. A.; Budnev, N. M.; Fedorov, O.; Gress, O. A.; Haungs, A.; Hiller, R.; Huege, T.; Kazarina, Y.; Kleifges, M.; Korosteleva, E. E.; Krömer, O.; Kungel, V.; Kuzmichev, L. A.; Lubsandorzhiev, N.; Mirgazov, R. R.; Monkhoev, R.; Osipova, E. A.; Pakhorukov, A.; Pankov, L.; Prosin, V. V.; Rubtsov, G. I.; Schröder, F. G.; Wischnewski, R.; Zagorodnikov, A.

2017-03-01

The Tunka Radio Extension (Tunka-Rex) is a radio detector at the TAIGA facility located in Siberia nearby the southern tip of Lake Baikal. Tunka-Rex measures air-showers induced by high-energy cosmic rays, in particular, the lateral distribution of the radio pulses. The depth of the air-shower maximum, statistically depends on the mass of the primary particle, is determined from the slope of the lateral distribution function (LDF). Using a model-independent approach, we have studied possible features of the one-dimensional slope method and tried to find improvements for the reconstruction of primary mass. To study the systematic uncertainties given by different primary particles, we have performed simulations using the CONEX and CoREAS software packages of the recently released CORSIKA v7.5 including the modern high-energy hadronic models QGSJet-II.04 and EPOS-LHC. The simulations have shown that the largest systematic uncertainty in the energy deposit is due to the unknown primary particle. Finally, we studied the relation between the polarization and the asymmetry of the LDF.

Cyber-Physical Trade-Offs in Distributed Detection Networks

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

Rao, Nageswara S; Yao, David K. Y.; Chin, J. C.

2010-01-01

We consider a network of sensors that measure the scalar intensity due to the background or a source combined with background, inside a two-dimensional monitoring area. The sensor measurements may be random due to the underlying nature of the source and background or due to sensor errors or both. The detection problem is infer the presence of a source of unknown intensity and location based on sensor measurements. In the conventional approach, detection decisions are made at the individual sensors, which are then combined at the fusion center, for example using the majority rule. With increased communication and computation costs,more » we show that a more complex fusion algorithm based on measurements achieves better detection performance under smooth and non-smooth source intensity functions, Lipschitz conditions on probability ratios and a minimum packing number for the state-space. We show that these conditions for trade-offs between the cyber costs and physical detection performance are applicable for two detection problems: (i) point radiation sources amidst background radiation, and (ii) sources and background with Gaussian distributions.« less

Rényi continuous entropy of DNA sequences.

PubMed

Vinga, Susana; Almeida, Jonas S

2004-12-07

Entropy measures of DNA sequences estimate their randomness or, inversely, their repeatability. L-block Shannon discrete entropy accounts for the empirical distribution of all length-L words and has convergence problems for finite sequences. A new entropy measure that extends Shannon's formalism is proposed. Renyi's quadratic entropy calculated with Parzen window density estimation method applied to CGR/USM continuous maps of DNA sequences constitute a novel technique to evaluate sequence global randomness without some of the former method drawbacks. The asymptotic behaviour of this new measure was analytically deduced and the calculation of entropies for several synthetic and experimental biological sequences was performed. The results obtained were compared with the distributions of the null model of randomness obtained by simulation. The biological sequences have shown a different p-value according to the kernel resolution of Parzen's method, which might indicate an unknown level of organization of their patterns. This new technique can be very useful in the study of DNA sequence complexity and provide additional tools for DNA entropy estimation. The main MATLAB applications developed and additional material are available at the webpage . Specialized functions can be obtained from the authors.

Experimental modelling of fragmentation applied to volcanic explosions

NASA Astrophysics Data System (ADS)

Haug, Øystein Thordén; Galland, Olivier; Gisler, Galen R.

2013-12-01

Explosions during volcanic eruptions cause fragmentation of magma and host rock, resulting in fragments with sizes ranging from boulders to fine ash. The products can be described by fragment size distributions (FSD), which commonly follow power laws with exponent D. The processes that lead to power-law distributions and the physical parameters that control D remain unknown. We developed a quantitative experimental procedure to study the physics of the fragmentation process through time. The apparatus consists of a Hele-Shaw cell containing a layer of cohesive silica flour that is fragmented by a rapid injection of pressurized air. The evolving fragmentation of the flour is monitored with a high-speed camera, and the images are analysed to obtain the evolution of the number of fragments (N), their average size (A), and the FSD. Using the results from our image-analysis procedure, we find transient empirical laws for N, A and the exponent D of the power-law FSD as functions of the initial air pressure. We show that our experimental procedure is a promising tool for unravelling the complex physics of fragmentation during phreatomagmatic and phreatic eruptions.

Online Cross-Validation-Based Ensemble Learning

PubMed Central

Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

2017-01-01

Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. PMID:28474419

Development of a European Ensemble System for Seasonal Prediction: Application to crop yield

NASA Astrophysics Data System (ADS)

Terres, J. M.; Cantelaube, P.

2003-04-01

Western European agriculture is highly intensive and the weather is the main source of uncertainty for crop yield assessment and for crop management. In the current system, at the time when a crop yield forecast is issued, the weather conditions leading up to harvest time are unknown and are therefore a major source of uncertainty. The use of seasonal weather forecast would bring additional information for the remaining crop season and has valuable benefit for improving the management of agricultural markets and environmentally sustainable farm practices. An innovative method for supplying seasonal forecast information to crop simulation models has been developed in the frame of the EU funded research project DEMETER. It consists in running a crop model on each individual member of the seasonal hindcasts to derive a probability distribution of crop yield. Preliminary results of cumulative probability function of wheat yield provides information on both the yield anomaly and the reliability of the forecast. Based on the spread of the probability distribution, the end-user can directly quantify the benefits and risks of taking weather-sensitive decisions.

Attention reduces spatial uncertainty in human ventral temporal cortex.

PubMed

Kay, Kendrick N; Weiner, Kevin S; Grill-Spector, Kalanit

2015-03-02

Ventral temporal cortex (VTC) is the latest stage of the ventral "what" visual pathway, which is thought to code the identity of a stimulus regardless of its position or size [1, 2]. Surprisingly, recent studies show that position information can be decoded from VTC [3-5]. However, the computational mechanisms by which spatial information is encoded in VTC are unknown. Furthermore, how attention influences spatial representations in human VTC is also unknown because the effect of attention on spatial representations has only been examined in the dorsal "where" visual pathway [6-10]. Here, we fill these significant gaps in knowledge using an approach that combines functional magnetic resonance imaging and sophisticated computational methods. We first develop a population receptive field (pRF) model [11, 12] of spatial responses in human VTC. Consisting of spatial summation followed by a compressive nonlinearity, this model accurately predicts responses of individual voxels to stimuli at any position and size, explains how spatial information is encoded, and reveals a functional hierarchy in VTC. We then manipulate attention and use our model to decipher the effects of attention. We find that attention to the stimulus systematically and selectively modulates responses in VTC, but not early visual areas. Locally, attention increases eccentricity, size, and gain of individual pRFs, thereby increasing position tolerance. However, globally, these effects reduce uncertainty regarding stimulus location and actually increase position sensitivity of distributed responses across VTC. These results demonstrate that attention actively shapes and enhances spatial representations in the ventral visual pathway. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of genomic rearrangements, horizontal gene transfer and role of plasmids in the evolution of industrial important Thermus species.

PubMed

Kumwenda, Benjamin; Litthauer, Derek; Reva, Oleg

2014-09-25

Bacteria of genus Thermus inhabit both man-made and natural thermal environments. Several Thermus species have shown biotechnological potential such as reduction of heavy metals which is essential for eradication of heavy metal pollution; removing of organic contaminants in water; opening clogged pipes, controlling global warming among many others. Enzymes from thermophilic bacteria have exhibited higher activity and stability than synthetic or enzymes from mesophilic organisms. Using Meiothermus silvanus DSM 9946 as a reference genome, high level of coordinated rearrangements has been observed in extremely thermophilic Thermus that may imply existence of yet unknown evolutionary forces controlling adaptive re-organization of whole genomes of thermo-extremophiles. However, no remarkable differences were observed across species on distribution of functionally related genes on the chromosome suggesting constraints imposed by metabolic networks. The metabolic network exhibit evolutionary pressures similar to levels of rearrangements as measured by the cross-clustering index. Using stratigraphic analysis of donor-recipient, intensive gene exchanges were observed from Meiothermus species and some unknown sources to Thermus species confirming a well established DNA uptake mechanism as previously proposed. Global genome rearrangements were found to play an important role in the evolution of Thermus bacteria at both genomic and metabolic network levels. Relatively higher level of rearrangements was observed in extremely thermophilic Thermus strains in comparison to the thermo-tolerant Thermus scotoductus. Rearrangements did not significantly disrupt operons and functionally related genes. Thermus species appeared to have a developed capability for acquiring DNA through horizontal gene transfer as shown by the donor-recipient stratigraphic analysis.

Attention reduces spatial uncertainty in human ventral temporal cortex

PubMed Central

Kay, Kendrick N.; Weiner, Kevin S.; Grill-Spector, Kalanit

2014-01-01

SUMMARY Ventral temporal cortex (VTC) is the latest stage of the ventral ‘what’ visual pathway, which is thought to code the identity of a stimulus regardless of its position or size [1, 2]. Surprisingly, recent studies show that position information can be decoded from VTC [3–5]. However, the computational mechanisms by which spatial information is encoded in VTC are unknown. Furthermore, how attention influences spatial representations in human VTC is also unknown because the effect of attention on spatial representations has only been examined in the dorsal ‘where’ visual pathway [6–10]. Here we fill these significant gaps in knowledge using an approach that combines functional magnetic resonance imaging and sophisticated computational methods. We first develop a population receptive field (pRF) model [11, 12] of spatial responses in human VTC. Consisting of spatial summation followed by a compressive nonlinearity, this model accurately predicts responses of individual voxels to stimuli at any position and size, explains how spatial information is encoded, and reveals a functional hierarchy in VTC. We then manipulate attention and use our model to decipher the effects of attention. We find that attention to the stimulus systematically and selectively modulates responses in VTC, but not early visual areas. Locally, attention increases eccentricity, size, and gain of individual pRFs, thereby increasing position tolerance. However, globally, these effects reduce uncertainty regarding stimulus location and actually increase position sensitivity of distributed responses across VTC. These results demonstrate that attention actively shapes and enhances spatial representations in the ventral visual pathway. PMID:25702580

The cotton transcription factor TCP14 functions in auxin-mediated epidermal cell differentiation and elongation.

PubMed

Wang, Miao-Ying; Zhao, Pi-Ming; Cheng, Huan-Qing; Han, Li-Bo; Wu, Xiao-Min; Gao, Peng; Wang, Hai-Yun; Yang, Chun-Lin; Zhong, Nai-Qin; Zuo, Jian-Ru; Xia, Gui-Xian

2013-07-01

Plant-specific TEOSINTE-BRANCHED1/CYCLOIDEA/PCF (TCP) transcription factors play crucial roles in development, but their functional mechanisms remain largely unknown. Here, we characterized the cellular functions of the class I TCP transcription factor GhTCP14 from upland cotton (Gossypium hirsutum). GhTCP14 is expressed predominantly in fiber cells, especially at the initiation and elongation stages of development, and its expression increased in response to exogenous auxin. Induced heterologous overexpression of GhTCP14 in Arabidopsis (Arabidopsis thaliana) enhanced initiation and elongation of trichomes and root hairs. In addition, root gravitropism was severely affected, similar to mutant of the auxin efflux carrier PIN-FORMED2 (PIN2) gene. Examination of auxin distribution in GhTCP14-expressing Arabidopsis by observation of auxin-responsive reporters revealed substantial alterations in auxin distribution in sepal trichomes and root cortical regions. Consistent with these changes, expression of the auxin uptake carrier AUXIN1 (AUX1) was up-regulated and PIN2 expression was down-regulated in the GhTCP14-expressing plants. The association of GhTCP14 with auxin responses was also evidenced by the enhanced expression of auxin response gene IAA3, a gene in the AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) family. Electrophoretic mobility shift assays showed that GhTCP14 bound the promoters of PIN2, IAA3, and AUX1, and transactivation assays indicated that GhTCP14 had transcription activation activity. Taken together, these results demonstrate that GhTCP14 is a dual-function transcription factor able to positively or negatively regulate expression of auxin response and transporter genes, thus potentially acting as a crucial regulator in auxin-mediated differentiation and elongation of cotton fiber cells.

The Cotton Transcription Factor TCP14 Functions in Auxin-Mediated Epidermal Cell Differentiation and Elongation1[C][W

PubMed Central

Wang, Miao-Ying; Zhao, Pi-Ming; Cheng, Huan-Qing; Han, Li-Bo; Wu, Xiao-Min; Gao, Peng; Wang, Hai-Yun; Yang, Chun-Lin; Zhong, Nai-Qin; Zuo, Jian-Ru; Xia, Gui-Xian

2013-01-01

Plant-specific TEOSINTE-BRANCHED1/CYCLOIDEA/PCF (TCP) transcription factors play crucial roles in development, but their functional mechanisms remain largely unknown. Here, we characterized the cellular functions of the class I TCP transcription factor GhTCP14 from upland cotton (Gossypium hirsutum). GhTCP14 is expressed predominantly in fiber cells, especially at the initiation and elongation stages of development, and its expression increased in response to exogenous auxin. Induced heterologous overexpression of GhTCP14 in Arabidopsis (Arabidopsis thaliana) enhanced initiation and elongation of trichomes and root hairs. In addition, root gravitropism was severely affected, similar to mutant of the auxin efflux carrier PIN-FORMED2 (PIN2) gene. Examination of auxin distribution in GhTCP14-expressing Arabidopsis by observation of auxin-responsive reporters revealed substantial alterations in auxin distribution in sepal trichomes and root cortical regions. Consistent with these changes, expression of the auxin uptake carrier AUXIN1 (AUX1) was up-regulated and PIN2 expression was down-regulated in the GhTCP14-expressing plants. The association of GhTCP14 with auxin responses was also evidenced by the enhanced expression of auxin response gene IAA3, a gene in the AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) family. Electrophoretic mobility shift assays showed that GhTCP14 bound the promoters of PIN2, IAA3, and AUX1, and transactivation assays indicated that GhTCP14 had transcription activation activity. Taken together, these results demonstrate that GhTCP14 is a dual-function transcription factor able to positively or negatively regulate expression of auxin response and transporter genes, thus potentially acting as a crucial regulator in auxin-mediated differentiation and elongation of cotton fiber cells. PMID:23715527

Probalistic Assessment of Radiation Risk for Solar Particle Events

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee Y.; Cucinotta, Francis A.

2008-01-01

For long duration missions outside of the protection of the Earth's magnetic field, exposure to solar particle events (SPEs) is a major safety concern for crew members during extra-vehicular activities (EVAs) on the lunar surface or Earth-to-moon or Earth-to-Mars transit. The large majority (90%) of SPEs have small or no health consequences because the doses are low and the particles do not penetrate to organ depths. However, there is an operational challenge to respond to events of unknown size and duration. We have developed a probabilistic approach to SPE risk assessment in support of mission design and operational planning. Using the historical database of proton measurements during the past 5 solar cycles, the functional form of hazard function of SPE occurrence per cycle was found for nonhomogeneous Poisson model. A typical hazard function was defined as a function of time within a non-specific future solar cycle of 4000 days duration. Distributions of particle fluences for a specified mission period were simulated ranging from its 5th to 95th percentile. Organ doses from large SPEs were assessed using NASA's Baryon transport model, BRYNTRN. The SPE risk was analyzed with the organ dose distribution for the given particle fluences during a mission period. In addition to the total particle fluences of SPEs, the detailed energy spectra of protons, especially at high energy levels, were recognized as extremely important for assessing the cancer risk associated with energetic particles for large events. The probability of exceeding the NASA 30-day limit of blood forming organ (BFO) dose inside a typical spacecraft was calculated for various SPE sizes. This probabilistic approach to SPE protection will be combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks in future work.

Herpes Simplex Virus Type 1 Neuronal Infection Perturbs Golgi Apparatus Integrity through Activation of Src Tyrosine Kinase and Dyn-2 GTPase

PubMed Central

Martin, Carolina; Leyton, Luis; Hott, Melissa; Arancibia, Yennyfer; Spichiger, Carlos; McNiven, Mark A.; Court, Felipe A.; Concha, Margarita I.; Burgos, Patricia V.; Otth, Carola

2017-01-01

Herpes simplex virus type 1 (HSV-1) is a ubiquitous pathogen that establishes a latent persistent neuronal infection in humans. The pathogenic effects of repeated viral reactivation in infected neurons are still unknown. Several studies have reported that during HSV-1 epithelial infection, the virus could modulate diverse cell signaling pathways remodeling the Golgi apparatus (GA) membranes, but the molecular mechanisms implicated, and the functional consequences to neurons is currently unknown. Here we report that infection of primary neuronal cultures with HSV-1 triggers Src tyrosine kinase activation and subsequent phosphorylation of Dynamin 2 GTPase, two players with a role in GA integrity maintenance. Immunofluorescence analyses showed that HSV-1 productive neuronal infection caused a scattered and fragmented distribution of the GA through the cytoplasm, contrasting with the uniform perinuclear distribution pattern observed in control cells. In addition, transmission electron microscopy revealed swollen cisternae and disorganized stacks in HSV-1 infected neurons compared to control cells. Interestingly, PP2, a selective inhibitor for Src-family kinases markedly reduced these morphological alterations of the GA induced by HSV-1 infection strongly supporting the possible involvement of Src tyrosine kinase. Finally, we showed that HSV-1 tegument protein VP11/12 is necessary but not sufficient to induce Dyn2 phosphorylation. Altogether, these results show that HSV-1 neuronal infection triggers activation of Src tyrosine kinase, phosphorylation of Dynamin 2 GTPase, and perturbation of GA integrity. These findings suggest a possible neuropathogenic mechanism triggered by HSV-1 infection, which could involve dysfunction of the secretory system in neurons and central nervous system. PMID:28879169

Herpes Simplex Virus Type 1 Neuronal Infection Perturbs Golgi Apparatus Integrity through Activation of Src Tyrosine Kinase and Dyn-2 GTPase.

