Modeling of EUV photoresists with a resist point spread function
International Nuclear Information System (INIS)
Cain, Jason P.; Naulleau, Patrick; Spanos, Costas J.
2005-01-01
Extreme ultraviolet (EUV) lithography is under development for possible deployment at the 32-nm technology node. One active area of research in this field is the development of photoresists that can meet the stringent requirements (high resolution, high sensitivity, low LER, etc.) of lithography in this regime. In order to facilitate research in this and other areas related to EUV lithography, a printing station based upon the 0.3-NA Micro Exposure Tool (MET) optic was established at the Advanced Light Source, a synchrotron facility at Lawrence Berkeley National Laboratory. A resist modeling technique using a resist point spread function has been shown to have good agreement with experiments for certain EUV resists such as Shipley EUV-2D [2]. The resist point spread function is a two-dimensional function that, when convolved with the simulated aerial image for a given mask pattern and applied to a threshold function, gives a representation of the photoresist pattern remaining after development. The simplicity of this modeling approach makes it attractive for rapid modeling of photoresists for process development applications. In this work, the resist point spread functions for three current high-resolution EUV photoresists [Rohm and Haas EUV-2D, Rohm and Haas MET-1K (XP 3454C), and KRS] are extracted experimentally. This model is then used in combination with aerial image simulations (including effects of projection optic aberrations) to predict the resist pattern for a variety of test patterns. A comparison is made between these predictions and experimental results to evaluate the effectiveness of this modeling technique for newer high-resolution EUV resists
Plasmon point spread functions: How do we model plasmon-mediated emission processes?
Willets, Katherine A.
2014-02-01
A major challenge with studying plasmon-mediated emission events is the small size of plasmonic nanoparticles relative to the wavelength of light. Objects smaller than roughly half the wavelength of light will appear as diffraction-limited spots in far-field optical images, presenting a significant experimental challenge for studying plasmonic processes on the nanoscale. Super-resolution imaging has recently been applied to plasmonic nanosystems and allows plasmon-mediated emission to be resolved on the order of ˜5 nm. In super-resolution imaging, a diffraction-limited spot is fit to some model function in order to calculate the position of the emission centroid, which represents the location of the emitter. However, the accuracy of the centroid position strongly depends on how well the fitting function describes the data. This Perspective discusses the commonly used two-dimensional Gaussian fitting function applied to super-resolution imaging of plasmon-mediated emission, then introduces an alternative model based on dipole point spread functions. The two fitting models are compared and contrasted for super-resolution imaging of nanoparticle scattering/luminescence, surface-enhanced Raman scattering, and surface-enhanced fluorescence.
Point spread function modeling and image restoration for cone-beam CT
International Nuclear Information System (INIS)
Zhang Hua; Shi Yikai; Huang Kuidong; Xu Zhe
2015-01-01
X-ray cone-beam computed tomography (CT) has such notable features as high efficiency and precision, and is widely used in the fields of medical imaging and industrial non-destructive testing, but the inherent imaging degradation reduces the quality of CT images. Aimed at the problems of projection image degradation and restoration in cone-beam CT, a point spread function (PSF) modeling method is proposed first. The general PSF model of cone-beam CT is established, and based on it, the PSF under arbitrary scanning conditions can be calculated directly for projection image restoration without the additional measurement, which greatly improved the application convenience of cone-beam CT. Secondly, a projection image restoration algorithm based on pre-filtering and pre-segmentation is proposed, which can make the edge contours in projection images and slice images clearer after restoration, and control the noise in the equivalent level to the original images. Finally, the experiments verified the feasibility and effectiveness of the proposed methods. (authors)
International Nuclear Information System (INIS)
Pino, Francisco; Roé, Nuria; Aguiar, Pablo; Falcon, Carles; Ros, Domènec; Pavía, Javier
2015-01-01
Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Three methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery
Energy Technology Data Exchange (ETDEWEB)
Pino, Francisco [Unitat de Biofísica, Facultat de Medicina, Universitat de Barcelona, Barcelona 08036, Spain and Servei de Física Mèdica i Protecció Radiològica, Institut Català d’Oncologia, L’Hospitalet de Llobregat 08907 (Spain); Roé, Nuria [Unitat de Biofísica, Facultat de Medicina, Universitat de Barcelona, Barcelona 08036 (Spain); Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es [Fundación Ramón Domínguez, Complexo Hospitalario Universitario de Santiago de Compostela 15706, Spain and Grupo de Imagen Molecular, Instituto de Investigacións Sanitarias de Santiago de Compostela (IDIS), Galicia 15782 (Spain); Falcon, Carles; Ros, Domènec [Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain and CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona 08036 (Spain); Pavía, Javier [Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 080836 (Spain); CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona 08036 (Spain); and Servei de Medicina Nuclear, Hospital Clínic, Barcelona 08036 (Spain)
2015-02-15
Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Three methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery
Computation of the lateral and axial point spread functions in ...
Indian Academy of Sciences (India)
and ρ is the radial coordinate in the aperture plane (u, v). 2.2.1 Computation of the transverse APSF and its irradiance. The amplitude impulse response of the considered aperture or the amplitude point spread function (APSF) is computed by operating the Fourier transform upon the aperture represented by eq. (8) to obtain ...
Point-spread function in depleted and partially depleted CCDs
International Nuclear Information System (INIS)
Groom, D.E.; Eberhard, P.H.; Holland, S.E.; Levi, M.E.; Palaio, N.P.; Perlmutter, S.; Stover, R.J.; Wei, M.
1999-01-01
The point spread function obtainable in an astronomical instrument using CCD readout is limited by a number of factors, among them the lateral diffusion of charge before it is collected in the potential wells. They study this problem both theoretically and experimentally, with emphasis on the thick CCDs on high-resistivity n-type substrates being developed at Lawrence Berkeley National Laboratory
Point spread functions and deconvolution of ultrasonic images.
Dalitz, Christoph; Pohle-Fröhlich, Regina; Michalk, Thorsten
2015-03-01
This article investigates the restoration of ultrasonic pulse-echo C-scan images by means of deconvolution with a point spread function (PSF). The deconvolution concept from linear system theory (LST) is linked to the wave equation formulation of the imaging process, and an analytic formula for the PSF of planar transducers is derived. For this analytic expression, different numerical and analytic approximation schemes for evaluating the PSF are presented. By comparing simulated images with measured C-scan images, we demonstrate that the assumptions of LST in combination with our formula for the PSF are a good model for the pulse-echo imaging process. To reconstruct the object from a C-scan image, we compare different deconvolution schemes: the Wiener filter, the ForWaRD algorithm, and the Richardson-Lucy algorithm. The best results are obtained with the Richardson-Lucy algorithm with total variation regularization. For distances greater or equal twice the near field distance, our experiments show that the numerically computed PSF can be replaced with a simple closed analytic term based on a far field approximation.
Graafsma, H; de Vries, R.Y.
1999-01-01
The maximum-entropy method (MEM) has been applied for the deconvolution of the point-spread function (PSF) of two-dimensional X-ray detectors. The method is robust, model and image independent, and only depends on the correct description of the two-dimensional point-spread function and gain factor
Aberrations of the point spread function of a multimode fiber due to partial mode excitation
Descloux, Adrien; Amitonova, Lyubov; Pinkse, Pepijn Willemszoon Harry
2016-01-01
We investigate the point spread function of a multimode fiber. The distortion of the focal spot created on the fiber output facet is studied for a variety of the parameters. We develop a theoretical model of wavefront shaping through a multimode fiber and use it to confirm our experimental results
Aberrations of the point spread function of a multimode fiber due to partial mode excitation
Descloux, Adrien; Amitonova, Lyubov V.; Pinkse, Pepijn W. H.
2016-08-01
We investigate the point spread function of a multimode fiber. The distortion of the focal spot created on the fiber output facet is studied for a variety of the parameters. We develop a theoretical model of wavefront shaping through a multimode fiber and use it to confirm our experimental results and analyze the nature of the focal distortions. We show that aberration-free imaging with a large field of view can be achieved by using an appropriate number of segments on the spatial light modulator during the wavefront-shaping procedure. The results describe aberration limits for imaging with multimode fibers as in, e.g., microendoscopy.
Estimation Methods of the Point Spread Function Axial Position: A Comparative Computational Study
Directory of Open Access Journals (Sweden)
Javier Eduardo Diaz Zamboni
2017-01-01
Full Text Available The precise knowledge of the point spread function is central for any imaging system characterization. In fluorescence microscopy, point spread function (PSF determination has become a common and obligatory task for each new experimental device, mainly due to its strong dependence on acquisition conditions. During the last decade, algorithms have been developed for the precise calculation of the PSF, which fit model parameters that describe image formation on the microscope to experimental data. In order to contribute to this subject, a comparative study of three parameter estimation methods is reported, namely: I-divergence minimization (MIDIV, maximum likelihood (ML and non-linear least square (LSQR. They were applied to the estimation of the point source position on the optical axis, using a physical model. Methods’ performance was evaluated under different conditions and noise levels using synthetic images and considering success percentage, iteration number, computation time, accuracy and precision. The main results showed that the axial position estimation requires a high SNR to achieve an acceptable success level and higher still to be close to the estimation error lower bound. ML achieved a higher success percentage at lower SNR compared to MIDIV and LSQR with an intrinsic noise source. Only the ML and MIDIV methods achieved the error lower bound, but only with data belonging to the optical axis and high SNR. Extrinsic noise sources worsened the success percentage, but no difference was found between noise sources for the same method for all methods studied.
Fast and accurate three-dimensional point spread function computation for fluorescence microscopy.
Li, Jizhou; Xue, Feng; Blu, Thierry
2017-06-01
The point spread function (PSF) plays a fundamental role in fluorescence microscopy. A realistic and accurately calculated PSF model can significantly improve the performance in 3D deconvolution microscopy and also the localization accuracy in single-molecule microscopy. In this work, we propose a fast and accurate approximation of the Gibson-Lanni model, which has been shown to represent the PSF suitably under a variety of imaging conditions. We express the Kirchhoff's integral in this model as a linear combination of rescaled Bessel functions, thus providing an integral-free way for the calculation. The explicit approximation error in terms of parameters is given numerically. Experiments demonstrate that the proposed approach results in a significantly smaller computational time compared with current state-of-the-art techniques to achieve the same accuracy. This approach can also be extended to other microscopy PSF models.
Point-spread functions of a polarizing microscope equipped with high-numerical-aperture lenses.
Oldenbourg, R; Török, P
2000-12-01
In an effort to establish the imaging properties of a new type of polarized-light microscope, we recorded images of small, uniaxial, birefringent crystals. We show that the sequence of in-focus and out-of-focus images, the so-called point-spread function, of a submicroscopic crystal can be used to measure the orientation of its optic axis in three-dimensional space. By analogy to conoscopic images out-of-focus images reveal the changes in relative phase shift between the extraordinary and the ordinary rays that propagate at different directions through the crystal. We also present simulated images of a pointlike anisotropic scattering particle and compare these with our experimental findings. The theoretical model is based on a complete vectorial theory for partial coherent imaging by use of polarized light and high-numerical-aperture lenses.
Marian, A; Charrière, F; Colomb, T; Montfort, F; Kühn, J; Marquet, P; Depeursinge, C
2007-02-01
The point spread function is widely used to characterize the three-dimensional imaging capabilities of an optical system. Usually, attention is paid only to the intensity point spread function, whereas the phase point spread function is most often neglected because the phase information is not retrieved in noninterferometric imaging systems. However, phase point spread functions are needed to evaluate phase-sensitive imaging systems and we believe that phase data can play an essential role in the full aberrations' characterization. In this paper, standard diffraction models have been used for the computation of the complex amplitude point spread function. In particular, the Debye vectorial model has been used to compute the amplitude point spread function of x63/0.85 and x100/1.3 microscope objectives, exemplifying the phase point spread function specific for each polarization component of the electromagnetic field. The effect of aberrations on the phase point spread function is then analyzed for a microscope objective used under nondesigned conditions, by developing the Gibson model (Gibson & Lanni, 1991), modified to compute the three-dimensional amplitude point spread function in amplitude and phase. The results have revealed a novel anomalous phase behaviour in the presence of spherical aberration, providing access to the quantification of the aberrations. This work mainly proposes a method to measure the complex three-dimensional amplitude point spread function of an optical imaging system. The approach consists in measuring and interpreting the amplitude point spread function by evaluating in amplitude and phase the image of a single emitting point, a 60-nm-diameter tip of a Near Field Scanning Optical Microscopy fibre, with an original digital holographic experimental setup. A single hologram gives access to the transverse amplitude point spread function. The three-dimensional amplitude point spread function is obtained by performing an axial scan of the
Point-spread functions for backscattered imaging in the scanning electron microscope
Hennig, Philipp; Denk, Winfried
2007-12-01
One knows the imaging system's properties are central to the correct interpretation of any image. In a scanning electron microscope regions of different composition generally interact in a highly nonlinear way during signal generation. Using Monte Carlo simulations we found that in resin-embedded, heavy metal-stained biological specimens staining is sufficiently dilute to allow an approximately linear treatment. We then mapped point-spread functions for backscattered-electron contrast, for primary energies of 3 and 7 keV and for different detector specifications. The point-spread functions are surprisingly well confined (both laterally and in depth) compared even to the distribution of only those scattered electrons that leave the sample again.
Quantitative electron tomography: The effect of the three-dimensional point spread function
Energy Technology Data Exchange (ETDEWEB)
Heidari, Hamed [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Van den Broek, Wouter [Institut für Experimentelle Physik, Universität Ulm, Albert-Einstein-Allee 11, 89081 Ulm (Germany); Bals, Sara, E-mail: sara.bals@ua.ac.be [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium)
2013-12-15
The intensity levels in a three-dimensional (3D) reconstruction, obtained by electron tomography, can be influenced by several experimental imperfections. Such artifacts will hamper a quantitative interpretation of the results. In this paper, we will correct for artificial intensity variations by determining the 3D point spread function (PSF) of a tomographic reconstruction based on high angle annular dark field scanning transmission electron microscopy. The large tails of the PSF cause an underestimation of the intensity of smaller particles, which in turn hampers an accurate radius estimate. Here, the error introduced by the PSF is quantified and corrected a posteriori. - Highlights: • Intensity variations in 3D reconstructions hamper quantification of tomography data. • These variations are corrected based on the point spread function. • The approach can be considered as an optimized route to 3D quantification.
Lan, Fei; Jiang, Minlin; Tao, Quan; Wei, Fanan; Li, Guangyong
2017-03-01
A Kelvin probe force microscopy (KPFM) image is sometimes difficult to interpret because it is a blurred representation of the true surface potential (SP) distribution of the materials under test. The reason for the blurring is that KPFM relies on the detection of electrostatic force, which is a long-range force compared to other surface forces. Usually, KPFM imaging model is described as the convolution of the true SP distribution of the sample with an intrinsic point spread function (PSF) of the measurement system. To restore the true SP signals from the blurred ones, the intrinsic PSF of the system is needed. In this work, we present a way to experimentally calibrate the PSF of the KPFM system. Taking the actual probe shape and experimental parameters into consideration, this calibration method leads to a more accurate PSF than the ones obtained from simulations. Moreover, a nonlinear reconstruction algorithm based on total variation (TV) regularization is applied to KPFM measurement to reverse the blurring caused by PSF during KPFM imaging process; as a result, noises are reduced and the fidelity of SP signals is improved.
International Nuclear Information System (INIS)
Dmochowski, Jacek P; Bikson, Marom; Parra, Lucas C
2012-01-01
Rational development of transcranial current stimulation (tCS) requires solving the ‘forward problem’: the computation of the electric field distribution in the head resulting from the application of scalp currents. Derivation of forward models has represented a major effort in brain stimulation research, with model complexity ranging from spherical shells to individualized head models based on magnetic resonance imagery. Despite such effort, an easily accessible benchmark head model is greatly needed when individualized modeling is either undesired (to observe general population trends as opposed to individual differences) or unfeasible. Here, we derive a closed-form linear system which relates the applied current to the induced electric potential. It is shown that in the spherical harmonic (Fourier) domain, a simple scalar multiplication relates the current density on the scalp to the electric potential in the brain. Equivalently, the current density in the head follows as the spherical convolution between the scalp current distribution and the point spread function of the head, which we derive. Thus, if one knows the spherical harmonic representation of the scalp current (i.e. the electrode locations and current intensity to be employed), one can easily compute the resulting electric field at any point inside the head. Conversely, one may also readily determine the scalp current distribution required to generate an arbitrary electric field in the brain (the ‘backward problem’ in tCS). We demonstrate the simplicity and utility of the model with a series of characteristic curves which sweep across a variety of stimulation parameters: electrode size, depth of stimulation, head size and anode–cathode separation. Finally, theoretically optimal montages for targeting an infinitesimal point in the brain are shown. (paper)
Quantitative electron tomography: the effect of the three-dimensional point spread function.
Heidari, Hamed; Van den Broek, Wouter; Bals, Sara
2013-12-01
The intensity levels in a three-dimensional (3D) reconstruction, obtained by electron tomography, can be influenced by several experimental imperfections. Such artifacts will hamper a quantitative interpretation of the results. In this paper, we will correct for artificial intensity variations by determining the 3D point spread function (PSF) of a tomographic reconstruction based on high angle annular dark field scanning transmission electron microscopy. The large tails of the PSF cause an underestimation of the intensity of smaller particles, which in turn hampers an accurate radius estimate. Here, the error introduced by the PSF is quantified and corrected a posteriori. Copyright © 2013 Elsevier B.V. All rights reserved.
POINT-SPREAD FUNCTIONS FOR THE EXTREME-ULTRAVIOLET CHANNELS OF SDO/AIA TELESCOPES
International Nuclear Information System (INIS)
Poduval, B.; DeForest, C. E.; Schmelz, J. T.; Pathak, S.
2013-01-01
We present the stray-light point-spread functions (PSFs) and their inverses we characterized for the Atmospheric Imaging Assembly (AIA) EUV telescopes on board the Solar Dynamics Observatory (SDO) spacecraft. The inverse kernels are approximate inverses under convolution. Convolving the original Level 1 images with them produces images with improved stray-light characteristics. We demonstrate the usefulness of these PSFs by applying them to two specific cases: photometry and differential emission measure (DEM) analysis. The PSFs consist of a narrow Gaussian core, a diffraction component, and a diffuse component represented by the sum of a Gaussian-truncated Lorentzian and a shoulder Gaussian. We determined the diffraction term using the measured geometry of the diffraction pattern identified in flare images and the theoretically computed intensities of the principal maxima of the first few diffraction orders. To determine the diffuse component, we fitted its parameterized model using iterative forward-modeling of the lunar interior in the SDO/AIA images from the 2011 March 4 lunar transit. We find that deconvolution significantly improves the contrast in dark features such as miniature coronal holes, though the effect was marginal in bright features. On a percentage-scattering basis, the PSFs for SDO/AIA are better by a factor of two than that of the EUV telescope on board the Transition Region And Coronal Explorer mission. A preliminary analysis suggests that deconvolution alone does not affect DEM analysis of small coronal loop segments with suitable background subtraction. We include the derived PSFs and their inverses as supplementary digital materials.
POINT-SPREAD FUNCTIONS FOR THE EXTREME-ULTRAVIOLET CHANNELS OF SDO/AIA TELESCOPES
Energy Technology Data Exchange (ETDEWEB)
Poduval, B.; DeForest, C. E. [Southwest Research Institute, 1050 Walnut Street, Suite 300, Boulder, CO 80302 (United States); Schmelz, J. T.; Pathak, S., E-mail: bala@boulder.swri.edu [Physics Department, University of Memphis, Memphis, TN 38152 (United States)
2013-03-10
We present the stray-light point-spread functions (PSFs) and their inverses we characterized for the Atmospheric Imaging Assembly (AIA) EUV telescopes on board the Solar Dynamics Observatory (SDO) spacecraft. The inverse kernels are approximate inverses under convolution. Convolving the original Level 1 images with them produces images with improved stray-light characteristics. We demonstrate the usefulness of these PSFs by applying them to two specific cases: photometry and differential emission measure (DEM) analysis. The PSFs consist of a narrow Gaussian core, a diffraction component, and a diffuse component represented by the sum of a Gaussian-truncated Lorentzian and a shoulder Gaussian. We determined the diffraction term using the measured geometry of the diffraction pattern identified in flare images and the theoretically computed intensities of the principal maxima of the first few diffraction orders. To determine the diffuse component, we fitted its parameterized model using iterative forward-modeling of the lunar interior in the SDO/AIA images from the 2011 March 4 lunar transit. We find that deconvolution significantly improves the contrast in dark features such as miniature coronal holes, though the effect was marginal in bright features. On a percentage-scattering basis, the PSFs for SDO/AIA are better by a factor of two than that of the EUV telescope on board the Transition Region And Coronal Explorer mission. A preliminary analysis suggests that deconvolution alone does not affect DEM analysis of small coronal loop segments with suitable background subtraction. We include the derived PSFs and their inverses as supplementary digital materials.
Point-spread function in ghost imaging system with thermal light.
Gao, Yang; Bai, Yanfeng; Fu, Xiquan
2016-10-31
The point-spread function (PSF) is fundamental importance in estimating the imaging resolution in optical imaging systems. By using the Collins formula, a analytical imaging formula for ghost imaging system is obtained. The intensity fluctuation correlation function can be viewed as the convolution of the original object and a PSF. The imaging resolution is determined by the width of PSF. Based on the optical transfer matrix theory, we present the analytical formula describing the width of the PSF, by which one can estimate imaging resolution of a new-designed imaging scheme when compared with that of the existing imaging system. Several typical ghost imaging systems are chosen to verify experimentally our theoretical results.
Synthesis of atmospheric turbulence point spread functions by sparse and redundant representations
Hunt, Bobby R.; Iler, Amber L.; Bailey, Christopher A.; Rucci, Michael A.
2018-02-01
Atmospheric turbulence is a fundamental problem in imaging through long slant ranges, horizontal-range paths, or uplooking astronomical cases through the atmosphere. An essential characterization of atmospheric turbulence is the point spread function (PSF). Turbulence images can be simulated to study basic questions, such as image quality and image restoration, by synthesizing PSFs of desired properties. In this paper, we report on a method to synthesize PSFs of atmospheric turbulence. The method uses recent developments in sparse and redundant representations. From a training set of measured atmospheric PSFs, we construct a dictionary of "basis functions" that characterize the atmospheric turbulence PSFs. A PSF can be synthesized from this dictionary by a properly weighted combination of dictionary elements. We disclose an algorithm to synthesize PSFs from the dictionary. The algorithm can synthesize PSFs in three orders of magnitude less computing time than conventional wave optics propagation methods. The resulting PSFs are also shown to be statistically representative of the turbulence conditions that were used to construct the dictionary.
Point Spread Function (PSF) noise filter strategy for geiger mode LiDAR
Smith, O'Neil; Stark, Robert; Smith, Philip; St. Romain, Randall; Blask, Steven
2013-05-01
LiDAR is an efficient optical remote sensing technology that has application in geography, forestry, and defense. The effectiveness is often limited by signal-to-noise ratio (SNR). Geiger mode avalanche photodiode (APD) detectors are able to operate above critical voltage, and a single photoelectron can initiate the current surge, making the device very sensitive. These advantages come at the expense of requiring computationally intensive noise filtering techniques. Noise is a problem which affects the imaging system and reduces the capability. Common noise-reduction algorithms have drawbacks such as over aggressive filtering, or decimating in order to improve quality and performance. In recent years, there has been growing interest on GPUs (Graphics Processing Units) for their ability to perform powerful massive parallel processing. In this paper, we leverage this capability to reduce the processing latency. The Point Spread Function (PSF) filter algorithm is a local spatial measure that has been GPGPU accelerated. The idea is to use a kernel density estimation technique for point clustering. We associate a local likelihood measure with every point of the input data capturing the probability that a 3D point is true target-return photons or noise (background photons, dark-current). This process suppresses noise and allows for detection of outliers. We apply this approach to the LiDAR noise filtering problem for which we have recognized a speed-up factor of 30-50 times compared to traditional sequential CPU implementation.
Extended Nijboer-Zernike approach for the computation of optical point-spread functions.
Janssen, Augustus J E M
2002-05-01
New Bessel-series representations for the calculation of the diffraction integral are presented yielding the point-spread function of the optical system, as occurs in the Nijboer-Zernike theory of aberrations. In this analysis one can allow an arbitrary aberration and a defocus part. The representations are presented in full detail for the cases of coma and astigmatism. The analysis leads to stably converging results in the case of large aberration or defocus values, while the applicability of the original Nijboer-Zernike theory is limited mainly to wave-front deviations well below the value of one wavelength. Because of its intrinsic speed, the analysis is well suited to supplement or to replace numerical calculations that are currently used in the fields of (scanning) microscopy, lithography, and astronomy. In a companion paper [J. Opt. Soc. Am. A 19, 860 (2002)], physical interpretations and applications in a lithographic context are presented, a convergence analysis is given, and a comparison is made with results obtained by using a numerical package.
Influence of Signal-to-Noise Ratio and Point Spread Function on Limits of Super-Resolution
Pham, T.Q.; Vliet, L.J. van; Schutte, K.
2005-01-01
This paper presents a method to predict the limit of possible resolution enhancement given a sequence of low resolution images. Three important parameters influence the outcome of this limit: the total Point Spread Function (PSF), the Signal-to-Noise Ratio (SNR) and the number of input images.
Influence of signal-to-noise ratio and point spread function on limits of super-resolution
Pham, T.Q.; Van Vliet, L.; Schutte, K.
2005-01-01
This paper presents a method to predict the limit of possible resolution enhancement given a sequence of lowresolution images. Three important parameters influence the outcome of this limit: the total Point Spread Function (PSF), the Signal-to-Noise Ratio (SNR) and the number of input images.
Fu, Shihang; Zhang, Li; Hu, Yao; Ding, Xiang
2018-01-01
Confocal Raman Microscopy (CRM) has matured to become one of the most powerful instruments in analytical science because of its molecular sensitivity and high spatial resolution. Compared with conventional Raman Microscopy, CRM can perform three dimensions mapping of tiny samples and has the advantage of high spatial resolution thanking to the unique pinhole. With the wide application of the instrument, there is a growing requirement for the evaluation of the imaging performance of the system. Point-spread function (PSF) is an important approach to the evaluation of imaging capability of an optical instrument. Among a variety of measurement methods of PSF, the point source method has been widely used because it is easy to operate and the measurement results are approximate to the true PSF. In the point source method, the point source size has a significant impact on the final measurement accuracy. In this paper, the influence of the point source sizes on the measurement accuracy of PSF is analyzed and verified experimentally. A theoretical model of the lateral PSF for CRM is established and the effect of point source size on full-width at half maximum of lateral PSF is simulated. For long-term preservation and measurement convenience, PSF measurement phantom using polydimethylsiloxane resin, doped with different sizes of polystyrene microspheres is designed. The PSF of CRM with different sizes of microspheres are measured and the results are compared with the simulation results. The results provide a guide for measuring the PSF of the CRM.
Braat, Joseph; Dirksen, Peter; Janssen, Augustus J E M
2002-05-01
We assess the validity of an extended Nijboer-Zernike approach [J. Opt. Soc. Am. A 19, 849 (2002)], based on ecently found Bessel-series representations of diffraction integrals comprising an arbitrary aberration and a defocus part, for the computation of optical point-spread functions of circular, aberrated optical systems. These new series representations yield a flexible means to compute optical point-spread functions, both accurately and efficiently, under defocus and aberration conditions that seem to cover almost all cases of practical interest. Because of the analytical nature of the formulas, there are no discretization effects limiting the accuracy, as opposed to the more commonly used numerical packages based on strictly numerical integration methods. Instead, we have an easily managed criterion, expressed in the number of terms to be included in the Bessel-series representations, guaranteeing the desired accuracy. For this reason, the analytical method can also serve as a calibration tool for the numerically based methods. The analysis is not limited to pointlike objects but can also be used for extended objects under various illumination conditions. The calculation schemes are simple and permit one to trace the relative strength of the various interfering complex-amplitude terms that contribute to the final image intensity function.
Point spread functions of the T2 decay in k-space trajectories with long echo train.
Qin, Qin
2012-10-01
T(2) decay during long echo trains of magnetic resonance (MR) imaging pulse sequences is known to cause a blurring effect, due to the peak broadening of the point spread function (PSF). In contrast, the simultaneous amplitude-loss effect, led by the peak reduction of the PSF, has gained much less attention. In this report, we analyzed the PSFs of both the truncation and T(2) decay for Cartesian (linear profile ordering and low-high ordering) and spiral trajectories, respectively. Then, we derived simple formulas to characterize both the blurring and amplitude-loss effects, which are functions of the ratios of the echo train duration (T(k)) over T(2) (T(k)/T(2)). Signal-to-noise ratio (SNR) per unit time was thus analyzed considering both the amplitude-loss effect induced by the T(2) decay and the SNR gain from the long acquisition duration based on MR sampling theory. Optimum T(k)/T(2) ratios to achieve maximum SNR per unit time were 1.2 for the Cartesian trajectory and 0.8 for the spiral trajectory. Copyright © 2012 Elsevier Inc. All rights reserved.
Sung, Hsin-Yueh; Yang, Sidney S.; Chang, Horng
2008-08-01
Due to the application of mobile phone lens, the clear image for the different object distance from infinity to close-up creates a new bargaining. We found that wave-front coding applied to extend the depth of field may solve this problem. By means of using cubic phase mask (CPM), the blurred point-spread function (PSF) is substantially invariant to defocus. Thus, the ideal hyperfocal distance condition can be satisfied as long as the constant blurred image can eventually be recovered by a simple digital signal processing. In this paper, we propose a different design method of computational imaging lens for mobile phone up to ideal depth of field based on PSF focus invariance. Because of the difficulty for comparing the similarity to different PSFs, we define a new metric, of correlation, to evaluate and optimize the PSF similarity. Besides, by means of adding the anti-symmetric free form phase plate at aperture stop and using the correlation and Strehl ratio as the two major optimization operands, we can get the optimum phase plate surface to achieve the required extended depth of field (EDoF). The resulted PSF on focal plane is significantly invariant to object distance varying from infinity to 10cm.
Three-Dimensional Super-Resolution in Eukaryotic Cells Using the Double-Helix Point Spread Function.
Carr, Alexander R; Ponjavic, Aleks; Basu, Srinjan; McColl, James; Santos, Ana Mafalda; Davis, Simon; Laue, Ernest D; Klenerman, David; Lee, Steven F
2017-04-11
Single-molecule localization microscopy, typically based on total internal reflection illumination, has taken our understanding of protein organization and dynamics in cells beyond the diffraction limit. However, biological systems exist in a complicated three-dimensional environment, which has required the development of new techniques, including the double-helix point spread function (DHPSF), to accurately visualize biological processes. The application of the DHPSF approach has so far been limited to the study of relatively small prokaryotic cells. By matching the refractive index of the objective lens immersion liquid to that of the sample media, we demonstrate DHPSF imaging of up to 15-μm-thick whole eukaryotic cell volumes in three to five imaging planes. We illustrate the capabilities of the DHPSF by exploring large-scale membrane reorganization in human T cells after receptor triggering, and by using single-particle tracking to image several mammalian proteins, including membrane, cytoplasmic, and nuclear proteins in T cells and embryonic stem cells. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.
Nunes, Rita G; Hajnal, Joseph V
2018-01-03
Point spread function (PSF) mapping enables estimating the displacement fields required for distortion correction of echo planar images. Recently, a highly accelerated approach was introduced for estimating displacements from the phase slope of under-sampled PSF mapping data. Sampling schemes with varying spacing were proposed requiring stepwise phase unwrapping. To avoid unwrapping errors, an alternative approach applying the concept of finite rate of innovation to PSF mapping (FRIP) is introduced, using a pattern search strategy to locate the PSF peak, and the two methods are compared. Fully sampled PSF data was acquired in six subjects at 3.0 T, and distortion maps were estimated after retrospective under-sampling. The two methods were compared for both previously published and newly optimized sampling patterns. Prospectively under-sampled data were also acquired. Shift maps were estimated and deviations relative to the fully sampled reference map were calculated. The best performance was achieved when using FRIP with a previously proposed sampling scheme. The two methods were comparable for the remaining schemes. The displacement field errors tended to be lower as the number of samples or their spacing increased. A robust method for estimating the position of the PSF peak has been introduced.
Yamaguchi, Shotaro; Wagatsuma, Kei; Miwa, Kenta; Ishii, Kenji; Inoue, Kazumasa; Fukushi, Masahiro
2018-03-01
The Bayesian penalized-likelihood reconstruction algorithm (BPL), Q.Clear, uses relative difference penalty as a regularization function to control image noise and the degree of edge-preservation in PET images. The present study aimed to determine the effects of suppression on edge artifacts due to point-spread-function (PSF) correction using a Q.Clear. Spheres of a cylindrical phantom contained a background of 5.3 kBq/mL of [ 18 F]FDG and sphere-to-background ratios (SBR) of 16, 8, 4 and 2. The background also contained water and spheres containing 21.2 kBq/mL of [ 18 F]FDG as non-background. All data were acquired using a Discovery PET/CT 710 and were reconstructed using three-dimensional ordered-subset expectation maximization with time-of-flight (TOF) and PSF correction (3D-OSEM), and Q.Clear with TOF (BPL). We investigated β-values of 200-800 using BPL. The PET images were analyzed using visual assessment and profile curves, edge variability and contrast recovery coefficients were measured. The 38- and 27-mm spheres were surrounded by higher radioactivity concentration when reconstructed with 3D-OSEM as opposed to BPL, which suppressed edge artifacts. Images of 10-mm spheres had sharper overshoot at high SBR and non-background when reconstructed with BPL. Although contrast recovery coefficients of 10-mm spheres in BPL decreased as a function of increasing β, higher penalty parameter decreased the overshoot. BPL is a feasible method for the suppression of edge artifacts of PSF correction, although this depends on SBR and sphere size. Overshoot associated with BPL caused overestimation in small spheres at high SBR. Higher penalty parameter in BPL can suppress overshoot more effectively. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Ackermann, M. [Deutsches Elektronen Synchrotron DESY, D-15738 Zeuthen (Germany); Ajello, M.; Allafort, A.; Bechtol, K.; Bloom, E. D.; Borgland, A. W.; Bottacini, E.; Buehler, R. [W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States); Asano, K. [Interactive Research Center of Science, Tokyo Institute of Technology, Meguro City, Tokyo 152-8551 (Japan); Atwood, W. B. [Santa Cruz Institute for Particle Physics, Department of Physics and Department of Astronomy and Astrophysics, University of California at Santa Cruz, Santa Cruz, CA 95064 (United States); Baldini, L.; Bellazzini, R.; Bregeon, J. [Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa (Italy); Ballet, J. [Laboratoire AIM, CEA-IRFU/CNRS/Universite Paris Diderot, Service d' Astrophysique, CEA Saclay, F-91191 Gif sur Yvette (France); Barbiellini, G. [Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, I-34127 Trieste (Italy); Bastieri, D. [Istituto Nazionale di Fisica Nucleare, Sezione di Padova, I-35131 Padova (Italy); Bonamente, E. [Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, I-06123 Perugia (Italy); Brandt, T. J. [CNRS, IRAP, F-31028 Toulouse cedex 4 (France); Brigida, M. [Dipartimento di Fisica ' M. Merlin' dell' Universita e del Politecnico di Bari, I-70126 Bari (Italy); Bruel, P., E-mail: mdwood@slac.stanford.edu, E-mail: mar0@uw.edu [Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, F-91128 Palaiseau (France); and others
2013-03-01
The Large Area Telescope (LAT) on the Fermi Gamma-ray Space Telescope is a pair-conversion telescope designed to detect photons with energies from Almost-Equal-To 20 MeV to >300 GeV. The pre-launch response functions of the LAT were determined through extensive Monte Carlo simulations and beam tests. The point-spread function (PSF) characterizing the angular distribution of reconstructed photons as a function of energy and geometry in the detector is determined here from two years of on-orbit data by examining the distributions of {gamma} rays from pulsars and active galactic nuclei (AGNs). Above 3 GeV, the PSF is found to be broader than the pre-launch PSF. We checked for dependence of the PSF on the class of {gamma}-ray source and observation epoch and found none. We also investigated several possible spatial models for pair-halo emission around BL Lac AGNs. We found no evidence for a component with spatial extension larger than the PSF and set upper limits on the amplitude of halo emission in stacked images of low- and high-redshift BL Lac AGNs and the TeV blazars 1ES0229+200 and 1ES0347-121.