PubMed

Martin, Carolina; Leyton, Luis; Hott, Melissa; Arancibia, Yennyfer; Spichiger, Carlos; McNiven, Mark A; Court, Felipe A; Concha, Margarita I; Burgos, Patricia V; Otth, Carola

2017-01-01

Herpes simplex virus type 1 (HSV-1) is a ubiquitous pathogen that establishes a latent persistent neuronal infection in humans. The pathogenic effects of repeated viral reactivation in infected neurons are still unknown. Several studies have reported that during HSV-1 epithelial infection, the virus could modulate diverse cell signaling pathways remodeling the Golgi apparatus (GA) membranes, but the molecular mechanisms implicated, and the functional consequences to neurons is currently unknown. Here we report that infection of primary neuronal cultures with HSV-1 triggers Src tyrosine kinase activation and subsequent phosphorylation of Dynamin 2 GTPase, two players with a role in GA integrity maintenance. Immunofluorescence analyses showed that HSV-1 productive neuronal infection caused a scattered and fragmented distribution of the GA through the cytoplasm, contrasting with the uniform perinuclear distribution pattern observed in control cells. In addition, transmission electron microscopy revealed swollen cisternae and disorganized stacks in HSV-1 infected neurons compared to control cells. Interestingly, PP2, a selective inhibitor for Src-family kinases markedly reduced these morphological alterations of the GA induced by HSV-1 infection strongly supporting the possible involvement of Src tyrosine kinase. Finally, we showed that HSV-1 tegument protein VP11/12 is necessary but not sufficient to induce Dyn2 phosphorylation. Altogether, these results show that HSV-1 neuronal infection triggers activation of Src tyrosine kinase, phosphorylation of Dynamin 2 GTPase, and perturbation of GA integrity. These findings suggest a possible neuropathogenic mechanism triggered by HSV-1 infection, which could involve dysfunction of the secretory system in neurons and central nervous system.

Adaptive Fuzzy Output Constrained Control Design for Multi-Input Multioutput Stochastic Nonstrict-Feedback Nonlinear Systems.

PubMed

Li, Yongming; Tong, Shaocheng

2017-12-01

In this paper, an adaptive fuzzy output constrained control design approach is addressed for multi-input multioutput uncertain stochastic nonlinear systems in nonstrict-feedback form. The nonlinear systems addressed in this paper possess unstructured uncertainties, unknown gain functions and unknown stochastic disturbances. Fuzzy logic systems are utilized to tackle the problem of unknown nonlinear uncertainties. The barrier Lyapunov function technique is employed to solve the output constrained problem. In the framework of backstepping design, an adaptive fuzzy control design scheme is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

Segmental Vitiligo.

PubMed

van Geel, Nanja; Speeckaert, Reinhart

2017-04-01

Segmental vitiligo is characterized by its early onset, rapid stabilization, and unilateral distribution. Recent evidence suggests that segmental and nonsegmental vitiligo could represent variants of the same disease spectrum. Observational studies with respect to its distribution pattern point to a possible role of cutaneous mosaicism, whereas the original stated dermatomal distribution seems to be a misnomer. Although the exact pathogenic mechanism behind the melanocyte destruction is still unknown, increasing evidence has been published on the autoimmune/inflammatory theory of segmental vitiligo. Copyright © 2016 Elsevier Inc. All rights reserved.

The challenge of annotating protein sequences: The tale of eight domains of unknown function in Pfam.

PubMed

Goonesekere, Nalin C W; Shipely, Krysten; O'Connor, Kevin

2010-06-01

The Pfam database is an important tool in genome annotation, since it provides a collection of curated protein families. However, a subset of these families, known as domains of unknown function (DUFs), remains poorly characterized. We have related sequences from DUF404, DUF407, DUF482, DUF608, DUF810, DUF853, DUF976 and DUF1111 to homologs in PDB, within the midnight zone (9-20%) of sequence identity. These relationships were extended to provide functional annotation by sequence analysis and model building. Also described are examples of residue plasticity within enzyme active sites, and change of function within homologous sequences of a DUF. Copyright 2010 Elsevier Ltd. All rights reserved.

Insight into nuclear body formation of phytochromes through stochastic modelling and experiment.

PubMed

Grima, Ramon; Sonntag, Sebastian; Venezia, Filippo; Kircher, Stefan; Smith, Robert W; Fleck, Christian

2018-05-01

Spatial relocalization of proteins is crucial for the correct functioning of living cells. An interesting example of spatial ordering is the light-induced clustering of plant photoreceptor proteins. Upon irradiation by white or red light, the red light-active phytochrome, phytochrome B, enters the nucleus and accumulates in large nuclear bodies. The underlying physical process of nuclear body formation remains unclear, but phytochrome B is thought to coagulate via a simple protein-protein binding process. We measure, for the first time, the distribution of the number of phytochrome B-containing nuclear bodies as well as their volume distribution. We show that the experimental data cannot be explained by a stochastic model of nuclear body formation via simple protein-protein binding processes using physically meaningful parameter values. Rather modelling suggests that the data is consistent with a two step process: a fast nucleation step leading to macroparticles followed by a subsequent slow step in which the macroparticles bind to form the nuclear body. An alternative explanation for the observed nuclear body distribution is that the phytochromes bind to a so far unknown molecular structure. We believe it is likely this result holds more generally for other nuclear body-forming plant photoreceptors and proteins. Creative Commons Attribution license.

Structural Constraints On The Spatial Distribution of Aftershocks

NASA Astrophysics Data System (ADS)

McCloskey, J.; Nalbant, S. S.; Steacy, S.; Nostro, C.; Scotti, O.; Baumont, D.

Real-time, forward modelling of spatial distributions of potentially damaging after- shocks by calculating stress perturbations due to large earthquakes may produce so- cially useful, time- dependent hazard estimates in the foreseeable future. Such calcula- tions, however, rely on the resolution of a stress perturbation tensor (SPT) onto planes whose geometry is unknown and decisions as to the orientations of these planes have a first order effect on the geometry of the resulting hazard distributions. Commonly, these decisions are based on the assumption that structures optimally oriented for fail- ure in the regional stress field, exist everywhere and stress maps are produced by resolving onto these orientations. Here we investigate this proposition using a 3D cal- culation for the optimally oriented planes (OOPs) for the 1992 Landers earthquake (M = 7.3). We examine the encouraged mechanisms as a function of location and show that enhancement for failure exists over a much wider area than in the equivalent, and more usual, 2.5D calculations. Mechanisms predicted in these areas are not consistent with the local structural geology, however, and corresponding aftershocks are gener- ally not observed. We argue that best hazard estimates will result from geometrically restricted versions of the OOP concept in which observed structure constrains possible orientations for failure.

OsNRAMP5 contributes to manganese translocation and distribution in rice shoots.

PubMed

Yang, Meng; Zhang, Yuanyuan; Zhang, Lejing; Hu, Jintao; Zhang, Xing; Lu, Kai; Dong, Huaxia; Wang, Dujun; Zhao, Fang-Jie; Huang, Chao-Feng; Lian, Xingming

2014-09-01

Manganese (Mn) is an essential micronutrient for plants playing an important role in many physiological functions. OsNRAMP5 is a major transporter responsible for Mn and cadmium uptake in rice, but whether it is involved in the root-to-shoot translocation and distribution of these metals is unknown. In this work, OsNRAMP5 was found to be highly expressed in hulls. It was also expressed in leaves but the expression level decreased with leaf age. High-magnification observations revealed that OsNRAMP5 was enriched in the vascular bundles of roots and shoots especially in the parenchyma cells surrounding the xylem. The osnramp5 mutant accumulated significantly less Mn in shoots than the wild-type plants even at high levels of Mn supply. Furthermore, a high supply of Mn could compensate for the loss in the root uptake ability in the mutant, but not in the root-to-shoot translocation of Mn, suggesting that the absence of OsNRAMP5 reduces the transport of Mn from roots to shoots. The results suggest that OsNRAMP5 plays an important role in the translocation and distribution of Mn in rice plants in addition to its role in Mn uptake. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR

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

Schneider, Michael D.; Dawson, William A.; Hogg, David W.

2015-07-01

Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxymore » properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.« less

Using meta-information of a posteriori Bayesian solutions of the hypocentre location task for improving accuracy of location error estimation

NASA Astrophysics Data System (ADS)

Debski, Wojciech

2015-06-01

The spatial location of sources of seismic waves is one of the first tasks when transient waves from natural (uncontrolled) sources are analysed in many branches of physics, including seismology, oceanology, to name a few. Source activity and its spatial variability in time, the geometry of recording network, the complexity and heterogeneity of wave velocity distribution are all factors influencing the performance of location algorithms and accuracy of the achieved results. Although estimating of the earthquake foci location is relatively simple, a quantitative estimation of the location accuracy is really a challenging task even if the probabilistic inverse method is used because it requires knowledge of statistics of observational, modelling and a priori uncertainties. In this paper, we addressed this task when statistics of observational and/or modelling errors are unknown. This common situation requires introduction of a priori constraints on the likelihood (misfit) function which significantly influence the estimated errors. Based on the results of an analysis of 120 seismic events from the Rudna copper mine operating in southwestern Poland, we propose an approach based on an analysis of Shanon's entropy calculated for the a posteriori distribution. We show that this meta-characteristic of the a posteriori distribution carries some information on uncertainties of the solution found.

A periodic review integrated inventory model with controllable safety stock and setup cost under service level constraint and distribution-free demand

NASA Astrophysics Data System (ADS)

Kurdhi, N. A.; Jamaluddin, A.; Jauhari, W. A.; Saputro, D. R. S.

2017-06-01

In this study, we consider a stochastic integrated manufacturer-retailer inventory model with service level constraint. The model analyzed in this article considers the situation in which the vendor and the buyer establish a long-term contract and strategic partnership to jointly determine the best strategy. The lead time and setup cost are assumed can be controlled by an additional crashing cost and an investment, respectively. It is assumed that shortages are allowed and partially backlogged on the buyer’s side, and that the protection interval (i.e., review period plus lead time) demand distribution is unknown but has given finite first and second moments. The objective is to apply the minmax distribution free approach to simultaneously optimize the review period, the lead time, the setup cost, the safety factor, and the number of deliveries in order to minimize the joint total expected annual cost. The service level constraint guarantees that the service level requirement can be satisfied at the worst case. By constructing Lagrange function, the analysis regarding the solution procedure is conducted, and a solution algorithm is then developed. Moreover, a numerical example and sensitivity analysis are given to illustrate the proposed model and to provide some observations and managerial implications.

Opening of an interface flaw in a layered elastic half-plane under compressive loading

NASA Technical Reports Server (NTRS)

Kennedy, J. M.; Fichter, W. B.; Goree, J. G.

1984-01-01

A static analysis is given of the problem of an elastic layer perfectly bonded, except for a frictionless interface crack, to a dissimilar elastic half-plane. The free surface of the layer is loaded by a finite pressure distribution directly over the crack. The problem is formulated using the two dimensional linear elasticity equations. Using Fourier transforms, the governing equations are converted to a pair of coupled singular integral equations. The integral equations are reduced to a set of simultaneous algebraic equations by expanding the unknown functions in a series of Jacobi polynomials and then evaluating the singular Cauchy-type integrals. The resulting equations are found to be ill-conditioned and, consequently, are solved in the least-squares sense. Results from the analysis show that, under a normal pressure distribution on the free surface of the layer and depending on the combination of geometric and material parameters, the ends of the crack can open. The resulting stresses at the crack-tips are singular, implying that crack growth is possible. The extent of the opening and the crack-top stress intensity factors depend on the width of the pressure distribution zone, the layer thickness, and the relative material properties of the layer and half-plane.

Retention in the Golgi apparatus and expression on the cell surface of Cfr/Esl-1/Glg-1/MG-160 are regulated by two distinct mechanisms.

PubMed

Miyaoka, Yuichiro; Kato, Hidenori; Ebato, Kazuki; Saito, Shigeru; Miyata, Naoko; Imamura, Toru; Miyajima, Atsushi

2011-11-15

Cfr (cysteine-rich fibroblast growth factor receptor) is an Fgf (fibroblast growth factor)-binding protein without a tyrosine kinase. We have shown previously that Cfr is involved in Fgf18 signalling via Fgf receptor 3c. However, as Cfr is also known as Glg (Golgi apparatus protein)-1 or MG-160 and occurs in the Golgi apparatus, it remains unknown how the distribution of Cfr is regulated. In the present study, we performed a mutagenic analysis of Cfr to show that two distinct regions contribute to its distribution and stability. First, the C-terminal region retains Cfr in the Golgi apparatus. Secondly, the Cfr repeats in the extracellular juxtamembrane region destabilizes Cfr passed through the Golgi apparatus. This destabilization does not depend on the cleavage and secretion of the extracellular domain of Cfr. Furthermore, we found that Cfr with a GPI (glycosylphosphatidylinositol) anchor was predominantly expressed on the cell surface in Ba/F3 cells and affected Fgf18 signalling in a similar manner to the full-length Cfr, indicating that the interaction of Cfr with Fgfs on the cell surface is important for its function in Fgf signalling. These results suggest that the expression of Cfr in the Golgi apparatus and on the plasma membrane is finely tuned through two distinct mechanisms for exhibiting different functions.

Time-to-event continual reassessment method incorporating treatment cycle information with application to an oncology phase I trial.

PubMed

Huang, Bo; Kuan, Pei Fen

2014-11-01

Delayed dose limiting toxicities (i.e. beyond first cycle of treatment) is a challenge for phase I trials. The time-to-event continual reassessment method (TITE-CRM) is a Bayesian dose-finding design to address the issue of long observation time and early patient drop-out. It uses a weighted binomial likelihood with weights assigned to observations by the unknown time-to-toxicity distribution, and is open to accrual continually. To avoid dosing at overly toxic levels while retaining accuracy and efficiency for DLT evaluation that involves multiple cycles, we propose an adaptive weight function by incorporating cyclical data of the experimental treatment with parameters updated continually. This provides a reasonable estimate for the time-to-toxicity distribution by accounting for inter-cycle variability and maintains the statistical properties of consistency and coherence. A case study of a First-in-Human trial in cancer for an experimental biologic is presented using the proposed design. Design calibrations for the clinical and statistical parameters are conducted to ensure good operating characteristics. Simulation results show that the proposed TITE-CRM design with adaptive weight function yields significantly shorter trial duration, does not expose patients to additional risk, is competitive against the existing weighting methods, and possesses some desirable properties. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Maximum Entropy Approach in Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

PubMed

Farsani, Zahra Amini; Schmid, Volker J

2017-01-01

In the estimation of physiological kinetic parameters from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) data, the determination of the arterial input function (AIF) plays a key role. This paper proposes a Bayesian method to estimate the physiological parameters of DCE-MRI along with the AIF in situations, where no measurement of the AIF is available. In the proposed algorithm, the maximum entropy method (MEM) is combined with the maximum a posterior approach (MAP). To this end, MEM is used to specify a prior probability distribution of the unknown AIF. The ability of this method to estimate the AIF is validated using the Kullback-Leibler divergence. Subsequently, the kinetic parameters can be estimated with MAP. The proposed algorithm is evaluated with a data set from a breast cancer MRI study. The application shows that the AIF can reliably be determined from the DCE-MRI data using MEM. Kinetic parameters can be estimated subsequently. The maximum entropy method is a powerful tool to reconstructing images from many types of data. This method is useful for generating the probability distribution based on given information. The proposed method gives an alternative way to assess the input function from the existing data. The proposed method allows a good fit of the data and therefore a better estimation of the kinetic parameters. In the end, this allows for a more reliable use of DCE-MRI. Schattauer GmbH.

Prepositioning emergency supplies under uncertainty: a parametric optimization method

NASA Astrophysics Data System (ADS)

Bai, Xuejie; Gao, Jinwu; Liu, Yankui

2018-07-01

Prepositioning of emergency supplies is an effective method for increasing preparedness for disasters and has received much attention in recent years. In this article, the prepositioning problem is studied by a robust parametric optimization method. The transportation cost, supply, demand and capacity are unknown prior to the extraordinary event, which are represented as fuzzy parameters with variable possibility distributions. The variable possibility distributions are obtained through the credibility critical value reduction method for type-2 fuzzy variables. The prepositioning problem is formulated as a fuzzy value-at-risk model to achieve a minimum total cost incurred in the whole process. The key difficulty in solving the proposed optimization model is to evaluate the quantile of the fuzzy function in the objective and the credibility in the constraints. The objective function and constraints can be turned into their equivalent parametric forms through chance constrained programming under the different confidence levels. Taking advantage of the structural characteristics of the equivalent optimization model, a parameter-based domain decomposition method is developed to divide the original optimization problem into six mixed-integer parametric submodels, which can be solved by standard optimization solvers. Finally, to explore the viability of the developed model and the solution approach, some computational experiments are performed on realistic scale case problems. The computational results reported in the numerical example show the credibility and superiority of the proposed parametric optimization method.

SLX-1 Is Required for Maintaining Genomic Integrity and Promoting Meiotic Noncrossovers in the Caenorhabditis elegans Germline

PubMed Central

Meyer, Katherine; Harper, J. Wade; Colaiácovo, Monica P.

2012-01-01

Although the SLX4 complex, which includes structure-specific nucleases such as XPF, MUS81, and SLX1, plays important roles in the repair of several kinds of DNA damage, the function of SLX1 in the germline remains unknown. Here we characterized the endonuclease activities of the Caenorhabditis elegans SLX-1-HIM-18/SLX-4 complex co-purified from human 293T cells and determined SLX-1 germline function via analysis of slx-1(tm2644) mutants. SLX-1 shows a HIM-18/SLX-4–dependent endonuclease activity toward replication forks, 5′-flaps, and Holliday junctions. slx-1 mutants exhibit hypersensitivity to UV, nitrogen mustard, and camptothecin, but not gamma irradiation. Consistent with a role in DNA repair, recombination intermediates accumulate in both mitotic and meiotic germ cells in slx-1 mutants. Importantly, meiotic crossover distribution, but not crossover frequency, is altered on chromosomes in slx-1 mutants compared to wild type. This alteration is not due to changes in either the levels or distribution of double-strand breaks (DSBs) along chromosomes. We propose that SLX-1 is required for repair at stalled or collapsed replication forks, interstrand crosslink repair, and nucleotide excision repair during mitosis. Moreover, we hypothesize that SLX-1 regulates the crossover landscape during meiosis by acting as a noncrossover-promoting factor in a subset of DSBs. PMID:22927825

Comprehensive phylogenetic analysis of bacterial reverse transcriptases.

PubMed

Toro, Nicolás; Nisa-Martínez, Rafael

2014-01-01

Much less is known about reverse transcriptases (RTs) in prokaryotes than in eukaryotes, with most prokaryotic enzymes still uncharacterized. Two surveys involving BLAST searches for RT genes in prokaryotic genomes revealed the presence of large numbers of diverse, uncharacterized RTs and RT-like sequences. Here, using consistent annotation across all sequenced bacterial species from GenBank and other sources via RAST, available from the PATRIC (Pathogenic Resource Integration Center) platform, we have compiled the data for currently annotated reverse transcriptases from completely sequenced bacterial genomes. RT sequences are broadly distributed across bacterial phyla, but green sulfur bacteria and cyanobacteria have the highest levels of RT sequence diversity (≤85% identity) per genome. By contrast, phylum Actinobacteria, for which a large number of genomes have been sequenced, was found to have a low RT sequence diversity. Phylogenetic analyses revealed that bacterial RTs could be classified into 17 main groups: group II introns, retrons/retron-like RTs, diversity-generating retroelements (DGRs), Abi-like RTs, CRISPR-Cas-associated RTs, group II-like RTs (G2L), and 11 other groups of RTs of unknown function. Proteobacteria had the highest potential functional diversity, as they possessed most of the RT groups. Group II introns and DGRs were the most widely distributed RTs in bacterial phyla. Our results provide insights into bacterial RT phylogeny and the basis for an update of annotation systems based on sequence/domain homology.

Comprehensive Phylogenetic Analysis of Bacterial Reverse Transcriptases

PubMed Central

Toro, Nicolás; Nisa-Martínez, Rafael

2014-01-01

Much less is known about reverse transcriptases (RTs) in prokaryotes than in eukaryotes, with most prokaryotic enzymes still uncharacterized. Two surveys involving BLAST searches for RT genes in prokaryotic genomes revealed the presence of large numbers of diverse, uncharacterized RTs and RT-like sequences. Here, using consistent annotation across all sequenced bacterial species from GenBank and other sources via RAST, available from the PATRIC (Pathogenic Resource Integration Center) platform, we have compiled the data for currently annotated reverse transcriptases from completely sequenced bacterial genomes. RT sequences are broadly distributed across bacterial phyla, but green sulfur bacteria and cyanobacteria have the highest levels of RT sequence diversity (≤85% identity) per genome. By contrast, phylum Actinobacteria, for which a large number of genomes have been sequenced, was found to have a low RT sequence diversity. Phylogenetic analyses revealed that bacterial RTs could be classified into 17 main groups: group II introns, retrons/retron-like RTs, diversity-generating retroelements (DGRs), Abi-like RTs, CRISPR-Cas-associated RTs, group II-like RTs (G2L), and 11 other groups of RTs of unknown function. Proteobacteria had the highest potential functional diversity, as they possessed most of the RT groups. Group II introns and DGRs were the most widely distributed RTs in bacterial phyla. Our results provide insights into bacterial RT phylogeny and the basis for an update of annotation systems based on sequence/domain homology. PMID:25423096

Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory.

PubMed

Emrich, Stephen M; Riggall, Adam C; Larocque, Joshua J; Postle, Bradley R

2013-04-10

Traditionally, load sensitivity of sustained, elevated activity has been taken as an index of storage for a limited number of items in visual short-term memory (VSTM). Recently, studies have demonstrated that the contents of a single item held in VSTM can be decoded from early visual cortex, despite the fact that these areas do not exhibit elevated, sustained activity. It is unknown, however, whether the patterns of neural activity decoded from sensory cortex change as a function of load, as one would expect from a region storing multiple representations. Here, we use multivoxel pattern analysis to examine the neural representations of VSTM in humans across multiple memory loads. In an important extension of previous findings, our results demonstrate that the contents of VSTM can be decoded from areas that exhibit a transient response to visual stimuli, but not from regions that exhibit elevated, sustained load-sensitive delay-period activity. Moreover, the neural information present in these transiently activated areas decreases significantly with increasing load, indicating load sensitivity of the patterns of activity that support VSTM maintenance. Importantly, the decrease in classification performance as a function of load is correlated with within-subject changes in mnemonic resolution. These findings indicate that distributed patterns of neural activity in putatively sensory visual cortex support the representation and precision of information in VSTM.

An analytical approach for the simulation of flow in a heterogeneous confined aquifer with a parameter zonation structure

NASA Astrophysics Data System (ADS)

Huang, Ching-Sheng; Yeh, Hund-Der

2016-11-01

This study introduces an analytical approach to estimate drawdown induced by well extraction in a heterogeneous confined aquifer with an irregular outer boundary. The aquifer domain is divided into a number of zones according to the zonation method for representing the spatial distribution of a hydraulic parameter field. The lateral boundary of the aquifer can be considered under the Dirichlet, Neumann or Robin condition at different parts of the boundary. Flow across the interface between two zones satisfies the continuities of drawdown and flux. Source points, each of which has an unknown volumetric rate representing the boundary effect on the drawdown, are allocated around the boundary of each zone. The solution of drawdown in each zone is expressed as a series in terms of the Theis equation with unknown volumetric rates from the source points. The rates are then determined based on the aquifer boundary conditions and the continuity requirements. The estimated aquifer drawdown by the present approach agrees well with a finite element solution developed based on the Mathematica function NDSolve. As compared with the existing numerical approaches, the present approach has a merit of directly computing the drawdown at any given location and time and therefore takes much less computing time to obtain the required results in engineering applications.

Inclusion of historical information in flood frequency analysis using a Bayesian MCMC technique: a case study for the power dam Orlík, Czech Republic

NASA Astrophysics Data System (ADS)

Gaál, Ladislav; Szolgay, Ján; Kohnová, Silvia; Hlavčová, Kamila; Viglione, Alberto

2010-01-01

The paper deals with at-site flood frequency estimation in the case when also information on hydrological events from the past with extraordinary magnitude are available. For the joint frequency analysis of systematic observations and historical data, respectively, the Bayesian framework is chosen, which, through adequately defined likelihood functions, allows for incorporation of different sources of hydrological information, e.g., maximum annual flood peaks, historical events as well as measurement errors. The distribution of the parameters of the fitted distribution function and the confidence intervals of the flood quantiles are derived by means of the Markov chain Monte Carlo simulation (MCMC) technique. The paper presents a sensitivity analysis related to the choice of the most influential parameters of the statistical model, which are the length of the historical period h and the perception threshold X0. These are involved in the statistical model under the assumption that except for the events termed as ‘historical’ ones, none of the (unknown) peak discharges from the historical period h should have exceeded the threshold X0. Both higher values of h and lower values of X0 lead to narrower confidence intervals of the estimated flood quantiles; however, it is emphasized that one should be prudent of selecting those parameters, in order to avoid making inferences with wrong assumptions on the unknown hydrological events having occurred in the past. The Bayesian MCMC methodology is presented on the example of the maximum discharges observed during the warm half year at the station Vltava-Kamýk (Czech Republic) in the period 1877-2002. Although the 2002 flood peak, which is related to the vast flooding that affected a large part of Central Europe at that time, occurred in the near past, in the analysis it is treated virtually as a ‘historical’ event in order to illustrate some crucial aspects of including information on extreme historical floods into at-site flood frequency analyses.

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

Kato, Go

We consider the situation where s replicas of a qubit with an unknown state and its orthogonal k replicas are given as an input, and we try to make c clones of the qubit with the unknown state. As a function of s, k, and c, we obtain the optimal fidelity between the qubit with an unknown state and the clone by explicitly giving a completely positive trace-preserving (CPTP) map that represents a cloning machine. We discuss dependency of the fidelity on the values of the parameters s, k, and c.

Adaptive Incentive Controls for Stackelberg Games with Unknown Cost Functionals.

DTIC Science & Technology

1984-01-01

APR EZT:: F I AN 73S e OsL:-: UNCLASSI?:-- Q4~.’~- .A.., 6, *~*i i~~*~~*.- U ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH UNKNOWN COST...AD-A161 885 ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH i/1 UNKNOWN COST FUNCTIONALSCU) ILLINOIS UNIV AT URBANA DECISION AND CONTROL LAB T...ORGANIZATION 6b. OFFICE SYMBOL 7.. NAME OF MONITORING ORGANIZATION CoriaeLcenef~pda~ Joint Services Electronics Program Laboratory, Univ. of Illinois N/A

Using Geothermal Play Types as an Analogue for Estimating Potential Resource Size

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

Terry, Rachel; Young, Katherine

Blind geothermal systems are becoming increasingly common as more geothermal fields are developed. Geothermal development is known to have high risk in the early stages of a project development because reservoir characteristics are relatively unknown until wells are drilled. Play types (or occurrence models) categorize potential geothermal fields into groups based on geologic characteristics. To aid in lowering exploration risk, these groups' reservoir characteristics can be used as analogues in new site exploration. The play type schemes used in this paper were Moeck and Beardsmore play types (Moeck et al. 2014) and Brophy occurrence models (Brophy et al. 2011). Operatingmore » geothermal fields throughout the world were classified based on their associated play type, and then reservoir characteristics data were catalogued. The distributions of these characteristics were plotted in histograms to develop probability density functions for each individual characteristic. The probability density functions can be used as input analogues in Monte Carlo estimations of resource potential for similar play types in early exploration phases. A spreadsheet model was created to estimate resource potential in undeveloped fields. The user can choose to input their own values for each reservoir characteristic or choose to use the probability distribution functions provided from the selected play type. This paper also addresses the United States Geological Survey's 1978 and 2008 assessment of geothermal resources by comparing their estimated values to reported values from post-site development. Information from the collected data was used in the comparison for thirty developed sites in the United States. No significant trends or suggestions for methodologies could be made by the comparison.« less

Taxonomic and functional characteristics of microbial communities and their correlation with physicochemical properties of four geothermal springs in Odisha, India

PubMed Central

Badhai, Jhasketan; Ghosh, Tarini S.; Das, Subrata K.

2015-01-01

This study describes microbial diversity in four tropical hot springs representing moderately thermophilic environments (temperature range: 40–58°C; pH: 7.2–7.4) with discrete geochemistry. Metagenome sequence data showed a dominance of Bacteria over Archaea; the most abundant phyla were Chloroflexi and Proteobacteria, although other phyla were also present, such as Acetothermia, Nitrospirae, Acidobacteria, Firmicutes, Deinococcus-Thermus, Bacteroidetes, Thermotogae, Euryarchaeota, Verrucomicrobia, Ignavibacteriae, Cyanobacteria, Actinobacteria, Planctomycetes, Spirochaetes, Armatimonadetes, Crenarchaeota, and Aquificae. The distribution of major genera and their statistical correlation analyses with the physicochemical parameters predicted that the temperature, aqueous concentrations of ions (such as sodium, chloride, sulfate, and bicarbonate), total hardness, dissolved solids and conductivity were the main environmental variables influencing microbial community composition and diversity. Despite the observed high taxonomic diversity, there were only little variations in the overall functional profiles of the microbial communities in the four springs. Genes involved in the metabolism of carbohydrates and carbon fixation were the most abundant functional class of genes present in these hot springs. The distribution of genes involved in carbon fixation predicted the presence of all the six known autotrophic pathways in the metagenomes. A high prevalence of genes involved in membrane transport, signal transduction, stress response, bacterial chemotaxis, and flagellar assembly were observed along with genes involved in the pathways of xenobiotic degradation and metabolism. The analysis of the metagenomic sequences affiliated to the candidate phylum Acetothermia from spring TB-3 provided new insight into the metabolism and physiology of yet-unknown members of this lineage of bacteria. PMID:26579081

The evolutionary history of plant T2/S-type ribonucleases

PubMed Central

Igić, Boris

2017-01-01

A growing number of T2/S-RNases are being discovered in plant genomes. Members of this protein family have a variety of known functions, but the vast majority are still uncharacterized. We present data and analyses of phylogenetic relationships among T2/S-RNases, and pay special attention to the group that contains the female component of the most widespread system of self-incompatibility in flowering plants. The returned emphasis on the initially identified component of this mechanism yields important conjectures about its evolutionary context. First, we find that the clade involved in self-rejection (class III) is found exclusively in core eudicots, while the remaining clades contain members from other vascular plants. Second, certain features, such as intron patterns, isoelectric point, and conserved amino acid regions, help differentiate S-RNases, which are necessary for expression of self-incompatibility, from other T2/S-RNase family members. Third, we devise and present a set of approaches to clarify new S-RNase candidates from existing genome assemblies. We use genomic features to identify putative functional and relictual S-loci in genomes of plants with unknown mechanisms of self-incompatibility. The widespread occurrence of possible relicts suggests that the loss of functional self-incompatibility may leave traces long after the fact, and that this manner of molecular fossil-like data could be an important source of information about the history and distribution of both RNase-based and other mechanisms of self-incompatibility. Finally, we release a public resource intended to aid the search for S-locus RNases, and help provide increasingly detailed information about their taxonomic distribution. PMID:28924504

(U) An Analytic Study of Piezoelectric Ejecta Mass Measurements

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

Tregillis, Ian Lee

2017-02-16

We consider the piezoelectric measurement of the areal mass of an ejecta cloud, for the specific case where ejecta are created by a single shock at the free surface and fly ballistically through vacuum to the sensor. To do so, we define time- and velocity-dependent ejecta “areal mass functions” at the source and sensor in terms of typically unknown distribution functions for the ejecta particles. Next, we derive an equation governing the relationship between the areal mass function at the source (which resides in the rest frame of the free surface) and at the sensor (which resides in the laboratorymore » frame). We also derive expressions for the analytic (“true”) accumulated ejecta mass at the sensor and the measured (“inferred”) value obtained via the standard method for analyzing piezoelectric voltage traces. This approach enables us to derive an exact expression for the error imposed upon a piezoelectric ejecta mass measurement (in a perfect system) by the assumption of instantaneous creation. We verify that when the ejecta are created instantaneously (i.e., when the time dependence is a delta function), the piezoelectric inference method exactly reproduces the correct result. When creation is not instantaneous, the standard piezo analysis will always overestimate the true mass. However, the error is generally quite small (less than several percent) for most reasonable velocity and time dependences. In some cases, errors exceeding 10-15% may require velocity distributions or ejecta production timescales inconsistent with experimental observations. These results are demonstrated rigorously with numerous analytic test problems.« less

Taxonomic and functional characteristics of microbial communities and their correlation with physicochemical properties of four geothermal springs in Odisha, India.

PubMed

Badhai, Jhasketan; Ghosh, Tarini S; Das, Subrata K

2015-01-01

This study describes microbial diversity in four tropical hot springs representing moderately thermophilic environments (temperature range: 40-58°C; pH: 7.2-7.4) with discrete geochemistry. Metagenome sequence data showed a dominance of Bacteria over Archaea; the most abundant phyla were Chloroflexi and Proteobacteria, although other phyla were also present, such as Acetothermia, Nitrospirae, Acidobacteria, Firmicutes, Deinococcus-Thermus, Bacteroidetes, Thermotogae, Euryarchaeota, Verrucomicrobia, Ignavibacteriae, Cyanobacteria, Actinobacteria, Planctomycetes, Spirochaetes, Armatimonadetes, Crenarchaeota, and Aquificae. The distribution of major genera and their statistical correlation analyses with the physicochemical parameters predicted that the temperature, aqueous concentrations of ions (such as sodium, chloride, sulfate, and bicarbonate), total hardness, dissolved solids and conductivity were the main environmental variables influencing microbial community composition and diversity. Despite the observed high taxonomic diversity, there were only little variations in the overall functional profiles of the microbial communities in the four springs. Genes involved in the metabolism of carbohydrates and carbon fixation were the most abundant functional class of genes present in these hot springs. The distribution of genes involved in carbon fixation predicted the presence of all the six known autotrophic pathways in the metagenomes. A high prevalence of genes involved in membrane transport, signal transduction, stress response, bacterial chemotaxis, and flagellar assembly were observed along with genes involved in the pathways of xenobiotic degradation and metabolism. The analysis of the metagenomic sequences affiliated to the candidate phylum Acetothermia from spring TB-3 provided new insight into the metabolism and physiology of yet-unknown members of this lineage of bacteria.

Blind beam-hardening correction from Poisson measurements

NASA Astrophysics Data System (ADS)

Gu, Renliang; Dogandžić, Aleksandar

2016-02-01

We develop a sparse image reconstruction method for Poisson-distributed polychromatic X-ray computed tomography (CT) measurements under the blind scenario where the material of the inspected object and the incident energy spectrum are unknown. We employ our mass-attenuation spectrum parameterization of the noiseless measurements and express the mass- attenuation spectrum as a linear combination of B-spline basis functions of order one. A block coordinate-descent algorithm is developed for constrained minimization of a penalized Poisson negative log-likelihood (NLL) cost function, where constraints and penalty terms ensure nonnegativity of the spline coefficients and nonnegativity and sparsity of the density map image; the image sparsity is imposed using a convex total-variation (TV) norm penalty term. This algorithm alternates between a Nesterov's proximal-gradient (NPG) step for estimating the density map image and a limited-memory Broyden-Fletcher-Goldfarb-Shanno with box constraints (L-BFGS-B) step for estimating the incident-spectrum parameters. To accelerate convergence of the density- map NPG steps, we apply function restart and a step-size selection scheme that accounts for varying local Lipschitz constants of the Poisson NLL. Real X-ray CT reconstruction examples demonstrate the performance of the proposed scheme.

Direction of information flow in large-scale resting-state networks is frequency-dependent.

PubMed

Hillebrand, Arjan; Tewarie, Prejaas; van Dellen, Edwin; Yu, Meichen; Carbo, Ellen W S; Douw, Linda; Gouw, Alida A; van Straaten, Elisabeth C W; Stam, Cornelis J

2016-04-05

Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-to-posterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequency-dependent reentry loops that are dominated by flow from parieto-occipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow.

Evolutionary cell biology: functional insight from "endless forms most beautiful".

PubMed

Richardson, Elisabeth; Zerr, Kelly; Tsaousis, Anastasios; Dorrell, Richard G; Dacks, Joel B

2015-12-15

In animal and fungal model organisms, the complexities of cell biology have been analyzed in exquisite detail and much is known about how these organisms function at the cellular level. However, the model organisms cell biologists generally use include only a tiny fraction of the true diversity of eukaryotic cellular forms. The divergent cellular processes observed in these more distant lineages are still largely unknown in the general scientific community. Despite the relative obscurity of these organisms, comparative studies of them across eukaryotic diversity have had profound implications for our understanding of fundamental cell biology in all species and have revealed the evolution and origins of previously observed cellular processes. In this Perspective, we will discuss the complexity of cell biology found across the eukaryotic tree, and three specific examples of where studies of divergent cell biology have altered our understanding of key functional aspects of mitochondria, plastids, and membrane trafficking. © 2015 Richardson et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Functional traits reveal the expansion and packing of ecological niche space underlying an elevational diversity gradient in passerine birds.