Shang, Kun; Cui, Bixiao; Ma, Jie; Shuai, Dongmei; Liang, Zhigang; Jansen, Floris; Zhou, Yun; Lu, Jie; Zhao, Guoguang
2017-08-01
Hybrid positron emission tomography/magnetic resonance (PET/MR) imaging is a new multimodality imaging technology that can provide structural and functional information simultaneously. The aim of this study was to investigate the effects of the time-of-flight (TOF) and point-spread function (PSF) on small lesions observed in PET/MR images from clinical patient image sets. This study evaluated 54 small lesions in 14 patients who had undergone 18 F-fluorodeoxyglucose (FDG) PET/MR. Lesions up to 30mm in diameter were included. The PET data were reconstructed with a baseline ordered-subsets expectation-maximization (OSEM) algorithm, OSEM+PSF, OSEM+TOF and OSEM+TOF+PSF. PET image quality and small lesions were visually evaluated and scored by a 3-point scale. A quantitative analysis was then performed using the mean and maximum standardized uptake value (SUV) of the small lesions (SUV mean and SUV max ). The lesions were divided into two groups according to the long-axis diameter and the location respectively and evaluated with each reconstruction algorithm. We also evaluated the background signal by analyzing the SUV liver . OSEM+TOF+PSF provided the highest value and OSEM+TOF or PSF showed a higher value than OSEM for the visual assessment and quantitative analysis. The combination of TOF and PSF increased the SUV mean by 26.6% and the SUV max by 30.0%. The SUV liver was not influenced by PSF or TOF. For the OSEM+TOF+PSF model, the change in SUV mean and SUV max for lesions PET/MR images, potentially improving small lesion detectability. Copyright © 2017 Elsevier B.V. All rights reserved.
Kidera, Daisuke; Kihara, Ken; Akamatsu, Go; Mikasa, Shohei; Taniguchi, Takafumi; Tsutsui, Yuji; Takeshita, Toshiki; Maebatake, Akira; Miwa, Kenta; Sasaki, Masayuki
2016-02-01
The aim of this study was to quantitatively evaluate the edge artifacts in PET images reconstructed using the point-spread function (PSF) algorithm at different sphere-to-background ratios of radioactivity (SBRs). We used a NEMA IEC body phantom consisting of six spheres with 37, 28, 22, 17, 13 and 10 mm in inner diameter. The background was filled with (18)F solution with a radioactivity concentration of 2.65 kBq/mL. We prepared three sets of phantoms with SBRs of 16, 8, 4 and 2. The PET data were acquired for 20 min using a Biograph mCT scanner. The images were reconstructed with the baseline ordered subsets expectation maximization (OSEM) algorithm, and with the OSEM + PSF correction model (PSF). For the image reconstruction, the number of iterations ranged from one to 10. The phantom PET image analyses were performed by a visual assessment of the PET images and profiles, a contrast recovery coefficient (CRC), which is the ratio of SBR in the images to the true SBR, and the percent change in the maximum count between the OSEM and PSF images (Δ % counts). In the PSF images, the spheres with a diameter of 17 mm or larger were surrounded by a dense edge in comparison with the OSEM images. In the spheres with a diameter of 22 mm or smaller, an overshoot appeared in the center of the spheres as a sharp peak in the PSF images in low SBR. These edge artifacts were clearly observed in relation to the increase of the SBR. The overestimation of the CRC was observed in 13 mm spheres in the PSF images. In the spheres with a diameter of 17 mm or smaller, the Δ % counts increased with an increasing SBR. The Δ % counts increased to 91 % in the 10-mm sphere at the SBR of 16. The edge artifacts in the PET images reconstructed using the PSF algorithm increased with an increasing SBR. In the small spheres, the edge artifact was observed as a sharp peak at the center of spheres and could result in overestimation.
Fan, Chong; Wu, Chaoyun; Li, Grand; Ma, Jun
2017-02-13
To solve the problem on inaccuracy when estimating the point spread function (PSF) of the ideal original image in traditional projection onto convex set (POCS) super-resolution (SR) reconstruction, this paper presents an improved POCS SR algorithm based on PSF estimation of low-resolution (LR) remote sensing images. The proposed algorithm can improve the spatial resolution of the image and benefit agricultural crop visual interpolation. The PSF of the highresolution (HR) image is unknown in reality. Therefore, analysis of the relationship between the PSF of the HR image and the PSF of the LR image is important to estimate the PSF of the HR image by using multiple LR images. In this study, the linear relationship between the PSFs of the HR and LR images can be proven. In addition, the novel slant knife-edge method is employed, which can improve the accuracy of the PSF estimation of LR images. Finally, the proposed method is applied to reconstruct airborne digital sensor 40 (ADS40) three-line array images and the overlapped areas of two adjacent GF-2 images by embedding the estimated PSF of the HR image to the original POCS SR algorithm. Experimental results show that the proposed method yields higher quality of reconstructed images than that produced by the blind SR method and the bicubic interpolation method.
Directory of Open Access Journals (Sweden)
Chong Fan
2017-02-01
Full Text Available To solve the problem on inaccuracy when estimating the point spread function (PSF of the ideal original image in traditional projection onto convex set (POCS super-resolution (SR reconstruction, this paper presents an improved POCS SR algorithm based on PSF estimation of low-resolution (LR remote sensing images. The proposed algorithm can improve the spatial resolution of the image and benefit agricultural crop visual interpolation. The PSF of the highresolution (HR image is unknown in reality. Therefore, analysis of the relationship between the PSF of the HR image and the PSF of the LR image is important to estimate the PSF of the HR image by using multiple LR images. In this study, the linear relationship between the PSFs of the HR and LR images can be proven. In addition, the novel slant knife-edge method is employed, which can improve the accuracy of the PSF estimation of LR images. Finally, the proposed method is applied to reconstruct airborne digital sensor 40 (ADS40 three-line array images and the overlapped areas of two adjacent GF-2 images by embedding the estimated PSF of the HR image to the original POCS SR algorithm. Experimental results show that the proposed method yields higher quality of reconstructed images than that produced by the blind SR method and the bicubic interpolation method.
International Nuclear Information System (INIS)
Nakamura, Akihiro; Tanizaki, Yasuo; Takeuchi, Miho
2014-01-01
While point spread function (PSF)-based positron emission tomography (PET) reconstruction effectively improves the spatial resolution and image quality of PET, it may damage its quantitative properties by producing edge artifacts, or Gibbs artifacts, which appear to cause overestimation of regional radioactivity concentration. In this report, we investigated how edge artifacts produce negative effects on the quantitative properties of PET. Experiments with a National Electrical Manufacturers Association (NEMA) phantom, containing radioactive spheres of a variety of sizes and background filled with cold air or water, or radioactive solutions, showed that profiles modified by edge artifacts were reproducible regardless of background μ values, and the effects of edge artifacts increased with increasing sphere-to-background radioactivity concentration ratio (S/B ratio). Profiles were also affected by edge artifacts in complex fashion in response to variable combinations of sphere sizes and S/B ratios; and central single-peak overestimation up to 50% was occasionally noted in relatively small spheres with high S/B ratios. Effects of edge artifacts were obscured in spheres with low S/B ratios. In patient images with a variety of focal lesions, areas of higher radioactivity accumulation were generally more enhanced by edge artifacts, but the effects were variable depending on the size of and accumulation in the lesion. PET images generated using PSF-based reconstruction are therefore not appropriate for the evaluation of SUV. (author)
Energy Technology Data Exchange (ETDEWEB)
Wang, Ruixing; Yang, LV [College of Optoelectronic Science and Engineering, National University of Defense Technology, Changsha, Hunan (China); Xu, Kele [College of Electronical Science and Engineering, National University of Defense Technology, Changsha, Hunan (China); Zhu, Li [Institute of Electrostatic and Electromagnetic Protection, Mechanical Engineering College, Shijiazhuang, Hebei (China)
2016-06-15
Purpose: Deconvolution is a widely used tool in the field of image reconstruction algorithm when the linear imaging system has been blurred by the imperfect system transfer function. However, due to the nature of Gaussian-liked distribution for point spread function (PSF), the components with coherent high frequency in the image are hard to restored in most of the previous scanning imaging system, even the relatively accurate PSF is acquired. We propose a novel method for deconvolution of images which are obtained by using shape-modulated PSF. Methods: We use two different types of PSF - Gaussian shape and donut shape - to convolute the original image in order to simulate the process of scanning imaging. By employing deconvolution of the two images with corresponding given priors, the image quality of the deblurred images are compared. Then we find the critical size of the donut shape compared with the Gaussian shape which has similar deconvolution results. Through calculation of tightened focusing process using radially polarized beam, such size of donut is achievable under same conditions. Results: The effects of different relative size of donut and Gaussian shapes are investigated. When the full width at half maximum (FWHM) ratio of donut and Gaussian shape is set about 1.83, similar resolution results are obtained through our deconvolution method. Decreasing the size of donut will favor the deconvolution method. A mask with both amplitude and phase modulation is used to create a donut-shaped PSF compared with the non-modulated Gaussian PSF. Donut with size smaller than our critical value is obtained. Conclusion: The utility of donutshaped PSF are proved useful and achievable in the imaging and deconvolution processing, which is expected to have potential practical applications in high resolution imaging for biological samples.
Spiga, D
2018-01-01
X-ray mirrors with high focusing performances are commonly used in different sectors of science, such as X-ray astronomy, medical imaging and synchrotron/free-electron laser beamlines. While deformations of the mirror profile may cause degradation of the focus sharpness, a deliberate deformation of the mirror can be made to endow the focus with a desired size and distribution, via piezo actuators. The resulting profile can be characterized with suitable metrology tools and correlated with the expected optical quality via a wavefront propagation code or, sometimes, predicted using geometric optics. In the latter case and for the special class of profile deformations with monotonically increasing derivative, i.e. concave upwards, the point spread function (PSF) can even be predicted analytically. Moreover, under these assumptions, the relation can also be reversed: from the desired PSF the required profile deformation can be computed analytically, avoiding the use of trial-and-error search codes. However, the computation has been so far limited to geometric optics, which entailed some limitations: for example, mirror diffraction effects and the size of the coherent X-ray source were not considered. In this paper, the beam-shaping formalism in the framework of physical optics is reviewed, in the limit of small light wavelengths and in the case of Gaussian intensity wavefronts. Some examples of shaped profiles are also shown, aiming at turning a Gaussian intensity distribution into a top-hat one, and checks of the shaping performances computing the at-wavelength PSF by means of the WISE code are made.
Directory of Open Access Journals (Sweden)
Taisuke Murata
2016-10-01
Full Text Available Abstract Background The point spread function (PSF of positron emission tomography (PET depends on the position across the field of view (FOV. Reconstruction based on PSF improves spatial resolution and quantitative accuracy. The present study aimed to quantify the effects of PSF correction as a function of the position of a traceable point-like 22Na source over the FOV on two PET scanners with a different detector design. Methods We used Discovery 600 and Discovery 710 (GE Healthcare PET scanners and traceable point-like 22Na sources (<1 MBq with a spherical absorber design that assures uniform angular distribution of the emitted annihilation photons. The source was moved in three directions at intervals of 1 cm from the center towards the peripheral FOV using a three-dimensional (3D-positioning robot, and data were acquired over a period of 2 min per point. The PET data were reconstructed by filtered back projection (FBP, the ordered subset expectation maximization (OSEM, OSEM + PSF, and OSEM + PSF + time-of-flight (TOF. Full width at half maximum (FWHM was determined according to the NEMA method, and total counts in regions of interest (ROI for each reconstruction were quantified. Results The radial FWHM of FBP and OSEM increased towards the peripheral FOV, whereas PSF-based reconstruction recovered the FWHM at all points in the FOV of both scanners. The radial FWHM for PSF was 30–50 % lower than that of OSEM at the center of the FOV. The accuracy of PSF correction was independent of detector design. Quantitative values were stable across the FOV in all reconstruction methods. The effect of TOF on spatial resolution and quantitation accuracy was less noticeable. Conclusions The traceable 22Na point-like source allowed the evaluation of spatial resolution and quantitative accuracy across the FOV using different reconstruction methods and scanners. PSF-based reconstruction reduces dependence of the spatial resolution on the
Directory of Open Access Journals (Sweden)
Yasuharu Wakabayashi
2016-01-01
Full Text Available Objective(s: The present study was conducted to examine whether the standardized uptake value (SUV may be affected by the spatial position of a lesion in the radial direction on positron emission tomography (PET images, obtained via two methods based on time-of-flight (TOF reconstruction and point spread function (PSF. Methods: A cylinder phantom with the sphere (30mm diameter, located in the center was used in this study. Fluorine-18 fluorodeoxyglucose (18F-FDG concentrations of 5.3 kBq/ml and 21.2 kBq/ml were used for the background in the cylinder phantom and the central sphere respectively. By the use of TOF and PSF, SUVmax and SUVmean were determined while moving the phantom in a horizontal direction (X direction from the center of field of view (FOV: 0 mm at 50, 100, 150 and 200 mm positions, respectively. Furthermore, we examined 41 patients (23 male, 18 female, mean age: 68±11.2 years with lymph node tumors , who had undergone 18F-FDG PET examinations. The distance of each lymph node from FOV center was measured, based on the clinical images. Results: As the distance of a lesion from the FOV center exceeded 100 mm, the value of SUVmax, which was obtained with the cylinder phantom, was overestimated, while SUVmean by TOF and/or PSF was underestimated. Based on the clinical examinations, the average volume of interest was 8.5 cm3. Concomitant use of PSF increased SUVmax and SUVmean by 27.9% and 2.8%, respectively. However, size of VOI and distance from the FOV center did not affect SUVmax or SUVmean in clinical examinations. Conclusion: The reliability of SUV quantification by TOF and/or PSF decreased, when the tumor was located at a 100 mm distance (or farther from the center of FOV. In clinical examinations, if the lymph node was located within 100 mm distance from the center of FOV, SUV remained stable within a constantly increasing range by use of both TOF and PSF. We conclude that, use of both TOF and PSF may be helpful.
Energy Technology Data Exchange (ETDEWEB)
Kotasidis, F A; Matthews, J C; Angelis, G I; Noonan, P J; Jackson, A [Imaging, Genomics and Proteomics, Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester (United Kingdom); Price, P [Academic Department of Radiation Oncology, University of Manchester, Manchester (United Kingdom); Lionheart, W R [School of Mathematics, Alan Turing Building, University of Manchester, Manchester (United Kingdom); Reader, A J, E-mail: fotis.kotasidis@mmic.man.ac.uk [Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC (Canada)
2011-05-21
Incorporation of a resolution model during statistical image reconstruction often produces images of improved resolution and signal-to-noise ratio. A novel and practical methodology to rapidly and accurately determine the overall emission and detection blurring component of the system matrix using a printed point source array within a custom-made Perspex phantom is presented. The array was scanned at different positions and orientations within the field of view (FOV) to examine the feasibility of extrapolating the measured point source blurring to other locations in the FOV and the robustness of measurements from a single point source array scan. We measured the spatially-variant image-based blurring on two PET/CT scanners, the B-Hi-Rez and the TruePoint TrueV. These measured spatially-variant kernels and the spatially-invariant kernel at the FOV centre were then incorporated within an ordinary Poisson ordered subset expectation maximization (OP-OSEM) algorithm and compared to the manufacturer's implementation using projection space resolution modelling (RM). Comparisons were based on a point source array, the NEMA IEC image quality phantom, the Cologne resolution phantom and two clinical studies (carbon-11 labelled anti-sense oligonucleotide [{sup 11}C]-ASO and fluorine-18 labelled fluoro-l-thymidine [{sup 18}F]-FLT). Robust and accurate measurements of spatially-variant image blurring were successfully obtained from a single scan. Spatially-variant resolution modelling resulted in notable resolution improvements away from the centre of the FOV. Comparison between spatially-variant image-space methods and the projection-space approach (the first such report, using a range of studies) demonstrated very similar performance with our image-based implementation producing slightly better contrast recovery (CR) for the same level of image roughness (IR). These results demonstrate that image-based resolution modelling within reconstruction is a valid alternative to
Intensity-dependent point spread image processing
International Nuclear Information System (INIS)
Cornsweet, T.N.; Yellott, J.I.
1984-01-01
There is ample anatomical, physiological and psychophysical evidence that the mammilian retina contains networks that mediate interactions among neighboring receptors, resulting in intersecting transformations between input images and their corresponding neural output patterns. The almost universally accepted view is that the principal form of interaction involves lateral inhibition, resulting in an output pattern that is the convolution of the input with a ''Mexican hat'' or difference-of-Gaussians spread function, having a positive center and a negative surround. A closely related process is widely applied in digital image processing, and in photography as ''unsharp masking''. The authors show that a simple and fundamentally different process, involving no inhibitory or subtractive terms can also account for the physiological and psychophysical findings that have been attributed to lateral inhibition. This process also results in a number of fundamental effects that occur in mammalian vision and that would be of considerable significance in robotic vision, but which cannot be explained by lateral inhibitory interaction
Computation of the lateral and axial point spread functions in ...
Indian Academy of Sciences (India)
... confocal scanning microscopes for the above-mentioned amplitude filters. These results of axial and lateral irradiances are graphically represented by constructing a computer program using MATLAB. The obtained results are compared with that obtained in case of circular, annular, and Martinez-Corral apodized aperture ...
Computation of the lateral and axial point spread functions in ...
Indian Academy of Sciences (India)
scanning microscopes for the above-mentioned amplitude filters. These results of axial and lateral irradiances are graphically represented by constructing a computer program using MATLAB. The obtained results are compared with that obtained in case of circular, annular, and Martinez-Corral apodized aperture. Keywords ...
A Practical Point Spread Model for Ocean Waters
National Research Council Canada - National Science Library
Hou, Weilin; Gray, Deric; Weidemann, Alan D; Arnone, Robert A
2008-01-01
.... These inherent optical properties (IOP), although measured frequently due to their important applications in ocean optics, especially in remote sensing, cannot be applied to underwater imaging issues directly, since they inherently reflect the chance of the single scattering.
“Hot Hand” in the National Basketball Association Point Spread Betting Market: A 34-Year Analysis
Directory of Open Access Journals (Sweden)
Benjamin Waggoner
2014-11-01
Full Text Available Several articles have looked at factors that affect the adjustments of point spreads, based on hot hands or streaks, for smaller durations of time. This study examines these effects for 34 regular seasons in the National Basketball Association (NBA. Estimating a Seemingly Unrelated Regression model using all 34 seasons, all streaks significantly impacted point spreads and difference in actual points. When estimating each season individually, differences emerged particularly examining winning and losing streaks of six games or more. The results indicate both the presence of momentum effects and the gambler’s fallacy.
Comparison and Validation of Point Spread Models for Imaging in Natural Waters
National Research Council Canada - National Science Library
Hou, Weilin; Gray, Deric; Weidemann, Alan; Arnone, Robert
2008-01-01
.... This will extend the performance range as well as the information retrieval from underwater electro-optical systems, which is critical in many civilian and military applications, including target...
National Research Council Canada - National Science Library
Jaffe, Jules S
2007-01-01
The objective of this project funded by ONR (grant # N00014-06-1-0374) was to measure, understand and be able to predict the propagation of light through the air-sea interface under various sea states...
Nonparametric Transfer Function Models
Liu, Jun M.; Chen, Rong; Yao, Qiwei
2009-01-01
In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584
Modelling of the over-exposed pixel area of CCD cameras caused by laser dazzling
Benoist, K.W.; Schleijpen, R.M.A.
2014-01-01
A simple model has been developed and implemented in Matlab code, predicting the over-exposed pixel area of cameras caused by laser dazzling. Inputs of this model are the laser irradiance on the front optics of the camera, the Point Spread Function (PSF) of the used optics, the integration time of
Dai, Honglin; Luo, Yongdao
2013-12-01
In recent years, with the development of the Flat-Field Holographic Concave Grating, they are adopted by all kinds of UV spectrometers. By means of single optical surface, the Flat-Field Holographic Concave Grating can implement dispersion and imaging that make the UV spectrometer system design quite compact. However, the calibration of the Flat-Field Holographic Concave Grating is very difficult. Various factors make its imaging quality difficult to be guaranteed. So we have to process the spectrum signal with signal restoration before using it. Guiding by the theory of signals and systems, and after a series of experiments, we found that our UV spectrometer system is a Linear Space- Variant System. It means that we have to measure PSF of every pixel of the system which contains thousands of pixels. Obviously, that's a large amount of calculation .For dealing with this problem, we proposes a novel signal restoration method. This method divides the system into several Linear Space-Invariant subsystems and then makes signal restoration with PSFs. Our experiments turn out that this method is effective and inexpensive.
Statistical modelling with quantile functions
Gilchrist, Warren
2000-01-01
Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.Statistical Modelling with Quantile Functions adds a new dimension to the practice of stati...
Functional Scaling of Musculoskeletal Models
DEFF Research Database (Denmark)
Lund, Morten Enemark; Andersen, Michael Skipper; de Zee, Mark
specific to the patient. This is accomplished using optimisation methods to determine patient-specific joint positions and orientations, which minimise the least-squares error between model markers and the recorded markers from a motion capture experiment. Functional joint positions and joint axis...... geometry, without the need for MR/CT scans. However, more validation activities are needed to better understand the effect of morphing musculoskeletal models based on functional joint parameters....
Functioning with a Sticky Model.
Reys, Robert E.
1981-01-01
A model that can be effectively used to develop the notion of function and provide varied practice by using "real world" examples and concrete objects is covered. The use of Popsicle-sticks is featured, with some suggestions for tasks involving functions with one operation, two operations, and inverse operations covered. (MP)
A deterministic width function model
Directory of Open Access Journals (Sweden)
C. E. Puente
2003-01-01
Full Text Available Use of a deterministic fractal-multifractal (FM geometric method to model width functions of natural river networks, as derived distributions of simple multifractal measures via fractal interpolating functions, is reported. It is first demonstrated that the FM procedure may be used to simulate natural width functions, preserving their most relevant features like their overall shape and texture and their observed power-law scaling on their power spectra. It is then shown, via two natural river networks (Racoon and Brushy creeks in the United States, that the FM approach may also be used to closely approximate existing width functions.
Zhang functions and various models
Zhang, Yunong
2015-01-01
This book focuses on solving different types of time-varying problems. It presents various Zhang dynamics (ZD) models by defining various Zhang functions (ZFs) in real and complex domains. It then provides theoretical analyses of such ZD models and illustrates their results. It also uses simulations to substantiate their efficacy and show the feasibility of the presented ZD approach (i.e., different ZFs leading to different ZD models), which is further applied to the repetitive motion planning (RMP) of redundant robots, showing its application potential.
Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions
Morelli, Eugene A.
2013-01-01
A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.
PLATO: PSF modelling using a micro-scanning technique
Directory of Open Access Journals (Sweden)
Ouazzani R-M.
2015-01-01
Full Text Available The PLATO space mission is designed to detect telluric planets in the habitable zone of solar type stars, and simultaneously characterise the host star using ultra high precision photometry. The photometry will be performed on board using weighted masks. However, to reach the required precision, corrections will have to be performed by the ground segment and will rely on precise knowledge of the instrument PSF (Point Spread Function. We here propose to model the PSF using a microscanning method.
Hierarchical models and functional traits
van Loon, E.E.; Shamoun-Baranes, J.; Sierdsema, H.; Bouten, W.; Cramer, W.; Badeck, F.; Krukenberg, B.; Klotz, S.; Kühn, I.; Schweiger, O.; Böhning-Gaese, K.; Schaefer, H.-C.; Kissling, D.; Brandl, R.; Brändle, M.; Fricke, R.; Leuschner, C.; Buschmann, H.; Köckermann, B.; Rose, L.
2006-01-01
Hierarchical models for animal abundance prediction are conceptually elegant. They are generally more parsimonous than non-hierarchical models derived from the same data, give relatively robust predictions and automatically provide consistent output at multiple (spatio-temporal) scales. Another
Response Surface Modeling Using Multivariate Orthogonal Functions
Morelli, Eugene A.; DeLoach, Richard
2001-01-01
A nonlinear modeling technique was used to characterize response surfaces for non-dimensional longitudinal aerodynamic force and moment coefficients, based on wind tunnel data from a commercial jet transport model. Data were collected using two experimental procedures - one based on modem design of experiments (MDOE), and one using a classical one factor at a time (OFAT) approach. The nonlinear modeling technique used multivariate orthogonal functions generated from the independent variable data as modeling functions in a least squares context to characterize the response surfaces. Model terms were selected automatically using a prediction error metric. Prediction error bounds computed from the modeling data alone were found to be- a good measure of actual prediction error for prediction points within the inference space. Root-mean-square model fit error and prediction error were less than 4 percent of the mean response value in all cases. Efficacy and prediction performance of the response surface models identified from both MDOE and OFAT experiments were investigated.
Functional Modeling of Neural-Glia Interaction
DEFF Research Database (Denmark)
Postnov, D.E.; Brazhe, N.A.; Sosnovtseva, Olga
2012-01-01
Functional modeling is an approach that focuses on the representation of the qualitative dynamics of the individual components (e.g. cells) of a system and on the structure of the interaction network.......Functional modeling is an approach that focuses on the representation of the qualitative dynamics of the individual components (e.g. cells) of a system and on the structure of the interaction network....
Neural modeling of prefrontal executive function
Energy Technology Data Exchange (ETDEWEB)
Levine, D.S. [Univ. of Texas, Arlington, TX (United States)
1996-12-31
Brain executive function is based in a distributed system whereby prefrontal cortex is interconnected with other cortical. and subcortical loci. Executive function is divided roughly into three interacting parts: affective guidance of responses; linkage among working memory representations; and forming complex behavioral schemata. Neural network models of each of these parts are reviewed and fit into a preliminary theoretical framework.
A Multivariate Approach to Functional Neuro Modeling
DEFF Research Database (Denmark)
Mørch, Niels J.S.
1998-01-01
by the application of linear and more flexible, nonlinear microscopic regression models to a real-world dataset. The dependency of model performance, as quantified by generalization error, on model flexibility and training set size is demonstrated, leading to the important realization that no uniformly optimal model......, provides the basis for a generalization theoretical framework relating model performance to model complexity and dataset size. Briefly summarized the major topics discussed in the thesis include: - An introduction of the representation of functional datasets by pairs of neuronal activity patterns...... exists. - Model visualization and interpretation techniques. The simplicity of this task for linear models contrasts the difficulties involved when dealing with nonlinear models. Finally, a visualization technique for nonlinear models is proposed. A single observation emerges from the thesis...
Prediction of Chemical Function: Model Development and ...
The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi
Thirring model partition functions and harmonic differentials
Freedman, D. Z.; Pilch, K.
1988-10-01
The partition function of the Thirring model on a Riemann surface is calculated using the representation of the model as a fermion interacting with an auxiliary vector potential. The Hodge decomposition of the potential is used and the integral over the harmonic forms is shown to reproduce exactly the soliton sum in the bosonic version of the theory.
The NJL Model for Quark Fragmentation Functions
Energy Technology Data Exchange (ETDEWEB)
T. Ito, W. Bentz, I. Cloet, A W Thomas, K. Yazaki
2009-10-01
A description of fragmentation functions which satisfy the momentum and isospin sum rules is presented in an effective quark theory. Concentrating on the pion fragmentation function, we first explain the reason why the elementary (lowest order) fragmentation process q → qπ is completely inadequate to describe the empirical data, although the “crossed” process π → qq describes the quark distribution functions in the pion reasonably well. Then, taking into account cascade-like processes in a modified jet-model approach, we show that the momentum and isospin sum rules can be satisfied naturally without introducing any ad-hoc parameters. We present numerical results for the Nambu-Jona-Lasinio model in the invariant mass regularization scheme, and compare the results with the empirical parametrizations. We argue that this NJL-jet model provides a very useful framework to calculate the fragmentation functions in an effective chiral quark theory.
Structure functions in the chiral bag model
Energy Technology Data Exchange (ETDEWEB)
Sanjose, V.; Vento, V.
1989-07-13
We calculate the structure functions of an isoscalar nuclear target for the deep inelastic scattering by leptons in an extended version of the chiral bag model which incorporates the qanti q structure of the pions in the cloud. Bjorken scaling and Regge behavior are satisfied. The model calculation reproduces the low-x behavior of the data but fails to explain the medium- to large-x behavior. Evolution of the quark structure functions seem inevitable to attempt a connection between the low-energy models and the high-energy behavior of quantum chromodynamics. (orig.).
Circumplex model of family function in practice.
Furst, A L
1983-08-01
The recent dramatic resurgence in Israel of family medicine as a medical specialty has stimulated interest in concepts that view family function and dysfunction from the standpoint of family relationships and interaction, and in which the family is seen as a unit rather than as a collection of individuals. One model of family functioning, the circumplex model, is explained. This is based upon two dimensions, cohesion and adaptability. The potential relevance of this model to family medicine in Israel is discussed, along with a brief account of the author's initial steps in developing it for use as a tool in practice.
Functional Error Models to Accelerate Nested Sampling
Josset, L.; Elsheikh, A. H.; Demyanov, V.; Lunati, I.
2014-12-01
The main challenge in groundwater problems is the reliance on large numbers of unknown parameters with wide rage of associated uncertainties. To translate this uncertainty to quantities of interest (for instance the concentration of pollutant in a drinking well), a large number of forward flow simulations is required. To make the problem computationally tractable, Josset et al. (2013, 2014) introduced the concept of functional error models. It consists in two elements: a proxy model that is cheaper to evaluate than the full physics flow solver and an error model to account for the missing physics. The coupling of the proxy model and the error models provides reliable predictions that approximate the full physics model's responses. The error model is tailored to the problem at hand by building it for the question of interest. It follows a typical approach in machine learning where both the full physics and proxy models are evaluated for a training set (subset of realizations) and the set of responses is used to construct the error model using functional data analysis. Once the error model is devised, a prediction of the full physics response for a new geostatistical realization can be obtained by computing the proxy response and applying the error model. We propose the use of functional error models in a Bayesian inference context by combining it to the Nested Sampling (Skilling 2006; El Sheikh et al. 2013, 2014). Nested Sampling offers a mean to compute the Bayesian Evidence by transforming the multidimensional integral into a 1D integral. The algorithm is simple: starting with an active set of samples, at each iteration, the sample with the lowest likelihood is kept aside and replaced by a sample of higher likelihood. The main challenge is to find this sample of higher likelihood. We suggest a new approach: first the active set is sampled, both proxy and full physics models are run and the functional error model is build. Then, at each iteration of the Nested
Bayesian Modelling of Functional Whole Brain Connectivity
DEFF Research Database (Denmark)
Røge, Rasmus
This thesis deals with parcellation of whole-brain functional magnetic resonance imaging (fMRI) using Bayesian inference with mixture models tailored to the fMRI data. In the three included papers and manuscripts, we analyze two different approaches to modeling fMRI signal; either we accept...... the prevalent strategy of standardizing of fMRI time series and model data using directional statistics or we model the variability in the signal across the brain and across multiple subjects. In either case, we use Bayesian nonparametric modeling to automatically learn from the fMRI data the number...... of funcional units, i.e. parcels. We benchmark the proposed mixture models against state of the art methods of brain parcellation, both probabilistic and non-probabilistic. The time series of each voxel are most often standardized using z-scoring which projects the time series data onto a hypersphere...
Frost heave modelling using porosity rate function
Michalowski, Radoslaw L.; Zhu, Ming
2006-07-01
Frost-susceptible soils are characterized by their sensitivity to freezing that is manifested in heaving of the ground surface. While significant contributions to explaining the nature of frost heave in soils were published in late 1920s, modelling efforts did not start until decades later. Several models describing the heaving process have been developed in the past, but none of them has been generally accepted as a tool in engineering applications. The approach explored in this paper is based on the concept of the porosity rate function dependent on two primary material parameters: the maximum rate, and the temperature at which the maximum rate occurs. The porosity rate is indicative of ice growth, and this growth is also dependent on the temperature gradient and the stress state in the freezing soil. The advantage of this approach over earlier models stems from a formulation consistent with continuum mechanics that makes it possible to generalize the model to arbitrary three-dimensional processes, and use the standard numerical techniques in solving boundary value problems. The physical premise for the model is discussed first, and the development of the constitutive model is outlined. The model is implemented in a 2-D finite element code, and the porosity rate function is calibrated and validated. Effectiveness of the model is then illustrated in an example of freezing of a vertical cut in frost-susceptible soil.
A systemic approach for modeling soil functions
Vogel, Hans-Jörg; Bartke, Stephan; Daedlow, Katrin; Helming, Katharina; Kögel-Knabner, Ingrid; Lang, Birgit; Rabot, Eva; Russell, David; Stößel, Bastian; Weller, Ulrich; Wiesmeier, Martin; Wollschläger, Ute
2018-03-01
The central importance of soil for the functioning of terrestrial systems is increasingly recognized. Critically relevant for water quality, climate control, nutrient cycling and biodiversity, soil provides more functions than just the basis for agricultural production. Nowadays, soil is increasingly under pressure as a limited resource for the production of food, energy and raw materials. This has led to an increasing demand for concepts assessing soil functions so that they can be adequately considered in decision-making aimed at sustainable soil management. The various soil science disciplines have progressively developed highly sophisticated methods to explore the multitude of physical, chemical and biological processes in soil. It is not obvious, however, how the steadily improving insight into soil processes may contribute to the evaluation of soil functions. Here, we present to a new systemic modeling framework that allows for a consistent coupling between reductionist yet observable indicators for soil functions with detailed process understanding. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. The non-linear character of these interactions produces stability and resilience of soil with respect to functional characteristics. We anticipate that this new conceptional framework will integrate the various soil science disciplines and help identify important future research questions at the interface between disciplines. It allows the overwhelming complexity of soil systems to be adequately coped with and paves the way for steadily improving our capability to assess soil functions based on scientific understanding.
The Goodwin model: behind the Hill function.
Directory of Open Access Journals (Sweden)
Didier Gonze
Full Text Available The Goodwin model is a 3-variable model demonstrating the emergence of oscillations in a delayed negative feedback-based system at the molecular level. This prototypical model and its variants have been commonly used to model circadian and other genetic oscillators in biology. The only source of non-linearity in this model is a Hill function, characterizing the repression process. It was mathematically shown that to obtain limit-cycle oscillations, the Hill coefficient must be larger than 8, a value often considered unrealistic. It is indeed difficult to explain such a high coefficient with simple cooperative dynamics. We present here molecular models of the standard Goodwin model, based on single or multisite phosphorylation/dephosphorylation processes of a transcription factor, which have been previously shown to generate switch-like responses. We show that when the phosphorylation/dephosphorylation processes are fast enough, the limit-cycle obtained with a multisite phosphorylation-based mechanism is in very good quantitative agreement with the oscillations observed in the Goodwin model. Conditions in which the detailed mechanism is well approximated by the Goodwin model are given. A variant of the Goodwin model which displays sharp thresholds and relaxation oscillations is also explained by a double phosphorylation/dephosphorylation-based mechanism through a bistable behavior. These results not only provide rational support for the Goodwin model but also highlight the crucial role of the speed of post-translational processes, whose response curve are usually established at a steady state, in biochemical oscillators.
Correlation functions of two-matrix models
International Nuclear Information System (INIS)
Bonora, L.; Xiong, C.S.
1993-11-01
We show how to calculate correlation functions of two matrix models without any approximation technique (except for genus expansion). In particular we do not use any continuum limit technique. This allows us to find many solutions which are invisible to the latter technique. To reach our goal we make full use of the integrable hierarchies and their reductions which were shown in previous papers to naturally appear in multi-matrix models. The second ingredient we use, even though to a lesser extent, are the W-constraints. In fact an explicit solution of the relevant hierarchy, satisfying the W-constraints (string equation), underlies the explicit calculation of the correlation functions. The correlation functions we compute lend themselves to a possible interpretation in terms of topological field theories. (orig.)
Hazard identification based on plant functional modelling
International Nuclear Information System (INIS)
Rasmussen, B.; Whetton, C.
1993-10-01
A major objective of the present work is to provide means for representing a process plant as a socio-technical system, so as to allow hazard identification at a high level. The method includes technical, human and organisational aspects and is intended to be used for plant level hazard identification so as to identify critical areas and the need for further analysis using existing methods. The first part of the method is the preparation of a plant functional model where a set of plant functions link together hardware, software, operations, work organisation and other safety related aspects of the plant. The basic principle of the functional modelling is that any aspect of the plant can be represented by an object (in the sense that this term is used in computer science) based upon an Intent (or goal); associated with each Intent are Methods, by which the Intent is realized, and Constraints, which limit the Intent. The Methods and Constraints can themselves be treated as objects and decomposed into lower-level Intents (hence the procedure is known as functional decomposition) so giving rise to a hierarchical, object-oriented structure. The plant level hazard identification is carried out on the plant functional model using the Concept Hazard Analysis method. In this, the user will be supported by checklists and keywords and the analysis is structured by pre-defined worksheets. The preparation of the plant functional model and the performance of the hazard identification can be carried out manually or with computer support. (au) (4 tabs., 10 ills., 7 refs.)
Symmetric Functional Model for Extensions of Hermitian
Ryzhov, V
2006-01-01
This paper offers the functional model of a class of non-selfadjoint extensions of a Hermitian operator with equal deficiency indices. The explicit form of dilation of a dissipative extension is offered and the symmetric form of Sz.Nagy-Foia\\c{s} model as developed by B.~Pavlov is constructed. A variant of functional model for a general non-selfadjoint non-dissipative extension is formulated. We illustrate the theory by two examples: singular perturbations of the Laplace operator in~$L_2(\\Real^3)$ by a finite number of point interactions, and the Schr\\"odinger operator on the half axis~$(0, \\infty)$ in the Weyl limit circle case at infinity.
Mathematical modeling and visualization of functional neuroimages
DEFF Research Database (Denmark)
Rasmussen, Peter Mondrup
This dissertation presents research results regarding mathematical modeling in the context of the analysis of functional neuroimages. Specifically, the research focuses on pattern-based analysis methods that recently have become popular within the neuroimaging community. Such methods attempt...... to predict or decode experimentally defined cognitive states based on brain scans. The topics covered in the dissertation are divided into two broad parts: The first part investigates the relative importance of model selection on the brain patterns extracted form analysis models. Typical neuroimaging data...... for extracting a global summary map from a trained model. Such summary maps provides the investigator with an overview of brain locations of importance to the model’s predictions. The sensitivity map proves as a versatile technique for model visualization. Furthermore, we perform a preliminary investigation...
Mathematical modeling and visualization of functional neuroimages
DEFF Research Database (Denmark)
Rasmussen, Peter Mondrup
This dissertation presents research results regarding mathematical modeling in the context of the analysis of functional neuroimages. Specifically, the research focuses on pattern-based analysis methods that recently have become popular analysis tools within the neuroimaging community. Such methods...... attempt to predict or decode experimentally defined cognitive states based on brain scans. The topics covered in the dissertation are divided into two broad parts: The first part investigates the relative importance of model selection on the brain patterns extracted form analysis models. Typical...... for extracting a global summary map from a trained model. Such summary maps provides the investigator with an overview of brain locations of importance to the model’s predictions. The sensitivity map proves as a versatile technique for model visualization. Furthermore, we perform a preliminary investigation...
Modeling dynamic functional connectivity using a wishart mixture model
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Madsen, Kristoffer Hougaard; Schmidt, Mikkel Nørgaard
2017-01-01
Dynamic functional connectivity (dFC) has recently become a popular way of tracking the temporal evolution of the brains functional integration. However, there does not seem to be a consensus on how to choose the complexity, i.e. number of brain states, and the time-scale of the dynamics, i.......e. the window length. In this work we use the Wishart Mixture Model (WMM) as a probabilistic model for dFC based on variational inference. The framework admits arbitrary window lengths and number of dynamic components and includes the static one-component model as a special case. We exploit that the WMM...... framework provides model selection by quantifying models generalization to new data. We use this to quantify the number of states within a prespecified window length. We further propose a heuristic procedure for choosing the window length based on contrasting for each window length the predictive...
Modelling of the over-exposed pixel area of CCD cameras caused by laser dazzling
Benoist, K.W.; Schleijpen, R.M.A.
2014-01-01
A simple model has been developed and implemented in Matlab code, predicting the over-exposed pixel area of cameras caused by laser dazzling. Inputs of this model are the laser irradiance on the front optics of the camera, the Point Spread Function (PSF) of the used optics, the integration time of the camera, and camera sensor specifications like pixel size, quantum efficiency and full well capacity. Effects of the read-out circuit of the camera are not incorporated. The model was evaluated w...
Multivariate Heteroscedasticity Models for Functional Brain Connectivity
Directory of Open Access Journals (Sweden)
Christof Seiler
2017-12-01
Full Text Available Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI. We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.
A Generic Modeling Process to Support Functional Fault Model Development
Maul, William A.; Hemminger, Joseph A.; Oostdyk, Rebecca; Bis, Rachael A.
2016-01-01
Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.
Functional Security Model: Managers Engineers Working Together
Guillen, Edward Paul; Quintero, Rulfo
2008-05-01
Information security has a wide variety of solutions including security policies, network architectures and technological applications, they are usually designed and implemented by security architects, but in its own complexity this solutions are difficult to understand by company managers and they are who finally fund the security project. The main goal of the functional security model is to achieve a solid security platform reliable and understandable in the whole company without leaving of side the rigor of the recommendations and the laws compliance in a single frame. This paper shows a general scheme of the model with the use of important standards and tries to give an integrated solution.
A general phenomenological model for work function
Brodie, I.; Chou, S. H.; Yuan, H.
2014-07-01
A general phenomenological model is presented for obtaining the zero Kelvin work function of any crystal facet of metals and semiconductors, both clean and covered with a monolayer of electropositive atoms. It utilizes the known physical structure of the crystal and the Fermi energy of the two-dimensional electron gas assumed to form on the surface. A key parameter is the number of electrons donated to the surface electron gas per surface lattice site or adsorbed atom, which is taken to be an integer. Initially this is found by trial and later justified by examining the state of the valence electrons of the relevant atoms. In the case of adsorbed monolayers of electropositive atoms a satisfactory justification could not always be found, particularly for cesium, but a trial value always predicted work functions close to the experimental values. The model can also predict the variation of work function with temperature for clean crystal facets. The model is applied to various crystal faces of tungsten, aluminium, silver, and select metal oxides, and most demonstrate good fits compared to available experimental values.
Mathematical Models of Cardiac Pacemaking Function
Directory of Open Access Journals (Sweden)
Pan eLi
2013-10-01
Full Text Available Over the past half century, there has been intense and fruitful interaction between experimental and computational investigations of cardiac function. This interaction has, for example, led to deep understanding of cardiac excitation-contraction coupling; how it works, as well as how it fails. However, many lines of inquiry remain unresolved, among them the initiation of each heartbeat. The sinoatrial node, a cluster of specialized pacemaking cells in the right atrium of the heart, spontaneously generates an electro-chemical wave that spreads through the atria and through the cardiac conduction system to the ventricles, initiating the contraction of cardiac muscle essential for pumping blood to the body. Despite the fundamental importance of this primary pacemaker, this process is still not fully understood, and ionic mechanisms underlying cardiac pacemaking function are currently under heated debate. Several mathematical models of sinoatrial node cell membrane electrophysiology have been constructed as based on different experimental data sets and hypotheses. As could be expected, these differing models offer diverse predictions about cardiac pacemaking activities. This paper aims to present the current state of debate over the origins of the pacemaking function of the sinoatrial node. Here, we will specifically review the state-of-the-art of cardiac pacemaker modeling, with a special emphasis on current discrepancies, limitations, and future challenges.
[Functional model of the middle ear ossicles].
Satoda, Takahiro; Shimoe, Saiji; Makihira, Seicho; Tamamoto, Mitsuhiro; Matsumoto, Atsue; Hara, Kumiko; Noso, Maki; Niitani, Yoshie; Sugiyama, Masaru; Takemoto, Toshinobu; Murayama, Takeshi; Amano, Hideaki; Nikawa, Hiroki
2009-06-01
In students' dissection practice, it is very difficult to teach students the structures and functions of the middle ear ossicles. The middle ear ossicles are too small to explain their structures and functions. Models are useful in explaining these points, but there have been no models that accurately explain the movements of the middle ear ossicles and the functions of the muscles in the middle ear. This time, we have made a model of middle ear ossicles. Our ear ossicles are made of paper-mache with metal in it. The incudomalleolar and incudostapedial articulations are made of rubber. The tensor tympani and the stapedius muscles are made of wire and the two wires can be fixed by cord stoppers. Our model explains clearly the following mechanisms of the middle ear ossicles. 1. The mechanism of sound conduction system. When the sound vibrates the tympanic membrane, malleus and incus rotate together. The long process of the incus pushes the head of the stapes. The sound is amplified by leverage. 2. Attenuation of sound by contractions of tensor tympani and stapedius muscles. When a loud sound is transmitted through the ossicular system, the tensor tympani muscle pulls the malleus inward while the stapedius muscle pulls the stapes outward. These two forces oppose each other and increase rigidity of the ossicular system, thus reducing the ossicular conduction. 3. The mechanism of how paralysis of stapedius muscle, caused by an injury to the facial nerve, results in hyperacusis. 4. This model also suggests a possible reason why the pars lucida of the tympanic membrane exists.
Functional Modeling for Monitoring of Robotic System
DEFF Research Database (Denmark)
Wu, Haiyan; Bateman, Rikke R.; Zhang, Xinxin
2018-01-01
supervisors or cooperators. In this work, we focus on developing a modeling framework for monitoring robotic system based on means-end analysis and the concept of action phases from action theory. A circular cascaded action phase structure is proposed for building the model of cyclical robotic events......With the expansion of robotic applications in the industrial domain, it is important that the robots can execute their tasks in a safe and reliable way. A monitoring system can be implemented to ensure the detection of abnormal situations of the robots and report the abnormality to their human....... This functional model provide a formal way of decompose robotic tasks and analyze each level of conditions for an action to be executed successfully. It can be used for monitoring robotic systems by checking the preconditions in the action phases and identifying the failure modes. The proposed method...
Functionalized anatomical models for EM-neuron Interaction modeling
Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang
2016-06-01
The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.
Functional RG approach to the Potts model
Ben Alì Zinati, Riccardo; Codello, Alessandro
2018-01-01
The critical behavior of the (n+1) -states Potts model in d-dimensions is studied with functional renormalization group techniques. We devise a general method to derive β-functions for continuous values of d and n and we write the flow equation for the effective potential (LPA’) when instead n is fixed. We calculate several critical exponents, which are found to be in good agreement with Monte Carlo simulations and ɛ-expansion results available in the literature. In particular, we focus on Percolation (n\\to0) and Spanning Forest (n\\to-1) which are the only non-trivial universality classes in d = 4,5 and where our methods converge faster.
Electricity price forecasting through transfer function models
International Nuclear Information System (INIS)
Nogales, F.J.; Conejo, A.J.
2006-01-01
Forecasting electricity prices in present day competitive electricity markets is a must for both producers and consumers because both need price estimates to develop their respective market bidding strategies. This paper proposes a transfer function model to predict electricity prices based on both past electricity prices and demands, and discuss the rationale to build it. The importance of electricity demand information is assessed. Appropriate metrics to appraise prediction quality are identified and used. Realistic and extensive simulations based on data from the PJM Interconnection for year 2003 are conducted. The proposed model is compared with naive and other techniques. Journal of the Operational Research Society (2006) 57, 350-356.doi:10.1057/palgrave.jors.2601995; published online 18 May 2005. (author)
A Prediction Model of the Capillary Pressure J-Function.
Directory of Open Access Journals (Sweden)
W S Xu
Full Text Available The capillary pressure J-function is a dimensionless measure of the capillary pressure of a fluid in a porous medium. The function was derived based on a capillary bundle model. However, the dependence of the J-function on the saturation Sw is not well understood. A prediction model for it is presented based on capillary pressure model, and the J-function prediction model is a power function instead of an exponential or polynomial function. Relative permeability is calculated with the J-function prediction model, resulting in an easier calculation and results that are more representative.
Functional methods in the generalized Dicke model
International Nuclear Information System (INIS)
Alcalde, M. Aparicio; Lemos, A.L.L. de; Svaiter, N.F.
2007-01-01
The Dicke model describes an ensemble of N identical two-level atoms (qubits) coupled to a single quantized mode of a bosonic field. The fermion Dicke model should be obtained by changing the atomic pseudo-spin operators by a linear combination of Fermi operators. The generalized fermion Dicke model is defined introducing different coupling constants between the single mode of the bosonic field and the reservoir, g 1 and g 2 for rotating and counter-rotating terms respectively. In the limit N -> ∞, the thermodynamic of the fermion Dicke model can be analyzed using the path integral approach with functional method. The system exhibits a second order phase transition from normal to superradiance at some critical temperature with the presence of a condensate. We evaluate the critical transition temperature and present the spectrum of the collective bosonic excitations for the general case (g 1 ≠ 0 and g 2 ≠ 0). There is quantum critical behavior when the coupling constants g 1 and g 2 satisfy g 1 + g 2 =(ω 0 Ω) 1/2 , where ω 0 is the frequency of the mode of the field and Ω is the energy gap between energy eigenstates of the qubits. Two particular situations are analyzed. First, we present the spectrum of the collective bosonic excitations, in the case g 1 ≠ 0 and g 2 ≠ 0, recovering the well known results. Second, the case g 1 ≠ 0 and g 2 ≠ 0 is studied. In this last case, it is possible to have a super radiant phase when only virtual processes are introduced in the interaction Hamiltonian. Here also appears a quantum phase transition at the critical coupling g 2 (ω 0 Ω) 1/2 , and for larger values for the critical coupling, the system enter in this super radiant phase with a Goldstone mode. (author)
Fully automated calculation of image-derived input function in simultaneous PET/MRI in a sheep model
Energy Technology Data Exchange (ETDEWEB)
Jochimsen, Thies H.; Zeisig, Vilia [Department of Nuclear Medicine, Leipzig University Hospital, Liebigstr. 18, Leipzig (Germany); Schulz, Jessica [Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig, D-04103 (Germany); Werner, Peter; Patt, Marianne; Patt, Jörg [Department of Nuclear Medicine, Leipzig University Hospital, Liebigstr. 18, Leipzig (Germany); Dreyer, Antje Y. [Fraunhofer Institute of Cell Therapy and Immunology, Perlickstr. 1, Leipzig, D-04103 (Germany); Translational Centre for Regenerative Medicine, University Leipzig, Philipp-Rosenthal-Str. 55, Leipzig, D-04103 (Germany); Boltze, Johannes [Fraunhofer Institute of Cell Therapy and Immunology, Perlickstr. 1, Leipzig, D-04103 (Germany); Translational Centre for Regenerative Medicine, University Leipzig, Philipp-Rosenthal-Str. 55, Leipzig, D-04103 (Germany); Fraunhofer Research Institution of Marine Biotechnology and Institute for Medical and Marine Biotechnology, University of Lübeck, Lübeck (Germany); Barthel, Henryk; Sabri, Osama; Sattler, Bernhard [Department of Nuclear Medicine, Leipzig University Hospital, Liebigstr. 18, Leipzig (Germany)
2016-02-13
Obtaining the arterial input function (AIF) from image data in dynamic positron emission tomography (PET) examinations is a non-invasive alternative to arterial blood sampling. In simultaneous PET/magnetic resonance imaging (PET/MRI), high-resolution MRI angiographies can be used to define major arteries for correction of partial-volume effects (PVE) and point spread function (PSF) response in the PET data. The present study describes a fully automated method to obtain the image-derived input function (IDIF) in PET/MRI. Results are compared to those obtained by arterial blood sampling. To segment the trunk of the major arteries in the neck, a high-resolution time-of-flight MRI angiography was postprocessed by a vessel-enhancement filter based on the inertia tensor. Together with the measured PSF of the PET subsystem, the arterial mask was used for geometrical deconvolution, yielding the time-resolved activity concentration averaged over a major artery. The method was compared to manual arterial blood sampling at the hind leg of 21 sheep (animal stroke model) during measurement of blood flow with O15-water. Absolute quantification of activity concentration was compared after bolus passage during steady state, i.e., between 2.5- and 5-min post injection. Cerebral blood flow (CBF) values from blood sampling and IDIF were also compared. The cross-calibration factor obtained by comparing activity concentrations in blood samples and IDIF during steady state is 0.98 ± 0.10. In all examinations, the IDIF provided a much earlier and sharper bolus peak than in the time course of activity concentration obtained by arterial blood sampling. CBF using the IDIF was 22 % higher than CBF obtained by using the AIF yielded by blood sampling. The small deviation between arterial blood sampling and IDIF during steady state indicates that correction of PVE and PSF is possible with the method presented. The differences in bolus dynamics and, hence, CBF values can be explained by the
Methods for deconvolving sparse positive delta function series
International Nuclear Information System (INIS)
Trussell, H.J.; Schwalbe, L.A.
1981-01-01
Sparse delta function series occur as data in many chemical analyses and seismic methods. These original data are often sufficiently degraded by the recording instrument response that the individual delta function peaks are difficult to distinguish and measure. A method, which has been used to measure these peaks, is to fit a parameterized model by a nonlinear least-squares fitting algorithm. The deconvolution approaches described have the advantage of not requiring a parameterized point spread function, nor do they expect a fixed number of peaks. Two new methods are presented. The maximum power technique is reviewed. A maximum a posteriori technique is introduced. Results on both simulated and real data by the two methods are presented. The characteristics of the data can determine which method gives superior results. 5 figures
Improved parameter estimation for hydrological models using weighted object functions
Stein, A.; Zaadnoordijk, W.J.
1999-01-01
This paper discusses the sensitivity of calibration of hydrological model parameters to different objective functions. Several functions are defined with weights depending upon the hydrological background. These are compared with an objective function based upon kriging. Calibration is applied to
Electron beam lithographic modeling assisted by artificial intelligence technology
Nakayamada, Noriaki; Nishimura, Rieko; Miura, Satoru; Nomura, Haruyuki; Kamikubo, Takashi
2017-07-01
We propose a new concept of tuning a point-spread function (a "kernel" function) in the modeling of electron beam lithography using the machine learning scheme. Normally in the work of artificial intelligence, the researchers focus on the output results from a neural network, such as success ratio in image recognition or improved production yield, etc. In this work, we put more focus on the weights connecting the nodes in a convolutional neural network, which are naturally the fractions of a point-spread function, and take out those weighted fractions after learning to be utilized as a tuned kernel. Proof-of-concept of the kernel tuning has been demonstrated using the examples of proximity effect correction with 2-layer network, and charging effect correction with 3-layer network. This type of new tuning method can be beneficial to give researchers more insights to come up with a better model, yet it might be too early to be deployed to production to give better critical dimension (CD) and positional accuracy almost instantly.
Function modeling: improved raster analysis through delayed reading and function raster datasets
John S. Hogland; Nathaniel M. Anderson; J .Greg Jones
2013-01-01
Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space, often limiting the types of analyses that can be performed. To address this issue, we have developed Function Modeling. Function Modeling is a new modeling framework that streamlines the...
Jesus, Danilo A; Iskander, D Robert
2015-12-01
Ray tracing is a powerful technique to understand the light behavior through an intricate optical system such as that of a human eye. The prediction of visual acuity can be achieved through characteristics of an optical system such as the geometrical point spread function. In general, its precision depends on the number of discrete rays and the accurate surface representation of each eye's components. Recently, a method that simplifies calculation of the geometrical point spread function has been proposed for circularly symmetric systems [Appl. Opt.53, 4784 (2014)]. An extension of this method to 2D noncircularly symmetric systems is proposed. In this method, a two-dimensional ray tracing procedure for an arbitrary number of surfaces and arbitrary surface shapes has been developed where surfaces, rays, and refractive indices are all represented in functional forms being approximated by Chebyshev polynomials. The Liou and Brennan anatomically accurate eye model has been adapted and used for evaluating the method. Further, real measurements of the anterior corneal surface of normal, astigmatic, and keratoconic eyes were substituted for the first surface in the model. The results have shown that performing ray tracing, utilizing the two-dimensional Chebyshev function approximation, is possible for noncircularly symmetric models, and that such calculation can be performed with a newly created Chebfun toolbox.
Van Eck, D.
2009-01-01
In this paper, I discuss a methodology for the conversion of functional models between functional taxonomies developed by Kitamura et al. (2007) and Ookubo et al. (2007). They apply their methodology to the conversion of functional models described in terms of the Functional Basis taxonomy into
Mirror neurons: functions, mechanisms and models.
Oztop, Erhan; Kawato, Mitsuo; Arbib, Michael A
2013-04-12
Mirror neurons for manipulation fire both when the animal manipulates an object in a specific way and when it sees another animal (or the experimenter) perform an action that is more or less similar. Such neurons were originally found in macaque monkeys, in the ventral premotor cortex, area F5 and later also in the inferior parietal lobule. Recent neuroimaging data indicate that the adult human brain is endowed with a "mirror neuron system," putatively containing mirror neurons and other neurons, for matching the observation and execution of actions. Mirror neurons may serve action recognition in monkeys as well as humans, whereas their putative role in imitation and language may be realized in human but not in monkey. This article shows the important role of computational models in providing sufficient and causal explanations for the observed phenomena involving mirror systems and the learning processes which form them, and underlines the need for additional circuitry to lift up the monkey mirror neuron circuit to sustain the posited cognitive functions attributed to the human mirror neuron system. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Modeling Bamboo as a Functionally Graded Material
Silva, Emílio Carlos Nelli; Walters, Matthew C.; Paulino, Glaucio H.
2008-02-01
Natural fibers are promising for engineering applications due to their low cost. They are abundantly available in tropical and subtropical regions of the world, and they can be employed as construction materials. Among natural fibers, bamboo has been widely used for housing construction around the world. Bamboo is an optimized composite material which exploits the concept of Functionally Graded Material (FGM). Biological structures, such as bamboo, are composite materials that have complicated shapes and material distribution inside their domain, and thus the use of numerical methods such as the finite element method and multiscale methods such as homogenization, can help to further understanding of the mechanical behavior of these materials. The objective of this work is to explore techniques such as the finite element method and homogenization to investigate the structural behavior of bamboo. The finite element formulation uses graded finite elements to capture the varying material distribution through the bamboo wall. To observe bamboo behavior under applied loads, simulations are conducted considering a spatially-varying Young's modulus, an averaged Young's modulus, and orthotropic constitutive properties obtained from homogenization theory. The homogenization procedure uses effective, axisymmetric properties estimated from the spatially-varying bamboo composite. Three-dimensional models of bamboo cells were built and simulated under tension, torsion, and bending load cases.
School Teams up for SSP Functional Models
Pignolet, G.; Lallemand, R.; Celeste, A.; von Muldau, H.
2002-01-01
Space Solar Power systems appear increasingly as one of the major solutions to the upcoming global energy crisis, by collecting solar energy in space where this is most easy, and sending it by microwave beam to the surface of the planet, where the need for controlled energy is located. While fully operational systems are still decades away, the need for major development efforts is with us now. Yet, for many decision-makers and for most of the public, SSP often still sounds like science fiction. Six functional demonstration systems, based on the Japanese SPS-2000 concept, have been built as a result of a cooperation between France and Japan, and they are currently used extensively, in Japan, in Europe and in North America, for executive presentations as well as for public exhibitions. There is demand for more models, both for science museums and for use by energy dedicated groups, and a senior high school in La Reunion, France, has picked up the challenge to make the production of such models an integrated practical school project for pre-college students. In December 2001, the administration and the teachers of the school have evaluated the feasibility of the project and eventually taken the go decision for the school year 2002- 2003, when for education purposes a temporary "school business company" will be incorporated with the goal to study and manufacture a limited series of professional quality SSP demonstration models, and to sell them world- wide to institutions and advocacy groups concerned with energy problems and with the environment. The different sections of the school will act as the different services of an integrated business : based on the current existing models, the electronic section will redesign the energy management system and the microwave projector module, while the mechanical section of the school will adapt and re-conceive the whole packaging of the demonstrator. The French and foreign language sections will write up a technical manual for
Variance Function Partially Linear Single-Index Models1.
Lian, Heng; Liang, Hua; Carroll, Raymond J
2015-01-01
We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.
Data Acquisition for Quality Loss Function Modelling
DEFF Research Database (Denmark)
Pedersen, Søren Nygaard; Howard, Thomas J.
2016-01-01
Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given by t...
A DSM-based framework for integrated function modelling
DEFF Research Database (Denmark)
Eisenbart, Boris; Gericke, Kilian; Blessing, Lucienne T. M.
2017-01-01
an integrated function modelling framework, which specifically aims at relating between the different function modelling perspectives prominently addressed in different disciplines. It uses interlinked matrices based on the concept of DSM and MDM in order to facilitate cross-disciplinary modelling and analysis...
Bayesian Joint Modeling of Multiple Brain Functional Networks
Lukemire, Joshua; Kundu, Suprateek; Pagnoni, Giuseppe; Guo, Ying
2017-01-01
Brain function is organized in coordinated modes of spatio-temporal activity (functional networks) exhibiting an intrinsic baseline structure with variations under different experimental conditions. Existing approaches for uncovering such network structures typically do not explicitly model shared and differential patterns across networks, thus potentially reducing the detection power. We develop an integrative modeling approach for jointly modeling multiple brain networks across experimental...
Functional Curriculum Models for Secondary Students with Mild Mental Impairment
Bouck, Emily C.
2009-01-01
This paper analyzed 10 commercially available functional curriculum models designed for secondary students with mild-to-moderate mental impairment. The models were examined with respect to the inclusion of functional curriculum components, the domains and subdomains of adulthood, the materials identified by the model to be used to deliver the…
A Functional Test Platform for the Community Land Model
Energy Technology Data Exchange (ETDEWEB)
Xu, Yang [ORNL; Thornton, Peter E [ORNL; King, Anthony Wayne [ORNL; Steed, Chad A [ORNL; Gu, Lianhong [ORNL; Schuchart, Joseph [ORNL
2014-01-01
A functional test platform is presented to create direct linkages between site measurements and the process-based ecosystem model within the Community Earth System Models (CESM). The platform consists of three major parts: 1) interactive user interfaces, 2) functional test model and 3) observational datasets. It provides much needed integration interfaces for both field experimentalists and ecosystem modelers to improve the model s representation of ecosystem processes within the CESM framework without large software overhead.
Exact 2-point function in Hermitian matrix model
International Nuclear Information System (INIS)
Morozov, A.; Shakirov, Sh.
2009-01-01
J. Harer and D. Zagier have found a strikingly simple generating function [1,2] for exact (all-genera) 1-point correlators in the Gaussian Hermitian matrix model. In this paper we generalize their result to 2-point correlators, using Toda integrability of the model. Remarkably, this exact 2-point correlation function turns out to be an elementary function - arctangent. Relation to the standard 2-point resolvents is pointed out. Some attempts of generalization to 3-point and higher functions are described.
On Support Functions for the Development of MFM Models
DEFF Research Database (Denmark)
Heussen, Kai; Lind, Morten
2012-01-01
A modeling environment and methodology are necessary to ensure quality and reusability of models in any domain. For MFM in particular, as a tool for modeling complex systems, awareness has been increasing for this need. Introducing the context of modeling support functions, this paper provides...... a review of MFM applications, and contextualizes the model development with respect to process design and operation knowledge. Developing a perspective for an environment for MFM-oriented model- and application-development a tool-chain is outlined and relevant software functions are discussed....... With a perspective on MFM-modeling for existing processes and automation design, modeling stages and corresponding formal model properties are identified. Finally, practically feasible support functions and model-checks to support the model-development are suggested....
Modelling Strategies for Functional Magnetic Resonance Imaging
DEFF Research Database (Denmark)
Madsen, Kristoffer Hougaard
2009-01-01
and generalisations to higher order arrays are considered. Additionally, an application of the natural conjugate prior for supervised learning in the general linear model to efficiently incorporate prior information for supervised analysis is presented. Further extensions include methods to model nuisance effects...... in fMIR data thereby suppressing noise for both supervised and unsupervised analysis techniques....
Functional modeling of neural-glial interaction
DEFF Research Database (Denmark)
Postnov, D.E.; Ryazanova, L.S.; Sosnovtseva, Olga
2007-01-01
We propose a generalized mathematical model for a small neural-glial ensemble. The model incorporates subunits of the tripartite synapse that includes a presynaptic neuron, the synaptic terminal itself, a postsynaptic neuron, and a glial cell. The glial cell is assumed to be activated via two...... different pathways: (i) the fast increase of intercellular [K+] produced by the spiking activity of the postsynaptic neuron, and (ii) the slow production of a mediator triggered by the synaptic activity. Our model predicts the long-term potentiation of the postsynaptic neuron as well as various [Ca2...
Mechanical modeling of skeletal muscle functioning
van der Linden, B.J.J.J.
1998-01-01
For movement of body or body segments is combined effort needed of the central nervous system and the muscular-skeletal system. This thesis deals with the mechanical functioning of skeletal muscle. That muscles come in a large variety of geometries, suggest the existence of a relation between muscle
Density functional theory and multiscale materials modeling
Indian Academy of Sciences (India)
In the macroscopic length scale, however, matter is usually treated as a continuous medium and a description using local mass density, energy density and other related density functions has been found to be quite appropriate. A unique single unified theoretical framework that emerges through the density concept at these ...
The Use of Function/Means Trees for Modelling Technical, Semantic and Business Functions
DEFF Research Database (Denmark)
Robotham, Antony John
2000-01-01
This paper considers the feasibility of using the function/means tree to create a single tree for a complete motor vehicle. It is argued that function/means trees can be used for modelling technical and semantic functions, but it is an inappropriate method for business functions when one tree...... of the vehicle is required. Life cycle modelling provides an effective means for determining all the required purpose functions and is considered a more effective method than the function/means tree for this task when the structure and mode of operation of the vehicle is well defined and understood....
The characteristic function of rough Heston models
Euch, Omar El; Rosenbaum, Mathieu
2016-01-01
It has been recently shown that rough volatility models, where the volatility is driven by a fractional Brownian motion with small Hurst parameter, provide very relevant dynamics in order to reproduce the behavior of both historical and implied volatilities. However, due to the non-Markovian nature of the fractional Brownian motion, they raise new issues when it comes to derivatives pricing. Using an original link between nearly unstable Hawkes processes and fractional volatility models, we c...
Genetic Prediction Models and Heritability Estimates for Functional ...
African Journals Online (AJOL)
This paper discusses these methodologies and their advantages and disadvantages. Heritability estimates obtained from these models are also reviewed. Linear methodologies can model binary and actual longevity, while RR and TM methodologies model binary survival. PH procedures model the hazard function of a cow ...
A Functional Model of the Aesthetic Response
Directory of Open Access Journals (Sweden)
Daniel Conrad
2010-01-01
Full Text Available In a process of somatic evolution, the brain semi-randomly generates initially-unstable neural circuits that are selectively stabilized if they succeed in making sense out of raw sensory input. The human aesthetic response serves the function of stabilizing the circuits that successfully mediate perception and interpretation, making those faculties more agile, conferring selective advantage. It is triggered by structures in art and nature that provoke the making of sense. Art is deliberate human action aimed at triggering the aesthetic response in others; thus, if successful, it serves the same function of making perception and interpretation more agile. These few principles initiate a cascade of emergent phenomena which account for many observed qualities of aesthetics, including universality and idiosyncrasy of taste, the relevance of artists’ intentions, the virtues of openness and resonance, the dysfunction of formulaic art, and the fact that methods of art correspond to modes of perceptual transformation.
Density functional theory and multiscale materials modeling*
Indian Academy of Sciences (India)
Unknown
Here the hardness kernel (Berkowitz et al 1985;. Ghosh 1990), ηµν(r, r′), represents the energy functional derivative . )( )( ],[. ),(. 2......... ′. =′ r r rr ν. µ β α. µν δρ δρ ρρ δ η. F. (27). We now specialize to the case of a set of atoms (say, M in number) located at the fixed positions {Ri} corre- sponding to a ...
Resnick, Barbara; Gruber-Baldini, Ann L; Hicks, Gregory; Ostir, Glen; Klinedinst, N Jennifer; Orwig, Denise; Magaziner, Jay
2016-07-01
Measurement of physical function post hip fracture has been conceptualized using multiple different measures. This study tested a comprehensive measurement model of physical function. This was a descriptive secondary data analysis including 168 men and 171 women post hip fracture. Using structural equation modeling, a measurement model of physical function which included grip strength, activities of daily living, instrumental activities of daily living, and performance was tested for fit at 2 and 12 months post hip fracture, and among male and female participants. Validity of the measurement model of physical function was evaluated based on how well the model explained physical activity, exercise, and social activities post hip fracture. The measurement model of physical function fit the data. The amount of variance the model or individual factors of the model explained varied depending on the activity. Decisions about the ideal way in which to measure physical function should be based on outcomes considered and participants. The measurement model of physical function is a reliable and valid method to comprehensively measure physical function across the hip fracture recovery trajectory. © 2015 Association of Rehabilitation Nurses.
Density functional theory and multiscale materials modeling
Indian Academy of Sciences (India)
One of the vital ingredients in the theoretical tools useful in materials modeling at all the length scales of interest is the concept of density. In the microscopic length scale, it is the electron density that has played a major role in providing a deeper understanding of chemical binding in atoms, molecules and solids.
Local and Global Function Model of the Liver
Energy Technology Data Exchange (ETDEWEB)
Wang, Hesheng, E-mail: hesheng@umich.edu [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Feng, Mary [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Jackson, Andrew [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Ten Haken, Randall K.; Lawrence, Theodore S. [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Cao, Yue [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Department of Radiology, University of Michigan, Ann Arbor, Michigan (United States); Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan (United States)
2016-01-01
Purpose: To develop a local and global function model in the liver based on regional and organ function measurements to support individualized adaptive radiation therapy (RT). Methods and Materials: A local and global model for liver function was developed to include both functional volume and the effect of functional variation of subunits. Adopting the assumption of parallel architecture in the liver, the global function was composed of a sum of local function probabilities of subunits, varying between 0 and 1. The model was fit to 59 datasets of liver regional and organ function measures from 23 patients obtained before, during, and 1 month after RT. The local function probabilities of subunits were modeled by a sigmoid function in relating to MRI-derived portal venous perfusion values. The global function was fitted to a logarithm of an indocyanine green retention rate at 15 minutes (an overall liver function measure). Cross-validation was performed by leave-m-out tests. The model was further evaluated by fitting to the data divided according to whether the patients had hepatocellular carcinoma (HCC) or not. Results: The liver function model showed that (1) a perfusion value of 68.6 mL/(100 g · min) yielded a local function probability of 0.5; (2) the probability reached 0.9 at a perfusion value of 98 mL/(100 g · min); and (3) at a probability of 0.03 [corresponding perfusion of 38 mL/(100 g · min)] or lower, the contribution to global function was lost. Cross-validations showed that the model parameters were stable. The model fitted to the data from the patients with HCC indicated that the same amount of portal venous perfusion was translated into less local function probability than in the patients with non-HCC tumors. Conclusions: The developed liver function model could provide a means to better assess individual and regional dose-responses of hepatic functions, and provide guidance for individualized treatment planning of RT.