PubMed

Pigot, Alex L; Trisos, Christopher H; Tobias, Joseph A

2016-01-13

Variation in species richness across environmental gradients may be associated with an expanded volume or increased packing of ecological niche space. However, the relative importance of these alternative scenarios remains unknown, largely because standardized information on functional traits and their ecological relevance is lacking for major diversity gradients. Here, we combine data on morphological and ecological traits for 523 species of passerine birds distributed across an Andes-to-Amazon elevation gradient. We show that morphological traits capture substantial variation in species dietary (75%) and foraging niches (60%) when multiple independent trait dimensions are considered. Having established these relationships, we show that the 14-fold increase in species richness towards the lowlands is associated with both an increased volume and density of functional trait space. However, we find that increases in volume contribute little to changes in richness, with most (78%) lowland species occurring within the range of trait space occupied at high elevations. Taken together, our results suggest that high species richness is mainly associated with a denser occupation of functional trait space, implying an increased specialization or overlap of ecological niches, and supporting the view that niche packing is the dominant trend underlying gradients of increasing biodiversity towards the lowland tropics. © 2016 The Author(s).

Identification of Novel Functional Inhibitors of Acid Sphingomyelinase

PubMed Central

Trapp, Stefan; Pechmann, Stefanie; Friedl, Astrid; Reichel, Martin; Mühle, Christiane; Terfloth, Lothar; Groemer, Teja W.; Spitzer, Gudrun M.; Liedl, Klaus R.; Gulbins, Erich; Tripal, Philipp

2011-01-01

We describe a hitherto unknown feature for 27 small drug-like molecules, namely functional inhibition of acid sphingomyelinase (ASM). These entities named FIASMAs (Functional Inhibitors of Acid SphingoMyelinAse), therefore, can be potentially used to treat diseases associated with enhanced activity of ASM, such as Alzheimer's disease, major depression, radiation- and chemotherapy-induced apoptosis and endotoxic shock syndrome. Residual activity of ASM measured in the presence of 10 µM drug concentration shows a bimodal distribution; thus the tested drugs can be classified into two groups with lower and higher inhibitory activity. All FIASMAs share distinct physicochemical properties in showing lipophilic and weakly basic properties. Hierarchical clustering of Tanimoto coefficients revealed that FIASMAs occur among drugs of various chemical scaffolds. Moreover, FIASMAs more frequently violate Lipinski's Rule-of-Five than compounds without effect on ASM. Inhibition of ASM appears to be associated with good permeability across the blood-brain barrier. In the present investigation, we developed a novel structure-property-activity relationship by using a random forest-based binary classification learner. Virtual screening revealed that only six out of 768 (0.78%) compounds of natural products functionally inhibit ASM, whereas this inhibitory activity occurs in 135 out of 2028 (6.66%) drugs licensed for medical use in humans. PMID:21909365

Endozoicomonas genomes reveal functional adaptation and plasticity in bacterial strains symbiotically associated with diverse marine hosts

PubMed Central

Neave, Matthew J.; Michell, Craig T.; Apprill, Amy; Voolstra, Christian R.

2017-01-01

Endozoicomonas bacteria are globally distributed and often abundantly associated with diverse marine hosts including reef-building corals, yet their function remains unknown. In this study we generated novel Endozoicomonas genomes from single cells and metagenomes obtained directly from the corals Stylophora pistillata, Pocillopora verrucosa, and Acropora humilis. We then compared these culture-independent genomes to existing genomes of bacterial isolates acquired from a sponge, sea slug, and coral to examine the functional landscape of this enigmatic genus. Sequencing and analysis of single cells and metagenomes resulted in four novel genomes with 60–76% and 81–90% genome completeness, respectively. These data also confirmed that Endozoicomonas genomes are large and are not streamlined for an obligate endosymbiotic lifestyle, implying that they have free-living stages. All genomes show an enrichment of genes associated with carbon sugar transport and utilization and protein secretion, potentially indicating that Endozoicomonas contribute to the cycling of carbohydrates and the provision of proteins to their respective hosts. Importantly, besides these commonalities, the genomes showed evidence for differential functional specificity and diversification, including genes for the production of amino acids. Given this metabolic diversity of Endozoicomonas we propose that different genotypes play disparate roles and have diversified in concert with their hosts. PMID:28094347

Functional traits reveal the expansion and packing of ecological niche space underlying an elevational diversity gradient in passerine birds

PubMed Central

Pigot, Alex L.; Trisos, Christopher H.; Tobias, Joseph A.

2016-01-01

Variation in species richness across environmental gradients may be associated with an expanded volume or increased packing of ecological niche space. However, the relative importance of these alternative scenarios remains unknown, largely because standardized information on functional traits and their ecological relevance is lacking for major diversity gradients. Here, we combine data on morphological and ecological traits for 523 species of passerine birds distributed across an Andes-to-Amazon elevation gradient. We show that morphological traits capture substantial variation in species dietary (75%) and foraging niches (60%) when multiple independent trait dimensions are considered. Having established these relationships, we show that the 14-fold increase in species richness towards the lowlands is associated with both an increased volume and density of functional trait space. However, we find that increases in volume contribute little to changes in richness, with most (78%) lowland species occurring within the range of trait space occupied at high elevations. Taken together, our results suggest that high species richness is mainly associated with a denser occupation of functional trait space, implying an increased specialization or overlap of ecological niches, and supporting the view that niche packing is the dominant trend underlying gradients of increasing biodiversity towards the lowland tropics. PMID:26740616

Form Follows Function: Learning about Function Helps Children Learn about Shape

ERIC Educational Resources Information Center

Ware, Elizabeth A.; Booth, Amy E.

2010-01-01

Object functions help young children to organize new artifact categories. However, the scope of their influence is unknown. We explore whether functions highlight property dimensions that are relevant to artifact categories in general. Specifically, using a longitudinal training procedure, we assessed whether experience with functions highlights…

Ichneumonidae (Hymenoptera) species new to the fauna of Norway

PubMed Central

2014-01-01

Abstract The present paper contains new distributional records for 61 species of ichneumon wasps (Hymenoptera, Ichneumonidae) previously unknown for Norway, six of them are reported from Scandinavia for the first time. PMID:24855440

Editorially Speaking - Energy: World Needs and Reserves

ERIC Educational Resources Information Center

Journal of Chemical Education, 1974

1974-01-01

Discusses the world's energy requirements in contrast with the world's known and unknown energy reserves to illustrate the need for a stable and more equitable world-wide energy distribution system, especially for oil-importing countries. (CC)

Model-free adaptive sliding mode controller design for generalized projective synchronization of the fractional-order chaotic system via radial basis function neural networks

NASA Astrophysics Data System (ADS)

Wang, L. M.

2017-09-01

A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) between two entirely unknown fractional-order chaotic systems subject to the external disturbances. To solve the difficulties from the little knowledge about the master-slave system and to overcome the bad effects of the external disturbances on the generalized projective synchronization, the radial basis function neural networks are used to approach the packaged unknown master system and the packaged unknown slave system (including the external disturbances). Consequently, based on the slide mode technology and the neural network theory, a model-free adaptive sliding mode controller is designed to guarantee asymptotic stability of the generalized projective synchronization error. The main contribution of this paper is that a control strategy is provided for the generalized projective synchronization between two entirely unknown fractional-order chaotic systems subject to the unknown external disturbances, and the proposed control strategy only requires that the master system has the same fractional orders as the slave system. Moreover, the proposed method allows us to achieve all kinds of generalized projective chaos synchronizations by turning the user-defined parameters onto the desired values. Simulation results show the effectiveness of the proposed method and the robustness of the controlled system.

Observer-based distributed adaptive fault-tolerant containment control of multi-agent systems with general linear dynamics.

PubMed

Ye, Dan; Chen, Mengmeng; Li, Kui

2017-11-01

In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation.

PubMed

Tkach, Itshak; Jevtić, Aleksandar; Nof, Shimon Y; Edan, Yael

2018-03-02

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors' performance, tasks' priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation †

PubMed Central

Nof, Shimon Y.; Edan, Yael

2018-01-01

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors’ performance, tasks’ priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems. PMID:29498683

Convergence Rates for Multivariate Smoothing Spline Functions.

DTIC Science & Technology

1982-10-01

GAI (,T) g (T)dT - g In order to show convergence of the series and obtain bounds on the terms, we need to estimate £ Now (1 + Ay v) AyV ( g ,#V...Cox* Technical Summary Report #2437 October 1982 ABSTRACT Given data z i - g (ti ) + ci, 1 4 i 4 n, where g is the unknown function, the ti are unknown...d-dimensional variables in a domain fl, and the ei are i.i.d. random errors, the smoothing spline estimate g n is defined to be the

Optimal Fault-Tolerant Control for Discrete-Time Nonlinear Strict-Feedback Systems Based on Adaptive Critic Design.

PubMed

Wang, Zhanshan; Liu, Lei; Wu, Yanming; Zhang, Huaguang

2018-06-01

This paper investigates the problem of optimal fault-tolerant control (FTC) for a class of unknown nonlinear discrete-time systems with actuator fault in the framework of adaptive critic design (ACD). A pivotal highlight is the adaptive auxiliary signal of the actuator fault, which is designed to offset the effect of the fault. The considered systems are in strict-feedback forms and involve unknown nonlinear functions, which will result in the causal problem. To solve this problem, the original nonlinear systems are transformed into a novel system by employing the diffeomorphism theory. Besides, the action neural networks (ANNs) are utilized to approximate a predefined unknown function in the backstepping design procedure. Combined the strategic utility function and the ACD technique, a reinforcement learning algorithm is proposed to set up an optimal FTC, in which the critic neural networks (CNNs) provide an approximate structure of the cost function. In this case, it not only guarantees the stability of the systems, but also achieves the optimal control performance as well. In the end, two simulation examples are used to show the effectiveness of the proposed optimal FTC strategy.

Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning.

PubMed

Yang, Xiong; Liu, Derong; Wang, Ding; Wei, Qinglai

2014-07-01

In this paper, a reinforcement-learning-based direct adaptive control is developed to deliver a desired tracking performance for a class of discrete-time (DT) nonlinear systems with unknown bounded disturbances. We investigate multi-input-multi-output unknown nonaffine nonlinear DT systems and employ two neural networks (NNs). By using Implicit Function Theorem, an action NN is used to generate the control signal and it is also designed to cancel the nonlinearity of unknown DT systems, for purpose of utilizing feedback linearization methods. On the other hand, a critic NN is applied to estimate the cost function, which satisfies the recursive equations derived from heuristic dynamic programming. The weights of both the action NN and the critic NN are directly updated online instead of offline training. By utilizing Lyapunov's direct method, the closed-loop tracking errors and the NN estimated weights are demonstrated to be uniformly ultimately bounded. Two numerical examples are provided to show the effectiveness of the present approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Repeatability of dose painting by numbers treatment planning in prostate cancer radiotherapy based on multiparametric magnetic resonance imaging

NASA Astrophysics Data System (ADS)

van Schie, Marcel A.; Steenbergen, Peter; Viet Dinh, Cuong; Ghobadi, Ghazaleh; van Houdt, Petra J.; Pos, Floris J.; Heijmink, Stijn W. T. J. P.; van der Poel, Henk G.; Renisch, Steffen; Vik, Torbjørn; van der Heide, Uulke A.

2017-07-01

Dose painting by numbers (DPBN) refers to a voxel-wise prescription of radiation dose modelled from functional image characteristics, in contrast to dose painting by contours which requires delineations to define the target for dose escalation. The direct relation between functional imaging characteristics and DPBN implies that random variations in images may propagate into the dose distribution. The stability of MR-only prostate cancer treatment planning based on DPBN with respect to these variations is as yet unknown. We conducted a test-retest study to investigate the stability of DPBN for prostate cancer in a semi-automated MR-only treatment planning workflow. Twelve patients received a multiparametric MRI on two separate days prior to prostatectomy. The tumor probability (TP) within the prostate was derived from image features with a logistic regression model. Dose mapping functions were applied to acquire a DPBN prescription map that served to generate an intensity modulated radiation therapy (IMRT) treatment plan. Dose calculations were done on a pseudo-CT derived from the MRI. The TP and DPBN map and the IMRT dose distribution were compared between both MRI sessions, using the intraclass correlation coefficient (ICC) to quantify repeatability of the planning pipeline. The quality of each treatment plan was measured with a quality factor (QF). Median ICC values for the TP and DPBN map and the IMRT dose distribution were 0.82, 0.82 and 0.88, respectively, for linear dose mapping and 0.82, 0.84 and 0.94 for square root dose mapping. A median QF of 3.4% was found among all treatment plans. We demonstrated the stability of DPBN radiotherapy treatment planning in prostate cancer, with excellent overall repeatability and acceptable treatment plan quality. Using validated tumor probability modelling and simple dose mapping techniques it was shown that despite day-to-day variations in imaging data still consistent treatment plans were obtained.

Geological and hydrogeological investigations in west Malaysia

NASA Technical Reports Server (NTRS)

Ahmad, J. B. (Principal Investigator); Khoon, S. Y.

1977-01-01

The author has identified the following significant results. Large structures along the east coast of the peninsula were discovered. Of particular significance were the circular structures which were believed to be associated with mineralization and whose existence was unknown. The distribution of the younger sediments along the east coast appeared to be more widespread than previously indicated. Along the Pahang coast on the southern end, small traces of raised beach lines were noted up to six miles inland. The existence of these beach lines was unknown due to their isolation in large coastal swamps.

Desired Accuracy Estimation of Noise Function from ECG Signal by Fuzzy Approach

PubMed Central

Vahabi, Zahra; Kermani, Saeed

2012-01-01

Unknown noise and artifacts present in medical signals with non-linear fuzzy filter will be estimated and then removed. An adaptive neuro-fuzzy interference system which has a non-linear structure presented for the noise function prediction by before Samples. This paper is about a neuro-fuzzy method to estimate unknown noise of Electrocardiogram signal. Adaptive neural combined with Fuzzy System to construct a fuzzy Predictor. For this system setting parameters such as the number of Membership Functions for each input and output, training epochs, type of MFs for each input and output, learning algorithm and etc. is determined by learning data. At the end simulated experimental results are presented for proper validation. PMID:23717810

Mining high-throughput experimental data to link gene and function.

PubMed

Blaby-Haas, Crysten E; de Crécy-Lagard, Valérie

2011-04-01

Nearly 2200 genomes that encode around 6 million proteins have now been sequenced. Around 40% of these proteins are of unknown function, even when function is loosely and minimally defined as 'belonging to a superfamily'. In addition to in silico methods, the swelling stream of high-throughput experimental data can give valuable clues for linking these unknowns with precise biological roles. The goal is to develop integrative data-mining platforms that allow the scientific community at large to access and utilize this rich source of experimental knowledge. To this end, we review recent advances in generating whole-genome experimental datasets, where this data can be accessed, and how it can be used to drive prediction of gene function. Copyright © 2011 Elsevier Ltd. All rights reserved.

Structural diversity of supercoiled DNA

PubMed Central

Irobalieva, Rossitza N.; Fogg, Jonathan M.; Catanese, Daniel J.; Sutthibutpong, Thana; Chen, Muyuan; Barker, Anna K.; Ludtke, Steven J.; Harris, Sarah A.; Schmid, Michael F.; Chiu, Wah; Zechiedrich, Lynn

2015-01-01

By regulating access to the genetic code, DNA supercoiling strongly affects DNA metabolism. Despite its importance, however, much about supercoiled DNA (positively supercoiled DNA, in particular) remains unknown. Here we use electron cryo-tomography together with biochemical analyses to investigate structures of individual purified DNA minicircle topoisomers with defined degrees of supercoiling. Our results reveal that each topoisomer, negative or positive, adopts a unique and surprisingly wide distribution of three-dimensional conformations. Moreover, we uncover striking differences in how the topoisomers handle torsional stress. As negative supercoiling increases, bases are increasingly exposed. Beyond a sharp supercoiling threshold, we also detect exposed bases in positively supercoiled DNA. Molecular dynamics simulations independently confirm the conformational heterogeneity and provide atomistic insight into the flexibility of supercoiled DNA. Our integrated approach reveals the three-dimensional structures of DNA that are essential for its function. PMID:26455586

Structural diversity of supercoiled DNA

NASA Astrophysics Data System (ADS)

Irobalieva, Rossitza N.; Fogg, Jonathan M.; Catanese, Daniel J.; Sutthibutpong, Thana; Chen, Muyuan; Barker, Anna K.; Ludtke, Steven J.; Harris, Sarah A.; Schmid, Michael F.; Chiu, Wah; Zechiedrich, Lynn

2015-10-01

By regulating access to the genetic code, DNA supercoiling strongly affects DNA metabolism. Despite its importance, however, much about supercoiled DNA (positively supercoiled DNA, in particular) remains unknown. Here we use electron cryo-tomography together with biochemical analyses to investigate structures of individual purified DNA minicircle topoisomers with defined degrees of supercoiling. Our results reveal that each topoisomer, negative or positive, adopts a unique and surprisingly wide distribution of three-dimensional conformations. Moreover, we uncover striking differences in how the topoisomers handle torsional stress. As negative supercoiling increases, bases are increasingly exposed. Beyond a sharp supercoiling threshold, we also detect exposed bases in positively supercoiled DNA. Molecular dynamics simulations independently confirm the conformational heterogeneity and provide atomistic insight into the flexibility of supercoiled DNA. Our integrated approach reveals the three-dimensional structures of DNA that are essential for its function.

Characterizing heterogeneous properties of cerebral aneurysms with unknown stress-free geometry: a precursor to in vivo identification.