Predictive assessment of models for dynamic functional connectivity
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Schmidt, Mikkel Nørgaard; Madsen, Kristoffer Hougaard
2018-01-01
In neuroimaging, it has become evident that models of dynamic functional connectivity (dFC), which characterize how intrinsic brain organization changes over time, can provide a more detailed representation of brain function than traditional static analyses. Many dFC models in the literature...... represent functional brain networks as a meta-stable process with a discrete number of states; however, there is a lack of consensus on how to perform model selection and learn the number of states, as well as a lack of understanding of how different modeling assumptions influence the estimated state...
Theory of model Hamiltonians and method of functional integration
International Nuclear Information System (INIS)
Popov, V.N.
1990-01-01
Results on application of functional integration method to statistical physics systems with model Hamiltonians Dicke and Bardeen-Cooper-Schrieffer (BCS) are presented. Representations of statistical sums of these functional integration models are obtained. Asymptotic formulae (in N → ∞ thermodynamic range) for statistical sums of various modifications of the Dicke model as well as for the Green functions and Bose-excitations collective spectrum are exactly proved. Analogous results without exact substantiation are obtained for statistical sums and spectrum of Bose-excitations of the BCS model. 21 refs
A model of synthesis based on functional reasoning
DEFF Research Database (Denmark)
Hansen, Claus Thorp; Zavbi, R.
2002-01-01
In this paper we propose a model of how to carry out functional reasoning. The model is based on the domain theory, and it links the stepwise determination of the artefact´s characteristics during the design process to different ways of carrying out functional reasoning found in the literature....... The model proposes of a set of the mental objects and a number of ways to carry out functional reasoning available to the engineering designer. The result of the research presented in this paper is the building of a hypothesis "in the form of a model" with explanatory power....
Modelling of functional systems of managerial accounting
Directory of Open Access Journals (Sweden)
O.V. Fomina
2017-12-01
Full Text Available The modern stage of managerial accounting development takes place under the powerful influence of managerial innovations. The article aimed at the development of integrational model of budgeting and the system of balanced indices in the system of managerial accounting that will contribute the increasing of relevance for making managerial decisions by managers of different levels management. As a result of the study the author proposed the highly pragmatical integration model of budgeting and system of the balanced indices in the system of managerial accounting, which is realized by the development of the system of gathering, consolidation, analysis, and interpretation of financial and nonfinancial information, contributes the increasing of relevance for making managerial decisions on the base of coordination and effective and purpose orientation both strategical and operative resources of an enterprise. The effective integrational process of the system components makes it possible to distribute limited resources rationally taking into account prospective purposes and strategic initiatives, to carry
Functional summary statistics for the Johnson-Mehl model
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
The Johnson-Mehl germination-growth model is a spatio-temporal point process model which among other things have been used for the description of neurotransmitters datasets. However, for such datasets parametric Johnson-Mehl models fitted by maximum likelihood have yet not been evaluated by means...... of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....
Evaluation of a differentiation model of preschoolers’ executive functions
Howard, Steven J.; Okely, Anthony D.; Ellis, Yvonne G.
2015-01-01
Despite the prominent role of executive functions in children’s emerging competencies, there remains debate regarding the structure and development of executive functions. In an attempt to reconcile these discrepancies, a differentiation model of executive function development was evaluated in the early years using 6-month age groupings. Specifically, 281 preschoolers completed measures of working memory, inhibition, and shifting. Results contradicted suggestions that executive functions foll...
Evaluation of a differentiation model of preschoolers’ executive functions
Howard, Steven J.; Okely, Anthony D.; Ellis, Yvonne G.
2015-01-01
Despite the prominent role of executive functions in children’s emerging competencies, there remains debate regarding the structure and development of executive functions. In an attempt to reconcile these discrepancies, a differentiation model of executive function development was evaluated in the early years using 6-month age groupings. Specifically, 281 preschoolers completed measures of working memory, inhibition, and shifting. Results contradicted suggestions that executive functions follow a single trajectory of progressive separation in childhood, instead suggesting that these functions may undergo a period of integration in the preschool years. These results highlight potential problems with current practices and theorizing in executive function research. PMID:25852603
Evaluation of a differentiation model of preschoolers' executive functions.
Howard, Steven J; Okely, Anthony D; Ellis, Yvonne G
2015-01-01
Despite the prominent role of executive functions in children's emerging competencies, there remains debate regarding the structure and development of executive functions. In an attempt to reconcile these discrepancies, a differentiation model of executive function development was evaluated in the early years using 6-month age groupings. Specifically, 281 preschoolers completed measures of working memory, inhibition, and shifting. Results contradicted suggestions that executive functions follow a single trajectory of progressive separation in childhood, instead suggesting that these functions may undergo a period of integration in the preschool years. These results highlight potential problems with current practices and theorizing in executive function research.
Multiloop functional renormalization group for general models
Kugler, Fabian B.; von Delft, Jan
2018-02-01
We present multiloop flow equations in the functional renormalization group (fRG) framework for the four-point vertex and self-energy, formulated for a general fermionic many-body problem. This generalizes the previously introduced vertex flow [F. B. Kugler and J. von Delft, Phys. Rev. Lett. 120, 057403 (2018), 10.1103/PhysRevLett.120.057403] and provides the necessary corrections to the self-energy flow in order to complete the derivative of all diagrams involved in the truncated fRG flow. Due to its iterative one-loop structure, the multiloop flow is well suited for numerical algorithms, enabling improvement of many fRG computations. We demonstrate its equivalence to a solution of the (first-order) parquet equations in conjunction with the Schwinger-Dyson equation for the self-energy.
Improved analyses using function datasets and statistical modeling
John S. Hogland; Nathaniel M. Anderson
2014-01-01
Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space and have limited statistical functionality and machine learning algorithms. To address this issue, we developed a new modeling framework using C# and ArcObjects and integrated that framework...
Partition function of nearest neighbour Ising models: Some new ...
Indian Academy of Sciences (India)
Administrator
While the formula- tion of the partition function pertaining to one- dimensional nearest neighbour Ising models is pedagogical and straight-forward,. 4 the same is not true for the two-dimensional Ising models. The cele- brated solution of Onsager. 5 for the two-dimensional. Ising model at H = 0 led to the detailed analysis of.
Functional Modelling for Fault Diagnosis and its application for NPP
DEFF Research Database (Denmark)
Lind, Morten; Zhang, Xinxin
2014-01-01
The paper presents functional modelling and its application for diagnosis in nuclear power plants.Functional modelling is defined and it is relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demon......The paper presents functional modelling and its application for diagnosis in nuclear power plants.Functional modelling is defined and it is relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed....... The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool the MFM Suite. MFM applications in nuclear power systems are described by two examples a PWR and a FBRreactor. The PWR example show how MFM can be used to model and reason about...
The basis function approach for modeling autocorrelation in ecological data.
Hefley, Trevor J; Broms, Kristin M; Brost, Brian M; Buderman, Frances E; Kay, Shannon L; Scharf, Henry R; Tipton, John R; Williams, Perry J; Hooten, Mevin B
2017-03-01
Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data. © 2016 by the Ecological Society of America.
Deep inelastic structure functions in the chiral bag model
Energy Technology Data Exchange (ETDEWEB)
Sanjose, V. (Valencia Univ. (Spain). Dept. de Didactica de las Ciencias Experimentales); Vento, V. (Valencia Univ. (Spain). Dept. de Fisica Teorica; Centro Mixto CSIC/Valencia Univ., Valencia (Spain). Inst. de Fisica Corpuscular)
1989-10-02
We calculate the structure functions for deep inelastic scattering on baryons in the cavity approximation to the chiral bag model. The behavior of these structure functions is analyzed in the Bjorken limit. We conclude that scaling is satisfied, but not Regge behavior. A trivial extension as a parton model can be achieved by introducing the structure function for the pion in a convolution picture. In this extended version of the model not only scaling but also Regge behavior is satisfied. Conclusions are drawn from the comparison of our results with experimental data. (orig.).
Composite spectral functions for solving Volterra's population model
International Nuclear Information System (INIS)
Ramezani, M.; Razzaghi, M.; Dehghan, M.
2007-01-01
An approximate method for solving Volterra's population model for population growth of a species in a closed system is proposed. Volterra's model is a nonlinear integro-differential equation, where the integral term represents the effect of toxin. The approach is based upon composite spectral functions approximations. The properties of composite spectral functions consisting of few terms of orthogonal functions are presented and are utilized to reduce the solution of the Volterra's model to the solution of a system of algebraic equations. The method is easy to implement and yields very accurate result
Functional Characterization of a Porcine Emphysema Model
DEFF Research Database (Denmark)
Bruun, Camilla Sichlau; Jensen, Louise Kruse; Leifsson, Páll Skuli
2013-01-01
phenotypes in humans. Also, the catalytic activities of metalloproteinases (MMPs) are central in the pathogenesis of emphysema/COPD. Especially MMP9, but also MMP2, MMP7, and MMP12 seem to be involved in human emphysema. MMP12−/− mice are protected from smoke-induced emphysema. ITGB6−/− mice spontaneously...... the expression of MMP2, MMP7, MMP9, MMP12, and TGF-β1 by quantitative PCR (qPCR). In addition, immunohistochemical stainings of the lungs with SP-B, SP-C, MMP9, and MMP12 antibodies were performed. The haematologic/immunologic status of the pigs also was studied.The qPCR study showed no difference between pigs...... develop age-related lung emphysema due to lack of ITGB6-TGF-β1 regulation of the MMP12 expression.A mutated pig phenotype characterized by age-related lung emphysema and resembling the ITGB6−/− mouse has been described previously. To investigate the emphysema pathogenesis in this pig model, we examined...
BioModels: Content, Features, Functionality, and Use
Juty, N; Ali, R; Glont, M; Keating, S; Rodriguez, N; Swat, MJ; Wimalaratne, SM; Hermjakob, H; Le Novère, N; Laibe, C; Chelliah, V
2015-01-01
BioModels is a reference repository hosting mathematical models that describe the dynamic interactions of biological components at various scales. The resource provides access to over 1,200 models described in literature and over 140,000 models automatically generated from pathway resources. Most model components are cross-linked with external resources to facilitate interoperability. A large proportion of models are manually curated to ensure reproducibility of simulation results. This tutorial presents BioModels' content, features, functionality, and usage. PMID:26225232
Beretvas, S. Natasha; Walker, Cindy M.
2012-01-01
This study extends the multilevel measurement model to handle testlet-based dependencies. A flexible two-level testlet response model (the MMMT-2 model) for dichotomous items is introduced that permits assessment of differential testlet functioning (DTLF). A distinction is made between this study's conceptualization of DTLF and that of…
Multinomial-exponential reliability function: a software reliability model
International Nuclear Information System (INIS)
Saiz de Bustamante, Amalio; Saiz de Bustamante, Barbara
2003-01-01
The multinomial-exponential reliability function (MERF) was developed during a detailed study of the software failure/correction processes. Later on MERF was approximated by a much simpler exponential reliability function (EARF), which keeps most of MERF mathematical properties, so the two functions together makes up a single reliability model. The reliability model MERF/EARF considers the software failure process as a non-homogeneous Poisson process (NHPP), and the repair (correction) process, a multinomial distribution. The model supposes that both processes are statistically independent. The paper discusses the model's theoretical basis, its mathematical properties and its application to software reliability. Nevertheless it is foreseen model applications to inspection and maintenance of physical systems. The paper includes a complete numerical example of the model application to a software reliability analysis
Computational Models for Calcium-Mediated Astrocyte Functions
Directory of Open Access Journals (Sweden)
Tiina Manninen
2018-04-01
Full Text Available The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro, but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop
Importance of predictor variables for models of chemical function
U.S. Environmental Protection Agency — Importance of random forest predictors for all classification models of chemical function. This dataset is associated with the following publication: Isaacs , K., M....
Commonsense Psychology and the Functional Requirements of Cognitive Models
National Research Council Canada - National Science Library
Gordon, Andrew S
2005-01-01
In this paper we argue that previous models of cognitive abilities (e.g. memory, analogy) have been constructed to satisfy functional requirements of implicit commonsense psychological theories held by researchers and nonresearchers alike...
Applying Functional Modeling for Accident Management of Nuclear Power Plant
DEFF Research Database (Denmark)
Lind, Morten; Zhang, Xinxin
2014-01-01
The paper investigate applications of functional modeling for accident management in complex industrial plant with special reference to nuclear power production. Main applications for information sharing among decision makers and decision support are identified. An overview of Multilevel Flow...
Applying Functional Modeling for Accident Management of Nucler Power Plant
DEFF Research Database (Denmark)
Lind, Morten; Zhang, Xinxin
2014-01-01
The paper investigates applications of functional modeling for accident management in complex industrial plant with special reference to nuclear power production. Main applications for information sharing among decision makers and decision support are identified. An overview of Multilevel Flow...
FUNCTIONAL MODELLING FOR FAULT DIAGNOSIS AND ITS APPLICATION FOR NPP
Directory of Open Access Journals (Sweden)
MORTEN LIND
2014-12-01
Full Text Available The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM, which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.
Global sensitivity analysis of computer models with functional inputs
International Nuclear Information System (INIS)
Iooss, Bertrand; Ribatet, Mathieu
2009-01-01
Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.
Generalized Functional Linear Models With Semiparametric Single-Index Interactions
Li, Yehua
2010-06-01
We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.
A no extensive statistical model for the nucleon structure function
Energy Technology Data Exchange (ETDEWEB)
Trevisan, Luis A. [Departamento de Matematica e Estatistica, Universidade Estadual de Ponta Grossa, 84010-790, Ponta Grossa, PR (Brazil); Mirez, Carlos [Instituto de Ciencia, Engenharia e Tecnologia - ICET, Universidade Federal dos Vales do Jequitinhonha e Mucuri - UFVJM, Campus do Mucuri, Rua do Cruzeiro 01, Jardim Sao Paulo, 39803-371, Teofilo Otoni, Minas Gerais (Brazil)
2013-03-25
We studied an application of nonextensive thermodynamics to describe the structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and two chemical potentials given by the corresponding up (u) and down (d) quark normalization in the nucleon.
How to use COSMIC Functional Size in Effort Estimation Models?
Gencel, Cigdem
2008-01-01
Although Functional Size Measurement (FSM) methods have become widely used by the software organizations, the functional size based effort estimation still needs further investigation. Most of the studies on effort estimation consider total functional size of the software as the primary input to estimation models and they mostly focus on identifying the project parameters which might have a significant effect on the size-effort relationship. This study brings suggestions on how to use COSMIC ...
Improved Wave-vessel Transfer Functions by Uncertainty Modelling
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam; Fønss Bach, Kasper; Iseki, Toshio
2016-01-01
This paper deals with uncertainty modelling of wave-vessel transfer functions used to calculate or predict wave-induced responses of a ship in a seaway. Although transfer functions, in theory, can be calculated to exactly reflect the behaviour of the ship when exposed to waves, uncertainty in input...
Optimisation of Transfer Function Models using Genetic Algorithms ...
African Journals Online (AJOL)
In order to obtain an optimum transfer function estimate, open source software based on genetic algorithm was developed. The software was developed with Visual Basic programming language. In order to test the software, a transfer function model was developed from data obtained from industry. The forecast obtained ...
Features of Functioning the Integrated Building Thermal Model
Directory of Open Access Journals (Sweden)
Morozov Maxim N.
2017-01-01
Full Text Available A model of the building heating system, consisting of energy source, a distributed automatic control system, elements of individual heating unit and heating system is designed. Application Simulink of mathematical package Matlab is selected as a platform for the model. There are the specialized application Simscape libraries in aggregate with a wide range of Matlab mathematical tools allow to apply the “acausal” modeling concept. Implementation the “physical” representation of the object model gave improving the accuracy of the models. Principle of operation and features of the functioning of the thermal model is described. The investigations of building cooling dynamics were carried out.
Asymptotic Optimality of Estimating Function Estimator for CHARN Model
Directory of Open Access Journals (Sweden)
Tomoyuki Amano
2012-01-01
Full Text Available CHARN model is a famous and important model in the finance, which includes many financial time series models and can be assumed as the return processes of assets. One of the most fundamental estimators for financial time series models is the conditional least squares (CL estimator. However, recently, it was shown that the optimal estimating function estimator (G estimator is better than CL estimator for some time series models in the sense of efficiency. In this paper, we examine efficiencies of CL and G estimators for CHARN model and derive the condition that G estimator is asymptotically optimal.
Cost damping and functional form in transport models
DEFF Research Database (Denmark)
Rich, Jeppe; Mabit, Stefan Lindhard
2016-01-01
take different forms and be represented as a non-linear-in-parameter form such as the well-known Box–Cox function. However, it could also be specified as non-linear-in-cost but linear-in-parameter forms, which are easier to estimate and improve model fit without increasing the number of parameters....... The specific contributions of the paper are as follows. Firstly, we discuss the phenomenon of cost damping in details and specifically why it occurs. Secondly, we provide a test of damping and an easy assessment of the (linear) damping rate for any variable by estimating two auxiliary linear models. This turns......Transport models allowing for cost damping are characterised by marginally decreasing cost sensitivities in demand. As a result, cost damping is a model extension of the simple linear-in-cost model requiring an appropriate non-linear link function between utility and cost. The link function may...
Likelihood functions for state space models with diffuse initial conditions
Koopman, S.J.; Shephard, N.; de Vos, A.F.
2010-01-01
State space models with non-stationary processes and/or fixed regression effects require a state vector with diffuse initial conditions. Different likelihood functions can be adopted for the estimation of parameters in time-series models with diffuse initial conditions. In this article, we consider
Likelihood functions for state space models with diffuse initial conditions
Francke, M.K.; Koopmans, S.J.; de Vos, A.F.
2008-01-01
State space models with nonstationary processes and fixed regression effects require a state vector with diffuse initial conditions. Different likelihood functions can be adopted for the estimation of parameters in time series models with diffuse initial conditions. In this paper we consider
Invention software support by integrating function and mathematical modeling
Chechurin, L.S.; Wits, Wessel Willems; Bakker, H.M.
2015-01-01
New idea generation is imperative for successful product innovation and technology development. This paper presents the development of a novel type of invention support software. The support tool integrates both function modeling and mathematical modeling, thereby enabling quantitative analyses on a
Predictive assessment of models for dynamic functional connectivity.
Nielsen, Søren F V; Schmidt, Mikkel N; Madsen, Kristoffer H; Mørup, Morten
2018-05-01
In neuroimaging, it has become evident that models of dynamic functional connectivity (dFC), which characterize how intrinsic brain organization changes over time, can provide a more detailed representation of brain function than traditional static analyses. Many dFC models in the literature represent functional brain networks as a meta-stable process with a discrete number of states; however, there is a lack of consensus on how to perform model selection and learn the number of states, as well as a lack of understanding of how different modeling assumptions influence the estimated state dynamics. To address these issues, we consider a predictive likelihood approach to model assessment, where models are evaluated based on their predictive performance on held-out test data. Examining several prominent models of dFC (in their probabilistic formulations) we demonstrate our framework on synthetic data, and apply it on two real-world examples: a face recognition EEG experiment and resting-state fMRI. Our results evidence that both EEG and fMRI are better characterized using dynamic modeling approaches than by their static counterparts, but we also demonstrate that one must be cautious when interpreting dFC because parameter settings and modeling assumptions, such as window lengths and emission models, can have a large impact on the estimated states and consequently on the interpretation of the brain dynamics. Copyright © 2018 Elsevier Inc. All rights reserved.
Density Functional Theory and Materials Modeling at Atomistic Length Scales
Directory of Open Access Journals (Sweden)
Swapan K. Ghosh
2002-04-01
Full Text Available Abstract: We discuss the basic concepts of density functional theory (DFT as applied to materials modeling in the microscopic, mesoscopic and macroscopic length scales. The picture that emerges is that of a single unified framework for the study of both quantum and classical systems. While for quantum DFT, the central equation is a one-particle Schrodinger-like Kohn-Sham equation, the classical DFT consists of Boltzmann type distributions, both corresponding to a system of noninteracting particles in the field of a density-dependent effective potential, the exact functional form of which is unknown. One therefore approximates the exchange-correlation potential for quantum systems and the excess free energy density functional or the direct correlation functions for classical systems. Illustrative applications of quantum DFT to microscopic modeling of molecular interaction and that of classical DFT to a mesoscopic modeling of soft condensed matter systems are highlighted.
Model Penentuan Nilai Target Functional Requirement Berbasis Utilitas
Directory of Open Access Journals (Sweden)
Cucuk Nur Rosyidi
2012-01-01
Full Text Available In a product design and development process, a designer faces a problem to decide functional requirement (FR target values. That decision is made under a risk since it is conducted in the early design phase using incomplete information. Utility function can be used to reflect the decision maker attitude towards the risk in making such decision. In this research, we develop a utility-based model to determine FR target values using quadratic utility function and information from Quality Function Deployment (QFD. A pencil design is used as a numerical example using quadratic utility function for each FR. The model can be applied for balancing customer and designer interest in determining FR target values.
Evaluation-Function-based Model-free Adaptive Fuzzy Control
Directory of Open Access Journals (Sweden)
Agus Naba
2016-12-01
Full Text Available Designs of adaptive fuzzy controllers (AFC are commonly based on the Lyapunov approach, which requires a known model of the controlled plant. They need to consider a Lyapunov function candidate as an evaluation function to be minimized. In this study these drawbacks were handled by designing a model-free adaptive fuzzy controller (MFAFC using an approximate evaluation function defined in terms of the current state, the next state, and the control action. MFAFC considers the approximate evaluation function as an evaluative control performance measure similar to the state-action value function in reinforcement learning. The simulation results of applying MFAFC to the inverted pendulum benchmark veriﬁed the proposed scheme’s efficacy.
Modelling the Impact of Soil Management on Soil Functions
Vogel, H. J.; Weller, U.; Rabot, E.; Stößel, B.; Lang, B.; Wiesmeier, M.; Urbanski, L.; Wollschläger, U.
2017-12-01
Due to an increasing soil loss and an increasing demand for food and energy there is an enormous pressure on soils as the central resource for agricultural production. Besides the importance of soils for biomass production there are other essential soil functions, i.e. filter and buffer for water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these functions have a direct feed back to biogeochemical cycles and climate. To render agricultural production efficient and sustainable we need to develop model tools that are capable to predict quantitatively the impact of a multitude of management measures on these soil functions. These functions are considered as emergent properties produced by soils as complex systems. The major challenge is to handle the multitude of physical, chemical and biological processes interacting in a non-linear manner. A large number of validated models for specific soil processes are available. However, it is not possible to simulate soil functions by coupling all the relevant processes at the detailed (i.e. molecular) level where they are well understood. A new systems perspective is required to evaluate the ensemble of soil functions and their sensitivity to external forcing. Another challenge is that soils are spatially heterogeneous systems by nature. Soil processes are highly dependent on the local soil properties and, hence, any model to predict soil functions needs to account for the site-specific conditions. For upscaling towards regional scales the spatial distribution of functional soil types need to be taken into account. We propose a new systemic model approach based on a thorough analysis of the interactions between physical, chemical and biological processes considering their site-specific characteristics. It is demonstrated for the example of soil compaction and the recovery of soil structure, water capacity and carbon stocks as a result of plant growth and biological
Nonparametric modeling of dynamic functional connectivity in fmri data
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Madsen, Kristoffer H.; Røge, Rasmus
2015-01-01
dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a nonparametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted......Dynamic functional connectivity (FC) has in recent years become a topic of interest in the neuroimaging community. Several models and methods exist for both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), and the results point towards the conclusion that FC exhibits...... in Bayesian statistical modeling we use the predictive likelihood to investigate if the model can discriminate between a motor task and rest both within and across subjects. We further investigate what drives dynamic states using the model on the entire data collated across subjects and task/rest. We find...
Partially linear varying coefficient models stratified by a functional covariate
Maity, Arnab
2012-10-01
We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric component and a profiling estimator of the parametric component of the model and derive their asymptotic properties. Specifically, we show the consistency of the nonparametric functional estimates and derive the asymptotic expansion of the estimates of the parametric component. We illustrate the performance of our methodology using a simulation study and a real data application.
Functional State Modelling of Cultivation Processes: Dissolved Oxygen Limitation State
Directory of Open Access Journals (Sweden)
Olympia Roeva
2015-04-01
Full Text Available A new functional state, namely dissolved oxygen limitation state for both bacteria Escherichia coli and yeast Saccharomyces cerevisiae fed-batch cultivation processes is presented in this study. Functional state modelling approach is applied to cultivation processes in order to overcome the main disadvantages of using global process model, namely complex model structure and a big number of model parameters. Alongwith the newly introduced dissolved oxygen limitation state, second acetate production state and first acetate production state are recognized during the fed-batch cultivation of E. coli, while mixed oxidative state and first ethanol production state are recognized during the fed-batch cultivation of S. cerevisiae. For all mentioned above functional states both structural and parameter identification is here performed based on experimental data of E. coli and S. cerevisiae fed-batch cultivations.
Embedded systems development from functional models to implementations
Zeng, Haibo; Natale, Marco; Marwedel, Peter
2014-01-01
This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems. The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results. Describes integration of heterogeneous models; Discusses synthesis of task model implementations and code implementations; Compares model-based design vs. model-driven approaches; Explains how to enforce correctness by construction in the functional and time domains; Includes optimization techniques for control performance.
Quark fragmentation functions in NJL-jet model
Bentz, Wolfgang; Matevosyan, Hrayr; Thomas, Anthony
2014-09-01
We report on our studies of quark fragmentation functions in the Nambu-Jona-Lasinio (NJL) - jet model. The results of Monte-Carlo simulations for the fragmentation functions to mesons and nucleons, as well as to pion and kaon pairs (dihadron fragmentation functions) are presented. The important role of intermediate vector meson resonances for those semi-inclusive deep inelastic production processes is emphasized. Our studies are very relevant for the extraction of transverse momentum dependent quark distribution functions from measured scattering cross sections. We report on our studies of quark fragmentation functions in the Nambu-Jona-Lasinio (NJL) - jet model. The results of Monte-Carlo simulations for the fragmentation functions to mesons and nucleons, as well as to pion and kaon pairs (dihadron fragmentation functions) are presented. The important role of intermediate vector meson resonances for those semi-inclusive deep inelastic production processes is emphasized. Our studies are very relevant for the extraction of transverse momentum dependent quark distribution functions from measured scattering cross sections. Supported by Grant in Aid for Scientific Research, Japanese Ministry of Education, Culture, Sports, Science and Technology, Project No. 20168769.
Driver steering model for closed-loop steering function analysis
Bolia, Pratiksh; Weiskircher, Thomas; Müller, Steffen
2014-05-01
In this paper, a two level preview driver steering control model for the use in numerical vehicle dynamics simulation is introduced. The proposed model is composed of cascaded control loops: The outer loop is the path following layer based on potential field framework. The inner loop tries to capture the driver's physical behaviour. The proposed driver model allows easy implementation of different driving situations to simulate a wide range of different driver types, moods and vehicle types. The expediency of the proposed driver model is shown with the help of developed driver steering assist (DSA) function integrated with a conventional series production (Electric Power steering System with rack assist servo unit) system. With the help of the DSA assist function, the driver is prevented from over saturating the front tyre forces and loss of stability and controllability during cornering. The simulation results show different driver reactions caused by the change in the parameters or properties of the proposed driver model if the DSA assist function is activated. Thus, the proposed driver model is useful for the advanced driver steering and vehicle stability assist function evaluation in the early stage of vehicle dynamics handling and stability evaluation.
Towards refactoring the Molecular Function Ontology with a UML profile for function modeling.
Burek, Patryk; Loebe, Frank; Herre, Heinrich
2017-10-04
Gene Ontology (GO) is the largest resource for cataloging gene products. This resource grows steadily and, naturally, this growth raises issues regarding the structure of the ontology. Moreover, modeling and refactoring large ontologies such as GO is generally far from being simple, as a whole as well as when focusing on certain aspects or fragments. It seems that human-friendly graphical modeling languages such as the Unified Modeling Language (UML) could be helpful in connection with these tasks. We investigate the use of UML for making the structural organization of the Molecular Function Ontology (MFO), a sub-ontology of GO, more explicit. More precisely, we present a UML dialect, called the Function Modeling Language (FueL), which is suited for capturing functions in an ontologically founded way. FueL is equipped, among other features, with language elements that arise from studying patterns of subsumption between functions. We show how to use this UML dialect for capturing the structure of molecular functions. Furthermore, we propose and discuss some refactoring options concerning fragments of MFO. FueL enables the systematic, graphical representation of functions and their interrelations, including making information explicit that is currently either implicit in MFO or is mainly captured in textual descriptions. Moreover, the considered subsumption patterns lend themselves to the methodical analysis of refactoring options with respect to MFO. On this basis we argue that the approach can increase the comprehensibility of the structure of MFO for humans and can support communication, for example, during revision and further development.
REVIEW: Zebrafish: A Renewed Model System For Functional Genomics
Wen, Xiao-Yan
2008-01-01
In the post genome era, a major goal in molecular biology is to determine the function of the many thousands of genes present in the vertebrate genome. The zebrafish (Danio rerio) provides an almost ideal genetic model to identify the biological roles of these novel genes, in part because their embryos are transparent and develop rapidly. The zebrafish has many advantages over mouse for genome-wide mutagenesis studies, allowing for easier, cheaper and faster functional characterization of novel genes in the vertebrate genome. Many molecular research tools such as chemical mutagenesis, transgenesis, gene trapping, gene knockdown, TILLING, gene targeting, RNAi and chemical genetic screen are now available in zebrafish. Combining all the forward, reverse, and chemical genetic tools, it is expected that zebrafish will make invaluable contribution to vertebrate functional genomics in functional annotation of the genes, modeling human diseases and drug discoveries.
A functional model for feline P-glycoprotein.
van Beusekom, C D; Lange, R; Schrickx, J A
2016-02-01
P-gp (ABCB1) belongs to the group of export transporters that is expressed in various species at biological barriers. Inhibition of P-gp can lead to changes in pharmacokinetics of drugs (drug-drug interactions), which can lead to toxicity and adverse side effects. This study aimed to establish a functional assay to measure the inhibitory potential of veterinary drugs on feline P-gp by means of fluorescence-associated flow cytometry of feline lymphoma cells. In this model, PSC833 and ivermectin potently inhibited P-gp function; cyclosporine and verapamil moderately inhibited P-gp function, whereas ketoconazole, itraconazole, diazepam, and its metabolites had no effect on P-gp function. This model can be used for testing the inhibitory potency of (new) drugs on feline P-gp. © 2015 John Wiley & Sons Ltd.
Pelagic functional group modeling: Progress, challenges and prospects
Hood, Raleigh R.; Laws, Edward A.; Armstrong, Robert A.; Bates, Nicholas R.; Brown, Christopher W.; Carlson, Craig A.; Chai, Fei; Doney, Scott C.; Falkowski, Paul G.; Feely, Richard A.; Friedrichs, Marjorie A. M.; Landry, Michael R.; Keith Moore, J.; Nelson, David M.; Richardson, Tammi L.; Salihoglu, Baris; Schartau, Markus; Toole, Dierdre A.; Wiggert, Jerry D.
2006-03-01
In this paper, we review the state of the art and major challenges in current efforts to incorporate biogeochemical functional groups into models that can be applied on basin-wide and global scales, with an emphasis on models that might ultimately be used to predict how biogeochemical cycles in the ocean will respond to global warming. We define the term "biogeochemical functional group" to refer to groups of organisms that mediate specific chemical reactions in the ocean. Thus, according to this definition, "functional groups" have no phylogenetic meaning—these are composed of many different species with common biogeochemical functions. Substantial progress has been made in the last decade toward quantifying the rates of these various functions and understanding the factors that control them. For some of these groups, we have developed fairly sophisticated models that incorporate this understanding, e.g. for diazotrophs (e.g. Trichodesmium), silica producers (diatoms) and calcifiers (e.g. coccolithophorids and specifically Emiliania huxleyi). However, current representations of nitrogen fixation and calcification are incomplete, i.e., based primarily upon models of Trichodesmium and E. huxleyi, respectively, and many important functional groups have not yet been considered in open-ocean biogeochemical models. Progress has been made over the last decade in efforts to simulate dimethylsulfide (DMS) production and cycling (i.e., by dinoflagellates and prymnesiophytes) and denitrification, but these efforts are still in their infancy, and many significant problems remain. One obvious gap is that virtually all functional group modeling efforts have focused on autotrophic microbes, while higher trophic levels have been completely ignored. It appears that in some cases (e.g., calcification), incorporating higher trophic levels may be essential not only for representing a particular biogeochemical reaction, but also for modeling export. Another serious problem is our
Bread dough rheology: Computing with a damage function model
Tanner, Roger I.; Qi, Fuzhong; Dai, Shaocong
2015-01-01
We describe an improved damage function model for bread dough rheology. The model has relatively few parameters, all of which can easily be found from simple experiments. Small deformations in the linear region are described by a gel-like power-law memory function. A set of large non-reversing deformations - stress relaxation after a step of shear, steady shearing and elongation beginning from rest, and biaxial stretching, is used to test the model. With the introduction of a revised strain measure which includes a Mooney-Rivlin term, all of these motions can be well described by the damage function described in previous papers. For reversing step strains, larger amplitude oscillatory shearing and recoil reasonable predictions have been found. The numerical methods used are discussed and we give some examples.
Linking density functional and mode coupling models for supercooled liquids
Premkumar, Leishangthem; Bidhoodi, Neeta; Das, Shankar P.
2015-01-01
We compare predictions from two familiar models of the metastable supercooled liquid respectively constructed with thermodynamic and dynamic approach. In the so called density functional theory (DFT) the free energy $F[\\rho]$ of the liquid is a functional of the inhomogeneous density $\\rho({\\bf r})$. The metastable state is identified as a local minimum of $F[\\rho]$. The sharp density profile characterizing $\\rho({\\bf r})$ is identified as a single particle oscillator, whose frequency is obta...
Stability of cylindrical plasma in the Bessel function model
International Nuclear Information System (INIS)
Yamagishi, T.; Gimblett, C.G.
1988-01-01
The stability of free boundary ideal and tearing modes in a cylindrical plasma is studied by examining the discontinuity (Δ') of the helical flux function given by the force free Bessel function model at the singular surface. The m = O and m = 1 free boundary tearing modes become strongly unstable when the singular surface is just inside the plasma boundary for a wide range of longitudinal wave numbers. (author)
Testing the Conditional Mean Function of Autoregressive Conditional Duration Models
DEFF Research Database (Denmark)
Hautsch, Nikolaus
be subject to censoring structures. In an empirical study based on financial transaction data we present an application of the model to estimate conditional asset price change probabilities. Evaluating the forecasting properties of the model, it is shown that the proposed approach is a promising competitor...... function. The dynamic properties of the model as well as an assessment of the estimation quality is investigated in a Monte Carlo study. It is illustrated that the model is a useful approach to estimate conditional failure probabilities based on (persistent) serial dependent duration data which might...