PubMed

Zhao, Xuefeng; Raghavan, Madhavan L; Lu, Jia

2011-05-01

Knowledge of elastic properties of cerebral aneurysms is crucial for understanding the biomechanical behavior of the lesion. However, characterizing tissue properties using in vivo motion data presents a tremendous challenge. Aside from the limitation of data accuracy, a pressing issue is that the in vivo motion does not expose the stress-free geometry. This is compounded by the nonlinearity, anisotropy, and heterogeneity of the tissue behavior. This article introduces a method for identifying the heterogeneous properties of aneurysm wall tissue under unknown stress-free configuration. In the proposed approach, an accessible configuration is taken as the reference; the unknown stress-free configuration is represented locally by a metric tensor describing the prestrain from the stress-free configuration to the reference configuration. Material parameters are identified together with the metric tensor pointwisely. The paradigm is tested numerically using a forward-inverse analysis loop. An image-derived sac is considered. The aneurysm tissue is modeled as an eightply laminate whose constitutive behavior is described by an anisotropic hyperelastic strain-energy function containing four material parameters. The parameters are assumed to vary continuously in two assigned patterns to represent two types of material heterogeneity. Nine configurations between the diastolic and systolic pressures are generated by forward quasi-static finite element analyses. These configurations are fed to the inverse analysis to delineate the material parameters and the metric tensor. The recovered and the assigned distributions are in good agreement. A forward verification is conducted by comparing the displacement solutions obtained from the recovered and the assigned material parameters at a different pressure. The nodal displacements are found in excellent agreement.

The Larva, ecology and distribution of Tinodes braueri McLachlan, 1878 (Trichoptera: Psychomyiidae)

PubMed Central

GRAF, WOLFRAM; KUČINIĆ, MLADEN; PREVIŠIĆ, ANA; VUČKOVIĆ, IVAN; WARINGER, JOHANN

2016-01-01

The hitherto unknown larva of Tinodes braueri McLachlan, 1878, is described and discussed in the context of contemporary Psychomyiidae keys. In addition, zoogeographical and ecological notes are included. PMID:26973366

Iterative algorithms for a non-linear inverse problem in atmospheric lidar

NASA Astrophysics Data System (ADS)

Denevi, Giulia; Garbarino, Sara; Sorrentino, Alberto

2017-08-01

We consider the inverse problem of retrieving aerosol extinction coefficients from Raman lidar measurements. In this problem the unknown and the data are related through the exponential of a linear operator, the unknown is non-negative and the data follow the Poisson distribution. Standard methods work on the log-transformed data and solve the resulting linear inverse problem, but neglect to take into account the noise statistics. In this study we show that proper modelling of the noise distribution can improve substantially the quality of the reconstructed extinction profiles. To achieve this goal, we consider the non-linear inverse problem with non-negativity constraint, and propose two iterative algorithms derived using the Karush-Kuhn-Tucker conditions. We validate the algorithms with synthetic and experimental data. As expected, the proposed algorithms out-perform standard methods in terms of sensitivity to noise and reliability of the estimated profile.

Accumulation and distribution of Zn in the shoots and reproductive structures of the halophyte plant species Kosteletzkya virginica as a function of salinity.

PubMed

Han, Ruiming; Quinet, Muriel; André, Emilie; van Elteren, Johannes Teun; Destrebecq, Florence; Vogel-Mikuš, Katarina; Cui, Guangling; Debeljak, Marta; Lefèvre, Isabelle; Lutts, Stanley

2013-09-01

Kosteletzkya virginica is a wetland halophyte that is a good candidate for rehabilitation of degraded salt marshes and production of oil as biodiesel. Salt marshes are frequently contaminated by heavy metals. The distribution of Zn in vegetative and reproductive organs of adult plants, and the NaCl influence on this distribution remain unknown and were thus explored in the present study. Plants were cultivated in a nutrient film technique system, from seedling stage until seed maturation in a control, Zn (100 μM), NaCl (50 mM) or Zn + NaCl medium. Photosynthesis, ion nutrition, malondialdehyde and non-protein thiol concentrations were quantified. Zinc distribution in reproductive organs was estimated by a laser ablation-inductively coupled plasma-mass spectrometry procedure (LA-ICP-MS). Adult plants accumulated up to 2 mg g(-1) DW Zn in the shoots. Zinc reduced plant growth, inhibited photosynthesis and reduced seed yield. Zinc accumulation in the seeds was only two times higher in Zn-treated plants than in controls. Exogenous NaCl neutralized the damaging action of Zn and modified the Zn distribution through a preferential accumulation of toxic ions in older leaves. Zinc was present in seed testa, endosperm and, to a lower extent, in embryo. Additional NaCl induced a chalazal retention of Zn during seed maturation and reduced final Zn seed content. It is concluded that NaCl 50 mM had a positive impact on the response of K. virginica to Zn toxicity and acts through a modification in Zn distribution rather than a decrease in Zn absorption.

High dendritic expression of Ih in the proximity of the axon origin controls the integrative properties of nigral dopamine neurons.

PubMed

Engel, Dominique; Seutin, Vincent

2015-11-15

The hyperpolarization-activated cation current Ih is expressed in dopamine neurons of the substantia nigra, but the subcellular distribution of the current and its role in synaptic integration remain unknown. We used cell-attached patch recordings to determine the localization profile of Ih along the somatodendritic axis of nigral dopamine neurons in slices from young rats. Ih density is higher in axon-bearing dendrites, in a membrane area close to the axon origin, than in the soma and axon-lacking dendrites. Dual current-clamp recordings revealed a similar contribution of Ih to the waveform of single excitatory postsynaptic potentials throughout the somatodendritic domain. The Ih blocker ZD 7288 increased the temporal summation in all dendrites with a comparable effect in axon- and non-axon dendrites. The strategic position of Ih in the proximity of the axon may influence importantly transitions between pacemaker and bursting activities and consequently the downstream release of dopamine. Dendrites of most neurons express voltage-gated ion channels in their membrane. In combination with passive properties, active currents confer to dendrites a high computational potential. The hyperpolarization-activated cation current Ih present in the dendrites of some pyramidal neurons affects their membrane and integration properties, synaptic plasticity and higher functions such as memory. A gradient of increasing h-channel density towards distal dendrites has been found to be responsible for the location independence of excitatory postsynaptic potential (EPSP) waveform and temporal summation in cortical and hippocampal pyramidal cells. However, reports on other cell types revealed that smoother gradients or even linear distributions of Ih can achieve homogeneous temporal summation. Although the existence of a robust, slowly activating Ih current has been repeatedly demonstrated in nigral dopamine neurons, its subcellular distribution and precise role in synaptic integration are unknown. Using cell-attached patch-clamp recordings, we find a higher Ih current density in the axon-bearing dendrite than in the soma or in dendrites without axon in nigral dopamine neurons. Ih is mainly concentrated in the dendritic membrane area surrounding the axon origin and decreases with increasing distances from this site. Single EPSPs and temporal summation are similarly affected by blockade of Ih in axon- and non-axon-bearing dendrites. The presence of Ih close to the axon is pivotal to control the integrative functions and the output signal of dopamine neurons and may consequently influence the downstream coding of movement. © 2015 The Authors. The Journal of Physiology © 2015 The Physiological Society.

A continuous optimization approach for inferring parameters in mathematical models of regulatory networks.

PubMed

Deng, Zhimin; Tian, Tianhai

2014-07-29

The advances of systems biology have raised a large number of sophisticated mathematical models for describing the dynamic property of complex biological systems. One of the major steps in developing mathematical models is to estimate unknown parameters of the model based on experimentally measured quantities. However, experimental conditions limit the amount of data that is available for mathematical modelling. The number of unknown parameters in mathematical models may be larger than the number of observation data. The imbalance between the number of experimental data and number of unknown parameters makes reverse-engineering problems particularly challenging. To address the issue of inadequate experimental data, we propose a continuous optimization approach for making reliable inference of model parameters. This approach first uses a spline interpolation to generate continuous functions of system dynamics as well as the first and second order derivatives of continuous functions. The expanded dataset is the basis to infer unknown model parameters using various continuous optimization criteria, including the error of simulation only, error of both simulation and the first derivative, or error of simulation as well as the first and second derivatives. We use three case studies to demonstrate the accuracy and reliability of the proposed new approach. Compared with the corresponding discrete criteria using experimental data at the measurement time points only, numerical results of the ERK kinase activation module show that the continuous absolute-error criteria using both function and high order derivatives generate estimates with better accuracy. This result is also supported by the second and third case studies for the G1/S transition network and the MAP kinase pathway, respectively. This suggests that the continuous absolute-error criteria lead to more accurate estimates than the corresponding discrete criteria. We also study the robustness property of these three models to examine the reliability of estimates. Simulation results show that the models with estimated parameters using continuous fitness functions have better robustness properties than those using the corresponding discrete fitness functions. The inference studies and robustness analysis suggest that the proposed continuous optimization criteria are effective and robust for estimating unknown parameters in mathematical models.

Environmental distribution of two widespread uncultured freshwater Euryarchaeota clades unveiled by specific primers and quantitative PCR.

PubMed

Restrepo-Ortiz, Claudia X; Casamayor, Emilio O

2013-12-01

Quantitative environmental distribution of two widely distributed uncultured freshwater Euryarchaeota with unknown functional role was explored by newly designed quantitative PCR primers targeting the 16S rRNA gene of clades Miscellaneous Euryarchaeota Group (MEG, containing the groups pMC2A384 and VALII/Eury4) and Deep-Sea Euryarchaeotal Groups (DSEG, targeting the cluster named VALIII containing the DHVE-3/DSEG, BC07-2A-27/DSEG-3 and DSEG-2 groups), respectively. The summer surface plankton of 28 lakes was analysed, and one additional dimictic deep alpine lake, Lake Redon, was temporally and vertically surveyed covering seasonal limnological variability. A trophic range between 0.2 and 5.2 μg l(-1) Chl a, and pH span from 3.8 to 9.5 was explored at altitudes between 632 and 2590 m above sea level. The primers showed to be highly selective with c. 85% coverage and 100% specificity. Only pH significantly explained the changes observed in gene abundances and environment. In Lake Redon, DSEG bloomed in deep stratified waters both in summer and early spring, and MEG at intermediate depths during the ice-cover period. Overall, MEG and DSEG showed a differential ecological distribution although correlational analyses indicated lack of coupling of both Euryarchaeota with phytoplankton (chlorophyll a). However, an intriguing positive and significant relationship was found between DSEG and putative ammonia oxidizing thaumarchaeota. © 2013 John Wiley & Sons Ltd and Society for Applied Microbiology.

A novel salt-inducible gene SbSI-1 from Salicornia brachiata confers salt and desiccation tolerance in E. coli.

PubMed

Yadav, Narendra Singh; Rashmi, Deo; Singh, Dinkar; Agarwal, Pradeep K; Jha, Bhavanath

2012-02-01

Salicornia brachiata is one of the extreme salt tolerant plants and grows luxuriantly in coastal areas. Previously we have reported isolation and characterization of ESTs from S. brachiata with large number of unknown gene sequences. Reverse Northern analysis showed upregulation and downregulation of few unknown genes in response to salinity. Some of these unknown genes were made full length and their functional analysis is being tested. In this study, we have selected a novel unknown salt inducible gene SbSI-1 (Salicornia brachiata salt inducible-1) for the functional validation. The SbSI-1 (Gen-Bank accession number JF 965339) was made full length and characterized in detail for its functional validation under desiccation and salinity. The SbSI-1 gene is 917 bp long, and contained 437 bp 3' UTR, and 480 bp ORF region encoding 159 amino acids protein with estimated molecular mass of 18.39 kDa and pI 8.58. The real time PCR analysis revealed high transcript expression in salt, desiccation, cold and heat stresses. However, the maximum expression was obtained by desiccation. The ORF region of SbSI-1 was cloned in pET28a vector and transformed in BL21 (DE3) E. coli cells. The SbSI-1 recombinant E. coli cells showed tolerance to desiccation and salinity stress compared to only vector in the presence of stress.

Somatodendritic and excitatory postsynaptic distribution of neuron-type dystrophin isoform, Dp40, in hippocampal neurons

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

Fujimoto, Takahiro; Itoh, Kyoko, E-mail: kxi14@koto.kpu-m.ac.jp; Yaoi, Takeshi

2014-09-12

Highlights: • Identification of dystrophin (Dp) shortest isoform, Dp40, is a neuron-type Dp. • Dp40 expression is temporally and differentially regulated in comparison to Dp71. • Somatodendritic and nuclear localization of Dp40. • Dp40 is localized to excitatory postsynapses. • Dp40 might play roles in dendritic and synaptic functions. - Abstract: The Duchenne muscular dystrophy (DMD) gene produces multiple dystrophin (Dp) products due to the presence of several promoters. We previously reported the existence of a novel short isoform of Dp, Dp40, in adult mouse brain. However, the exact biochemical expression profile and cytological distribution of the Dp40 protein remainmore » unknown. In this study, we generated a polyclonal antibody against the NH{sub 2}-terminal region of the Dp40 and identified the expression profile of Dp40 in the mouse brain. Through an analysis using embryonic and postnatal mouse cerebrums, we found that Dp40 emerged from the early neonatal stages until adulthood, whereas Dp71, an another Dp short isoform, was highly detected in both prenatal and postnatal cerebrums. Intriguingly, relative expressions of Dp40 and Dp71 were prominent in cultured dissociated neurons and non-neuronal cells derived from mouse hippocampus, respectively. Furthermore, the immunocytological distribution of Dp40 was analyzed in dissociated cultured neurons, revealing that Dp40 is detected in the soma and its dendrites, but not in the axon. It is worthy to note that Dp40 is localized along the subplasmalemmal region of the dendritic shafts, as well as at excitatory postsynaptic sites. Thus, Dp40 was identified as a neuron-type Dp possibly involving dendritic and synaptic functions.« less

Energy spectra unfolding of fast neutron sources using the group method of data handling and decision tree algorithms

NASA Astrophysics Data System (ADS)

Hosseini, Seyed Abolfazl; Afrakoti, Iman Esmaili Paeen

2017-04-01

Accurate unfolding of the energy spectrum of a neutron source gives important information about unknown neutron sources. The obtained information is useful in many areas like nuclear safeguards, nuclear nonproliferation, and homeland security. In the present study, the energy spectrum of a poly-energetic fast neutron source is reconstructed using the developed computational codes based on the Group Method of Data Handling (GMDH) and Decision Tree (DT) algorithms. The neutron pulse height distribution (neutron response function) in the considered NE-213 liquid organic scintillator has been simulated using the developed MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif University of Technology). The developed computational codes based on the GMDH and DT algorithms use some data for training, testing and validation steps. In order to prepare the required data, 4000 randomly generated energy spectra distributed over 52 bins are used. The randomly generated energy spectra and the simulated neutron pulse height distributions by MCNPX-ESUT for each energy spectrum are used as the output and input data. Since there is no need to solve the inverse problem with an ill-conditioned response matrix, the unfolded energy spectrum has the highest accuracy. The 241Am-9Be and 252Cf neutron sources are used in the validation step of the calculation. The unfolded energy spectra for the used fast neutron sources have an excellent agreement with the reference ones. Also, the accuracy of the unfolded energy spectra obtained using the GMDH is slightly better than those obtained from the DT. The results obtained in the present study have good accuracy in comparison with the previously published paper based on the logsig and tansig transfer functions.

On the mechanics of stress analysis of fiber-reinforced composites

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

Lee, V.G.

A general mathematical formulation is developed for the three-dimensional inclusion and inhomogeneity problems, which are practically important in many engineering applications such as fiber pullout of reinforced composites, load transfer behavior in the stiffened structural components, and material defects and impurities existing in engineering materials. First, the displacement field (Green's function) for an elastic solid subjected to various distributions of ring loading is derived in closed form using the Papkovich-Neuber displacement potentials and the Hankel transforms. The Green's functions are used to derive the displacement and stress fields due to a finite cylindrical inclusion of prescribed dilatational eigenstrain such asmore » thermal expansion caused by an internal heat source. Unlike an elliptical inclusion, the interior stress field in the cylindrical inclusion is not uniform. Next, the three-dimensional inhomogeneity problem of a cylindrical fiber embedded in an infinite matrix of different material properties is considered to study load transfer of a finite fiber to an elastic medium. By using the equivalent inclusion method, the fiber is modeled as an inclusion with distributed eigenstrains of unknown strength, and the inhomogeneity problem can be treated as an equivalent inclusion problem. The eigenstrains are determined to simulate the disturbance due to the existing fiber. The equivalency of elastic field between inhomogeneity and inclusion problems leads to a set of integral equations. To solve the integral equations, the inclusion domain is discretized into a finite number of sub-inclusions with uniform eigenstrains, and the integral equations are reduced to a set of algebraic equations. The distributions of eigenstrains, interior stress field and axial force along the fiber are presented for various fiber lengths and the ratio of material properties of the fiber relative to the matrix.« less

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

Target and double spin asymmetries of deeply virtual π0 production with a longitudinally polarized proton target and CLAS

NASA Astrophysics Data System (ADS)

Kim, A.; Avakian, H.; Burkert, V.; Joo, K.; Kim, W.; Adhikari, K. P.; Akbar, Z.; Anefalos Pereira, S.; Badui, R. A.; Battaglieri, M.; Batourine, V.; Bedlinskiy, I.; Biselli, A. S.; Boiarinov, S.; Bosted, P.; Briscoe, W. J.; Brooks, W. K.; Bültmann, S.; Cao, T.; Carman, D. S.; Celentano, A.; Chandavar, S.; Charles, G.; Chetry, T.; Colaneri, L.; Cole, P. L.; Compton, N.; Contalbrigo, M.; Cortes, O.; Crede, V.; D'Angelo, A.; Dashyan, N.; De Vita, R.; De Sanctis, E.; Djalali, C.; Egiyan, H.; El Alaoui, A.; El Fassi, L.; Eugenio, P.; Fedotov, G.; Fersch, R.; Filippi, A.; Fleming, J. A.; Fradi, A.; Garc con, M.; Ghandilyan, Y.; Gilfoyle, G. P.; Giovanetti, K. L.; Girod, F. X.; Gohn, W.; Golovatch, E.; Gothe, R. W.; Griffioen, K. A.; Guo, L.; Hafidi, K.; Hanretty, C.; Hattawy, M.; Heddle, D.; Hicks, K.; Holtrop, M.; Ilieva, Y.; Ireland, D. G.; Ishkhanov, B. S.; Jenkins, D.; Jiang, H.; Jo, H. S.; Joosten, S.; Keller, D.; Khachatryan, G.; Khandaker, M.; Klein, A.; Klein, F. J.; Kubarovsky, V.; Kuhn, S. E.; Kuleshov, S. V.; Lanza, L.; Lenisa, P.; Lu, H. Y.; MacGregor, I. J. D.; Markov, N.; Mattione, P.; McCracken, M. E.; McKinnon, B.; Mokeev, V.; Movsisyan, A.; Munevar, E.; Nadel-Turonski, P.; Net, L. A.; Niccolai, S.; Osipenko, M.; Ostrovidov, A. I.; Paolone, M.; Park, K.; Pasyuk, E.; Phelps, W.; Pisano, S.; Pogorelko, O.; Price, J. W.; Prok, Y.; Ripani, M.; Rizzo, A.; Rosner, G.; Rossi, P.; Roy, P.; Salgado, C.; Schumacher, R. A.; Seder, E.; Sharabian, Y. G.; Skorodumina, Iu.; Smith, G. D.; Sokhan, D.; Sparveris, N.; Stepanyan, S.; Stoler, P.; Strakovsky, I. I.; Strauch, S.; Sytnik, V.; Taiuti, M.; Torayev, B.; Ungaro, M.; Voskanyan, H.; Voutier, E.; Watts, D. P.; Wei, X.; Weinstein, L. B.; Zachariou, N.; Zana, L.; Zhang, J.