Advances on statistical/thermodynamical models for unpolarized structure functions
Energy Technology Data Exchange (ETDEWEB)
Trevisan, Luis A. [Departamento de Matematica e Estatistica, Universidade Estadual de Ponta Grossa, 84010-790, Ponta Grossa, PR (Brazil); Mirez, Carlos [Universidade Federal dos Vales do Jequitinhonha e Mucuri, Campus do Mucuri, 39803-371, Teofilo Otoni, Minas Gerais (Brazil); Tomio, Lauro [Instituto de Fisica Teorica, Universidade Estadual Paulista, R. Dr. Bento Teobaldo Ferraz 271, Bl II Barra Funda, 01140070, Sao Paulo, SP (Brazil)
2013-03-25
During the eights and nineties many statistical/thermodynamical models were proposed to describe the nucleons' structure functions and distribution of the quarks in the hadrons. Most of these models describe the compound quarks and gluons inside the nucleon as a Fermi / Bose gas respectively, confined in a MIT bag with continuous energy levels. Another models considers discrete spectrum. Some interesting features of the nucleons are obtained by these models, like the sea asymmetries {sup -}d/{sup -}u and {sup -}d-{sup -}u.
Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites
Wong, Aloysius Tze
2015-06-09
Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.
Conserved functional motifs and homology modelling to predict hidden moonlighting functional sites
Directory of Open Access Journals (Sweden)
Helen R Irving
2015-06-01
Full Text Available Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here we review how hidden moonlighting functional centers which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico which in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.
Using special functions to model the propagation of airborne diseases
Bolaños, Daniela
2014-06-01
Some special functions of the mathematical physics are using to obtain a mathematical model of the propagation of airborne diseases. In particular we study the propagation of tuberculosis in closed rooms and we model the propagation using the error function and the Bessel function. In the model, infected individual emit pathogens to the environment and this infect others individuals who absorb it. The evolution in time of the concentration of pathogens in the environment is computed in terms of error functions. The evolution in time of the number of susceptible individuals is expressed by a differential equation that contains the error function and it is solved numerically for different parametric simulations. The evolution in time of the number of infected individuals is plotted for each numerical simulation. On the other hand, the spatial distribution of the pathogen around the source of infection is represented by the Bessel function K0. The spatial and temporal distribution of the number of infected individuals is computed and plotted for some numerical simulations. All computations were made using software Computer algebra, specifically Maple. It is expected that the analytical results that we obtained allow the design of treatment rooms and ventilation systems that reduce the risk of spread of tuberculosis.
Optimal hemodynamic response model for functional near-infrared spectroscopy
Directory of Open Access Journals (Sweden)
Muhammad Ahmad Kamran
2015-06-01
Full Text Available 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 using two Gamma functions with six unknown parameters. The HRF model is supposed to be 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 twelve 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 ten real and fifteen 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.
Functional dynamic factor models with application to yield curve forecasting
Hays, Spencer
2012-09-01
Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.
DEFINE: A Service-Oriented Dynamically Enabling Function Model
Directory of Open Access Journals (Sweden)
Tan Wei-Yi
2017-01-01
In this paper, we introduce an innovative Dynamically Enable Function In Network Equipment (DEFINE to allow tenant get the network service quickly. First, DEFINE decouples an application into different functional components, and connects these function components in a reconfigurable method. Second, DEFINE provides a programmable interface to the third party, who can develop their own processing modules according to their own needs. To verify the effectiveness of this model, we set up an evaluating network with a FPGA-based OpenFlow switch prototype, and deployed several applications on it. Our results show that DEFINE has excellent flexibility and performance.
Hypnosis as a model of functional neurologic disorders.
Deeley, Q
2016-01-01
In the 19th century it was recognized that neurologic symptoms could be caused by "morbid ideation" as well as organic lesions. The subsequent observation that hysteric (now called "functional") symptoms could be produced and removed by hypnotic suggestion led Charcot to hypothesize that suggestion mediated the effects of ideas on hysteric symptoms through as yet unknown effects on brain activity. The advent of neuroimaging 100 years later revealed strikingly similar neural correlates in experiments matching functional symptoms with clinical analogs created by suggestion. Integrative models of suggested and functional symptoms regard these alterations in brain function as the endpoint of a broader set of changes in information processing due to suggestion. These accounts consider that suggestions alter experience by mobilizing representations from memory systems, and altering causal attributions, during preconscious processing which alters the content of what is provided to our highly edited subjective version of the world. Hypnosis as a model for functional symptoms draws attention to how radical alterations in experience and behavior can conform to the content of mental representations through effects on cognition and brain function. Experimental study of functional symptoms and their suggested counterparts in hypnosis reveals the distinct and shared processes through which this can occur. © 2016 Elsevier B.V. All rights reserved.
Descriptions and models of safety functions - a prestudy
International Nuclear Information System (INIS)
Harms-Ringdahl, L.
1999-09-01
A study has been made with the focus on different theories and applications concerning 'safety functions' and 'barriers'. In this report, a safety function is defined as a technical or organisational function with the aim to reduce probability and/or consequences associated with a hazard. The study contains a limited review of practice and theories related to safety, with a focus on applications from nuclear and industrial safety. The study is based on a literature review and interviews. A summary has been made of definitions and terminology, which shows a large variation. E.g. 'barrier' can have a precise physical and technical meaning, or it can include human, technical and organisational elements. Only a few theoretical models describing safety functions have been found. One section of the report summarises problems related to safety issues and procedures. They concern errors in procedure design and user compliance. A proposal for describing and structuring safety functions has been made. Dimensions in a description could be degree of abstraction, systems level, the different parts of the function, etc. A model for safety functions has been proposed, which includes the division of a safety function in a number connected 'safety function elements'. One conclusion is that there is a potential for improving theories and tools for safety work and procedures. Safety function could be a useful concept in such a development, and advantages and disadvantages with this is discussed. If further work should be done, it is recommended that this is made as a combination of theoretical analysis and case studies
A hive model determination of multiplicity-free Schur function products and skew Schur functions
Dou, Donna Q. J.; Tang, Robert L.; King, Ronald C.
2009-01-01
The hive model is a combinatorial device that may be used to determine Littlewood-Richardson coefficients and study their properties. It represents an alternative to the use of the Littlewood-Richardson rule. Here properties of hives are used to determine all possible multiplicity-free Schur function products and skew Schur function expansions. This confirms the results of Stembridge, Gutschwager, and Thomas and Yong, and sheds light on the combinatorial origin of the conditions for being mul...
Model Adequacy and the Macroevolution of Angiosperm Functional Traits.
Pennell, Matthew W; FitzJohn, Richard G; Cornwell, William K; Harmon, Luke J
2015-08-01
Making meaningful inferences from phylogenetic comparative data requires a meaningful model of trait evolution. It is thus important to determine whether the model is appropriate for the data and the question being addressed. One way to assess this is to ask whether the model provides a good statistical explanation for the variation in the data. To date, researchers have focused primarily on the explanatory power of a model relative to alternative models. Methods have been developed to assess the adequacy, or absolute explanatory power, of phylogenetic trait models, but these have been restricted to specific models or questions. Here we present a general statistical framework for assessing the adequacy of phylogenetic trait models. We use our approach to evaluate the statistical performance of commonly used trait models on 337 comparative data sets covering three key angiosperm functional traits. In general, the models we tested often provided poor statistical explanations for the evolution of these traits. This was true for many different groups and at many different scales. Whether such statistical inadequacy will qualitatively alter inferences drawn from comparative data sets will depend on the context. Regardless, assessing model adequacy can provide interesting biological insights-how and why a model fails to describe variation in a data set give us clues about what evolutionary processes may have driven trait evolution across time.
Regional differences in prediction models of lung function in Germany
Directory of Open Access Journals (Sweden)
Schäper Christoph
2010-04-01
Full Text Available Abstract Background Little is known about the influencing potential of specific characteristics on lung function in different populations. The aim of this analysis was to determine whether lung function determinants differ between subpopulations within Germany and whether prediction equations developed for one subpopulation are also adequate for another subpopulation. Methods Within three studies (KORA C, SHIP-I, ECRHS-I in different areas of Germany 4059 adults performed lung function tests. The available data consisted of forced expiratory volume in one second, forced vital capacity and peak expiratory flow rate. For each study multivariate regression models were developed to predict lung function and Bland-Altman plots were established to evaluate the agreement between predicted and measured values. Results The final regression equations for FEV1 and FVC showed adjusted r-square values between 0.65 and 0.75, and for PEF they were between 0.46 and 0.61. In all studies gender, age, height and pack-years were significant determinants, each with a similar effect size. Regarding other predictors there were some, although not statistically significant, differences between the studies. Bland-Altman plots indicated that the regression models for each individual study adequately predict medium (i.e. normal but not extremely high or low lung function values in the whole study population. Conclusions Simple models with gender, age and height explain a substantial part of lung function variance whereas further determinants add less than 5% to the total explained r-squared, at least for FEV1 and FVC. Thus, for different adult subpopulations of Germany one simple model for each lung function measures is still sufficient.
Towards aspect-oriented functional--structural plant modelling.
Cieslak, Mikolaj; Seleznyova, Alla N; Prusinkiewicz, Przemyslaw; Hanan, Jim
2011-10-01
Functional-structural plant models (FSPMs) are used to integrate knowledge and test hypotheses of plant behaviour, and to aid in the development of decision support systems. A significant amount of effort is being put into providing a sound methodology for building them. Standard techniques, such as procedural or object-oriented programming, are not suited for clearly separating aspects of plant function that criss-cross between different components of plant structure, which makes it difficult to reuse and share their implementations. The aim of this paper is to present an aspect-oriented programming approach that helps to overcome this difficulty. The L-system-based plant modelling language L+C was used to develop an aspect-oriented approach to plant modelling based on multi-modules. Each element of the plant structure was represented by a sequence of L-system modules (rather than a single module), with each module representing an aspect of the element's function. Separate sets of productions were used for modelling each aspect, with context-sensitive rules facilitated by local lists of modules to consider/ignore. Aspect weaving or communication between aspects was made possible through the use of pseudo-L-systems, where the strict-predecessor of a production rule was specified as a multi-module. The new approach was used to integrate previously modelled aspects of carbon dynamics, apical dominance and biomechanics with a model of a developing kiwifruit shoot. These aspects were specified independently and their implementation was based on source code provided by the original authors without major changes. This new aspect-oriented approach to plant modelling is well suited for studying complex phenomena in plant science, because it can be used to integrate separate models of individual aspects of plant development and function, both previously constructed and new, into clearly organized, comprehensive FSPMs. In a future work, this approach could be further
Lyapunov functions for a dengue disease transmission model
Energy Technology Data Exchange (ETDEWEB)
Tewa, Jean Jules [Department of Mathematics, Faculty of Science, University of Yaounde I, P.O. Box 812, Yaounde (Cameroon)], E-mail: tewa@univ-metz.fr; Dimi, Jean Luc [Department of Mathematics, Faculty of Science, University Marien Ngouabi, P.O. Box 69, Brazzaville (Congo, The Democratic Republic of the)], E-mail: jldimi@yahoo.fr; Bowong, Samuel [Department of Mathematics and Computer Science, Faculty of Science, University of Douala, P.O. Box 24157, Douala (Cameroon)], E-mail: samuelbowong@yahoo.fr
2009-01-30
In this paper, we study a model for the dynamics of dengue fever when only one type of virus is present. For this model, Lyapunov functions are used to show that when the basic reproduction ratio is less than or equal to one, the disease-free equilibrium is globally asymptotically stable, and when it is greater than one there is an endemic equilibrium which is also globally asymptotically stable.
Lyapunov functions for a dengue disease transmission model
International Nuclear Information System (INIS)
Tewa, Jean Jules; Dimi, Jean Luc; Bowong, Samuel
2009-01-01
In this paper, we study a model for the dynamics of dengue fever when only one type of virus is present. For this model, Lyapunov functions are used to show that when the basic reproduction ratio is less than or equal to one, the disease-free equilibrium is globally asymptotically stable, and when it is greater than one there is an endemic equilibrium which is also globally asymptotically stable.
Directory of Open Access Journals (Sweden)
Solomencevs Artūrs
2016-05-01
Full Text Available The approach called “Topological Functioning Model for Software Engineering” (TFM4SE applies the Topological Functioning Model (TFM for modelling the business system in the context of Model Driven Architecture. TFM is a mathematically formal computation independent model (CIM. TFM4SE is compared to an approach that uses BPMN as a CIM. The comparison focuses on CIM modelling and on transformation to UML Sequence diagram on the platform independent (PIM level. The results show the advantages and drawbacks the formalism of TFM brings into the development.
Functional multiple indicators, multiple causes measurement error models.
Tekwe, Carmen D; Zoh, Roger S; Bazer, Fuller W; Wu, Guoyao; Carroll, Raymond J
2017-05-08
Objective measures of oxygen consumption and carbon dioxide production by mammals are used to predict their energy expenditure. Since energy expenditure is not directly observable, it can be viewed as a latent construct with multiple physical indirect measures such as respiratory quotient, volumetric oxygen consumption, and volumetric carbon dioxide production. Metabolic rate is defined as the rate at which metabolism occurs in the body. Metabolic rate is also not directly observable. However, heat is produced as a result of metabolic processes within the body. Therefore, metabolic rate can be approximated by heat production plus some errors. While energy expenditure and metabolic rates are correlated, they are not equivalent. Energy expenditure results from physical function, while metabolism can occur within the body without the occurrence of physical activities. In this manuscript, we present a novel approach for studying the relationship between metabolic rate and indicators of energy expenditure. We do so by extending our previous work on MIMIC ME models to allow responses that are sparsely observed functional data, defining the sparse functional multiple indicators, multiple cause measurement error (FMIMIC ME) models. The mean curves in our proposed methodology are modeled using basis splines. A novel approach for estimating the variance of the classical measurement error based on functional principal components is presented. The model parameters are estimated using the EM algorithm and a discussion of the model's identifiability is provided. We show that the defined model is not a trivial extension of longitudinal or functional data methods, due to the presence of the latent construct. Results from its application to data collected on Zucker diabetic fatty rats are provided. Simulation results investigating the properties of our approach are also presented. © 2017, The International Biometric Society.
Improved protein model quality assessments by changing the target function.
Uziela, Karolis; Menéndez Hurtado, David; Shu, Nanjiang; Wallner, Björn; Elofsson, Arne
2018-03-09
Protein modeling quality is an important part of protein structure prediction. We have for more than a decade developed a set of methods for this problem. We have used various types of description of the protein and different machine learning methodologies. However, common to all these methods has been the target function used for training. The target function in ProQ describes the local quality of a residue in a protein model. In all versions of ProQ the target function has been the S-score. However, other quality estimation functions also exist, which can be divided into superposition- and contact-based methods. The superposition-based methods, such as S-score, are based on a rigid body superposition of a protein model and the native structure, while the contact-based methods compare the local environment of each residue. Here, we examine the effects of retraining our latest predictor, ProQ3D, using identical inputs but different target functions. We find that the contact-based methods are easier to predict and that predictors trained on these measures provide some advantages when it comes to identifying the best model. One possible reason for this is that contact based methods are better at estimating the quality of multi-domain targets. However, training on the S-score gives the best correlation with the GDT_TS score, which is commonly used in CASP to score the global model quality. To take the advantage of both of these features we provide an updated version of ProQ3D that predicts local and global model quality estimates based on different quality estimates. © 2018 Wiley Periodicals, Inc.
The functional neuroanatomy of bipolar disorder: a consensus model
Strakowski, Stephen M; Adler, Caleb M; Almeida, Jorge; Altshuler, Lori L; Blumberg, Hilary P; Chang, Kiki D; DelBello, Melissa P; Frangou, Sophia; McIntosh, Andrew; Phillips, Mary L; Sussman, Jessika E; Townsend, Jennifer D
2013-01-01
Objectives Functional neuroimaging methods have proliferated in recent years, such that functional magnetic resonance imaging, in particular, is now widely used to study bipolar disorder. However, discrepant findings are common. A workgroup was organized by the Department of Psychiatry, University of Cincinnati (Cincinnati, OH, USA) to develop a consensus functional neuroanatomic model of bipolar I disorder based upon the participants’ work as well as that of others. Methods Representatives from several leading bipolar disorder neuroimaging groups were organized to present an overview of their areas of expertise as well as focused reviews of existing data. The workgroup then developed a consensus model of the functional neuroanatomy of bipolar disorder based upon these data. Results Among the participants, a general consensus emerged that bipolar I disorder arises from abnormalities in the structure and function of key emotional control networks in the human brain. Namely, disruption in early development (e.g., white matter connectivity, prefrontal pruning) within brain networks that modulate emotional behavior leads to decreased connectivity among ventral prefrontal networks and limbic brain regions, especially amygdala. This developmental failure to establish healthy ventral prefrontal–limbic modulation underlies the onset of mania and ultimately, with progressive changes throughout these networks over time and with affective episodes, a bipolar course of illness. Conclusions This model provides a potential substrate to guide future investigations and areas needing additional focus are identified. PMID:22631617
Laguerre-Gauss basis functions in observer models
Burgess, Arthur E.
2003-05-01
Observer models based on linear classifiers with basis functions (channels) are useful for evaluation of detection performance with medical images. They allow spatial domain calculations with a covariance matrix of tractable size. The term "channelized Fisher-Hotelling observer" will be used here. It is also called the "channelized Hotelling observer" model. There are an infinite number of basis function (channel ) sets that could be employed. Examples of channel sets that have been used include: difference of Gaussian (DOG) filters, difference of Mesa (DOM) filters and Laguerre-Gauss (LG) basis functions. Another option, sums of LG functions (LGS), will also be presented here. This set has the advantage of having no DC response. The effect of the number of images used to estimate model observer performance will be described, for both filtered 1/f3 noise and GE digital mammogram backgrounds. Finite sample image sets introduce both bias and variance to the estimate. The results presented here agree with previous work on linear classifiers. The LGS basis set gives a small but statistically significant reduction in bias. However, this may not be of much practical benefit. Finally, the effect of varying the number of basis functions included in the set will be addressed. It was found that four LG bases or three LGS bases are adequate.
A review of function modeling : Approaches and applications
Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.
2008-01-01
This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research
Mass corrections to Green functions in instanton vacuum model
International Nuclear Information System (INIS)
Esaibegyan, S.V.; Tamaryan, S.N.
1987-01-01
The first nonvanishing mass corrections to the effective Green functions are calculated in the model of instanton-based vacuum consisting of a superposition of instanton-antiinstanton fluctuations. The meson current correlators are calculated with account of these corrections; the mass spectrum of pseudoscalar octet as well as the value of the kaon axial constant are found. 7 refs
Gene Discovery and Functional Analyses in the Model Plant Arabidopsis
DEFF Research Database (Denmark)
Feng, Cai-ping; Mundy, J.
2006-01-01
The present mini-review describes newer methods and strategies, including transposon and T-DNA insertions, TILLING, Deleteagene, and RNA interference, to functionally analyze genes of interest in the model plant Arabidopsis. The relative advantages and disadvantages of the systems are also...
Partition function of nearest neighbour Ising models: Some new ...
Indian Academy of Sciences (India)
Administrator
insights. †. G NANDHINI and M V SANGARANARAYANAN*. Department of Chemistry, Indian Institute of Technology Madras, Chennai 600 036 e-mail: sangara@iitm.ac.in. Abstract. The partition function for one-dimensional nearest neighbour Ising models is estimated by summing all the energy terms in the Hamiltonian for ...
From dynamics to structure and function of model biomolecular systems
Fontaine-Vive-Curtaz, F.
2007-01-01
The purpose of this thesis was to extend recent works on structure and dynamics of hydrogen bonded crystals to model biomolecular systems and biological processes. The tools that we have used are neutron scattering (NS) and density functional theory (DFT) and force field (FF) based simulation
All genus correlation functions for the hermitian 1-matrix model
Eynard, B.
2004-01-01
We rewrite the loop equations of the hermitian matrix model, in a way which allows to compute all the correlation functions, to all orders in the topological $1/N^2$ expansion, as residues on an hyperelliptical curve. Those residues, can be represented diagrammaticaly as Feynmann graphs of a cubic interaction field theory on the curve.
Software Design Modelling with Functional Petri Nets | Bakpo ...
African Journals Online (AJOL)
In this paper, an equivalent functional Petri Net (FPN) model is developed for each of the three constructs of structured programs and a FPN Software prototype proposed for the conventional programming construct: if-then-else statement. The motivating idea is essentially to show that FPNs could be used as an alternative ...
An adaptive complex network model for brain functional networks.
Directory of Open Access Journals (Sweden)
Ignacio J Gomez Portillo
Full Text Available Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution.
Colombian ocean waves and coasts modeled by special functions
Duque Tisnés, Simón
2013-06-01
Modeling the ocean bottom and surface of both Atlantic and Pacific Oceans near the Colombian coast is a subject of increasing attention due to the possibility of finding oil deposits that haven't been discovered, and as a way of monitoring the ocean limits of Colombia with other countries not only covering the possibility of naval intrusion but as a chance to detect submarine devices that are used by illegal groups for different unwished purposes. In the development of this topic it would be necessary to use Standard Hydrodynamic Equations to model the mathematical shape of ocean waves that will take differential equations forms. Those differential equations will be solved using computer algebra software and methods. The mentioned solutions will involve the use of Special Functions such as Bessel Functions, Whittaker, Heun, and so on. Using the Special Functions mentioned above, the obtained results will be simulated by numerical methods obtaining the typical patterns around the Colombian coasts (both surface and bottom). Using this simulation as a non-perturbed state, any change in the patter could be taken as an external perturbation caused by a strange body or device in an specific area or region modeled, building this simulation as an ocean radar or an unusual object finder. It's worth mentioning that the use of stronger or more rigorous methods and more advanced Special Functions would generate better theoretical results, building a more accurate simulation model that would lead to a finest detection.
Systemic Modeling of Biological Functions in Consideration of Physiome Project
Minamitani, Haruyuki
Emerging of the physiome project provides various influences on the medical, biological and pharmaceutical development. In this paper, as an example of physiome research, neural network model analysis providing the conduction mechanisms of pain and tactile sensations was presented, and the functional relations between neural activities of the network cells and stimulus intensity applied on the peripheral receptive fields were described. The modeling presented here is based on the various assumptions made by the results of physiological and anatomical studies reported in the literature. The functional activities of spinothalamic and thalamocortical cells show a good agreement with the physiological and psychophysical functions of somatosensory system that are very instructive for covering the gap between physiologically and psychophysically aspects of pain and tactile sensation.
Functional Model to Estimate the Inelastic Displacement Ratio
Directory of Open Access Journals (Sweden)
Ceangu Vlad
2017-12-01
Full Text Available In this paper a functional model to estimate the inelastic displacement ratio as a function of the ductility factor is presented. The coefficients of the functional model are approximated using nonlinear regression. The used data is in the form of computed displacement for an inelastic single degree of freedom system with a fixed ductility factor. The inelastic seismic response spectra of constant ductility factors are used for generating data. A method for selecting ground-motions that have similar frequency content to that of the ones picked for the comparison is presented. The variability of the seismic response of nonlinear single degree of freedom systems with different hysteretic behavior is presented.
Functional Nonlinear Mixed Effects Models For Longitudinal Image Data
Luo, Xinchao; Zhu, Lixing; Kong, Linglong; Zhu, Hongtu
2015-01-01
Motivated by studying large-scale longitudinal image data, we propose a novel functional nonlinear mixed effects modeling (FN-MEM) framework to model the nonlinear spatial-temporal growth patterns of brain structure and function and their association with covariates of interest (e.g., time or diagnostic status). Our FNMEM explicitly quantifies a random nonlinear association map of individual trajectories. We develop an efficient estimation method to estimate the nonlinear growth function and the covariance operator of the spatial-temporal process. We propose a global test and a simultaneous confidence band for some specific growth patterns. We conduct Monte Carlo simulation to examine the finite-sample performance of the proposed procedures. We apply FNMEM to investigate the spatial-temporal dynamics of white-matter fiber skeletons in a national database for autism research. Our FNMEM may provide a valuable tool for charting the developmental trajectories of various neuropsychiatric and neurodegenerative disorders. PMID:26213453
Development on electromagnetic impedance function modeling and its estimation
International Nuclear Information System (INIS)
Sutarno, D.
2015-01-01
Today the Electromagnetic methods such as magnetotellurics (MT) and controlled sources audio MT (CSAMT) is used in a broad variety of applications. Its usefulness in poor seismic areas and its negligible environmental impact are integral parts of effective exploration at minimum cost. As exploration was forced into more difficult areas, the importance of MT and CSAMT, in conjunction with other techniques, has tended to grow continuously. However, there are obviously important and difficult problems remaining to be solved concerning our ability to collect process and interpret MT as well as CSAMT in complex 3D structural environments. This talk aim at reviewing and discussing the recent development on MT as well as CSAMT impedance functions modeling, and also some improvements on estimation procedures for the corresponding impedance functions. In MT impedance modeling, research efforts focus on developing numerical method for computing the impedance functions of three dimensionally (3-D) earth resistivity models. On that reason, 3-D finite elements numerical modeling for the impedances is developed based on edge element method. Whereas, in the CSAMT case, the efforts were focused to accomplish the non-plane wave problem in the corresponding impedance functions. Concerning estimation of MT and CSAMT impedance functions, researches were focused on improving quality of the estimates. On that objective, non-linear regression approach based on the robust M-estimators and the Hilbert transform operating on the causal transfer functions, were used to dealing with outliers (abnormal data) which are frequently superimposed on a normal ambient MT as well as CSAMT noise fields. As validated, the proposed MT impedance modeling method gives acceptable results for standard three dimensional resistivity models. Whilst, the full solution based modeling that accommodate the non-plane wave effect for CSAMT impedances is applied for all measurement zones, including near-, transition
Development on electromagnetic impedance function modeling and its estimation
Energy Technology Data Exchange (ETDEWEB)
Sutarno, D., E-mail: Sutarno@fi.itb.ac.id [Earth Physics and Complex System Division Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung (Indonesia)
2015-09-30
Today the Electromagnetic methods such as magnetotellurics (MT) and controlled sources audio MT (CSAMT) is used in a broad variety of applications. Its usefulness in poor seismic areas and its negligible environmental impact are integral parts of effective exploration at minimum cost. As exploration was forced into more difficult areas, the importance of MT and CSAMT, in conjunction with other techniques, has tended to grow continuously. However, there are obviously important and difficult problems remaining to be solved concerning our ability to collect process and interpret MT as well as CSAMT in complex 3D structural environments. This talk aim at reviewing and discussing the recent development on MT as well as CSAMT impedance functions modeling, and also some improvements on estimation procedures for the corresponding impedance functions. In MT impedance modeling, research efforts focus on developing numerical method for computing the impedance functions of three dimensionally (3-D) earth resistivity models. On that reason, 3-D finite elements numerical modeling for the impedances is developed based on edge element method. Whereas, in the CSAMT case, the efforts were focused to accomplish the non-plane wave problem in the corresponding impedance functions. Concerning estimation of MT and CSAMT impedance functions, researches were focused on improving quality of the estimates. On that objective, non-linear regression approach based on the robust M-estimators and the Hilbert transform operating on the causal transfer functions, were used to dealing with outliers (abnormal data) which are frequently superimposed on a normal ambient MT as well as CSAMT noise fields. As validated, the proposed MT impedance modeling method gives acceptable results for standard three dimensional resistivity models. Whilst, the full solution based modeling that accommodate the non-plane wave effect for CSAMT impedances is applied for all measurement zones, including near-, transition
Optimal hemodynamic response model for functional near-infrared spectroscopy.
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).
Bessel functions in mass action modeling of memories and remembrances
Energy Technology Data Exchange (ETDEWEB)
Freeman, Walter J. [Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720-3206 (United States); Capolupo, Antonio [Dipartimento di Fisica, E.R. Caianiello Universitá di Salerno, and INFN Gruppo collegato di Salerno, Fisciano 84084 (Italy); Kozma, Robert [Department of Mathematics, Memphis University, Memphis, TN 38152 (United States); Olivares del Campo, Andrés [The Blackett Laboratory, Imperial College London, Prince Consort Road, London SW7 2BZ (United Kingdom); Vitiello, Giuseppe, E-mail: vitiello@sa.infn.it [Dipartimento di Fisica, E.R. Caianiello Universitá di Salerno, and INFN Gruppo collegato di Salerno, Fisciano 84084 (Italy)
2015-10-02
Data from experimental observations of a class of neurological processes (Freeman K-sets) present functional distribution reproducing Bessel function behavior. We model such processes with couples of damped/amplified oscillators which provide time dependent representation of Bessel equation. The root loci of poles and zeros conform to solutions of K-sets. Some light is shed on the problem of filling the gap between the cellular level dynamics and the brain functional activity. Breakdown of time-reversal symmetry is related with the cortex thermodynamic features. This provides a possible mechanism to deduce lifetime of recorded memory. - Highlights: • We consider data from observations of impulse responses of cortex to electric shocks. • These data are fitted by Bessel functions which may be represented by couples of damped/amplified oscillators. • We study the data by using couples of damped/amplified oscillators. • We discuss lifetime and other properties of the considered brain processes.
Universality of correlation functions in random matrix models of QCD
International Nuclear Information System (INIS)
Jackson, A.D.; Sener, M.K.; Verbaarschot, J.J.M.
1997-01-01
We demonstrate the universality of the spectral correlation functions of a QCD inspired random matrix model that consists of a random part having the chiral structure of the QCD Dirac operator and a deterministic part which describes a schematic temperature dependence. We calculate the correlation functions analytically using the technique of Itzykson-Zuber integrals for arbitrary complex supermatrices. An alternative exact calculation for arbitrary matrix size is given for the special case of zero temperature, and we reproduce the well-known Laguerre kernel. At finite temperature, the microscopic limit of the correlation functions are calculated in the saddle-point approximation. The main result of this paper is that the microscopic universality of correlation functions is maintained even though unitary invariance is broken by the addition of a deterministic matrix to the ensemble. (orig.)
Production functions for climate policy modeling. An empirical analysis
International Nuclear Information System (INIS)
Van der Werf, Edwin
2008-01-01
Quantitative models for climate policy modeling differ in the production structure used and in the sizes of the elasticities of substitution. The empirical foundation for both is generally lacking. This paper estimates the parameters of 2-level CES production functions with capital, labour and energy as inputs, and is the first to systematically compare all nesting structures. Using industry-level data from 12 OECD countries, we find that the nesting structure where capital and labour are combined first, fits the data best, but for most countries and industries we cannot reject that all three inputs can be put into one single nest. These two nesting structures are used by most climate models. However, while several climate policy models use a Cobb-Douglas function for (part of the) production function, we reject elasticities equal to one, in favour of considerably smaller values. Finally we find evidence for factor-specific technological change. With lower elasticities and with factor-specific technological change, some climate policy models may find a bigger effect of endogenous technological change on mitigating the costs of climate policy. (author)
Identifying Model-Based Reconfiguration Goals through Functional Deficiencies
Benazera, Emmanuel; Trave-Massuyes, Louise
2004-01-01
Model-based diagnosis is now advanced to the point autonomous systems face some uncertain and faulty situations with success. The next step toward more autonomy is to have the system recovering itself after faults occur, a process known as model-based reconfiguration. After faults occur, given a prediction of the nominal behavior of the system and the result of the diagnosis operation, this paper details how to automatically determine the functional deficiencies of the system. These deficiencies are characterized in the case of uncertain state estimates. A methodology is then presented to determine the reconfiguration goals based on the deficiencies. Finally, a recovery process interleaves planning and model predictive control to restore the functionalities in prioritized order.
Parton distribution functions with QED corrections in the valon model
Mottaghizadeh, Marzieh; Taghavi Shahri, Fatemeh; Eslami, Parvin
2017-10-01
The parton distribution functions (PDFs) with QED corrections are obtained by solving the QCD ⊗QED DGLAP evolution equations in the framework of the "valon" model at the next-to-leading-order QCD and the leading-order QED approximations. Our results for the PDFs with QED corrections in this phenomenological model are in good agreement with the newly related CT14QED global fits code [Phys. Rev. D 93, 114015 (2016), 10.1103/PhysRevD.93.114015] and APFEL (NNPDF2.3QED) program [Comput. Phys. Commun. 185, 1647 (2014), 10.1016/j.cpc.2014.03.007] in a wide range of x =[10-5,1 ] and Q2=[0.283 ,108] GeV2 . The model calculations agree rather well with those codes. In the latter, we proposed a new method for studying the symmetry breaking of the sea quark distribution functions inside the proton.
Advanced Mirror & Modelling Technology Development
Effinger, Michael; Stahl, H. Philip; Abplanalp, Laura; Maffett, Steven; Egerman, Robert; Eng, Ron; Arnold, William; Mosier, Gary; Blaurock, Carl
2014-01-01
The 2020 Decadal technology survey is starting in 2018. Technology on the shelf at that time will help guide selection to future low risk and low cost missions. The Advanced Mirror Technology Development (AMTD) team has identified development priorities based on science goals and engineering requirements for Ultraviolet Optical near-Infrared (UVOIR) missions in order to contribute to the selection process. One key development identified was lightweight mirror fabrication and testing. A monolithic, stacked, deep core mirror was fused and replicated twice to achieve the desired radius of curvature. It was subsequently successfully polished and tested. A recently awarded second phase to the AMTD project will develop larger mirrors to demonstrate the lateral scaling of the deep core mirror technology. Another key development was rapid modeling for the mirror. One model focused on generating optical and structural model results in minutes instead of months. Many variables could be accounted for regarding the core, face plate and back structure details. A portion of a spacecraft model was also developed. The spacecraft model incorporated direct integration to transform optical path difference to Point Spread Function (PSF) and between PSF to modulation transfer function. The second phase to the project will take the results of the rapid mirror modeler and integrate them into the rapid spacecraft modeler.
A propositional representation model of anatomical and functional brain data.
Maturana, Pablo; Batrancourt, Bénédicte
2011-01-01
Networks can represent a large number of systems. Recent advances in the domain of networks have been transferred to the field of neuroscience. For example, the graph model has been used in neuroscience research as a methodological tool to examine brain networks organization, topology and complex dynamics, as well as a framework to test the structure-function hypothesis using neuroimaging data. In the current work we propose a graph-theoretical framework to represent anatomical, functional and neuropsychological assessment instruments information. On the one hand, interrelationships between anatomic elements constitute an anatomical graph. On the other hand, a functional graph contains several cognitive functions and their more elementary cognitive processes. Finally, the neuropsychological assessment instruments graph includes several neuropsychological tests and scales linked with their different sub-tests and variables. The two last graphs are connected by relations of type "explore" linking a particular instrument with the cognitive function it explores. We applied this framework to a sample of patients with focal brain damage. Each patient was related to: (i) the cerebral entities injured (assessed with structural neuroimaging data) and (ii) the neusopsychological assessment tests carried out (weight by performance). Our model offers a suitable platform to visualize patients' relevant information, facilitating the representation, standardization and sharing of clinical data. At the same time, the integration of a large number of patients in this framework will make possible to explore relations between anatomy (injured entities) and function (performance in different tests assessing different cognitive functions) and the use of neurocomputational tools for graph analysis may help diagnostic and contribute to the comprehension of neural bases of cognitive functions. Copyright © 2011 Elsevier Ltd. All rights reserved.
Future of Plant Functional Types in Terrestrial Biosphere Models
Wullschleger, S. D.; Euskirchen, E. S.; Iversen, C. M.; Rogers, A.; Serbin, S.
2015-12-01
Earth system models describe the physical, chemical, and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. Plant functional types (PFTs) have been adopted by modelers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current, and future distribution of vegetation. Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration, and shrub expansion. However, representation of above- and especially belowground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water, and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology, and remote sensing will be
Development of an Upper Extremity Function Measurement Model.
Hong, Ickpyo; Simpson, Annie N; Li, Chih-Ying; Velozo, Craig A
This study demonstrated the development of a measurement model for gross upper-extremity function (GUE). The dependent variable was the Rasch calibration of the 27 ICF-GUE test items. The predictors were object weight, lifting distance from floor, carrying, and lifting. Multiple regression was used to investigate the contribution that each independent variable makes to the model with 203 outpatients. Object weight and lifting distance were the only statistically and clinically significant independent variables in the model, accounting for 83% of the variance (p model indicates that, with each one pound increase in object weight, item challenge increases by 0.16 (p measurement model for the ICF-GUE can be explained by object weight and distance lifted from the floor.
A Comparison of Functional Models for Use in the Function-Failure Design Method
Stock, Michael E.; Stone, Robert B.; Tumer, Irem Y.
2006-01-01
When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar functionality. To capitalize on this finding, a knowledge base of historical failure information linked to functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed functional descriptions are derived for each failed component based
Function modeling improves the efficiency of spatial modeling using big data from remote sensing
John Hogland; Nathaniel Anderson
2017-01-01
Spatial modeling is an integral component of most geographic information systems (GISs). However, conventional GIS modeling techniques can require substantial processing time and storage space and have limited statistical and machine learning functionality. To address these limitations, many have parallelized spatial models using multiple coding libraries and have...
Extreme compression and modeling of bidirectional texture function.
Haindl, Michal; Filip, Jirí
2007-10-01
The recent advanced representation for realistic real-world materials in virtual reality applications is the Bidirectional Texture Function (BTF) which describes rough texture appearance for varying illumination and viewing conditions. Such a function can be represented by thousands of measurements (images) per material sample. The resulting BTF size excludes its direct rendering in graphical applications and some compression of these huge BTF data spaces is obviously inevitable. In this paper we present a novel, fast probabilistic model-based algorithm for realistic BTF modeling allowing an extreme compression with the possibility of a fast hardware implementation. Its ultimate aim is to create a visual impression of the same material without a pixel-wise correspondence to the original measurements. The analytical step of the algorithm starts with a BTF space segmentation and a range map estimation by photometric stereo of the BTF surface, followed by the spectral and spatial factorization of selected sub-space color texture images. Single mono-spectral band-limited factors are independently modeled by their dedicated spatial probabilistic model. During rendering, the sub-space images of arbitrary size are synthesized and both color (possibly multi-spectral) and range information is combined in a bump-mapping filter according to the view and illumination directions. The presented model offers a huge BTF compression ratio unattainable by any alternative sampling-based BTF synthesis method. Simultaneously this model can be used to reconstruct missing parts of the BTF measurement space.
Thresholding functional connectomes by means of mixture modeling.
Bielczyk, Natalia Z; Walocha, Fabian; Ebel, Patrick W; Haak, Koen V; Llera, Alberto; Buitelaar, Jan K; Glennon, Jeffrey C; Beckmann, Christian F
2018-05-01
Functional connectivity has been shown to be a very promising tool for studying the large-scale functional architecture of the human brain. In network research in fMRI, functional connectivity is considered as a set of pair-wise interactions between the nodes of the network. These interactions are typically operationalized through the full or partial correlation between all pairs of regional time series. Estimating the structure of the latent underlying functional connectome from the set of pair-wise partial correlations remains an open research problem though. Typically, this thresholding problem is approached by proportional thresholding, or by means of parametric or non-parametric permutation testing across a cohort of subjects at each possible connection. As an alternative, we propose a data-driven thresholding approach for network matrices on the basis of mixture modeling. This approach allows for creating subject-specific sparse connectomes by modeling the full set of partial correlations as a mixture of low correlation values associated with weak or unreliable edges in the connectome and a sparse set of reliable connections. Consequently, we propose to use alternative thresholding strategy based on the model fit using pseudo-False Discovery Rates derived on the basis of the empirical null estimated as part of the mixture distribution. We evaluate the method on synthetic benchmark fMRI datasets where the underlying network structure is known, and demonstrate that it gives improved performance with respect to the alternative methods for thresholding connectomes, given the canonical thresholding levels. We also demonstrate that mixture modeling gives highly reproducible results when applied to the functional connectomes of the visual system derived from the n-back Working Memory task in the Human Connectome Project. The sparse connectomes obtained from mixture modeling are further discussed in the light of the previous knowledge of the functional architecture
Spin-density functional for exchange anisotropic Heisenberg model
International Nuclear Information System (INIS)
Prata, G.N.; Penteado, P.H.; Souza, F.C.; Libero, Valter L.
2009-01-01
Ground-state energies for antiferromagnetic Heisenberg models with exchange anisotropy are estimated by means of a local-spin approximation made in the context of the density functional theory. Correlation energy is obtained using the non-linear spin-wave theory for homogeneous systems from which the spin functional is built. Although applicable to chains of any size, the results are shown for small number of sites, to exhibit finite-size effects and allow comparison with exact-numerical data from direct diagonalization of small chains.
Using the Drosophila Nephrocyte to Model Podocyte Function and Disease
Directory of Open Access Journals (Sweden)
Martin Helmstädter
2017-12-01
Full Text Available Glomerular disorders are a major cause of end-stage renal disease and effective therapies are often lacking. Nephrocytes are considered to be part of the Drosophila excretory system and form slit diaphragms across cellular membrane invaginations. Nehphrocytes have been shown to share functional, morphological, and molecular features with podocytes, which form the glomerular filter in vertebrates. Here, we report the progress and the evolving tool-set of this model system. Combining a functional, accessible slit diaphragm with the power of the genetic tool-kit in Drosophila, the nephrocyte has the potential to greatly advance our understanding of the glomerular filtration barrier in health and disease.
Analysis of a Heroin Epidemic Model with Saturated Treatment Function
Directory of Open Access Journals (Sweden)
Isaac Mwangi Wangari
2017-01-01
Full Text Available A mathematical model is developed that examines how heroin addiction spreads in society. The model is formulated to take into account the treatment of heroin users by incorporating a realistic functional form that “saturates” representing the limited availability of treatment. Bifurcation analysis reveals that the model has an intrinsic backward bifurcation whenever the saturation parameter is larger than a fixed threshold. We are particularly interested in studying the model’s global stability. In the absence of backward bifurcations, Lyapunov functions can often be found and used to prove global stability. However, in the presence of backward bifurcations, such Lyapunov functions may not exist or may be difficult to construct. We make use of the geometric approach to global stability to derive a condition that ensures that the system is globally asymptotically stable. Numerical simulations are also presented to give a more complete representation of the model dynamics. Sensitivity analysis performed by Latin hypercube sampling (LHS suggests that the effective contact rate in the population, the relapse rate of heroin users undergoing treatment, and the extent of saturation of heroin users are mechanisms fuelling heroin epidemic proliferation.
Auditory temporal integration and the power function model.
Gerken, G M; Bhat, V K; Hutchison-Clutter, M
1990-08-01
The auditory temporal integration function was studied with the objective of improving both its quantitative description and the specification of its principle independent variable, stimulus duration. In Sec. I, temporal integration data from 20 studies were subjected to uniform analyses using standardized definitions of duration and two models of temporal integration. Analyses revealed that these data were best described by a power function model used in conjunction with a definition of duration, termed assigned duration, that de-emphasized the rise/fall portions of the stimuli. There was a strong effect of stimulus frequency and, in general, the slope of the temporal integration function was less than 10 dB per decade of duration; i.e., a power function exponent less than 1.0. In Sec. II, an experimental study was performed to further evaluate the models and definitions. Detection thresholds were measured in 11 normal-hearing human subjects using a total of 24 single-burst and multiple-burst acoustic stimuli of 3.125 kHz. The issues addressed are: the quantitative description of the temporal integration function; the definition of stimulus duration; the similarity of the integration processes for single-burst and multiple-burst stimuli; and the contribution of rise/fall time to the integration process. A power function in conjunction with the assigned duration definition was again most effective in describing the data. Single- and multiple-burst stimuli both seemed to be integrated by the same central mechanism, with data for each type of stimulus being described by a power function exponent of approximately 0.6 at 3.125 kHz. It was concluded that the contribution of the rise/fall portions of the stimuli can be factored out from the rest of the temporal integration process. In Sec. III, the conclusions that emerged from the review of published work and the present experimental work suggested that auditory temporal integration is best described by a power function
Photonic encryption : modeling and functional analysis of all optical logic.
Energy Technology Data Exchange (ETDEWEB)
Tang, Jason D.; Schroeppel, Richard Crabtree; Robertson, Perry J.
2004-10-01
With the build-out of large transport networks utilizing optical technologies, more and more capacity is being made available. Innovations in Dense Wave Division Multiplexing (DWDM) and the elimination of optical-electrical-optical conversions have brought on advances in communication speeds as we move into 10 Gigabit Ethernet and above. Of course, there is a need to encrypt data on these optical links as the data traverses public and private network backbones. Unfortunately, as the communications infrastructure becomes increasingly optical, advances in encryption (done electronically) have failed to keep up. This project examines the use of optical logic for implementing encryption in the photonic domain to achieve the requisite encryption rates. This paper documents the innovations and advances of work first detailed in 'Photonic Encryption using All Optical Logic,' [1]. A discussion of underlying concepts can be found in SAND2003-4474. In order to realize photonic encryption designs, technology developed for electrical logic circuits must be translated to the photonic regime. This paper examines S-SEED devices and how discrete logic elements can be interconnected and cascaded to form an optical circuit. Because there is no known software that can model these devices at a circuit level, the functionality of S-SEED devices in an optical circuit was modeled in PSpice. PSpice allows modeling of the macro characteristics of the devices in context of a logic element as opposed to device level computational modeling. By representing light intensity as voltage, 'black box' models are generated that accurately represent the intensity response and logic levels in both technologies. By modeling the behavior at the systems level, one can incorporate systems design tools and a simulation environment to aid in the overall functional design. Each black box model takes certain parameters (reflectance, intensity, input response), and models the optical ripple
Transient finite element modeling of functional electrical stimulation.
Filipovic, Nenad D; Peulic, Aleksandar S; Zdravkovic, Nebojsa D; Grbovic-Markovic, Vesna M; Jurisic-Skevin, Aleksandra J
2011-03-01
Transcutaneous functional electrical stimulation is commonly used for strengthening muscle. However, transient effects during stimulation are not yet well explored. The effect of an amplitude change of the stimulation can be described by static model, but there is no differency for different pulse duration. The aim of this study is to present the finite element (FE) model of a transient electrical stimulation on the forearm. Discrete FE equations were derived by using a standard Galerkin procedure. Different tissue conductive and dielectric properties are fitted using least square method and trial and error analysis from experimental measurement. This study showed that FE modeling of electrical stimulation can give the spatial-temporal distribution of applied current in the forearm. Three different cases were modeled with the same geometry but with different input of the current pulse, in order to fit the tissue properties by using transient FE analysis. All three cases were compared with experimental measurements of intramuscular voltage on one volunteer.
Computation of Schenberg response function by using finite element modelling
International Nuclear Information System (INIS)
Frajuca, C; Bortoli, F S; Magalhaes, N S
2016-01-01
Schenberg is a detector of gravitational waves resonant mass type, with a central frequency of operation of 3200 Hz. Transducers located on the surface of the resonating sphere, according to a distribution half-dodecahedron, are used to monitor a strain amplitude. The development of mechanical impedance matchers that act by increasing the coupling of the transducers with the sphere is a major challenge because of the high frequency and small in size. The objective of this work is to study the Schenberg response function obtained by finite element modeling (FEM). Finnaly, the result is compared with the result of the simplified model for mass spring type system modeling verifying if that is suitable for the determination of sensitivity detector, as the conclusion the both modeling give the same results. (paper)
A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity.
Zhu, Yingying; Zhu, Xiaofeng; Kim, Minjeong; Yan, Jin; Wu, Guorong
2017-06-01
Functional connectivity (FC) has been widely investigated in many imaging-based neuroscience and clinical studies. Since functional Magnetic Resonance Image (MRI) signal is just an indirect reflection of brain activity, it is difficult to accurately quantify the FC strength only based on signal correlation. To address this limitation, we propose a learning-based tensor model to derive high sensitivity and specificity connectome biomarkers at the individual level from resting-state fMRI images. First, we propose a learning-based approach to estimate the intrinsic functional connectivity. In addition to the low level region-to-region signal correlation, latent module-to-module connection is also estimated and used to provide high level heuristics for measuring connectivity strength. Furthermore, sparsity constraint is employed to automatically remove the spurious connections, thus alleviating the issue of searching for optimal threshold. Second, we integrate our learning-based approach with the sliding-window technique to further reveal the dynamics of functional connectivity. Specifically, we stack the functional connectivity matrix within each sliding window and form a 3D tensor where the third dimension denotes for time. Then we obtain dynamic functional connectivity (dFC) for each individual subject by simultaneously estimating the within-sliding-window functional connectivity and characterizing the across-sliding-window temporal dynamics. Third, in order to enhance the robustness of the connectome patterns extracted from dFC, we extend the individual-based 3D tensors to a population-based 4D tensor (with the fourth dimension stands for the training subjects) and learn the statistics of connectome patterns via 4D tensor analysis. Since our 4D tensor model jointly (1) optimizes dFC for each training subject and (2) captures the principle connectome patterns, our statistical model gains more statistical power of representing new subject than current state
Quadratic inference functions in marginal models for longitudinal data.
Song, Peter X-K; Jiang, Zhichang; Park, Eunjoo; Qu, Annie
2009-12-20
The quadratic inference function (QIF) is a new statistical methodology developed for the estimation and inference in longitudinal data analysis using marginal models. This method is an alternative to the popular generalized estimating equations approach, and it has several useful properties such as robustness, a goodness-of-fit test and model selection. This paper presents an introductory review of the QIF, with a strong emphasis on its applications. In particular, a recently developed SAS MACRO QIF is illustrated in this paper to obtain numerical results.
Mouse Models of Allergic Diseases: TSLP and Its Functional Roles
Directory of Open Access Journals (Sweden)
Miyuki Omori-Miyake
2012-01-01
Full Text Available The cytokine TSLP was originally identified in a murine thymic stromal cell line as a lymphoid growth factor. After the discovery of TSLP, extensive molecular genetic analyses and gene targeting experiments have demonstrated that TSLP plays an essential role in allergic diseases. In this review, we discuss the current status of TSLP and its functional role in allergic diseases particularly by focusing on effects of TSLP on haematopoietic cells in mouse models. It is our conclusion that a number of research areas, i.e., a new source of TSLP, effects of TSLP on non-haematopoietic and haematopoietic cells, synergistic interactions of cytokines including IL-25 and IL-33 and a regulation of TSLP expression and its function, are critically needed to understand the whole picture of TSLP involvement in allergic diseases. The mouse models will thus contribute further to our understanding of TSLP involvement in allergic diseases and development of therapeutic measures for human allergic diseases.
Potts model partition functions on two families of fractal lattices
Gong, Helin; Jin, Xian'an
2014-11-01
The partition function of q-state Potts model, or equivalently the Tutte polynomial, is computationally intractable for regular lattices. The purpose of this paper is to compute partition functions of q-state Potts model on two families of fractal lattices. Based on their self-similar structures and by applying the subgraph-decomposition method, we divide their Tutte polynomials into two summands, and for each summand we obtain a recursive formula involving the other summand. As a result, the number of spanning trees and their asymptotic growth constants, and a lower bound of the number of connected spanning subgraphs or acyclic root-connected orientations for each of such two lattices are obtained.
The Use of Modeling Approach for Teaching Exponential Functions
Nunes, L. F.; Prates, D. B.; da Silva, J. M.
2017-12-01
This work presents a discussion related to the teaching and learning of mathematical contents related to the study of exponential functions in a freshman students group enrolled in the first semester of the Science and Technology Bachelor’s (STB of the Federal University of Jequitinhonha and Mucuri Valleys (UFVJM). As a contextualization tool strongly mentioned in the literature, the modelling approach was used as an educational teaching tool to produce contextualization in the teaching-learning process of exponential functions to these students. In this sense, were used some simple models elaborated with the GeoGebra software and, to have a qualitative evaluation of the investigation and the results, was used Didactic Engineering as a methodology research. As a consequence of this detailed research, some interesting details about the teaching and learning process were observed, discussed and described.
Thermal shock analysis of functionally graded materials by micromechanical model
International Nuclear Information System (INIS)
Ueda, Sei
2002-01-01
The transient thermoelastic behavior of the functionally graded plate due to a thermal shock with temperature dependent properties is studied in this paper. The development of a micromechanical model for the functionally graded materials is presented and its application to thermoelastic analysis is discussed for the case of the W-Cu functionally graded material for the International Thermonuclear Experimental Reactor divertor plate. The divertor plate is made of a graded layer bonded between a homogeneous substrate and a homogeneous coating, and it is subjected to a cycle of heating and cooling on the coating surface of the material. The thermal and elastic properties of the material are dependent on the temperature and the position. Numerical calculations are carried out, and the results for the transient temperature and thermal stress distributions are displayed graphically. (author)
A review of function modeling: Approaches and applications
Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.
2008-01-01
This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research fields of artificial intelligence, design theory, and maintenance are discussed. In this discussion the goals are to highlight the features of various classical approaches in relation to FM, to delin...
Using computational models to relate structural and functional brain connectivity
Czech Academy of Sciences Publication Activity Database
Hlinka, Jaroslav; Coombes, S.
2012-01-01
Roč. 36, č. 2 (2012), s. 2137-2145 ISSN 0953-816X R&D Projects: GA MŠk 7E08027 EU Projects: European Commission(XE) 200728 - BRAINSYNC Institutional research plan: CEZ:AV0Z10300504 Keywords : brain disease * computational modelling * functional connectivity * graph theory * structural connectivity Subject RIV: FH - Neurology Impact factor: 3.753, year: 2012
Unsteady Aerodynamic Modeling of A Maneuvering Aircraft Using Indicial Functions
2016-03-30
Paper Undergraduate Student Paper Postgraduate Student Paper █ Unsteady Aerodynamic Modeling of A Maneuvering Aircraft Using Indicial Functions...this configuration exhibit strong pitch up behaviour at a relatively low angle of attack and lateral instability that can lead to serious aerodynamic...reduce flight speed, the reduced flight speed helps to have a smaller radius turn and total travelled time. Next, the airplane starts to roll as the
Model Complexities of Shallow Networks Representing Highly Varying Functions
Czech Academy of Sciences Publication Activity Database
Kůrková, Věra; Sanguineti, M.
2016-01-01
Roč. 171, 1 January (2016), s. 598-604 ISSN 0925-2312 R&D Projects: GA MŠk(CZ) LD13002 Grant - others:grant for Visiting Professors(IT) GNAMPA-INdAM Institutional support: RVO:67985807 Keywords : shallow networks * model complexity * highly varying functions * Chernoff bound * perceptrons * Gaussian kernel units Subject RIV: IN - Informatics, Computer Science Impact factor: 3.317, year: 2016
Di Maggio, Jimena; Fernández, Carolina; Parodi, Elisa R; Diaz, M Soledad; Estrada, Vanina
2016-01-01
In this paper we address the formulation of two mechanistic water quality models that differ in the way the phytoplankton community is described. We carry out parameter estimation subject to differential-algebraic constraints and validation for each model and comparison between models performance. The first approach aggregates phytoplankton species based on their phylogenetic characteristics (Taxonomic group model) and the second one, on their morpho-functional properties following Reynolds' classification (Functional group model). The latter approach takes into account tolerance and sensitivity to environmental conditions. The constrained parameter estimation problems are formulated within an equation oriented framework, with a maximum likelihood objective function. The study site is Paso de las Piedras Reservoir (Argentina), which supplies water for consumption for 450,000 population. Numerical results show that phytoplankton morpho-functional groups more closely represent each species growth requirements within the group. Each model performance is quantitatively assessed by three diagnostic measures. Parameter estimation results for seasonal dynamics of the phytoplankton community and main biogeochemical variables for a one-year time horizon are presented and compared for both models, showing the functional group model enhanced performance. Finally, we explore increasing nutrient loading scenarios and predict their effect on phytoplankton dynamics throughout a one-year time horizon. Copyright © 2015 Elsevier Ltd. All rights reserved.
Linking density functional and mode coupling models for supercooled liquids.
Premkumar, Leishangthem; Bidhoodi, Neeta; Das, Shankar P
2016-03-28
We compare predictions from two familiar models of the metastable supercooled liquid, respectively, constructed with thermodynamic and dynamic approaches. In the so called density functional theory the free energy F[ρ] of the liquid is a functional of the inhomogeneous density ρ(r). The metastable state is identified as a local minimum of F[ρ]. The sharp density profile characterizing ρ(r) is identified as a single particle oscillator, whose frequency is obtained from the parameters of the optimum density function. On the other hand, a dynamic approach to supercooled liquids is taken in the mode coupling theory (MCT) which predict a sharp ergodicity-non-ergodicity transition at a critical density. The single particle dynamics in the non-ergodic state, treated approximately, represents a propagating mode whose characteristic frequency is computed from the corresponding memory function of the MCT. The mass localization parameters in the above two models (treated in their simplest forms) are obtained, respectively, in terms of the corresponding natural frequencies depicted and are shown to have comparable magnitudes.
Linking density functional and mode coupling models for supercooled liquids
Energy Technology Data Exchange (ETDEWEB)
Premkumar, Leishangthem; Bidhoodi, Neeta; Das, Shankar P. [School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067 (India)
2016-03-28
We compare predictions from two familiar models of the metastable supercooled liquid, respectively, constructed with thermodynamic and dynamic approaches. In the so called density functional theory the free energy F[ρ] of the liquid is a functional of the inhomogeneous density ρ(r). The metastable state is identified as a local minimum of F[ρ]. The sharp density profile characterizing ρ(r) is identified as a single particle oscillator, whose frequency is obtained from the parameters of the optimum density function. On the other hand, a dynamic approach to supercooled liquids is taken in the mode coupling theory (MCT) which predict a sharp ergodicity-non-ergodicity transition at a critical density. The single particle dynamics in the non-ergodic state, treated approximately, represents a propagating mode whose characteristic frequency is computed from the corresponding memory function of the MCT. The mass localization parameters in the above two models (treated in their simplest forms) are obtained, respectively, in terms of the corresponding natural frequencies depicted and are shown to have comparable magnitudes.
Calibration of two complex ecosystem models with different likelihood functions
Hidy, Dóra; Haszpra, László; Pintér, Krisztina; Nagy, Zoltán; Barcza, Zoltán
2014-05-01
The biosphere is a sensitive carbon reservoir. Terrestrial ecosystems were approximately carbon neutral during the past centuries, but they became net carbon sinks due to climate change induced environmental change and associated CO2 fertilization effect of the atmosphere. Model studies and measurements indicate that the biospheric carbon sink can saturate in the future due to ongoing climate change which can act as a positive feedback. Robustness of carbon cycle models is a key issue when trying to choose the appropriate model for decision support. The input parameters of the process-based models are decisive regarding the model output. At the same time there are several input parameters for which accurate values are hard to obtain directly from experiments or no local measurements are available. Due to the uncertainty associated with the unknown model parameters significant bias can be experienced if the model is used to simulate the carbon and nitrogen cycle components of different ecosystems. In order to improve model performance the unknown model parameters has to be estimated. We developed a multi-objective, two-step calibration method based on Bayesian approach in order to estimate the unknown parameters of PaSim and Biome-BGC models. Biome-BGC and PaSim are a widely used biogeochemical models that simulate the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere, and within the components of the terrestrial ecosystems (in this research the developed version of Biome-BGC is used which is referred as BBGC MuSo). Both models were calibrated regardless the simulated processes and type of model parameters. The calibration procedure is based on the comparison of measured data with simulated results via calculating a likelihood function (degree of goodness-of-fit between simulated and measured data). In our research different likelihood function formulations were used in order to examine the effect of the different model
A dynamic model for functional mapping of biological rhythms.
Fu, Guifang; Luo, Jiangtao; Berg, Arthur; Wang, Zhong; Li, Jiahan; Das, Kiranmoy; Li, Runze; Wu, Rongling
2011-01-01
Functional mapping is a statistical method for mapping quantitative trait loci (QTLs) that regulate the dynamic pattern of a biological trait. This method integrates mathematical aspects of biological complexity into a mixture model for genetic mapping and tests the genetic effects of QTLs by comparing genotype-specific curve parameters. As a way of quantitatively specifying the dynamic behavior of a system, differential equations have proven to be powerful for modeling and unraveling the biochemical, molecular, and cellular mechanisms of a biological process, such as biological rhythms. The equipment of functional mapping with biologically meaningful differential equations provides new insights into the genetic control of any dynamic processes. We formulate a new functional mapping framework for a dynamic biological rhythm by incorporating a group of ordinary differential equations (ODE). The Runge-Kutta fourth order algorithm was implemented to estimate the parameters that define the system of ODE. The new model will find its implications for understanding the interplay between gene interactions and developmental pathways in complex biological rhythms.
Modeling Marine Electromagnetic Survey with Radial Basis Function Networks
Directory of Open Access Journals (Sweden)
Agus Arif
2014-11-01
Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network[1].[1] This manuscript is an extended version of our previous paper, entitled Radial Basis Function Networks for Modeling Marine Electromagnetic Survey, which had been presented on 2011 International Conference on Electrical Engineering and Informatics, 17-19 July 2011, Bandung, Indonesia.
Batterham, A M; George, K P
1997-12-01
In the exercise sciences, simple allometry (y = axb) is rapidly becoming the method of choice for scaling physiological and human performance data for differences in body size. The purpose of this study is to detail the specific regression diagnostics required to validate such models. The sum (T, in kg) of the "snatch" and "clean-and-jerk" lifts of the medalists from the 1995 Men's and Women's World Weightlifting Championships was modeled as a function of body mass (M, in kg). A log-linearized allometric model (ln T = ln a + b ln M) yielded a common mass exponent (b) of 0. 47 (95% confidence interval = 0.43-0.51, P < 0.01). However, size-related patterned deviations in the residuals were evident, indicating that the allometric model was poorly specified and that the mass exponent was not size independent. Model respecification revealed that second-order polynomials provided the best fit, supporting previous modeling of weightlifting data (R. G. Sinclair. Can. J. Appl. Sport Sci. 10: 94-98, 1985). The model parameters (means +/- SE) were T = (21.48 +/- 16.55) + (6.119 +/- 0.359)M - (0. 022 +/- 0.002)M2 (R2 = 0.97) for men and T = (-20.73 +/- 24.14) + (5. 662 +/- 0.722)M - (0.031 +/- 0.005)M2 (R2 = 0.92) for women. We conclude that allometric scaling should be applied only when all underlying model assumptions have been rigorously evaluated.
The stochastic resonance for the incidence function model of metapopulation
Li, Jiang-Cheng; Dong, Zhi-Wei; Zhou, Ruo-Wei; Li, Yun-Xian; Qian, Zhen-Wei
2017-06-01
A stochastic model with endogenous and exogenous periodicities is proposed in this paper on the basis of metapopulation dynamics to model the crop yield losses due to pests and diseases. The rationale is that crop yield losses occur because the physiology of the growing crop is negatively affected by pests and diseases in a dynamic way over time as crop both grows and develops. Metapopulation dynamics can thus be used to model the resultant crop yield losses. The stochastic metapopulation process is described by using the Simplified Incidence Function model (IFM). Compared to the original IFMs, endogenous and exogenous periodicities are considered in the proposed model to handle the cyclical patterns observed in pest infestations, diseases epidemics, and exogenous affecting factors such as temperature and rainfalls. Agricultural loss data in China are used to fit the proposed model. Experimental results demonstrate that: (1) Model with endogenous and exogenous periodicities is a better fit; (2) When the internal system fluctuations and external environmental fluctuations are negatively correlated, EIL or the cost of loss is monotonically increasing; when the internal system fluctuations and external environmental fluctuations are positively correlated, an outbreak of pests and diseases might occur; (3) If the internal system fluctuations and external environmental fluctuations are positively correlated, an optimal patch size can be identified which will greatly weaken the effects of external environmental influence and hence inhibit pest infestations and disease epidemics.
Theoretical limit of spatial resolution in diffuse optical tomography using a perturbation model
International Nuclear Information System (INIS)
Konovalov, A B; Vlasov, V V
2014-01-01
We have assessed the limit of spatial resolution of timedomain diffuse optical tomography (DOT) based on a perturbation reconstruction model. From the viewpoint of the structure reconstruction accuracy, three different approaches to solving the inverse DOT problem are compared. The first approach involves reconstruction of diffuse tomograms from straight lines, the second – from average curvilinear trajectories of photons and the third – from total banana-shaped distributions of photon trajectories. In order to obtain estimates of resolution, we have derived analytical expressions for the point spread function and modulation transfer function, as well as have performed a numerical experiment on reconstruction of rectangular scattering objects with circular absorbing inhomogeneities. It is shown that in passing from reconstruction from straight lines to reconstruction using distributions of photon trajectories we can improve resolution by almost an order of magnitude and exceed the accuracy of reconstruction of multi-step algorithms used in DOT. (optical tomography)
Team models in neurorehabilitation: structure, function, and culture change.
Karol, Robert L
2014-01-01
Neurorehabilitation requires a team effort. Over time the nature of teams has evolved from single discipline work through multi-disciplinary and inter-disciplinary teams to trans-disciplinary teams. However, there are inconsistencies in the literature and clinical practice as to the structure and function of these team models. Each model engenders advantages over its predecessor and unless the models are well understood clinicians may labor in a model that is less efficacious than the most transcendent model. To define and examine the models of single discipline care, multi-disciplinary teams, inter-disciplinary teams, and trans-disciplinary teams and to review in depth trans-disciplinary teams as the most advanced team model. This paper will also consider professional roles and integration across disciplines as well as the crucial topics of staff selection, attendance in rounds and the nature of rounds, staff physical plant assignments, and leadership responsibilities. Leadership responsibilities that will be addressed include scope of practice and role release, peer pressure, and culture change issues. The trans-disciplinary model is the gold standard for teams in neurorehabilitation because they entail more integrated service delivery than do other teams. Trans-disciplinary teams also represent a more persons-centered approach. To initiate a trans-disciplinary model, team members must have excellent communication and shared decision making including persons with brain injury. Leadership must address staff selection, scope of practice and role-release. Otherwise, the model will fail due to peer pressure and institutional or program cultural variables.
Gaussian copula as a likelihood function for environmental models
Wani, O.; Espadas, G.; Cecinati, F.; Rieckermann, J.
2017-12-01
Parameter estimation of environmental models always comes with uncertainty. To formally quantify this parametric uncertainty, a likelihood function needs to be formulated, which is defined as the probability of observations given fixed values of the parameter set. A likelihood function allows us to infer parameter values from observations using Bayes' theorem. The challenge is to formulate a likelihood function that reliably describes the error generating processes which lead to the observed monitoring data, such as rainfall and runoff. If the likelihood function is not representative of the error statistics, the parameter inference will give biased parameter values. Several uncertainty estimation methods that are currently being used employ Gaussian processes as a likelihood function, because of their favourable analytical properties. Box-Cox transformation is suggested to deal with non-symmetric and heteroscedastic errors e.g. for flow data which are typically more uncertain in high flows than in periods with low flows. Problem with transformations is that the results are conditional on hyper-parameters, for which it is difficult to formulate the analyst's belief a priori. In an attempt to address this problem, in this research work we suggest learning the nature of the error distribution from the errors made by the model in the "past" forecasts. We use a Gaussian copula to generate semiparametric error distributions . 1) We show that this copula can be then used as a likelihood function to infer parameters, breaking away from the practice of using multivariate normal distributions. Based on the results from a didactical example of predicting rainfall runoff, 2) we demonstrate that the copula captures the predictive uncertainty of the model. 3) Finally, we find that the properties of autocorrelation and heteroscedasticity of errors are captured well by the copula, eliminating the need to use transforms. In summary, our findings suggest that copulas are an
Colour-independent partition functions in coloured vertex models
Energy Technology Data Exchange (ETDEWEB)
Foda, O., E-mail: omar.foda@unimelb.edu.au [Dept. of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010 (Australia); Wheeler, M., E-mail: mwheeler@lpthe.jussieu.fr [Laboratoire de Physique Théorique et Hautes Energies, CNRS UMR 7589 (France); Université Pierre et Marie Curie – Paris 6, 4 place Jussieu, 75252 Paris cedex 05 (France)
2013-06-11
We study lattice configurations related to S{sub n}, the scalar product of an off-shell state and an on-shell state in rational A{sub n} integrable vertex models, n∈{1,2}. The lattice lines are colourless and oriented. The state variables are n conserved colours that flow along the line orientations, but do not necessarily cover every bond in the lattice. Choosing boundary conditions such that the positions where the colours flow into the lattice are fixed, and where they flow out are summed over, we show that the partition functions of these configurations, with these boundary conditions, are n-independent. Our results extend to trigonometric A{sub n} models, and to all n. This n-independence explains, in vertex-model terms, results from recent studies of S{sub 2} (Caetano and Vieira, 2012, [1], Wheeler, (arXiv:1204.2089), [2]). Namely, 1.S{sub 2}, which depends on two sets of Bethe roots, {b_1} and {b_2}, and cannot (as far as we know) be expressed in single determinant form, degenerates in the limit {b_1}→∞, and/or {b_2}→∞, into a product of determinants, 2. Each of the latter determinants is an A{sub 1} vertex-model partition function.
Colour-independent partition functions in coloured vertex models
International Nuclear Information System (INIS)
Foda, O.; Wheeler, M.
2013-01-01
We study lattice configurations related to S n , the scalar product of an off-shell state and an on-shell state in rational A n integrable vertex models, n∈{1,2}. The lattice lines are colourless and oriented. The state variables are n conserved colours that flow along the line orientations, but do not necessarily cover every bond in the lattice. Choosing boundary conditions such that the positions where the colours flow into the lattice are fixed, and where they flow out are summed over, we show that the partition functions of these configurations, with these boundary conditions, are n-independent. Our results extend to trigonometric A n models, and to all n. This n-independence explains, in vertex-model terms, results from recent studies of S 2 (Caetano and Vieira, 2012, [1], Wheeler, (arXiv:1204.2089), [2]). Namely, 1.S 2 , which depends on two sets of Bethe roots, {b 1 } and {b 2 }, and cannot (as far as we know) be expressed in single determinant form, degenerates in the limit {b 1 }→∞, and/or {b 2 }→∞, into a product of determinants, 2. Each of the latter determinants is an A 1 vertex-model partition function
Plant lessons: exploring ABCB functionality through structural modeling
Directory of Open Access Journals (Sweden)
Aurélien eBailly
2012-01-01
Full Text Available In contrast to mammalian ABCB1 proteins, narrow substrate specificity has been extensively documented for plant orthologs shown to catalyze the transport of the plant hormone, auxin. Using the crystal structures of the multidrug exporters Sav1866 and MmABCB1 as templates, we have developed structural models of plant ABCB proteins with a common architecture. Comparisons of these structures identified kingdom-specific candidate substrate-binding regions within the translocation chamber formed by the transmembrane domains of ABCBs from the model plant Arabidopsis. These results suggest an early evolutionary divergence of plant and mammalian ABCBs. Validation of these models becomes a priority for efforts to elucidate ABCB function and manipulate this class of transporters to enhance plant productivity and quality.