2017-05-01

The target and double spin asymmetries of the exclusive pseudoscalar channel e → p → → epπ0 were measured for the first time in the deep-inelastic regime using a longitudinally polarized 5.9 GeV electron beam and a longitudinally polarized proton target at Jefferson Lab with the CEBAF Large Acceptance Spectrometer (CLAS). The data were collected over a large kinematic phase space and divided into 110 four-dimensional bins of Q2, xB, -t and ϕ. Large values of asymmetry moments clearly indicate a substantial contribution to the polarized structure functions from transverse virtual photon amplitudes. The interpretation of experimental data in terms of generalized parton distributions (GPDs) provides the first insight on the chiral-odd GPDs H˜T and ET, and complement previous measurements of unpolarized structure functions sensitive to the GPDs HT and EbarT. These data provide a crucial input for parametrizations of essentially unknown chiral-odd GPDs and will strongly influence existing theoretical calculations based on the handbag formalism.

Cutting Edge: c-Maf Is Required for Regulatory T Cells To Adopt RORγt+ and Follicular Phenotypes.

PubMed

Wheaton, Joshua D; Yeh, Chen-Hao; Ciofani, Maria

2017-12-15

Regulatory T cells (Tregs) adopt specialized phenotypes defined by coexpression of lineage-defining transcription factors, such as RORγt, Bcl-6, or PPARγ, alongside Foxp3. These Treg subsets have unique tissue distributions and diverse roles in maintaining organismal homeostasis. However, despite extensive functional characterization, the factors driving Treg specialization are largely unknown. In this article, we show that c-Maf is a critical transcription factor regulating this process in mice, essential for generation of both RORγt + Tregs and T follicular regulatory cells, but not for adipose-resident Tregs. c-Maf appears to function primarily in Treg specialization, because IL-10 production, expression of other effector molecules, and general immune homeostasis are not c-Maf dependent. As in other T cells, c-Maf is induced in Tregs by IL-6 and TGF-β, suggesting that a combination of inflammatory and tolerogenic signals promote c-Maf expression. Therefore, c-Maf is a novel regulator of Treg specialization, which may integrate disparate signals to facilitate environmental adaptation. Copyright © 2017 by The American Association of Immunologists, Inc.

High-affinity kainate receptor subunits are necessary for ionotropic but not metabotropic signaling.

PubMed

Fernandes, Herman B; Catches, Justin S; Petralia, Ronald S; Copits, Bryan A; Xu, Jian; Russell, Theron A; Swanson, Geoffrey T; Contractor, Anis

2009-09-24

Kainate receptors signal through both ionotropic and metabotropic pathways. The high-affinity subunits, GluK4 and GluK5, are unique among the five receptor subunits, as they do not form homomeric receptors but modify the properties of heteromeric assemblies. Disruption of the Grik4 gene locus resulted in a significant reduction in synaptic kainate receptor currents. Moreover, ablation of GluK4 and GluK5 caused complete loss of synaptic ionotropic kainate receptor function. The principal subunits were distributed away from postsynaptic densities and presynaptic active zones. There was also a profound alteration in the activation properties of the remaining kainate receptors. Despite this, kainate receptor-mediated inhibition of the slow afterhyperpolarization current (I(sAHP)), which is dependent on metabotropic pathways, was intact in GluK4/GluK5 knockout mice. These results uncover a previously unknown obligatory role for the high-affinity subunits for ionotropic kainate receptor function and further demonstrate that kainate receptor participation in metabotropic signaling pathways does not require their classic role as ion channels.

Phylogenetic survey of soluble saxitoxin-binding activity in pursuit of the function and molecular evolution of saxiphilin, a relative of transferrin.

PubMed Central

Llewellyn, L E; Bell, P M; Moczydlowski, E G

1997-01-01

Saxiphilin is a soluble protein of unknown function which binds the neurotoxin, saxitoxin (STX), with high affinity. Molecular characterization of saxiphilin from the North American bullfrog, Rana catesbeiana, has previously shown that it is a member of the transferrin family. In this study we surveyed various animal species to investigate the phylogenetic distribution of saxiphilin, as detected by the presence of soluble [3H]STX binding activity in plasma, haemolymph or tissue extracts. We found that saxiphilin activity is readily detectable in a wide variety of arthropods, fish, amphibians, and reptiles. The pharmacological characteristics of [3H]STX binding activity in phylogenetically diverse species indicates that a protein homologous to bullfrog saxiphilin is likely to be constitutively expressed in many ectothermic animals. The results suggest that the saxiphilin gene is evolutionarily as old as an ancestral gene encoding bilobed transferrin, an Fe(2+)-binding and transport protein which has been identified in several arthropods and all the vertebrates which have been studied. PMID:9225480

Boundary Control of Linear Uncertain 1-D Parabolic PDE Using Approximate Dynamic Programming.

PubMed

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

This paper develops a near optimal boundary control method for distributed parameter systems governed by uncertain linear 1-D parabolic partial differential equations (PDE) by using approximate dynamic programming. A quadratic surface integral is proposed to express the optimal cost functional for the infinite-dimensional state space. Accordingly, the Hamilton-Jacobi-Bellman (HJB) equation is formulated in the infinite-dimensional domain without using any model reduction. Subsequently, a neural network identifier is developed to estimate the unknown spatially varying coefficient in PDE dynamics. Novel tuning law is proposed to guarantee the boundedness of identifier approximation error in the PDE domain. A radial basis network (RBN) is subsequently proposed to generate an approximate solution for the optimal surface kernel function online. The tuning law for near optimal RBN weights is created, such that the HJB equation error is minimized while the dynamics are identified and closed-loop system remains stable. Ultimate boundedness (UB) of the closed-loop system is verified by using the Lyapunov theory. The performance of the proposed controller is successfully confirmed by simulation on an unstable diffusion-reaction process.

A Genetic Cascade of let-7-ncl-1-fib-1 Modulates Nucleolar Size and rRNA Pool in Caenorhabditis elegans

PubMed Central

Chiou, Pey-Tsyr; Chen, Po-Hsiang; Lee, Ching-Ming; Chu, Yu-De; Yu, Hsiang; Hsiung, Kuei-Ching; Tsai, Yi-Tzang; Lee, Chi-Chang; Chang, Yu-Sun; Chan, Shih-Peng; Tan, Bertrand Chin-Ming; Lo, Szecheng J.

2015-01-01

Ribosome biogenesis takes place in the nucleolus, the size of which is often coordinated with cell growth and development. However, how metazoans control nucleolar size remains largely unknown. Caenorhabditis elegans provides a good model to address this question owing to distinct tissue distribution of nucleolar sizes and a mutant, ncl-1, which exhibits larger nucleoli than wild-type worms. Here, through a series of loss-of-function analyses, we report that the nucleolar size is regulated by a circuitry composed of microRNA let-7, translation repressor NCL-1, and a major nucleolar pre-rRNA processing protein FIB-1/fibrillarin. In cooperation with RNA binding proteins PUF and NOS, NCL-1 suppressed the translation of FIB-1/fibrillarin, while let-7 targeted the 3’UTR of ncl-1 and inhibited its expression. Consequently, the abundance of FIB-1 is tightly controlled and correlated with the nucleolar size. Together, our findings highlight a novel genetic cascade by which post-transcriptional regulators interplay in developmental control of nucleolar size and function. PMID:26492166

How whales used to filter: exceptionally preserved baleen in a Miocene cetotheriid.

PubMed

Marx, Felix G; Collareta, Alberto; Gioncada, Anna; Post, Klaas; Lambert, Olivier; Bonaccorsi, Elena; Urbina, Mario; Bianucci, Giovanni

2017-08-01

Baleen is a comb-like structure that enables mysticete whales to bulk feed on vast quantities of small prey, and ultimately allowed them to become the largest animals on Earth. Because baleen rarely fossilises, extremely little is known about its evolution, structure and function outside the living families. Here we describe, for the first time, the exceptionally preserved baleen apparatus of an entirely extinct mysticete morphotype: the Late Miocene cetotheriid, Piscobalaena nana, from the Pisco Formation of Peru. The baleen plates of P. nana are closely spaced and built around relatively dense, fine tubules, as in the enigmatic pygmy right whale, Caperea marginata. Phosphatisation of the intertubular horn, but not the tubules themselves, suggests in vivo intertubular calcification. The size of the rack matches the distribution of nutrient foramina on the palate, and implies the presence of an unusually large subrostral gap. Overall, the baleen morphology of Piscobalaena likely reflects the interacting effects of size, function and phylogeny, and reveals a previously unknown degree of complexity in modern mysticete feeding evolution. © 2017 Anatomical Society.

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

Viscoelasticity, postseismic slip, fault interactions, and the recurrence of large earthquakes

USGS Publications Warehouse

Michael, A.J.

2005-01-01

The Brownian Passage Time (BPT) model for earthquake recurrence is modified to include transient deformation due to either viscoelasticity or deep post seismic slip. Both of these processes act to increase the rate of loading on the seismogenic fault for some time after a large event. To approximate these effects, a decaying exponential term is added to the BPT model's uniform loading term. The resulting interevent time distributions remain approximately lognormal, but the balance between the level of noise (e.g., unknown fault interactions) and the coefficient of variability of the interevent time distribution changes depending on the shape of the loading function. For a given level of noise in the loading process, transient deformation has the effect of increasing the coefficient of variability of earthquake interevent times. Conversely, the level of noise needed to achieve a given level of variability is reduced when transient deformation is included. Using less noise would then increase the effect of known fault interactions modeled as stress or strain steps because they would be larger with respect to the noise. If we only seek to estimate the shape of the interevent time distribution from observed earthquake occurrences, then the use of a transient deformation model will not dramatically change the results of a probability study because a similar shaped distribution can be achieved with either uniform or transient loading functions. However, if the goal is to estimate earthquake probabilities based on our increasing understanding of the seismogenic process, including earthquake interactions, then including transient deformation is important to obtain accurate results. For example, a loading curve based on the 1906 earthquake, paleoseismic observations of prior events, and observations of recent deformation in the San Francisco Bay region produces a 40% greater variability in earthquake recurrence than a uniform loading model with the same noise level.

Prostate cancer and industrial pollution Risk around putative focus in a multi-source scenario.

PubMed

Ramis, Rebeca; Diggle, Peter; Cambra, Koldo; López-Abente, Gonzalo

2011-04-01

Prostate cancer is the second most common type of cancer among men but its aetiology is still largely unknown. Different studies have proposed several risk factors such as ethnic origin, age, genetic factors, hormonal factors, diet and insulin-like growth factor, but the spatial distribution of the disease suggests that other environmental factors are involved. This paper studies the spatial distribution of prostate cancer mortality in an industrialized area using distances from each of a number of industrial facilities as indirect measures of exposure to industrial pollution. We studied the Gran Bilbao area (Spain) with a population of 791,519 inhabitants distributed in 657 census tracts. There were 20 industrial facilities within the area, 8 of them in the central axis of the region. We analysed prostate cancer mortality during the period 1996-2003. There were 883 deaths giving a crude rate of 14 per 100,000 inhabitants. We extended the standard Poisson regression model by the inclusion of a multiplicative non-linear function to model the effect of distance from an industrial facility. The function's shape combined an elevated risk close to the source with a neutral effect at large distance. We also included socio-demographic covariates in the model to control potential confounding. We aggregated the industrial facilities by sector: metal, mineral, chemical and other activities. Results relating to metal industries showed a significantly elevated risk by a factor of approximately 1.4 in the immediate vicinity, decaying with distance to a value of 1.08 at 12km. The remaining sectors did not show a statistically significant excess of risk at the source. Notwithstanding the limitations of this kind of study, we found evidence of association between the spatial distribution of prostate cancer mortality aggregated by census tracts and proximity to metal industrial facilities located within the area, after adjusting for socio-demographic characteristics at municipality level. Copyright © 2010 Elsevier Ltd. All rights reserved.

Modeling gene expression measurement error: a quasi-likelihood approach

PubMed Central

Strimmer, Korbinian

2003-01-01

Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution) or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale). Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood). Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic) variance structure of the data. As the quasi-likelihood behaves (almost) like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye) effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also improved the power of tests to identify differential expression. PMID:12659637

Extension of the lod score: the mod score.

PubMed

Clerget-Darpoux, F

2001-01-01

In 1955 Morton proposed the lod score method both for testing linkage between loci and for estimating the recombination fraction between them. If a disease is controlled by a gene at one of these loci, the lod score computation requires the prior specification of an underlying model that assigns the probabilities of genotypes from the observed phenotypes. To address the case of linkage studies for diseases with unknown mode of inheritance, we suggested (Clerget-Darpoux et al., 1986) extending the lod score function to a so-called mod score function. In this function, the variables are both the recombination fraction and the disease model parameters. Maximizing the mod score function over all these parameters amounts to maximizing the probability of marker data conditional on the disease status. Under the absence of linkage, the mod score conforms to a chi-square distribution, with extra degrees of freedom in comparison to the lod score function (MacLean et al., 1993). The mod score is asymptotically maximum for the true disease model (Clerget-Darpoux and Bonaïti-Pellié, 1992; Hodge and Elston, 1994). Consequently, the power to detect linkage through mod score will be highest when the space of models where the maximization is performed includes the true model. On the other hand, one must avoid overparametrization of the model space. For example, when the approach is applied to affected sibpairs, only two constrained disease model parameters should be used (Knapp et al., 1994) for the mod score maximization. It is also important to emphasize the existence of a strong correlation between the disease gene location and the disease model. Consequently, there is poor resolution of the location of the susceptibility locus when the disease model at this locus is unknown. Of course, this is true regardless of the statistics used. The mod score may also be applied in a candidate gene strategy to model the potential effect of this gene in the disease. Since, however, it ignores the information provided both by disease segregation and by linkage disequilibrium between the marker alleles and the functional disease alleles, its power of discrimination between genetic models is weak. The MASC method (Clerget-Darpoux et al., 1988) has been designed to address more efficiently the objectives of a candidate gene approach.

Adaptive Fuzzy Output-Constrained Fault-Tolerant Control of Nonlinear Stochastic Large-Scale Systems With Actuator Faults.

PubMed

Li, Yongming; Ma, Zhiyao; Tong, Shaocheng

2017-09-01

The problem of adaptive fuzzy output-constrained tracking fault-tolerant control (FTC) is investigated for the large-scale stochastic nonlinear systems of pure-feedback form. The nonlinear systems considered in this paper possess the unstructured uncertainties, unknown interconnected terms and unknown nonaffine nonlinear faults. The fuzzy logic systems are employed to identify the unknown lumped nonlinear functions so that the problems of structured uncertainties can be solved. An adaptive fuzzy state observer is designed to solve the nonmeasurable state problem. By combining the barrier Lyapunov function theory, adaptive decentralized and stochastic control principles, a novel fuzzy adaptive output-constrained FTC approach is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

Neuro-adaptive backstepping control of SISO non-affine systems with unknown gain sign.

PubMed

Ramezani, Zahra; Arefi, Mohammad Mehdi; Zargarzadeh, Hassan; Jahed-Motlagh, Mohammad Reza

2016-11-01

This paper presents two neuro-adaptive controllers for a class of uncertain single-input, single-output (SISO) nonlinear non-affine systems with unknown gain sign. The first approach is state feedback controller, so that a neuro-adaptive state-feedback controller is constructed based on the backstepping technique. The second approach is an observer-based controller and K-filters are designed to estimate the system states. The proposed method relaxes a priori knowledge of control gain sign and therefore by utilizing the Nussbaum-type functions this problem is addressed. In these methods, neural networks are employed to approximate the unknown nonlinear functions. The proposed adaptive control schemes guarantee that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Finally, the theoretical results are numerically verified through simulation examples. Simulation results show the effectiveness of the proposed methods. Copyright © 2016 ISA. All rights reserved.

Post-metamorphic development of skin glands in a true toad: Parotoids versus dorsal skin.

PubMed

Regueira, Eleonora; Dávila, Camila; Sassone, Alina G; O'Donohoe, María E Ailín; Hermida, Gladys N

2017-05-01

Chemical defenses in amphibians are a common antipredatory and antimicrobial strategy related to the presence of dermal glands that synthesize and store toxic or unpalatable substances. Glands are either distributed throughout the skin or aggregated in multiglandular structures, being the parotoids the most ubiquitous macrogland in toads of Bufonidae. Even though dermal glands begin to develop during late-larval stages, many species, including Rhinella arenarum, have immature glands by the end of metamorphosis, and their post-metamorphic growth is unknown. Herein, we compared the post-metamorphic development of parotoids and dorsal glands by histological and allometric studies in a size series of R. arenarum. Histological and histochemical studies to detect proteins, acidic glycoconjugates, and catecholamines, showed that both, parotoids and dorsal glands, acquire characteristics of adults in individuals larger than 50 mm; that is, a moment in which the cryptic coloration disappears. Parotoid height increased allometrically as a function of body size, whereas the size of small dorsal glands decreased with body size. The number of glands in the dorsum was not linearly related to body size, appearing to be an individual characteristic. Only adult specimens had intraepithelial granular glands in the duct of the largest glands of the parotoids. Since toxic secretions accumulate in the central glands of parotoids, allometric growth of parotoids may translate into greater protection from predators in the largest animals. Conversely, large glands in the dorsum, which produce a proteinaceous secretion of unknown function, grow isometrically to body size. Some characteristics, like intraepithelial glands in the ducts and basophilic glands in the dorsum, are limited to adults. © 2017 Wiley Periodicals, Inc.

Early signs of recovery of Acropora palmata in St. John, US Virgin Islands

USGS Publications Warehouse

Muller, E.M.; Rogers, Caroline S.; van Woesik, R.