Plant Lessons: Exploring ABCB Functionality Through Structural Modeling
Bailly, Aurélien; Yang, Haibing; Martinoia, Enrico; Geisler, Markus; Murphy, Angus S.
2012-01-01
In contrast to mammalian ABCB1 proteins, narrow substrate specificity has been extensively documented for plant orthologs shown to catalyze the transport of the plant hormone, auxin. Using the crystal structures of the multidrug exporters Sav1866 and MmABCB1 as templates, we have developed structural models of plant ABCB proteins with a common architecture. Comparisons of these structures identified kingdom-specific candidate substrate-binding regions within the translocation chamber formed by the transmembrane domains of ABCBs from the model plant Arabidopsis. These results suggest an early evolutionary divergence of plant and mammalian ABCBs. Validation of these models becomes a priority for efforts to elucidate ABCB function and manipulate this class of transporters to enhance plant productivity and quality. PMID:22639627
Simple model for low-frequency guitar function
DEFF Research Database (Denmark)
Christensen, Ove; Vistisen, Bo B.
1980-01-01
- frequency guitar function. The model predicts frequency responce of sound pressure and top plate mobility which are in close quantitative agreement with experimental responses. The absolute sound pressure level and mobility level are predicted to within a few decibels, and the equivalent piston area......The frequency response of sound pressure and top plate mobility is studied around the two first resonances of the guitar. These resonances are shown to result from a coupling between the fundamental top plate mode and the Helmholtz resonance of the cavity. A simple model is proposed for low...... of the top plate is determined. All parameters of this model can directly be derived from measurements of the frequencies of the two first resonances and of the cavity Helmholtz resonance. The Helmholtz resonance is found as the antiresonance in the spectrum of top plate mobility....
Model-based cartilage thickness measurement in the submillimeter range
Streekstra, G. J.; Strackee, S. D.; Maas, M.; ter Wee, R.; Venema, H. W.
2007-01-01
Current methods of image-based thickness measurement in thin sheet structures utilize second derivative zero crossings to locate the layer boundaries. It is generally acknowledged that the nonzero width of the point spread function (PSF) limits the accuracy of this measurement procedure. We propose
K-space model of motion artifacts in synthetic transmit aperture ultrasound imaging
DEFF Research Database (Denmark)
Nikolov, Svetoslav; Jensen, Jørgen Arendt
2003-01-01
Synthetic transmit aperture (STA) imaging gives the possibility to acquire an image with only few emissions and is appealing for 3D ultrasound imaging. Even though the number of emissions is low, the change in position of the scatterers prohibits the coherent summations of ultrasound echoes and l...... resolution image as a sum of rotated PSFs of a single LRI. The approximation is validated with a Field II simulation. The model predicts and explains the motion artifacts, and gives an intuitive feeling of what would happen for different velocities....... is used to develop an approximation of the point spread function (PSF) of a LRI. It is shown that the PSF of LRIs obtained by transmitting with different elements can be viewed as rotated versions of each other. Summing several LRIs gives a high resolution image. The model approximates the PSF of a high...
Functional gait analysis in a spinal contusion rat model.
Bhimani, Abhiraj D; Kheirkhah, Pouyan; Arnone, Gregory D; Nahhas, Cindy R; Kumar, Prateek; Wonais, Matt; Hidrogo, Hugo; Aguilar, Eddy; Spalinski, Daniel; Gopalka, Mahie; Roth, Steven; Mehta, Ankit I
2017-12-01
Evaluating functional performance of spinal cord injury (SCI) rat models is essential for the development of novel treatments and breakthroughs. However, due to the variety of functional analysis methods available - each with its own strengths and weaknesses - it can be challenging to choose the most appropriate functional analysis test for the animal model. Therefore, we analyzed the strengths and weaknesses of five methods in order to determine which test is not only accurate and easily reproducible, but also relatively inexpensive so that it can be adopted universally. When comparing the Basso, Beattie, and Bresnahan (BBB) test, Ladder walking test, CatWalk test, Rotating Rod test, Microsoft Kinect system and VICON, we used the criteria of sensitivity, quality of data generated, statistical analysis of data, and rate of human error. These specific tests were chosen in order to compare the advantages and disadvantages of simple yet effective methods (BBB, Ladder test, and Rotating Rod test) to more complex and computerized methods (Catwalk, Microsoft Kinect and VICON). Copyright © 2017 Elsevier Ltd. All rights reserved.
Two-point functions in a holographic Kondo model
Energy Technology Data Exchange (ETDEWEB)
Erdmenger, Johanna [Institut für Theoretische Physik und Astrophysik, Julius-Maximilians-Universität Würzburg,Am Hubland, D-97074 Würzburg (Germany); Max-Planck-Institut für Physik (Werner-Heisenberg-Institut),Föhringer Ring 6, D-80805 Munich (Germany); Hoyos, Carlos [Department of Physics, Universidad de Oviedo, Avda. Calvo Sotelo 18, 33007, Oviedo (Spain); O’Bannon, Andy [STAG Research Centre, Physics and Astronomy, University of Southampton,Highfield, Southampton SO17 1BJ (United Kingdom); Papadimitriou, Ioannis [SISSA and INFN - Sezione di Trieste, Via Bonomea 265, I 34136 Trieste (Italy); Probst, Jonas [Rudolf Peierls Centre for Theoretical Physics, University of Oxford,1 Keble Road, Oxford OX1 3NP (United Kingdom); Wu, Jackson M.S. [Department of Physics and Astronomy, University of Alabama, Tuscaloosa, AL 35487 (United States)
2017-03-07
We develop the formalism of holographic renormalization to compute two-point functions in a holographic Kondo model. The model describes a (0+1)-dimensional impurity spin of a gauged SU(N) interacting with a (1+1)-dimensional, large-N, strongly-coupled Conformal Field Theory (CFT). We describe the impurity using Abrikosov pseudo-fermions, and define an SU(N)-invariant scalar operator O built from a pseudo-fermion and a CFT fermion. At large N the Kondo interaction is of the form O{sup †}O, which is marginally relevant, and generates a Renormalization Group (RG) flow at the impurity. A second-order mean-field phase transition occurs in which O condenses below a critical temperature, leading to the Kondo effect, including screening of the impurity. Via holography, the phase transition is dual to holographic superconductivity in (1+1)-dimensional Anti-de Sitter space. At all temperatures, spectral functions of O exhibit a Fano resonance, characteristic of a continuum of states interacting with an isolated resonance. In contrast to Fano resonances observed for example in quantum dots, our continuum and resonance arise from a (0+1)-dimensional UV fixed point and RG flow, respectively. In the low-temperature phase, the resonance comes from a pole in the Green’s function of the form −i〈O〉{sup 2}, which is characteristic of a Kondo resonance.
Evaluation of a modified rat model for functional dyspepsia.
Liang, Qiankun; Yan, Yuan; Mao, Lanfang; Du, Xiaojuan; Liang, Jingjing; Liu, Junhong; Wang, Longde; Li, Hongfang
2018-04-13
The purpose of this study was to establish a modified rat model with functional dyspepsia (FD) and analyze the changes in gastrointestinal motility and brain-gut peptide levels in serum and brain-gut axis. Male Wistar rats were divided into control group (Con) and FD model group. FD model was established by stimulating semi-starvation rats via tail damping, provocation, and forced exercise fatigue until gastrointestinal motility disorder appeared, and then levels of motilin, leptin, cholecystokinin (CCK), and vasoactive intestinal peptide (VIP) were detected in serum by enzyme linked immunosorbent assay and in duodenum, antrum, and hypothalamus by immunohistochemistry, reverse transcriptase-polymerase chain reaction, and Western blot. The results showed rates of intestinal propulsion and gastric emptying slowed down markedly compared to Con (P < 0.05), the gastrointestinal electric activity attenuated, and migrating motor complex (MMC) interrupted in the model group. The levels of leptin and VIP markedly increased, but motilin decreased as compared to the Con (P < 0.05) in serum and in the above tissues. It is interesting that the level of CCK decreased in the antrum and duodenum but increased in the hypothalamus as compared to Con (P < 0.05). The modified rat model meets the diagnostic criteria of FD and can be used as a method for studying FD in animals.
A method of PSF generation for 3D brightfield deconvolution.
Tadrous, P J
2010-02-01
This paper addresses the problem of 3D deconvolution of through focus widefield microscope datasets (Z-stacks). One of the most difficult stages in brightfield deconvolution is finding the point spread function. A theoretically calculated point spread function (called a 'synthetic PSF' in this paper) requires foreknowledge of many system parameters and still gives only approximate results. A point spread function measured from a sub-resolution bead suffers from low signal-to-noise ratio, compounded in the brightfield setting (by contrast to fluorescence) by absorptive, refractive and dispersal effects. This paper describes a method of point spread function estimation based on measurements of a Z-stack through a thin sample. This Z-stack is deconvolved by an idealized point spread function derived from the same Z-stack to yield a point spread function of high signal-to-noise ratio that is also inherently tailored to the imaging system. The theory is validated by a practical experiment comparing the non-blind 3D deconvolution of the yeast Saccharomyces cerevisiae with the point spread function generated using the method presented in this paper (called the 'extracted PSF') to a synthetic point spread function. Restoration of both high- and low-contrast brightfield structures is achieved with fewer artefacts using the extracted point spread function obtained with this method. Furthermore the deconvolution progresses further (more iterations are allowed before the error function reaches its nadir) with the extracted point spread function compared to the synthetic point spread function indicating that the extracted point spread function is a better fit to the brightfield deconvolution model than the synthetic point spread function.
Functional networks inference from rule-based machine learning models.
Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume
2016-01-01
Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The
Analyzing availability using transfer function models and cross spectral analysis
International Nuclear Information System (INIS)
Singpurwalla, N.D.
1980-01-01
The paper shows how the methods of multivariate time series analysis can be used in a novel way to investigate the interrelationships between a series of operating (running) times and a series of maintenance (down) times of a complex system. Specifically, the techniques of cross spectral analysis are used to help obtain a Box-Jenkins type transfer function model for the running times and the down times of a nuclear reactor. A knowledge of the interrelationships between the running times and the down times is useful for an evaluation of maintenance policies, for replacement policy decisions, and for evaluating the availability and the readiness of complex systems
Bidirectional Texture Function Modeling: State of the Art Survey
Czech Academy of Sciences Publication Activity Database
Filip, Jiří; Haindl, Michal
2009-01-01
Roč. 31, č. 11 (2009), s. 1921-1940 ISSN 0162-8828 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593; GA AV ČR 1ET400750407 Grant - others:EC Marie Curie(BE) 41358; GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : BTF * surface texture * 3D texture Subject RIV: BD - Theory of Information Impact factor: 4.378, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/filip-bidirectional texture function modeling state of the art survey.pdf
Approximate models for the analysis of laser velocimetry correlation functions
International Nuclear Information System (INIS)
Robinson, D.P.
1981-01-01
Velocity distributions in the subchannels of an eleven pin test section representing a slice through a Fast Reactor sub-assembly were measured with a dual beam laser velocimeter system using a Malvern K 7023 digital photon correlator for signal processing. Two techniques were used for data reduction of the correlation function to obtain velocity and turbulence values. Whilst both techniques were in excellent agreement on the velocity, marked discrepancies were apparent in the turbulence levels. As a consequence of this the turbulence data were not reported. Subsequent investigation has shown that the approximate technique used as the basis of Malvern's Data Processor 7023V is restricted in its range of application. In this note alternative approximate models are described and evaluated. The objective of this investigation was to develop an approximate model which could be used for on-line determination of the turbulence level. (author)
Structure and Function of a Nonruminant Gut: A Porcine Model
DEFF Research Database (Denmark)
Tajima, Kiyoshi; Aminov, Rustam
2015-01-01
In many aspects, the anatomical, physiological, and microbial diversity features of the ruminant gut are different from that of the monogastric animals. Thus, the main aim of this chapter is to give a comparative overview of the structure and function of the gastrointestinal tract of a nonruminant...... monogastric animal, and here it is represented by a pig model. In this chapter, we describe and discuss (i) microbial diversity in different parts of the porcine gut; (ii) differences between the ruminant and nonruminant gut; (iii) main events during colonization and succession of microbiota in the porcine...... gut; (iv) effects of various feed additives including antibiotics, phages, probiotics, and prebiotics on pigs; and (v) the use of the porcine model in translational medicine....
Dynamics Model Abstraction Scheme Using Radial Basis Functions
Directory of Open Access Journals (Sweden)
Silvia Tolu
2012-01-01
Full Text Available This paper presents a control model for object manipulation. Properties of objects and environmental conditions influence the motor control and learning. System dynamics depend on an unobserved external context, for example, work load of a robot manipulator. The dynamics of a robot arm change as it manipulates objects with different physical properties, for example, the mass, shape, or mass distribution. We address active sensing strategies to acquire object dynamical models with a radial basis function neural network (RBF. Experiments are done using a real robot’s arm, and trajectory data are gathered during various trials manipulating different objects. Biped robots do not have high force joint servos and the control system hardly compensates all the inertia variation of the adjacent joints and disturbance torque on dynamic gait control. In order to achieve smoother control and lead to more reliable sensorimotor complexes, we evaluate and compare a sparse velocity-driven versus a dense position-driven control scheme.
DEFF Research Database (Denmark)
Øjelund, Henrik; Sadegh, Payman
2000-01-01
be obtained. This paper presents a new approach for system modelling under partial (global) information (or the so called Gray-box modelling) that seeks to perserve the benefits of the global as well as local methodologies sithin a unified framework. While the proposed technique relies on local approximations......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality....
Models for predicting objective function weights in prostate cancer IMRT
International Nuclear Information System (INIS)
Boutilier, Justin J.; Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.
2015-01-01
Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR
Modeling of fingerlike functionally graded microstructure piezoelectric actuator
Almajid, Abdulhakim; Hudnut, Steven W.; Taya, Minoru
2000-06-01
The mechanical behavior of a cylindrical, finger-like shaped, piezoelectric actuator with Functionally Graded Microstructure (FGM) was modeled by our analytical model and FEM. Different layers or lamina of different piezoelectric volume fraction in a polymer matrix were stacked to create FGM. Although the bimorph plate exhibit reasonably high out-of-plane displacement, induced stress field remains very high limiting its long life use. FGM piezoelectric plates have been developed to increase the out-of-plane displacement while reducing the stresses where the electro-elastic properties are graded through the plate thickness. Finger-like shape piezo actuators are developed where the properties are graded in the radial direction. FGM piezoelectric type actuator showed promising results in that the deflections to any direction can be obtained by manipulating the magnitude and direction of the applied electric field. Analytical modeling in computing the deflection of the finger-like actuator and stress field induced in each lamina was developed and compared to FEM modeling. The theory of cylindrical FGM is based on lamination theory in which the coordinate system is changed from the rectangular to cylindrical one and from infinite to finite plate.
The integrated Earth System Model Version 1: formulation and functionality
Energy Technology Data Exchange (ETDEWEB)
Collins, William D.; Craig, Anthony P.; Truesdale, John E.; Di Vittorio, Alan; Jones, Andrew D.; Bond-Lamberty, Benjamin; Calvin, Katherine V.; Edmonds, James A.; Kim, Son H.; Thomson, Allison M.; Patel, Pralit L.; Zhou, Yuyu; Mao, Jiafu; Shi, Xiaoying; Thornton, Peter E.; Chini, Louise M.; Hurtt, George C.
2015-07-23
The integrated Earth System Model (iESM) has been developed as a new tool for pro- jecting the joint human/climate system. The iESM is based upon coupling an Integrated Assessment Model (IAM) and an Earth System Model (ESM) into a common modeling in- frastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species, land use and land cover change, and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. The iESM project integrates the economic and human dimension modeling of an IAM and a fully coupled ESM within a sin- gle simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore- omitted feedbacks between natural and societal drivers, we can improve scientific under- standing of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper de- scribes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.
An Evolutionary Game Theory Model of Spontaneous Brain Functioning.
Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano
2017-11-22
Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.
Modeling Marine Electromagnetic Survey with Radial Basis Function Networks
Directory of Open Access Journals (Sweden)
Agus Arif
2011-08-01
Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Martinez, Josue G.
2010-06-01
The authors consider the analysis of hierarchical longitudinal functional data based upon a functional principal components approach. In contrast to standard frequentist approaches to selecting the number of principal components, the authors do model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order to overcome this, the authors show how to apply Stochastic Approximation Monte Carlo (SAMC) to this problem, a method that has the potential to explore the entire space and does not become trapped in local extrema. The combination of reversible jump methods and SAMC in hierarchical longitudinal functional data is simplified by a polar coordinate representation of the principal components. The approach is easy to implement and does well in simulated data in determining the distribution of the number of principal components, and in terms of its frequentist estimation properties. Empirical applications are also presented.
Minimal models on Riemann surfaces: The partition functions
International Nuclear Information System (INIS)
Foda, O.
1990-01-01
The Coulomb gas representation of the A n series of c=1-6/[m(m+1)], m≥3, minimal models is extended to compact Riemann surfaces of genus g>1. An integral representation of the partition functions, for any m and g is obtained as the difference of two gaussian correlation functions of a background charge, (background charge on sphere) x (1-g), and screening charges integrated over the surface. The coupling constant x (compacitification radius) 2 of the gaussian expressions are, as on the torus, m(m+1), and m/(m+1). The partition functions obtained are modular invariant, have the correct conformal anomaly and - restricting the propagation of states to a single handle - one can verify explicitly the decoupling of the null states. On the other hand, they are given in terms of coupled surface integrals, and it remains to show how they degenerate consistently to those on lower-genus surfaces. In this work, this is clear only at the lattice level, where no screening charges appear. (orig.)
Minimal models on Riemann surfaces: The partition functions
Energy Technology Data Exchange (ETDEWEB)
Foda, O. (Katholieke Univ. Nijmegen (Netherlands). Inst. voor Theoretische Fysica)
1990-06-04
The Coulomb gas representation of the A{sub n} series of c=1-6/(m(m+1)), m{ge}3, minimal models is extended to compact Riemann surfaces of genus g>1. An integral representation of the partition functions, for any m and g is obtained as the difference of two gaussian correlation functions of a background charge, (background charge on sphere) x (1-g), and screening charges integrated over the surface. The coupling constant x (compacitification radius){sup 2} of the gaussian expressions are, as on the torus, m(m+1), and m/(m+1). The partition functions obtained are modular invariant, have the correct conformal anomaly and - restricting the propagation of states to a single handle - one can verify explicitly the decoupling of the null states. On the other hand, they are given in terms of coupled surface integrals, and it remains to show how they degenerate consistently to those on lower-genus surfaces. In this work, this is clear only at the lattice level, where no screening charges appear. (orig.).
Schaefferkoetter, Joshua; Casey, Michael; Townsend, David; El Fakhri, Georges
2013-03-01
Time-of-flight (TOF) and point spread function (PSF) modeling have been shown to improve PET reconstructions, but the impact on physicians in the clinical setting has not been thoroughly investigated. A lesion detection and localization study was performed using simulated lesions in real patient images. Four reconstruction schemes were considered: ordinary Poisson OSEM (OP) alone and combined with TOF, PSF, and TOF + PSF. The images were presented to physicians experienced in reading PET images, and the performance of each was quantified using localization receiver operating characteristic. Numerical observers (non-prewhitening and Hotelling) were used to identify optimal reconstruction parameters, and observer SNR was compared to the performance of the physicians. The numerical models showed good agreement with human performance, and best performance was achieved by both when using TOF + PSF. These findings suggest a large potential benefit of TOF + PSF for oncology PET studies, especially in the detection of small, low-intensity, focal disease in larger patients.
International Nuclear Information System (INIS)
Schaefferkoetter, Joshua; Casey, Michael; Townsend, David; El Fakhri, Georges
2013-01-01
Time-of-flight (TOF) and point spread function (PSF) modeling have been shown to improve PET reconstructions, but the impact on physicians in the clinical setting has not been thoroughly investigated. A lesion detection and localization study was performed using simulated lesions in real patient images. Four reconstruction schemes were considered: ordinary Poisson OSEM (OP) alone and combined with TOF, PSF, and TOF + PSF. The images were presented to physicians experienced in reading PET images, and the performance of each was quantified using localization receiver operating characteristic. Numerical observers (non-prewhitening and Hotelling) were used to identify optimal reconstruction parameters, and observer SNR was compared to the performance of the physicians. The numerical models showed good agreement with human performance, and best performance was achieved by both when using TOF + PSF. These findings suggest a large potential benefit of TOF + PSF for oncology PET studies, especially in the detection of small, low-intensity, focal disease in larger patients. (paper)
Ayasso, Hacheme; Mohammad-Djafari, Ali
2010-09-01
In this paper, we propose a method to simultaneously restore and to segment piecewise homogeneous images degraded by a known point spread function (PSF) and additive noise. For this purpose, we propose a family of nonhomogeneous Gauss-Markov fields with Potts region labels model for images to be used in a Bayesian estimation framework. The joint posterior law of all the unknowns (the unknown image, its segmentation (hidden variable) and all the hyperparameters) is approximated by a separable probability law via the variational Bayes technique. This approximation gives the possibility to obtain practically implemented joint restoration and segmentation algorithm. We will present some preliminary results and comparison with a MCMC Gibbs sampling based algorithm. We may note that the prior models proposed in this work are particularly appropriate for the images of the scenes or objects that are composed of a finite set of homogeneous materials. This is the case of many images obtained in nondestructive testing (NDT) applications.
Melittin restores proteasome function in an animal model of ALS
Directory of Open Access Journals (Sweden)
Lee Sang Min
2011-06-01
Full Text Available Abstract Amyotrophic lateral sclerosis (ALS is a paralyzing disorder characterized by the progressive degeneration and death of motor neurons and occurs both as a sporadic and familial disease. Mutant SOD1 (mtSOD1 in motor neurons induces vulnerability to the disease through protein misfolding, mitochondrial dysfunction, oxidative damage, cytoskeletal abnormalities, defective axonal transport- and growth factor signaling, excitotoxicity, and neuro-inflammation. Melittin is a 26 amino acid protein and is one of the components of bee venom which is used in traditional Chinese medicine to inhibit of cancer cell proliferation and is known to have anti-inflammatory and anti-arthritic effects. The purpose of the present study was to determine if melittin could suppress motor neuron loss and protein misfolding in the hSOD1G93A mouse, which is commonly used as a model for inherited ALS. Meltittin was injected at the 'ZuSanLi' (ST36 acupuncture point in the hSOD1G93A animal model. Melittin-treated animals showed a decrease in the number of microglia and in the expression level of phospho-p38 in the spinal cord and brainstem. Interestingly, melittin treatment in symptomatic ALS animals improved motor function and reduced the level of neuron death in the spinal cord when compared to the control group. Furthermore, we found increased of α-synuclein modifications, such as phosphorylation or nitration, in both the brainstem and spinal cord in hSOD1G93A mice. However, melittin treatment reduced α-synuclein misfolding and restored the proteasomal activity in the brainstem and spinal cord of symptomatic hSOD1G93A transgenic mice. Our research suggests a potential functional link between melittin and the inhibition of neuroinflammation in an ALS animal model.
Density Functional Theory Modeling of Ferrihydrite Nanoparticle Adsorption Behavior
Kubicki, J.
2016-12-01
Ferrihydrite is a critical substrate for adsorption of oxyanion species in the environment1. The nanoparticulate nature of ferrihydrite is inherent to its formation, and hence it has been called a "nano-mineral"2. The nano-scale size and unusual composition of ferrihydrite has made structural determination of this phase problematic. Michel et al.3 have proposed an atomic structure for ferrihydrite, but this model has been controversial4,5. Recent work has shown that the Michel et al.3 model structure may be reasonably accurate despite some deficiencies6-8. An alternative model has been proposed by Manceau9. This work utilizes density functional theory (DFT) calculations to model both the structure of ferrihydrite nanoparticles based on the Michel et al. 3 model as refined in Hiemstra8 and the modified akdalaite model of Manceau9. Adsorption energies of carbonate, phosphate, sulfate, chromate, arsenite and arsenate are calculated. Periodic projector-augmented planewave calculations were performed with the Vienna Ab-initio Simulation Package (VASP10) on an approximately 1.7 nm diameter Michel nanoparticle (Fe38O112H110) and on a 2 nm Manceau nanoparticle (Fe38O95H76). After energy minimization of the surface H and O atoms. The model will be used to assess the possible configurations of adsorbed oxyanions on the model nanoparticles. Brown G.E. Jr. and Calas G. (2012) Geochemical Perspectives, 1, 483-742. Hochella M.F. and Madden A.S. (2005) Elements, 1, 199-203. Michel, F.M., Ehm, L., Antao, S.M., Lee, P.L., Chupas, P.J., Liu, G., Strongin, D.R., Schoonen, M.A.A., Phillips, B.L., and Parise, J.B., 2007, Science, 316, 1726-1729. Rancourt, D.G., and Meunier, J.F., 2008, American Mineralogist, 93, 1412-1417. Manceau, A., 2011, American Mineralogist, 96, 521-533. Maillot, F., Morin, G., Wang, Y., Bonnin, D., Ildefonse, P., Chaneac, C., Calas, G., 2011, Geochimica et Cosmochimica Acta, 75, 2708-2720. Pinney, N., Kubicki, J.D., Middlemiss, D.S., Grey, C.P., and Morgan, D
Applying fuzzy analytic network process in quality function deployment model
Directory of Open Access Journals (Sweden)
Mohammad Ali Afsharkazemi
2012-08-01
Full Text Available In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view.
Caballero, Marc; Moreira, Ibério de P R; Bofill, Josep Maria
2013-05-07
A comparison model is proposed based on the Löwdin partitioning technique to analyze the differences in the treatment of electron correlation by the wave function and density functional models. This comparison model provides a tool to understand the inherent structure of both theories and its discrepancies in terms of the subjacent mathematical structure and the necessary conditions for variationality required for the energy functional. Some numerical results on simple molecules are also reported revealing the known phenomenon of "overcorrelation" of density functional theory methods.
Dynamic density functional theory of solid tumor growth: Preliminary models
Directory of Open Access Journals (Sweden)
Arnaud Chauviere
2012-03-01
Full Text Available Cancer is a disease that can be seen as a complex system whose dynamics and growth result from nonlinear processes coupled across wide ranges of spatio-temporal scales. The current mathematical modeling literature addresses issues at various scales but the development of theoretical methodologies capable of bridging gaps across scales needs further study. We present a new theoretical framework based on Dynamic Density Functional Theory (DDFT extended, for the first time, to the dynamics of living tissues by accounting for cell density correlations, different cell types, phenotypes and cell birth/death processes, in order to provide a biophysically consistent description of processes across the scales. We present an application of this approach to tumor growth.
Drosophila Cancer Models Identify Functional Differences between Ret Fusions
Directory of Open Access Journals (Sweden)
Sarah Levinson
2016-09-01
Full Text Available We generated and compared Drosophila models of RET fusions CCDC6-RET and NCOA4-RET. Both RET fusions directed cells to migrate, delaminate, and undergo EMT, and both resulted in lethality when broadly expressed. In all phenotypes examined, NCOA4-RET was more severe than CCDC6-RET, mirroring their effects on patients. A functional screen against the Drosophila kinome and a library of cancer drugs found that CCDC6-RET and NCOA4-RET acted through different signaling networks and displayed distinct drug sensitivities. Combining data from the kinome and drug screens identified the WEE1 inhibitor AZD1775 plus the multi-kinase inhibitor sorafenib as a synergistic drug combination that is specific for NCOA4-RET. Our work emphasizes the importance of identifying and tailoring a patient’s treatment to their specific RET fusion isoform and identifies a multi-targeted therapy that may prove effective against tumors containing the NCOA4-RET fusion.
Efficient time-domain model of the graphene dielectric function
Prokopeva, Ludmila J.; Kildishev, Alexander V.
2013-09-01
A honey-comb monolayer lattice of carbon atoms, graphene, is not only ultra-thin, ultra-light, flexible and strong, but also highly conductive when doped and exhibits strong interaction with electromagnetic radiation in the spectral range from microwaves to the ultraviolet. Moreover, this interaction can be effectively controlled electrically. High flexibility and conductivity makes graphene an attractive material for numerous photonic applications requiring transparent conducting electrodes: touchscreens, liquid crystal displays, organic photovoltaic cells, and organic light-emitting diodes. Meanwhile, its tunability makes it desirable for optical modulators, tunable filters and polarizers. This paper deals with the basics of the time-domain modeling of the graphene dielectric function under a random-phase approximation. We focus at applicability of Padé approximants to the interband dielectric function (IDF) of single layer graphene. Our study is centered on the development of a two-critical points approximation (2CPA) of the IDF within a single-electron framework with negligible carrier scattering and a realistic range of chemical potential at room temperature. This development is successfully validated by comparing reflection and transmission spectra computed by a numerical method in time-domain versus semi-analytical calculations in frequency domain. Finally, we sum up our results - (1) high-quality approximation, (2) tunability, and (3) second-order accurate numerical FDTD implementation of the 2CPA of IDF demonstrated across the desired range of the chemical potential to temperature ratios (4 - 23). Finally, we put forward future directions for time-domain modeling of optical response of graphene with wide range of tunable and fabrication-dependent parameters, including other broadening factors and variations of temperature and chemical potentials.
Stand diameter distribution modelling and prediction based on Richards function.
Directory of Open Access Journals (Sweden)
Ai-guo Duan
Full Text Available The objective of this study was to introduce application of the Richards equation on modelling and prediction of stand diameter distribution. The long-term repeated measurement data sets, consisted of 309 diameter frequency distributions from Chinese fir (Cunninghamia lanceolata plantations in the southern China, were used. Also, 150 stands were used as fitting data, the other 159 stands were used for testing. Nonlinear regression method (NRM or maximum likelihood estimates method (MLEM were applied to estimate the parameters of models, and the parameter prediction method (PPM and parameter recovery method (PRM were used to predict the diameter distributions of unknown stands. Four main conclusions were obtained: (1 R distribution presented a more accurate simulation than three-parametric Weibull function; (2 the parameters p, q and r of R distribution proved to be its scale, location and shape parameters, and have a deep relationship with stand characteristics, which means the parameters of R distribution have good theoretical interpretation; (3 the ordinate of inflection point of R distribution has significant relativity with its skewness and kurtosis, and the fitted main distribution range for the cumulative diameter distribution of Chinese fir plantations was 0.4∼0.6; (4 the goodness-of-fit test showed diameter distributions of unknown stands can be well estimated by applying R distribution based on PRM or the combination of PPM and PRM under the condition that only quadratic mean DBH or plus stand age are known, and the non-rejection rates were near 80%, which are higher than the 72.33% non-rejection rate of three-parametric Weibull function based on the combination of PPM and PRM.
Scrutinio, Domenico; Lanzillo, Bernardo; Guida, Pietro; Mastropasqua, Filippo; Monitillo, Vincenzo; Pusineri, Monica; Formica, Roberto; Russo, Giovanna; Guarnaschelli, Caterina; Ferretti, Chiara; Calabrese, Gianluigi
2017-12-01
Prediction of outcome after stroke rehabilitation may help clinicians in decision-making and planning rehabilitation care. We developed and validated a predictive tool to estimate the probability of achieving improvement in physical functioning (model 1) and a level of independence requiring no more than supervision (model 2) after stroke rehabilitation. The models were derived from 717 patients admitted for stroke rehabilitation. We used multivariable logistic regression analysis to build each model. Then, each model was prospectively validated in 875 patients. Model 1 included age, time from stroke occurrence to rehabilitation admission, admission motor and cognitive Functional Independence Measure scores, and neglect. Model 2 included age, male gender, time since stroke onset, and admission motor and cognitive Functional Independence Measure score. Both models demonstrated excellent discrimination. In the derivation cohort, the area under the curve was 0.883 (95% confidence intervals, 0.858-0.910) for model 1 and 0.913 (95% confidence intervals, 0.884-0.942) for model 2. The Hosmer-Lemeshow χ 2 was 4.12 ( P =0.249) and 1.20 ( P =0.754), respectively. In the validation cohort, the area under the curve was 0.866 (95% confidence intervals, 0.840-0.892) for model 1 and 0.850 (95% confidence intervals, 0.815-0.885) for model 2. The Hosmer-Lemeshow χ 2 was 8.86 ( P =0.115) and 34.50 ( P =0.001), respectively. Both improvement in physical functioning (hazard ratios, 0.43; 0.25-0.71; P =0.001) and a level of independence requiring no more than supervision (hazard ratios, 0.32; 0.14-0.68; P =0.004) were independently associated with improved 4-year survival. A calculator is freely available for download at https://goo.gl/fEAp81. This study provides researchers and clinicians with an easy-to-use, accurate, and validated predictive tool for potential application in rehabilitation research and stroke management. © 2017 American Heart Association, Inc.
Plant functional type mapping for earth system models
Directory of Open Access Journals (Sweden)
B. Poulter
2011-11-01
Full Text Available The sensitivity of global carbon and water cycling to climate variability is coupled directly to land cover and the distribution of vegetation. To investigate biogeochemistry-climate interactions, earth system models require a representation of vegetation distributions that are either prescribed from remote sensing data or simulated via biogeography models. However, the abstraction of earth system state variables in models means that data products derived from remote sensing need to be post-processed for model-data assimilation. Dynamic global vegetation models (DGVM rely on the concept of plant functional types (PFT to group shared traits of thousands of plant species into usually only 10–20 classes. Available databases of observed PFT distributions must be relevant to existing satellite sensors and their derived products, and to the present day distribution of managed lands. Here, we develop four PFT datasets based on land-cover information from three satellite sensors (EOS-MODIS 1 km and 0.5 km, SPOT4-VEGETATION 1 km, and ENVISAT-MERIS 0.3 km spatial resolution that are merged with spatially-consistent Köppen-Geiger climate zones. Using a beta (ß diversity metric to assess reclassification similarity, we find that the greatest uncertainty in PFT classifications occur most frequently between cropland and grassland categories, and in dryland systems between shrubland, grassland and forest categories because of differences in the minimum threshold required for forest cover. The biogeography-biogeochemistry DGVM, LPJmL, is used in diagnostic mode with the four PFT datasets prescribed to quantify the effect of land-cover uncertainty on climatic sensitivity of gross primary productivity (GPP and transpiration fluxes. Our results show that land-cover uncertainty has large effects in arid regions, contributing up to 30% (20% uncertainty in the sensitivity of GPP (transpiration to precipitation. The availability of PFT datasets that are consistent
Directory of Open Access Journals (Sweden)
Max Mäuhlhäuser
2011-01-01
Full Text Available Developing applications comprising service composition is a complex task. Therefore, to lower the skill barrier for developers, it is important to describe the problem at hand on an abstract level and not to focus on implementation details. This can be done using declarative programming which allows to describe only the result of the problem (which is what the developer wants rather than the description of the implementation. We therefore use purely declarative model-to-model transformations written in a universal model transformation language which is capable of handling even non functional properties using optimization and mathematical programming. This makes it easier to understand and describe service composition and non-functional properties for the developer.
John S. Hogland; Nathaniel M. Anderson
2015-01-01
Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space, often limiting the types of analyses that can be performed. To address this issue, we have developed Function Modeling. Function Modeling is a new modeling framework that streamlines the...
Annotation and retrieval system of CAD models based on functional semantics
Wang, Zhansong; Tian, Ling; Duan, Wenrui
2014-11-01
CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs(AAG) is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System(FSMARS), is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.
Economic modelling of energy services: Rectifying misspecified energy demand functions
International Nuclear Information System (INIS)
Hunt, Lester C.; Ryan, David L.