2014-01-01

Since the 1980s, diseases have caused significant declines in the population of the threatened Caribbean coral Acropora palmata. Yet it is largely unknown whether the population densities have recovered from these declines and whether there have been any recent shifts in size-frequency distributions toward large colonies. It is also unknown whether colony size influences the risk of disease infection, the most common stressor affecting this species. To address these unknowns, we examined A. palmata colonies at ten sites around St. John, US Virgin Islands, in 2004 and 2010. The prevalence of white-pox disease was highly variable among sites, ranging from 0 to 53 %, and this disease preferentially targeted large colonies. We found that colony density did not significantly change over the 6-year period, although six out of ten sites showed higher densities through time. The size-frequency distributions of coral colonies at all sites were positively skewed in both 2004 and 2010, however, most sites showed a temporal shift toward more large-sized colonies. This increase in large-sized colonies occurred despite the presence of white-pox disease, a severe bleaching event, and several storms. This study provides evidence of slow recovery of the A. palmata population around St. John despite the persistence of several stressors.

Near real-time estimation of ionosphere vertical total electron content from GNSS satellites using B-splines in a Kalman filter

NASA Astrophysics Data System (ADS)

Erdogan, Eren; Schmidt, Michael; Seitz, Florian; Durmaz, Murat

2017-02-01

Although the number of terrestrial global navigation satellite system (GNSS) receivers supported by the International GNSS Service (IGS) is rapidly growing, the worldwide rather inhomogeneously distributed observation sites do not allow the generation of high-resolution global ionosphere products. Conversely, with the regionally enormous increase in highly precise GNSS data, the demands on (near) real-time ionosphere products, necessary in many applications such as navigation, are growing very fast. Consequently, many analysis centers accepted the responsibility of generating such products. In this regard, the primary objective of our work is to develop a near real-time processing framework for the estimation of the vertical total electron content (VTEC) of the ionosphere using proper models that are capable of a global representation adapted to the real data distribution. The global VTEC representation developed in this work is based on a series expansion in terms of compactly supported B-spline functions, which allow for an appropriate handling of the heterogeneous data distribution, including data gaps. The corresponding series coefficients and additional parameters such as differential code biases of the GNSS satellites and receivers constitute the set of unknown parameters. The Kalman filter (KF), as a popular recursive estimator, allows processing of the data immediately after acquisition and paves the way of sequential (near) real-time estimation of the unknown parameters. To exploit the advantages of the chosen data representation and the estimation procedure, the B-spline model is incorporated into the KF under the consideration of necessary constraints. Based on a preprocessing strategy, the developed approach utilizes hourly batches of GPS and GLONASS observations provided by the IGS data centers with a latency of 1 h in its current realization. Two methods for validation of the results are performed, namely the self consistency analysis and a comparison with Jason-2 altimetry data. The highly promising validation results allow the conclusion that under the investigated conditions our derived near real-time product is of the same accuracy level as the so-called final post-processed products provided by the IGS with a latency of several days or even weeks.

A motion algorithm to extract physical and motion parameters of mobile targets from cone-beam computed tomographic images.

PubMed

Alsbou, Nesreen; Ahmad, Salahuddin; Ali, Imad

2016-05-17

A motion algorithm has been developed to extract length, CT number level and motion amplitude of a mobile target from cone-beam CT (CBCT) images. The algorithm uses three measurable parameters: Apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm are tested with mobile targets having different well-known sizes that are made from tissue-equivalent gel which is inserted into a thorax phantom. The phantom moves sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0-20 mm. Using this motion algorithm, three unknown parameters are extracted that include: Length of the target, CT number level, speed or motion amplitude for the mobile targets from CBCT images. The motion algorithm solves for the three unknown parameters using measured length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agrees with the measured lengths which are dependent on the target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, the target length and motion amplitude. Motion frequency and phase do not affect the elongation and CT number distribution of the mobile target and could not be determined. A motion algorithm has been developed to extract three parameters that include length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement of motion tracking and sorting of the images into different breathing phases. The motion model developed here works well for tumors that have simple shapes, high contrast relative to surrounding tissues and move nearly in regular motion pattern that can be approximated with a simple sinusoidal function. This algorithm has potential applications in diagnostic CT imaging and radiotherapy in terms of motion management.

Kurtosis Approach for Nonlinear Blind Source Separation

NASA Technical Reports Server (NTRS)

Duong, Vu A.; Stubbemd, Allen R.

2005-01-01

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation.

Optimal hemodynamic response model for functional near-infrared spectroscopy

PubMed Central

Kamran, Muhammad A.; Jeong, Myung Yung; Mannan, Malik M. N.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650–950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > tcritical and p-value < 0.05). PMID:26136668

Optimal hemodynamic response model for functional near-infrared spectroscopy.

PubMed

Kamran, Muhammad A; Jeong, Myung Yung; Mannan, Malik M N

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650-950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > t critical and p-value < 0.05).

Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds

NASA Astrophysics Data System (ADS)

Seko, Atsuto; Hayashi, Hiroyuki; Kashima, Hisashi; Tanaka, Isao

2018-01-01

Chemically relevant compositions (CRCs) and atomic arrangements of inorganic compounds have been collected as inorganic crystal structure databases. Machine learning is a unique approach to search for currently unknown CRCs from vast candidates. Herein we propose matrix- and tensor-based recommender system approaches to predict currently unknown CRCs from database entries of CRCs. Firstly, the performance of the recommender system approaches to discover currently unknown CRCs is examined. A Tucker decomposition recommender system shows the best discovery rate of CRCs as the majority of the top 100 recommended ternary and quaternary compositions correspond to CRCs. Secondly, systematic density functional theory (DFT) calculations are performed to investigate the phase stability of the recommended compositions. The phase stability of the 27 compositions reveals that 23 currently unknown compounds are newly found to be stable. These results indicate that the recommender system has great potential to accelerate the discovery of new compounds.

Adaptive fuzzy prescribed performance control for MIMO nonlinear systems with unknown control direction and unknown dead-zone inputs.

PubMed

Shi, Wuxi; Luo, Rui; Li, Baoquan

2017-01-01

In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

An Analytical Methodology for Predicting Repair Time Distributions of Advanced Technology Aircraft.

DTIC Science & Technology

1985-12-01

1984. 3. Barlow, Richard E. "Mathematical Theory of Reliabilitys A Historical Perspective." ZEEE Transactions on Reliability, 33. 16-19 (April 1984...Technology (AU), Wright-Patterson AFB OH, March 1971. 11. Coppola, Anthony. "Reliability Engineering of J- , Electronic Equipment," ZEEE Transactions on...1982. 64. Woodruff, Brian W. at al. "Modified Goodness-o-Fit Tests for Gamma Distributions with Unknown Location and Scale Parameters," ZEEE

Functions of maize genes encoding pyruvate phosphate dikinase in developing endosperm

USDA-ARS?s Scientific Manuscript database

Pyruvate phosphate dikinase reversibly converts AMP, pyrophosphate and phosphoenolpyruvate (PEP) to ATP, orthophosphate and pyruvate. Maize PPDK functions in mesophyll in C4 photosynthesis, yet also is highly abundant in starchy endosperm during grain fill where its function is unknown. To investiga...

Mapping the unknown: Modeling future scenarios of riverine fish communities

EPA Science Inventory

Riverscapes can be defined by spatial and temporal variation in a suite of environmental conditions that influence the distribution and persistence of riverine fish populations. Fish in riverscapes can exhibit extensive movements, require seasonally-distinct habitats for spawnin...

Autonomic nervous system function in young children with functional abdominal pain or irritable bowel syndrome

USDA-ARS?s Scientific Manuscript database

Adults with irritable bowel syndrome (IBS) have been reported to have alterations in autonomic nervous system function as measured by vagal activity via heart rate variability. Whether the same is true for children is unknown. We compared young children 7 to 10 years of age with functional abdominal...

Genome-wide protein-protein interactions and protein function exploration in cyanobacteria

PubMed Central

Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

2015-01-01

Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and “interologs” in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033

Somatodendritic and excitatory postsynaptic distribution of neuron-type dystrophin isoform, Dp40, in hippocampal neurons.

PubMed

Fujimoto, Takahiro; Itoh, Kyoko; Yaoi, Takeshi; Fushiki, Shinji

2014-09-12

The Duchenne muscular dystrophy (DMD) gene produces multiple dystrophin (Dp) products due to the presence of several promoters. We previously reported the existence of a novel short isoform of Dp, Dp40, in adult mouse brain. However, the exact biochemical expression profile and cytological distribution of the Dp40 protein remain unknown. In this study, we generated a polyclonal antibody against the NH2-terminal region of the Dp40 and identified the expression profile of Dp40 in the mouse brain. Through an analysis using embryonic and postnatal mouse cerebrums, we found that Dp40 emerged from the early neonatal stages until adulthood, whereas Dp71, an another Dp short isoform, was highly detected in both prenatal and postnatal cerebrums. Intriguingly, relative expressions of Dp40 and Dp71 were prominent in cultured dissociated neurons and non-neuronal cells derived from mouse hippocampus, respectively. Furthermore, the immunocytological distribution of Dp40 was analyzed in dissociated cultured neurons, revealing that Dp40 is detected in the soma and its dendrites, but not in the axon. It is worthy to note that Dp40 is localized along the subplasmalemmal region of the dendritic shafts, as well as at excitatory postsynaptic sites. Thus, Dp40 was identified as a neuron-type Dp possibly involving dendritic and synaptic functions. Copyright © 2014 Elsevier Inc. All rights reserved.

Pharmacokinetics, Tissue Distribution, and Anti-Lipogenic/Adipogenic Effects of Allyl-Isothiocyanate Metabolites

PubMed Central

Ahn, Jiyun; Chung, Woo-Jae; Jang, Young Jin; Seong, Ki-Seung; Moon, Jae-Hak; Ha, Tae Youl; Jung, Chang Hwa

2015-01-01

Allyl-isothiocyanate (AITC) is an organosulfur phytochemical found in abundance in common cruciferous vegetables such as mustard, wasabi, and cabbage. Although AITC is metabolized primarily through the mercapturic acid pathway, its exact pharmacokinetics remains undefined and the biological function of AITC metabolites is still largely unknown. In this study, we evaluated the inhibitory effects of AITC metabolites on lipid accumulation in vitro and elucidated the pharmacokinetics and tissue distribution of AITC metabolites in rats. We found that AITC metabolites generally conjugate with glutathione (GSH) or N-acetylcysteine (NAC) and are distributed in most organs and tissues. Pharmacokinetic analysis showed a rapid uptake and complete metabolism of AITC following oral administration to rats. Although AITC has been reported to exhibit anti-tumor activity in bladder cancer, the potential bioactivity of its metabolites has not been explored. We found that GSH-AITC and NAC-AITC effectively inhibit adipogenic differentiation of 3T3-L1 preadipocytes and suppress expression of PPAR-γ, C/EBPα, and FAS, which are up-regulated during adipogenesis. GSH-AITC and NAC-AITC also suppressed oleic acid-induced lipid accumulation and lipogenesis in hepatocytes. Our findings suggest that AITC is almost completely metabolized in the liver and rapidly excreted in urine through the mercapturic acid pathway following administration in rats. AITC metabolites may exert anti-obesity effects through suppression of adipogenesis or lipogenesis. PMID:26317351

Pharmacokinetics, Tissue Distribution, and Anti-Lipogenic/Adipogenic Effects of Allyl-Isothiocyanate Metabolites.

PubMed

Kim, Yang-Ji; Lee, Da-Hye; Ahn, Jiyun; Chung, Woo-Jae; Jang, Young Jin; Seong, Ki-Seung; Moon, Jae-Hak; Ha, Tae Youl; Jung, Chang Hwa

2015-01-01

Allyl-isothiocyanate (AITC) is an organosulfur phytochemical found in abundance in common cruciferous vegetables such as mustard, wasabi, and cabbage. Although AITC is metabolized primarily through the mercapturic acid pathway, its exact pharmacokinetics remains undefined and the biological function of AITC metabolites is still largely unknown. In this study, we evaluated the inhibitory effects of AITC metabolites on lipid accumulation in vitro and elucidated the pharmacokinetics and tissue distribution of AITC metabolites in rats. We found that AITC metabolites generally conjugate with glutathione (GSH) or N-acetylcysteine (NAC) and are distributed in most organs and tissues. Pharmacokinetic analysis showed a rapid uptake and complete metabolism of AITC following oral administration to rats. Although AITC has been reported to exhibit anti-tumor activity in bladder cancer, the potential bioactivity of its metabolites has not been explored. We found that GSH-AITC and NAC-AITC effectively inhibit adipogenic differentiation of 3T3-L1 preadipocytes and suppress expression of PPAR-γ, C/EBPα, and FAS, which are up-regulated during adipogenesis. GSH-AITC and NAC-AITC also suppressed oleic acid-induced lipid accumulation and lipogenesis in hepatocytes. Our findings suggest that AITC is almost completely metabolized in the liver and rapidly excreted in urine through the mercapturic acid pathway following administration in rats. AITC metabolites may exert anti-obesity effects through suppression of adipogenesis or lipogenesis.

Studies of peripheral thyroxine distribution in thyrotoxicosis and hypothyroidism.

PubMed

Nicoloff, J T; Dowling, J T

1968-09-01

Compartmental analysis of the peripheral distribution of labeled thyroxine was applied to various groups of subjects with thyrotoxicosis and hypothyroidism. It was observed that the hepatic incorporation of thyroxine was augmented in subjects with Graves' disease when compared to non-Graves' disease control groups at all levels of thyroid function. Decreased values of hepatic incorporation occurred in primary hypothyroid subjects. These lowered values were not acutely corrected by elevation of the serum thyroxine level, but were observed to be rectified after several months' therapy with exogenous thyroid hormone. These alterations of the hepatic thyroxine-(131)I incorporation were independently verified by direct quantitative liver scintiscan determinations. Employing a dual thyroxine tracer system, we were able to demonstrate that during the early phases of equilibration of a tracer dose of thyroxine, alterations in the rate of deiodination were observed to be present in the various thyroid disease states. Increased deiodination rates were found in subjects with Graves' disease and the reverse was noted in patients with primary hypothyroidism. Kinetic analysis of thyroxine compartmental distribution during this early phase of equilibration of a labeled thyroxine tracer indicated that the primary tissue uptake occurred in the liver. These findings supported the contention that the amount of labeled thyroxine incorporated in the liver may be directly related to the deiodination rate of thyroxine by that organ. The pathogenetic basis of these alterations is presently unknown.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits.

PubMed

Fu, Liya; Wang, You-Gan

2011-02-15

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which clearly demonstrates the advantages of the rank regression models.

Modelling the electric field and the current density generated by cerebellar transcranial DC stimulation in humans.

PubMed

Parazzini, Marta; Rossi, Elena; Ferrucci, Roberta; Liorni, Ilaria; Priori, Alberto; Ravazzani, Paolo

2014-03-01

Transcranial Direct Current Stimulation (tDCS) over the cerebellum (or cerebellar tDCS) modulates working memory, changes cerebello-brain interaction, and affects locomotion in humans. Also, the use of tDCS has been proposed for the treatment of disorders characterized by cerebellar dysfunction. Nonetheless, the electric field (E) and current density (J) spatial distributions generated by cerebellar tDCS are unknown. This work aimed to estimate E and J distributions during cerebellar tDCS. Computational electromagnetics techniques were applied in three human realistic models of different ages and gender. The stronger E and J occurred mainly in the cerebellar cortex, with some spread (up to 4%) toward the occipital cortex. Also, changes by ±1cm in the position of the active electrode resulted in a small effect (up to 4%) in the E and J spatial distribution in the cerebellum. Finally, the E and J spreads to the brainstem and the heart were negligible, thus further supporting the safety of this technique. Despite inter-individual differences, our modeling study confirms that the cerebellum is the structure mainly involved by cerebellar tDCS. Modeling approach reveals that during cerebellar tDCS the current spread to other structures outside the cerebellum is unlike to produce functional effects. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Eco-Evolutionary Dynamics of Episomes among Ecologically Cohesive Bacterial Populations

DOE PAGES

Xue, Hong; Cordero, Otto X.; Camas, Francisco M.; ...

2015-05-05

Although plasmids and other episomes are recognized as key players in horizontal gene transfer among microbes, their diversity and dynamics among ecologically structured host populations in the wild remain poorly understood. Here, we show that natural populations of marine Vibrionaceae bacteria host large numbers of families of episomes, consisting of plasmids and a surprisingly high fraction of plasmid-like temperate phages. Episomes are unevenly distributed among host populations, and contrary to the notion that high-density communities in biofilms act as hot spots of gene transfer, we identified a strong bias for episomes to occur in free-living as opposed to particle-attached cells.more » Mapping of episomal families onto host phylogeny shows that, with the exception of all phage and a few plasmid families, most are of recent evolutionary origin and appear to have spread rapidly by horizontal transfer. Such high eco-evolutionary turnover is particularly surprising for plasmids that are, based on previously suggested categorization, putatively nontransmissible, indicating that this type of plasmid is indeed frequently transferred by currently unknown mechanisms. Finally, analysis of recent gene transfer among plasmids reveals a network of extensive exchange connecting nearly all episomes. Genes functioning in plasmid transfer and maintenance are frequently exchanged, suggesting that plasmids can be rapidly transformed from one category to another. The broad distribution of episomes among distantly related hosts and the observed promiscuous recombination patterns show how episomes can offer their hosts rapid assembly and dissemination of novel functions.« less

Failure of lysosome clustering and positioning in the juxtanuclear region in cells deficient in rapsyn

PubMed Central

Aittaleb, Mohamed; Chen, Po-Ju; Akaaboune, Mohammed

2015-01-01

ABSTRACT Rapsyn, a scaffold protein, is required for the clustering of acetylcholine receptors (AChRs) at contacts between motor neurons and differentiating muscle cells. Rapsyn is also expressed in cells that do not express AChRs. However, its function in these cells remains unknown. Here, we show that rapsyn plays an AChR-independent role in organizing the distribution and mobility of lysosomes. In cells devoid of AChRs, rapsyn selectively induces the clustering of lysosomes at high density in the juxtanuclear region without affecting the distribution of other intracellular organelles. However, when the same cells overexpress AChRs, rapsyn is recruited away from lysosomes to colocalize with AChR clusters on the cell surface. In rapsyn-deficient (Rapsn−/−) myoblasts or cells overexpressing rapsyn mutants, lysosomes are scattered within the cell and highly dynamic. The increased mobility of lysosomes in Rapsn−/− cells is associated with a significant increase in lysosomal exocytosis, as evidenced by increased release of lysosomal enzymes and plasma membrane damage when cells were challenged with the bacterial pore-forming toxin streptolysin-O. These findings uncover a new link between rapsyn, lysosome positioning, exocytosis and plasma membrane integrity. PMID:26330529

Global biogeography of Prochlorococcus genome diversity in the surface ocean.

PubMed

Kent, Alyssa G; Dupont, Chris L; Yooseph, Shibu; Martiny, Adam C

2016-08-01

Prochlorococcus, the smallest known photosynthetic bacterium, is abundant in the ocean's surface layer despite large variation in environmental conditions. There are several genetically divergent lineages within Prochlorococcus and superimposed on this phylogenetic diversity is extensive gene gain and loss. The environmental role in shaping the global ocean distribution of genome diversity in Prochlorococcus is largely unknown, particularly in a framework that considers the vertical and lateral mechanisms of evolution. Here we show that Prochlorococcus field populations from a global circumnavigation harbor extensive genome diversity across the surface ocean, but this diversity is not randomly distributed. We observed a significant correspondence between phylogenetic and gene content diversity, including regional differences in both phylogenetic composition and gene content that were related to environmental factors. Several gene families were strongly associated with specific regions and environmental factors, including the identification of a set of genes related to lower nutrient and temperature regions. Metagenomic assemblies of natural Prochlorococcus genomes reinforced this association by providing linkage of genes across genomic backbones. Overall, our results show that the phylogeography in Prochlorococcus taxonomy is echoed in its genome content. Thus environmental variation shapes the functional capabilities and associated ecosystem role of the globally abundant Prochlorococcus.

Amyloid precursor protein at node of Ranvier modulates nodal formation

PubMed Central

Xu, De-En; Zhang, Wen-Min; Yang, Zara Zhuyun; Zhu, Hong-Mei; Yan, Ke; Li, Shao; Bagnard, Dominique; Dawe, Gavin S; Ma, Quan-Hong; Xiao, Zhi-Cheng

2014-01-01

Amyloid precursor protein (APP), commonly associated with Alzheimer disease, is upregulated and distributes evenly along the injured axons, and therefore, also known as a marker of demyelinating axonal injury and axonal degeneration. However, the physiological distribution and function of APP along myelinated axons was unknown. We report that APP aggregates at nodes of Ranvier (NOR) in the myelinated central nervous system (CNS) axons but not in the peripheral nervous system (PNS). At CNS NORs, APP expression co-localizes with tenascin-R and is flanked by juxtaparanodal potassium channel expression demonstrating that APP localized to NOR. In APP-knockout (KO) mice, nodal length is significantly increased, while sodium channels are still clustered at NORs. Moreover, APP KO and APP-overexpressing transgenic (APP TG) mice exhibited a decreased and an increased thickness of myelin in spinal cords, respectively, although the changes are limited in comparison to their littermate WT mice. The thickness of myelin in APP KO sciatic nerve also increased in comparison to that in WT mice. Our observations indicate that APP acts as a novel component at CNS NORs, modulating nodal formation and has minor effects in promoting myelination. PMID:25482638

Distributed Lag Models: Examining Associations between the Built Environment and Health

PubMed Central

Baek, Jonggyu; Sánchez, Brisa N.; Berrocal, Veronica J.; Sanchez-Vaznaugh, Emma V.

2016-01-01

Built environment factors constrain individual level behaviors and choices, and thus are receiving increasing attention to assess their influence on health. Traditional regression methods have been widely used to examine associations between built environment measures and health outcomes, where a fixed, pre-specified spatial scale (e.g., 1 mile buffer) is used to construct environment measures. However, the spatial scale for these associations remains largely unknown and misspecifying it introduces bias. We propose the use of distributed lag models (DLMs) to describe the association between built environment features and health as a function of distance from the locations of interest and circumvent a-priori selection of a spatial scale. Based on simulation studies, we demonstrate that traditional regression models produce associations biased away from the null when there is spatial correlation among the built environment features. Inference based on DLMs is robust under a range of scenarios of the built environment. We use this innovative application of DLMs to examine the association between the availability of convenience stores near California public schools, which may affect children’s dietary choices both through direct access to junk food and exposure to advertisement, and children’s body mass index z-scores (BMIz). PMID:26414942

Membrane vesicles in sea water: heterogeneous DNA content and implications for viral abundance estimates

PubMed Central

Biller, Steven J; McDaniel, Lauren D; Breitbart, Mya; Rogers, Everett; Paul, John H; Chisholm, Sallie W

2017-01-01

Diverse microbes release membrane-bound extracellular vesicles from their outer surfaces into the surrounding environment. Vesicles are found in numerous habitats including the oceans, where they likely have a variety of functional roles in microbial ecosystems. Extracellular vesicles are known to contain a range of biomolecules including DNA, but the frequency with which DNA is packaged in vesicles is unknown. Here, we examine the quantity and distribution of DNA associated with vesicles released from five different bacteria. The average quantity of double-stranded DNA and size distribution of DNA fragments released within vesicles varies among different taxa. Although some vesicles contain sufficient DNA to be visible following staining with the SYBR fluorescent DNA dyes typically used to enumerate viruses, this represents only a small proportion (<0.01–1%) of vesicles. Thus DNA is packaged heterogeneously within vesicle populations, and it appears that vesicles are likely to be a minor component of SYBR-visible particles in natural sea water compared with viruses. Consistent with this hypothesis, chloroform treatment of coastal and offshore seawater samples reveals that vesicles increase epifluorescence-based particle (viral) counts by less than an order of magnitude and their impact is variable in space and time. PMID:27824343

Online cross-validation-based ensemble learning.

PubMed

Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

2018-01-30

Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and, as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Exact analytical formulae for linearly distributed vortex and source sheets in uence computation in 2D vortex methods

NASA Astrophysics Data System (ADS)

Kuzmina, K. S.; Marchevsky, I. K.; Ryatina, E. P.

2017-11-01

We consider the methodology of numerical schemes development for two-dimensional vortex method. We describe two different approaches to deriving integral equation for unknown vortex sheet intensity. We simulate the velocity of the surface line of an airfoil as the influence of attached vortex and source sheets. We consider a polygonal approximation of the airfoil and assume intensity distributions of free and attached vortex sheets and attached source sheet to be approximated with piecewise constant or piecewise linear (continuous or discontinuous) functions. We describe several specific numerical schemes that provide different accuracy and have a different computational cost. The study shows that a Galerkin-type approach to solving boundary integral equation requires computing several integrals and double integrals over the panels. We obtain exact analytical formulae for all the necessary integrals, which makes it possible to raise significantly the accuracy of vortex sheet intensity computation and improve the quality of velocity and vorticity field representation, especially in proximity to the surface line of the airfoil. All the formulae are written down in the invariant form and depend only on the geometric relationship between the positions of the beginnings and ends of the panels.

Nonspecific uptake and homeostasis drive the oceanic cadmium cycle

NASA Astrophysics Data System (ADS)

Horner, Tristan J.; Lee, Renee B. Y.; Henderson, Gideon M.; Rickaby, Rosalind E. M.

2013-02-01

The global marine distributions of Cd and phosphate are closely correlated, which has led to Cd being considered as a marine micronutrient, despite its toxicity to life. The explanation for this nutrient-like behavior is unknown because there is only one identified biochemical function for Cd, an unusual Cd/Zn carbonic anhydrase. Recent developments in Cd isotope mass spectrometry have revealed that Cd uptake by phytoplankton causes isotopic fractionation in the open ocean and in culture. Here we investigate the physiochemical pathways that fractionate Cd isotopes by performing subcellular Cd isotope analysis on genetically modified microorganisms. We find that expression of the Cd/Zn carbonic anhydrase makes no difference to the Cd isotope composition of whole cells. Instead, a large proportion of the Cd is partitioned into cell membranes with a similar direction and magnitude of Cd isotopic fractionation to that seen in surface seawater. This observation is well explained if Cd is mistakenly imported with other divalent metals and subsequently managed by binding within the cell to avoid toxicity. This process may apply to other divalent metals, whereby nonspecific uptake and subsequent homeostasis may contribute to elemental and isotopic distributions in seawater, even for elements commonly considered as micronutrients.

The Origin and Evolution of Baeyer—Villiger Monooxygenases (BVMOs): An Ancestral Family of Flavin Monooxygenases

PubMed Central

Mascotti, Maria Laura; Lapadula, Walter Jesús; Juri Ayub, Maximiliano

2015-01-01

The Baeyer—Villiger Monooxygenases (BVMOs) are enzymes belonging to the “Class B” of flavin monooxygenases and are capable of performing exquisite selective oxidations. These enzymes have been studied from a biotechnological perspective, but their physiological substrates and functional roles are widely unknown. Here, we investigated the origin, taxonomic distribution and evolutionary history of the BVMO genes. By using in silico approaches, 98 BVMO encoding genes were detected in the three domains of life: Archaea, Bacteria and Eukarya. We found evidence for the presence of these genes in Metazoa (Hydra vulgaris, Oikopleura dioica and Adineta vaga) and Haptophyta (Emiliania huxleyi) for the first time. Furthermore, a search for other “Class B” monooxygenases (flavoprotein monooxygenases –FMOs – and N-hydroxylating monooxygenases – NMOs) was conducted. These sequences were also found in the three domains of life. Phylogenetic analyses of all “Class B” monooxygenases revealed that NMOs and BVMOs are monophyletic, whereas FMOs form a paraphyletic group. Based on these results, we propose that BVMO genes were already present in the last universal common ancestor (LUCA) and their current taxonomic distribution is the result of differential duplication and loss of paralogous genes. PMID:26161776

Could thermal sensitivity of mitochondria determine species distribution in a changing climate?

PubMed

Iftikar, Fathima I; MacDonald, Julia R; Baker, Daniel W; Renshaw, Gillian M C; Hickey, Anthony J R

2014-07-01

For many aquatic species, the upper thermal limit (Tmax) and the heart failure temperature (THF) are only a few degrees away from the species' current environmental temperatures. While the mechanisms mediating temperature-induced heart failure (HF) remain unresolved, energy flow and/or oxygen supply disruptions to cardiac mitochondria may be impacted by heat stress. Recent work using a New Zealand wrasse (Notolabrus celidotus) found that ATP synthesis capacity of cardiac mitochondria collapses prior to T(HF). However, whether this effect is limited to one species from one thermal habitat remains unknown. The present study confirmed that cardiac mitochondrial dysfunction contributes to heat stress-induced HF in two additional wrasses that occupy cold temperate (Notolabrus fucicola) and tropical (Thalassoma lunare) habitats. With exposure to heat stress, T. lunare had the least scope to maintain heart function with increasing temperature. Heat-exposed fish of all species showed elevated plasma succinate, and the heart mitochondria from the cold temperate N. fucicola showed decreased phosphorylation efficiencies (depressed respiratory control ratio, RCR), cytochrome c oxidase (CCO) flux and electron transport system (ETS) flux. In situ assays conducted across a range of temperatures using naive tissues showed depressed complex II (CII) and CCO capacity, limited ETS reserve capacities and lowered efficiencies of pyruvate uptake in T. lunare and N. celidotus. Notably, alterations of mitochondrial function were detectable at saturating oxygen levels, indicating that cardiac mitochondrial insufficiency can occur prior to HF without oxygen limitation. Our data support the view that species distribution may be related to the thermal limits of mitochondrial stability and function, which will be important as oceans continue to warm. © 2014. Published by The Company of Biologists Ltd.

Modeling Pair Distribution Functions of Rare-Earth Phosphate Glasses Using Principal Component Analysis.

PubMed

Cole, Jacqueline M; Cheng, Xie; Payne, Michael C

2016-11-07

The use of principal component analysis (PCA) to statistically infer features of local structure from experimental pair distribution function (PDF) data is assessed on a case study of rare-earth phosphate glasses (REPGs). Such glasses, codoped with two rare-earth ions (R and R') of different sizes and optical properties, are of interest to the laser industry. The determination of structure-property relationships in these materials is an important aspect of their technological development. Yet, realizing the local structure of codoped REPGs presents significant challenges relative to their singly doped counterparts; specifically, R and R' are difficult to distinguish in terms of establishing relative material compositions, identifying atomic pairwise correlation profiles in a PDF that are associated with each ion, and resolving peak overlap of such profiles in PDFs. This study demonstrates that PCA can be employed to help overcome these structural complications, by statistically inferring trends in PDFs that exist for a restricted set of experimental data on REPGs, and using these as training data to predict material compositions and PDF profiles in unknown codoped REPGs. The application of these PCA methods to resolve individual atomic pairwise correlations in t(r) signatures is also presented. The training methods developed for these structural predictions are prevalidated by testing their ability to reproduce known physical phenomena, such as the lanthanide contraction, on PDF signatures of the structurally simpler singly doped REPGs. The intrinsic limitations of applying PCA to analyze PDFs relative to the quality control of source data, data processing, and sample definition, are also considered. While this case study is limited to lanthanide-doped REPGs, this type of statistical inference may easily be extended to other inorganic solid-state materials and be exploited in large-scale data-mining efforts that probe many t(r) functions.

Understanding genetic control of root system architecture in soybean: Insights into the genetic basis of lateral root number.

PubMed

Prince, Silvas J; Valliyodan, Babu; Ye, Heng; Yang, Ming; Tai, Shuaishuai; Hu, Wushu; Murphy, Mackensie; Durnell, Lorellin A; Song, Li; Joshi, Trupti; Liu, Yang; Van de Velde, Jan; Vandepoele, Klaas; Grover Shannon, J; Nguyen, Henry T

2018-05-10

Developing crops with better root systems is a promising strategy to ensure productivity in both optimum and stress environments. Root system architectural (RSA) traits in 397 soybean accessions were characterized and a high-density single nucleotide polymorphisms (SNP) based genome-wide association study was performed to identify the underlying genes associated with root structure. SNPs associated with root architectural traits specific to landraces and elite germplasm pools were detected. Four loci were detected in landraces for lateral root number (LRN) and distribution of root thickness in diameter class I with a major locus on chromosome 16. This major loci was detected in the coding region of unknown protein, and subsequent analyses demonstrated that root traits are affected with mutated haplotypes of the gene. In elite germplasm pool, three significant SNPs in alanine-glyoxalate aminotransferase, Leucine-Rich Repeat receptor/No apical meristem and unknown functional genes were found to govern multiple traits including root surface area and volume. However, no major loci were detected for LRN in elite germplasm. Nucleotide diversity analysis found evidence of selective sweeps around the landraces LRN gene. Soybean accessions with minor and mutated allelic variants of LRN gene were found to perform better in both water-limited and optimal field conditions. This article is protected by copyright. All rights reserved.

Automated genomic context analysis and experimental validation platform for discovery of prokaryote transcriptional regulator functions

DOE PAGES

Martí-Arbona, Ricardo; Mu, Fangping; Nowak-Lovato, Kristy L.; ...

2014-12-18

In this study, the clustering of genes in a pathway and the co-location of functionally related genes is widely recognized in prokaryotes. We used these characteristics to predict the metabolic involvement for a Transcriptional Regulator (TR) of unknown function, identified and confirmed its biological activity. software tool that identifies the genes encoded within a defined genomic neighborhood for the subject TR and its homologs was developed. The output lists of genes in the genetic neighborhoods, their annotated functions, the reactants/products, and identifies the metabolic pathway in which the encoded-proteins function. When a set of TRs of known function was analyzed,more » we observed that their homologs frequently had conserved genomic neighborhoods that co-located the metabolically related genes regulated by the subject TR. We postulate that TR effectors are metabolites in the identified pathways; indeed the known effectors were present. We analyzed Bxe_B3018 from Burkholderia xenovorans, a TR of unknown function and predicted that this TR was related to the glycine, threonine and serine degradation. We tested the binding of metabolites in these pathways and for those that bound, their ability to modulate TR binding to its specific DNA operator sequence. Using rtPCR, we confirmed that methylglyoxal was an effector of Bxe_3018. These studies provide the proof of concept and validation of a systematic approach to the discovery of the biological activity for proteins of unknown function, in this case a TR. Bxe_B3018 is a methylglyoxal responsive TR that controls the expression of an operon composed of a putative efflux system.« less

Multivariate analysis applied to the study of spatial distributions found in drug-eluting stent coatings by confocal Raman microscopy.

PubMed

Balss, Karin M; Long, Frederick H; Veselov, Vladimir; Orana, Argjenta; Akerman-Revis, Eugena; Papandreou, George; Maryanoff, Cynthia A

2008-07-01

Multivariate data analysis was applied to confocal Raman measurements on stents coated with the polymers and drug used in the CYPHER Sirolimus-eluting Coronary Stents. Partial least-squares (PLS) regression was used to establish three independent calibration curves for the coating constituents: sirolimus, poly(n-butyl methacrylate) [PBMA], and poly(ethylene-co-vinyl acetate) [PEVA]. The PLS calibrations were based on average spectra generated from each spatial location profiled. The PLS models were tested on six unknown stent samples to assess accuracy and precision. The wt % difference between PLS predictions and laboratory assay values for sirolimus was less than 1 wt % for the composite of the six unknowns, while the polymer models were estimated to be less than 0.5 wt % difference for the combined samples. The linearity and specificity of the three PLS models were also demonstrated with the three PLS models. In contrast to earlier univariate models, the PLS models achieved mass balance with better accuracy. This analysis was extended to evaluate the spatial distribution of the three constituents. Quantitative bitmap images of drug-eluting stent coatings are presented for the first time to assess the local distribution of components.

Identification and Characterization of Putative Integron-Like Elements of the Heavy-Metal-Hypertolerant Strains of Pseudomonas spp.

PubMed

Ciok, Anna; Adamczuk, Marcin; Bartosik, Dariusz; Dziewit, Lukasz

2016-11-28

Pseudomonas strains isolated from the heavily contaminated Lubin copper mine and Zelazny Most post-flotation waste reservoir in Poland were screened for the presence of integrons. This analysis revealed that two strains carried homologous DNA regions composed of a gene encoding a DNA_BRE_C domain-containing tyrosine recombinase (with no significant sequence similarity to other integrases of integrons) plus a three-component array of putative integron gene cassettes. The predicted gene cassettes encode three putative polypeptides with homology to (i) transmembrane proteins, (ii) GCN5 family acetyltransferases, and (iii) hypothetical proteins of unknown function (homologous proteins are encoded by the gene cassettes of several class 1 integrons). Comparative sequence analyses identified three structural variants of these novel integron-like elements within the sequenced bacterial genomes. Analysis of their distribution revealed that they are found exclusively in strains of the genus Pseudomonas .