2015-01-01
estimation of an aggregate energy demand function for the UK with data over the period 1960–2011. - Highlights: • Introduces explicit modelling of demands for energy services • Derives estimable energy demand equations from energy service demands • Demonstrates the implicit misspecification with typical energy demand equations • Empirical implementation using aggregate and individual energy source data • Illustrative empirical example using UK data and energy efficiency modelling
Bethea, Cynthia L; Kim, Aaron; Cameron, Judy L
2013-02-01
A body of knowledge implicates an increase in output from the locus ceruleus (LC) during stress. We questioned the innervation and function of the LC in our macaque model of Functional Hypothalamic Amenorrhea, also known as Stress-Induced Amenorrhea. Cohorts of macaques were initially characterized as highly stress resilient (HSR) or stress-sensitive (SS) based upon the presence or absence of ovulation during a protocol involving 2 menstrual cycles with psychosocial and metabolic stress. Afterwards, the animals were rested until normal menstrual cycles resumed and then euthanized on day 5 of a new menstrual cycle [a] in the absence of further stress; or [b] after 5 days of resumed psychosocial and metabolic stress. In this study, parameters of the LC were examined in HSR and SS animals in the presence and absence of stress (2×2 block design) using ICC and image analysis. Tyrosine hydroxylase (TH) is the rate-limiting enzyme for the synthesis of catecholamines; and the TH level was used to assess by inference, NE output. The pixel area of TH-positive dendrites extending outside the medial border of the LC was significantly increased by stress to a similar degree in both HSR and SS animals (p<0.0001). There is a significant CRF innervation of the LC. The positive pixel area of CRF boutons, lateral to the LC, was higher in SS than HSR animals in the absence of stress. Five days of moderate stress significantly increased the CRF-positive bouton pixel area in the HSR group (p<0.02), but not in the SS group. There is also a significant serotonin innervation of the LC. A marked increase in medial serotonin dendrite swelling and beading was observed in the SS+stress group, which may be a consequence of excitotoxicity. The dendrite beading interfered with analysis of axonal boutons. However, at one anatomical level, the serotonin-positive bouton area was obtained between the LC and the superior cerebellar peduncle. Serotonin-positive bouton pixel area was significantly
A quantitative confidence signal detection model: 1. Fitting psychometric functions
Yi, Yongwoo
2016-01-01
Perceptual thresholds are commonly assayed in the laboratory and clinic. When precision and accuracy are required, thresholds are quantified by fitting a psychometric function to forced-choice data. The primary shortcoming of this approach is that it typically requires 100 trials or more to yield accurate (i.e., small bias) and precise (i.e., small variance) psychometric parameter estimates. We show that confidence probability judgments combined with a model of confidence can yield psychometric parameter estimates that are markedly more precise and/or markedly more efficient than conventional methods. Specifically, both human data and simulations show that including confidence probability judgments for just 20 trials can yield psychometric parameter estimates that match the precision of those obtained from 100 trials using conventional analyses. Such an efficiency advantage would be especially beneficial for tasks (e.g., taste, smell, and vestibular assays) that require more than a few seconds for each trial, but this potential benefit could accrue for many other tasks. PMID:26763777
Applying Quality Function Deployment Model in Burn Unit Service Improvement.
Keshtkaran, Ali; Hashemi, Neda; Kharazmi, Erfan; Abbasi, Mehdi
2016-01-01
Quality function deployment (QFD) is one of the most effective quality design tools. This study applies QFD technique to improve the quality of the burn unit services in Ghotbedin Hospital in Shiraz, Iran. First, the patients' expectations of burn unit services and their priorities were determined through Delphi method. Thereafter, burn unit service specifications were determined through Delphi method. Further, the relationships between the patients' expectations and service specifications and also the relationships between service specifications were determined through an expert group's opinion. Last, the final importance scores of service specifications were calculated through simple additive weighting method. The findings show that burn unit patients have 40 expectations in six different areas. These expectations are in 16 priority levels. Burn units also have 45 service specifications in six different areas. There are four-level relationships between the patients' expectations and service specifications and four-level relationships between service specifications. The most important burn unit service specifications have been identified in this study. The QFD model developed in the study can be a general guideline for QFD planners and executives.
A modelling framework to simulate foliar fungal epidemics using functional-structural plant models.
Garin, Guillaume; Fournier, Christian; Andrieu, Bruno; Houlès, Vianney; Robert, Corinne; Pradal, Christophe
2014-09-01
Sustainable agriculture requires the identification of new, environmentally responsible strategies of crop protection. Modelling of pathosystems can allow a better understanding of the major interactions inside these dynamic systems and may lead to innovative protection strategies. In particular, functional-structural plant models (FSPMs) have been identified as a means to optimize the use of architecture-related traits. A current limitation lies in the inherent complexity of this type of modelling, and thus the purpose of this paper is to provide a framework to both extend and simplify the modelling of pathosystems using FSPMs. Different entities and interactions occurring in pathosystems were formalized in a conceptual model. A framework based on these concepts was then implemented within the open-source OpenAlea modelling platform, using the platform's general strategy of modelling plant-environment interactions and extending it to handle plant interactions with pathogens. New developments include a generic data structure for representing lesions and dispersal units, and a series of generic protocols to communicate with objects representing the canopy and its microenvironment in the OpenAlea platform. Another development is the addition of a library of elementary models involved in pathosystem modelling. Several plant and physical models are already available in OpenAlea and can be combined in models of pathosystems using this framework approach. Two contrasting pathosystems are implemented using the framework and illustrate its generic utility. Simulations demonstrate the framework's ability to simulate multiscaled interactions within pathosystems, and also show that models are modular components within the framework and can be extended. This is illustrated by testing the impact of canopy architectural traits on fungal dispersal. This study provides a framework for modelling a large number of pathosystems using FSPMs. This structure can accommodate both
International Nuclear Information System (INIS)
Modarres, Mohammad; Cheon, Se Woo
1999-01-01
Most of the complex systems are formed through some hierarchical evolution. Therefore, those systems can be best described through hierarchical frameworks. This paper describes some fundamental attributes of complex physical systems and several hierarchies such as functional, behavioral, goal/condition, and event hierarchies, then presents a function-centered approach to system modeling. Based on the function-centered concept, this paper describes the joint goal tree-success tree (GTST) and the master logic diagram (MLD) as a framework for developing models of complex physical systems. A function-based lexicon for classifying the most common elements of engineering systems for use in the GTST-MLD framework has been proposed. The classification is based on the physical conservation laws that govern the engineering systems. Functional descriptions based on conservation laws provide a simple and rich vocabulary for modeling complex engineering systems
EVALUATION OF RATIONAL FUNCTION MODEL FOR GEOMETRIC MODELING OF CHANG'E-1 CCD IMAGES
Directory of Open Access Journals (Sweden)
Y. Liu
2012-08-01
Full Text Available Rational Function Model (RFM is a generic geometric model that has been widely used in geometric processing of high-resolution earth-observation satellite images, due to its generality and excellent capability of fitting complex rigorous sensor models. In this paper, the feasibility and precision of RFM for geometric modeling of China's Chang'E-1 (CE-1 lunar orbiter images is presented. The RFM parameters of forward-, nadir- and backward-looking CE-1 images are generated though least squares solution using virtual control points derived from the rigorous sensor model. The precision of the RFM is evaluated by comparing with the rigorous sensor model in both image space and object space. Experimental results using nine images from three orbits show that RFM can precisely fit the rigorous sensor model of CE-1 CCD images with a RMS residual error of 1/100 pixel level in image space and less than 5 meters in object space. This indicates that it is feasible to use RFM to describe the imaging geometry of CE-1 CCD images and spacecraft position and orientation. RFM will enable planetary data centers to have an option to supply RFM parameters of orbital images while keeping the original orbit trajectory data confidential.
DEFF Research Database (Denmark)
Stradi, Daniele; Martinez, Umberto; Blom, Anders
2016-01-01
an atomistic approach based on density functional theory and nonequilibrium Green's function, which includes all the relevant ingredients required to model realistic metal-semiconductor interfaces and allows for a direct comparison between theory and experiments via I-Vbias curve simulations. We apply...
Validation of a functional model for integration of safety into process system design
DEFF Research Database (Denmark)
Wu, J.; Lind, M.; Zhang, X.
2015-01-01
Qualitative modeling paradigm offers process systems engineering a potential for developing effective tools for handling issues related to Process Safety. A qualitative functional modeling environment can accommodate different levels of abstraction for capturing knowledge associated...... with the process system functionalities as required for the intended safety applications. To provide the scientific rigor and facilitate the acceptance of qualitative modelling, this contribution focuses on developing a scientifically based validation method for functional models. The Multilevel Flow Modeling (MFM......) methodology is adopted in the paper as a formalized qualitative functional modeling methodology for dynamic process systems. A functional model validation procedure is proposed to assess whether the intended modeling purpose indeed represents a relevant proposal and whether the model represents the system...
Fabrication, Characterization and Modeling of Functionally Graded Materials
Lee, Po-Hua
In the past few decades, a number of theoretical and experimental studies for design, fabrication and performance analysis of solar panel systems (photovoltaic/thermal systems) have been documented. The existing literature shows that the use of solar energy provides a promising solution to alleviate the shortage of natural resources and the environmental pollution associated with electricity generation. A hybrid solar panel has been invented to integrate photovoltaic (PV) cells onto a substrate through a functionally graded material (FGM) with water tubes cast inside, through which water flow serves as both a heat sink and a solar heat collector. Due to the unique and graded material properties of FGMs, this novel design not only supplies efficient thermal harvest and electrical production, but also provides benefits such as structural integrity and material efficiency. In this work, a sedimentation method has been used to fabricate aluminum (Al) and high-density polyethylene (HDPE) FGMs. The size effect of aluminum powder on the material gradation along the depth direction is investigated. Aluminum powder or the mixture of Al and HDPE powder is thoroughly mixed and uniformly dispersed in ethanol and then subjected to sedimentation. During the sedimentation process, the concentration of Al and HDPE particles temporally and spatially changes in the depth direction due to the non-uniform motion of particles; this change further affects the effective viscosity of the suspension and thus changes the drag force of particles. A Stokes' law based model is developed to simulate the sedimentation process, demonstrate the effect of manufacturing parameters on sedimentation, and predict the graded microstructure of deposition in the depth direction. In order to improve the modeling for sedimentation behavior of particles, the Eshelby's equivalent inclusion method (EIM) is presented to determine the interaction between particles, which is not considered in a Stokes' law based
Energy Technology Data Exchange (ETDEWEB)
Thienpont, Benedicte; Barata, Carlos [Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA, CSIC), Jordi Girona, 18-26, 08034 Barcelona (Spain); Raldúa, Demetrio, E-mail: drpqam@cid.csic.es [Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA, CSIC), Jordi Girona, 18-26, 08034 Barcelona (Spain); Maladies Rares: Génétique et Métabolisme (MRGM), University of Bordeaux, EA 4576, F-33400 Talence (France)
2013-06-01
Maternal thyroxine (T4) plays an essential role in fetal brain development, and even mild and transitory deficits in free-T4 in pregnant women can produce irreversible neurological effects in their offspring. Women of childbearing age are daily exposed to mixtures of chemicals disrupting the thyroid gland function (TGFDs) through the diet, drinking water, air and pharmaceuticals, which has raised the highest concern for the potential additive or synergic effects on the development of mild hypothyroxinemia during early pregnancy. Recently we demonstrated that zebrafish eleutheroembryos provide a suitable alternative model for screening chemicals impairing the thyroid hormone synthesis. The present study used the intrafollicular T4-content (IT4C) of zebrafish eleutheroembryos as integrative endpoint for testing the hypotheses that the effect of mixtures of TGFDs with a similar mode of action [inhibition of thyroid peroxidase (TPO)] was well predicted by a concentration addition concept (CA) model, whereas the response addition concept (RA) model predicted better the effect of dissimilarly acting binary mixtures of TGFDs [TPO-inhibitors and sodium-iodide symporter (NIS)-inhibitors]. However, CA model provided better prediction of joint effects than RA in five out of the six tested mixtures. The exception being the mixture MMI (TPO-inhibitor)-KClO{sub 4} (NIS-inhibitor) dosed at a fixed ratio of EC{sub 10} that provided similar CA and RA predictions and hence it was difficult to get any conclusive result. There results support the phenomenological similarity criterion stating that the concept of concentration addition could be extended to mixture constituents having common apical endpoints or common adverse outcomes. - Highlights: • Potential synergic or additive effect of mixtures of chemicals on thyroid function. • Zebrafish as alternative model for testing the effect of mixtures of goitrogens. • Concentration addition seems to predict better the effect of
Minimal models for N-K-functions(infinity)
Dijksma, Aad; Luger, Annemarie; Shondin, Yuri; Langer, M; Luger, A; Woracek, H
2006-01-01
We present explicit realizations in terms of self-adjoint operators and linear relations for a non-zero scalar generalized Nevanlinna function N(z) and the function (N) over cap (z) = -1/N(z) under the assumption that N(z) has exactly one generalized pole which is not of positive type namely at z =
Mittag-Leffler function for discrete fractional modelling
Directory of Open Access Journals (Sweden)
Guo-Cheng Wu
2016-01-01
Full Text Available From the difference equations on discrete time scales, this paper numerically investigates one discrete fractional difference equation in the Caputo delta’s sense which has an explicit solution in form of the discrete Mittag-Leffler function. The exact numerical values of the solutions are given in comparison with the truncated Mittag-Leffler function.
SYNTHESIS OF INFORMATION MODEL FOR ALTERNATIVE FUNCTIONAL DIAGNOSTICS PROCEDURE
P. F. Shchapov; R. P. Miguschenko
2014-01-01
Probabilistic approaches in information theory and information theory of measurement, allowing to calculate and analyze the amount expected to models measuring conversions and encoding tasks random measurement signals were considered. A probabilistic model of diagnostic information model transformation and diagnostic procedures was developed. Conditions for obtaining the maximum amount of diagnostic information were found out.
Scattering function for a model of interacting surfaces
International Nuclear Information System (INIS)
Colangelo, P.; Gonnella, G.; Maritan, A.
1993-01-01
The two-point correlation function of an ensemble of interacting closed self-avoiding surfaces on a cubic lattice is analyzed in the disordered phase, which corresponds to the paramagnetic region in a related spin formulation. Mean-field theory and Monte Carlo simulations predict the existence of a disorder line which corresponds to a transition from an exponential decay to an oscillatory damped behavior of the two-point correlation function. The relevance of the results for the description of amphiphilic systems in a microemulsion phase is discussed. The scattering function is also calculated for a bicontinuous phase coexisting with the paramagnetic phase
Bioinorganic Chemistry Modeled with the TPSSh Density Functional
DEFF Research Database (Denmark)
Kepp, Kasper Planeta
2008-01-01
In this work, the TPSSh density functional has been benchmarked against a test set of experimental structures and bond energies for 80 transition-metal-containing diatomics. It is found that the TPSSh functional gives structures of the same quality as other commonly used hybrid and nonhybrid...... functionals such as B3LYP and BP86. TPSSh gives a slope of 0.99 upon linear fitting to experimental bond energies, whereas B3LYP and BP86, representing 20% and 0% exact exchange, respectively, give linear fits with slopes of 0.91 and 1.07. Thus, TPSSh eliminates the large systematic component of the error...... promising density functional for use and further development within the field of bioinorganic chemistry....
National Research Council Canada - National Science Library
Sznaier, Mario
2001-01-01
.... In this chapter we propose a suboptimal regulator for nonlinear parameter varying, control affine systems based upon the combination of model predictive and control Lyapunov function techniques...
Modeling Alzheimer Disease Through Functional Independence and Participation.
Zucchella, Chiara; Bartolo, Michelangelo; Bernini, Sara; Picascia, Marta; Malinverni, Paola; Sinforiani, Elena
2017-01-01
The relationship between cognitive and functional impairment in Alzheimer Disease (AD) at the earliest stages of the disease is not well characterized. This study aimed at investigating such relationships along AD evolution by means of the Disability Assessment for Dementia (DAD). Consecutive pairs of AD outpatients and their primary informal caregivers were enrolled. Patients were evaluated by means of the Mini Mental State Examination and neuropsychological tests. A clinician completed the Clinical Dementia Rating Scale to stage dementia severity and interviewed the caregivers to complete the Neuropsychiatric Inventory to assess behavioral disturbances and the DAD to evaluate patients' functional competence. A total of 158 dyads were enrolled; the Mini Mental State Examination score was used to stratify patients into 4 groups (>24; 20 to 23.9; 10 to 19.9; <10) that were compared. The statistical analysis revealed that all the cognitive domains were positively related to functional independence, but only logical and executive functions seemed to predict autonomy. An intergroup comparison did not show significant differences in the DAD subscales measuring initiation, planning and organization, and performance. The role of education emerged, confirming the relevance of cognitive reserve. As the field moves toward earlier intervention in preclinical AD, the detection of early functional changes may drive the definition of trials on prevention or intervention for dementia.
Nonparametric modeling of dynamic functional connectivity in fmri data
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Madsen, Kristoffer H; Røge, Rasmus
2015-01-01
dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a nonparametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted...
Modelling graphene quantum dot functionalization via ethylene-dinitrobenzoyl
Noori, Keian; Hübener, Hannes; Kymakis, Emmanuel; Giustino, Feliciano
2016-03-01
Ethylene-dinitrobenzoyl (EDNB) linked to graphene oxide has been shown to improve the performance of graphene/polymer organic photovoltaics. Its binding conformation on graphene, however, is not yet clear, nor have its effects on work function and optical absorption been explored more generally for graphene quantum dots. In this report, we clarify the linkage of EDNB to GQDs from first principles and show that the binding of the molecule increases the work function of graphene, while simultaneously modifying its absorption in the ultraviolet region.
Modelling graphene quantum dot functionalization via ethylene-dinitrobenzoyl
Energy Technology Data Exchange (ETDEWEB)
Noori, Keian; Giustino, Feliciano [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); Hübener, Hannes [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); Nano-Bio Spectroscopy Group and European Theoretical Spectroscopy Facility (ETSF), Universidad del País Vasco CFM CSIC-UPV/EHU-MPC & DIPC, Av. Tolosa 72, 20018 San Sebastián (Spain); Kymakis, Emmanuel [Center of Materials Technology and Photonics & Electrical Engineering Department, Technological Educational Institute (TEI) of Crete, Heraklion, 71004 Crete (Greece)
2016-03-21
Ethylene-dinitrobenzoyl (EDNB) linked to graphene oxide has been shown to improve the performance of graphene/polymer organic photovoltaics. Its binding conformation on graphene, however, is not yet clear, nor have its effects on work function and optical absorption been explored more generally for graphene quantum dots. In this report, we clarify the linkage of EDNB to GQDs from first principles and show that the binding of the molecule increases the work function of graphene, while simultaneously modifying its absorption in the ultraviolet region.
Substance-field Model for Functional Pneumatic Design
Xu, Z. G.; Yang, D. Y.; Shen, W. D.; Liu, T. T.
2017-07-01
The Substance-field analysis is put forward. The functional analysis method is studied to find out the problem, and an improved algorithm is put forward. The internal combustion engine is taken as an example, the harmful function is recognized, and is improved, i.e, high pressure gas is introduced to remove polluted air. The working principle of pneumatic engine is described, the thermodynamic engineering is analyzed, the energy release amounts are analyzed in the isothermal, polymorphism and adiabatic processes. It is concluded that, the isothermal process releases the most energy than the others. The expansion process of the pneumatic engine should be as close as possible to the isothermal process.
A universal Model-R Coupler to facilitate the use of R functions for model calibration and analysis
Wu, Yiping; Liu, Shuguang; Yan, Wende
2014-01-01
Mathematical models are useful in various fields of science and engineering. However, it is a challenge to make a model utilize the open and growing functions (e.g., model inversion) on the R platform due to the requirement of accessing and revising the model's source code. To overcome this barrier, we developed a universal tool that aims to convert a model developed in any computer language to an R function using the template and instruction concept of the Parameter ESTimation program (PEST) and the operational structure of the R-Soil and Water Assessment Tool (R-SWAT). The developed tool (Model-R Coupler) is promising because users of any model can connect an external algorithm (written in R) with their model to implement various model behavior analyses (e.g., parameter optimization, sensitivity and uncertainty analysis, performance evaluation, and visualization) without accessing or modifying the model's source code.
Full wave model of image formation in optical coherence tomography applicable to general samples.
Munro, Peter R T; Curatolo, Andrea; Sampson, David D
2015-02-09
We demonstrate a highly realistic model of optical coherence tomography, based on an existing model of coherent optical microscopes, which employs a full wave description of light. A defining feature of the model is the decoupling of the key functions of an optical coherence tomography system: sample illumination, light-sample interaction and the collection of light scattered by the sample. We show how such a model can be implemented using the finite-difference time-domain method to model light propagation in general samples. The model employs vectorial focussing theory to represent the optical system and, thus, incorporates general illumination beam types and detection optics. To demonstrate its versatility, we model image formation of a stratified medium, a numerical point-spread function phantom and a numerical phantom, based upon a physical three-dimensional structured phantom employed in our laboratory. We show that simulated images compare well with experimental images of a three-dimensional structured phantom. Such a model provides a powerful means to advance all aspects of optical coherence tomography imaging.
Evaluation of Preservation Planning within OAIS, based on the Planets Functional Model
Sierman, Barbara; Wheatley, Paul
2010-01-01
This report gives an overview of the Planets Functional Model and relates it to the Planets deliverables. It also gives a set of recommendations for the OAIS model. The Report was part of the European FP6 Project Planets
Improving the realism of hydrologic model functioning through GRACE
Rakovec, O.; Kumar, R.; Attinger, S.; Samaniego, L. E.
2017-12-01
Increased availability and quality of near real-time observations should improve understanding of predictive skills of hydrological models. Recent studies have shown the limited capability of river discharge data alone to adequately constrain different components of distributed model parameterizations. In this study, the GRACE satellite-based total water storage (TWS) anomaly is used to complement the discharge data with an aim to improve the fidelity of mesoscale hydrologic model (mHM) through multivariate parameter estimation. The study is conducted in 83 European basins covering a wide range of hydro-climatic regimes. The model parameterization complemented with the TWS anomalies leads to statistically significant improvements in (1) discharge simulations during low-flow period, and (2) evapotranspiration estimates which are evaluated against independent (FLUXNET) data. Overall, there is no significant deterioration in model performance for the discharge simulations when complemented by information from the TWS anomalies. However, considerable changes in the partitioning of precipitation into runoff components are noticed by in-/exclusion of TWS during the parameter estimation. A cross-validation test carried out to assess the transferability and robustness of the calibrated parameters to other locations further confirms the benefit of complementary TWS data. In particular, the evapotranspiration estimates show more robust performance when TWS data are incorporated during the parameter estimation, in comparison with the benchmark model constrained against discharge only. This study highlights the value for incorporating multiple data sources during parameter estimation to improve the overall realism of hydrologic model and its applications over large domains.
The PASS model for the assessment of cognitive functioning in ...
African Journals Online (AJOL)
Diversity is an acknowledged characteristic of the South African society. Traditional standardised methods of assessment for cognitive functioning have been discouraged or abandoned, as they have been found to be discriminatory. Arguing for a systematic assessment process, a previous researcher has stated that ...
Modelling functional and structural impact of non-synonymous ...
African Journals Online (AJOL)
... that could affect protein function and structure. Further wet-lab confirmatory analysis in a pathological association study involving a larger population of goats is required at the DQA1 locus. This would lay a sound foundation for breeding disease-resistant individuals in the future. Keywords: Goats, in silico, mutants, protein, ...
Covariance Functions and Random Regression Models in the ...
African Journals Online (AJOL)
ARC-IRENE
CFs were on age of the cow expressed in months (AM) using quadratic (order three) regressions based on orthogonal (Legendre) polynomials, initially proposed by Kirkpatrick & Heckman (1989). The matrices of coefficients KG and KC (corresponding to the additive genetic and permanent environmental functions, G.
A Model for Teaching Literary Analysis Using Systemic Functional Grammar
McCrocklin, Shannon; Slater, Tammy
2017-01-01
This article introduces an approach that middle-school teachers can follow to help their students carry out linguistic-based literary analyses. As an example, it draws on Systemic Functional Grammar (SFG) to show how J.K. Rowling used language to characterize Hermione as an intelligent female in "Harry Potter and the Deathly Hallows."…
Diaphragm function in animal models of chronic obstructive pulmonary disease
Machiels, H.A.
2008-01-01
COPD is characterized by progressive and irreversible airway obstruction. The diaphragm is the main inspiratory muscle. In patients with COPD, structural and functional alterations are present in this skeletal muscle. Dysfunction of respiratory muscles limits the exercise capacity and activities of
Type-2 fuzzy elliptic membership functions for modeling uncertainty
DEFF Research Database (Denmark)
Kayacan, Erdal; Sarabakha, Andriy; Coupland, Simon
2018-01-01
Whereas type-1 and type-2 membership functions (MFs) are the core of any fuzzy logic system, there are no performance criteria available to evaluate the goodness or correctness of the fuzzy MFs. In this paper, we make extensive analysis in terms of the capability of type-2 elliptic fuzzy MFs in m...
Secure and Resilient Functional Modeling for Navy Cyber-Physical Systems
2017-05-24
models were implemented in MATLAB/Simulink as simulation models and evaluated with an example system model of an engine cooling system . The UCI team is...Cyber-Physical Systems ” and submitted for publication to IEEE Conference on Automation Science and Engineering (CASE) 2017. Functional Editor (SCCT...release; distribution is unlimited. Page 1 of 4 Secure & Resilient Functional Modeling for Navy Cyber-Physical Systems FY17 Quarter 2 Technical Progress
Diffusion Forecasting Model with Basis Functions from QR-Decomposition
Harlim, John; Yang, Haizhao
2017-12-01
The diffusion forecasting is a nonparametric approach that provably solves the Fokker-Planck PDE corresponding to Itô diffusion without knowing the underlying equation. The key idea of this method is to approximate the solution of the Fokker-Planck equation with a discrete representation of the shift (Koopman) operator on a set of basis functions generated via the diffusion maps algorithm. While the choice of these basis functions is provably optimal under appropriate conditions, computing these basis functions is quite expensive since it requires the eigendecomposition of an N× N diffusion matrix, where N denotes the data size and could be very large. For large-scale forecasting problems, only a few leading eigenvectors are computationally achievable. To overcome this computational bottleneck, a new set of basis functions constructed by orthonormalizing selected columns of the diffusion matrix and its leading eigenvectors is proposed. This computation can be carried out efficiently via the unpivoted Householder QR factorization. The efficiency and effectiveness of the proposed algorithm will be shown in both deterministically chaotic and stochastic dynamical systems; in the former case, the superiority of the proposed basis functions over purely eigenvectors is significant, while in the latter case forecasting accuracy is improved relative to using a purely small number of eigenvectors. Supporting arguments will be provided on three- and six-dimensional chaotic ODEs, a three-dimensional SDE that mimics turbulent systems, and also on the two spatial modes associated with the boreal winter Madden-Julian Oscillation obtained from applying the Nonlinear Laplacian Spectral Analysis on the measured Outgoing Longwave Radiation.
Prediction of Chemical Function: Model Development and Application
The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (...
Functional Testing Protocols for Commercial Building Efficiency Baseline Modeling Software
Energy Technology Data Exchange (ETDEWEB)
Jump, David; Price, Phillip N.; Granderson, Jessica; Sohn, Michael
2013-09-06
This document describes procedures for testing and validating proprietary baseline energy modeling software accuracy in predicting energy use over the period of interest, such as a month or a year. The procedures are designed according to the methodology used for public domain baselining software in another LBNL report that was (like the present report) prepared for Pacific Gas and Electric Company: ?Commercial Building Energy Baseline Modeling Software: Performance Metrics and Method Testing with Open Source Models and Implications for Proprietary Software Testing Protocols? (referred to here as the ?Model Analysis Report?). The test procedure focuses on the quality of the software?s predictions rather than on the specific algorithms used to predict energy use. In this way the software vendor is not required to divulge or share proprietary information about how their software works, while enabling stakeholders to assess its performance.
Dynamic modelling of pectin extraction describing yield and functional characteristics
DEFF Research Database (Denmark)
Andersen, Nina Marianne; Cognet, T.; Santacoloma, P. A.
2017-01-01
A dynamic model of pectin extraction is proposed that describes pectin yield, degree of esterification and intrinsic viscosity. The dynamic model is one dimensional in the peel geometry and includes mass transport of pectin by diffusion and reaction kinetics of hydrolysis, degradation and de......-esterification. The model takes into account the effects of the process conditions such as temperature and acid concentration on extraction kinetics. It is shown that the model describes pectin bulk solution concentration, degree of esterification and intrinsic viscosity in pilot scale extractions from lime peel...... at different temperatures (60 °C, 70 °C, 80 °C) and pH (1.5, 2.3, 3.1) values....
Functional Testing Protocols for Commercial Building Efficiency Baseline Modeling Software
Jump, David
2014-01-01
This document describes procedures for testing and validating proprietary baseline energy modeling software accuracy in predicting energy use over the period of interest, such as a month or a year. The procedures are designed according to the methodology used for public domain baselining software in another LBNL report that was (like the present report) prepared for Pacific Gas and Electric Company: ?Commercial Building Energy Baseline Modeling Software: Performance Metrics and Method Testing...
Modeling of Tilting-Pad Journal Bearings with Transfer Functions
Directory of Open Access Journals (Sweden)
J. A. Vázquez
2001-01-01
Full Text Available Tilting-pad journal bearings are widely used to promote stability in modern rotating machinery. However, the dynamics associated with pad motion alters this stabilizing capacity depending on the operating speed of the machine and the bearing geometric parameters, particularly the bearing preload. In modeling the dynamics of the entire rotor-bearing system, the rotor is augmented with a model of the bearings. This model may explicitly include the pad degrees of freedom or may implicitly include them by using dynamic matrix reduction methods. The dynamic reduction models may be represented as a set of polynomials in the eigenvalues of the system used to determine stability. All tilting-pad bearings can then be represented by a fixed size matrix with polynomial elements interacting with the rotor. This paper presents a procedure to calculate the coefficients of polynomials for implicit bearing models. The order of the polynomials changes to reflect the number of pads in the bearings. This results in a very compact and computationally efficient method for fully including the dynamics of tilting-pad bearings or other multiple degrees of freedom components that interact with rotors. The fixed size of the dynamic reduction matrices permits the method to be easily incorporated into rotor dynamic stability codes. A recursive algorithm is developed and presented for calculating the coefficients of the polynomials. The method is applied to stability calculations for a model of a typical industrial compressor.
A Model-Based Approach to Constructing Music Similarity Functions
West, Kris; Lamere, Paul
2006-12-01
Several authors have presented systems that estimate the audio similarity of two pieces of music through the calculation of a distance metric, such as the Euclidean distance, between spectral features calculated from the audio, related to the timbre or pitch of the signal. These features can be augmented with other, temporally or rhythmically based features such as zero-crossing rates, beat histograms, or fluctuation patterns to form a more well-rounded music similarity function. It is our contention that perceptual or cultural labels, such as the genre, style, or emotion of the music, are also very important features in the perception of music. These labels help to define complex regions of similarity within the available feature spaces. We demonstrate a machine-learning-based approach to the construction of a similarity metric, which uses this contextual information to project the calculated features into an intermediate space where a music similarity function that incorporates some of the cultural information may be calculated.
Buckled graphene: A model study based on density functional theory
Khan, Yasser
2010-09-01
We make use of ab initio calculations within density functional theory to investigate the influence of buckling on the electronic structure of single layer graphene. Our systematic study addresses a wide range of bond length and bond angle variations in order to obtain insights into the energy scale associated with the formation of ripples in a graphene sheet. © 2010 Elsevier B.V. All rights reserved.
Source function for tritium transport models in the Pacific
International Nuclear Information System (INIS)
Fine, R.A.; Ostlund, H.G.
1977-01-01
An empirically fitted function describes surface Pacific Ocean tritium concentrations as varying exponentially with latitude, the r.m.s. fit to observations is 18%. The oceanic tritium concentration maximum in the North Pacific, which resulted from nuclear weapons testing, lagged the rain data by two to three years occurring in 1965--66. Tritium-salinity correlations are consistent with climatology. Tritium-longitude correlations are consistent with surface water circulation
Empirical Network Model of Human Higher Cognitive Brain Functions
1990-03-31
inference of the cogni- tive psychologists, psychophysiologists, neu- tive processes tairing placa during brief analy- rologists and psychiatrists that so...John and Schwartz 1978) that result from direct communication between cortical distinguish between early exogenous and later en- 0 EVENT-RELATED...Bartlett. F.. Thatcher. R.. Kaye. H.. Valdes. P and Schwartz . E. i 1977a) Neurometmcs: numencal taxonomy identifies different profiles of brain functions
A functional model for characterizing long-distance movement behaviour
Buderman, Frances E.; Hooten, Mevin B.; Ivan, Jacob S.; Shenk, Tanya M.
2016-01-01
Advancements in wildlife telemetry techniques have made it possible to collect large data sets of highly accurate animal locations at a fine temporal resolution. These data sets have prompted the development of a number of statistical methodologies for modelling animal movement.Telemetry data sets are often collected for purposes other than fine-scale movement analysis. These data sets may differ substantially from those that are collected with technologies suitable for fine-scale movement modelling and may consist of locations that are irregular in time, are temporally coarse or have large measurement error. These data sets are time-consuming and costly to collect but may still provide valuable information about movement behaviour.We developed a Bayesian movement model that accounts for error from multiple data sources as well as movement behaviour at different temporal scales. The Bayesian framework allows us to calculate derived quantities that describe temporally varying movement behaviour, such as residence time, speed and persistence in direction. The model is flexible, easy to implement and computationally efficient.We apply this model to data from Colorado Canada lynx (Lynx canadensis) and use derived quantities to identify changes in movement behaviour.
Validation of a functional model for integration of safety into process system design
DEFF Research Database (Denmark)
Wu, J.; Lind, M.; Zhang, X.
2015-01-01
Qualitative modeling paradigm offers process systems engineering a potential for developing effective tools for handling issues related to Process Safety. A qualitative functional modeling environment can accommodate different levels of abstraction for capturing knowledge associated with the proc......Qualitative modeling paradigm offers process systems engineering a potential for developing effective tools for handling issues related to Process Safety. A qualitative functional modeling environment can accommodate different levels of abstraction for capturing knowledge associated...... with the process system functionalities as required for the intended safety applications. To provide the scientific rigor and facilitate the acceptance of qualitative modelling, this contribution focuses on developing a scientifically based validation method for functional models. The Multilevel Flow Modeling (MFM...
Range walk error correction and modeling on Pseudo-random photon counting system
Shen, Shanshan; Chen, Qian; He, Weiji
2017-08-01
Signal to noise ratio and depth accuracy are modeled for the pseudo-random ranging system with two random processes. The theoretical results, developed herein, capture the effects of code length and signal energy fluctuation are shown to agree with Monte Carlo simulation measurements. First, the SNR is developed as a function of the code length. Using Geiger-mode avalanche photodiodes (GMAPDs), longer code length is proven to reduce the noise effect and improve SNR. Second, the Cramer-Rao lower bound on range accuracy is derived to justify that longer code length can bring better range accuracy. Combined with the SNR model and CRLB model, it is manifested that the range accuracy can be improved by increasing the code length to reduce the noise-induced error. Third, the Cramer-Rao lower bound on range accuracy is shown to converge to the previously published theories and introduce the Gauss range walk model to range accuracy. Experimental tests also converge to the presented boundary model in this paper. It has been proven that depth error caused by the fluctuation of the number of detected photon counts in the laser echo pulse leads to the depth drift of Time Point Spread Function (TPSF). Finally, numerical fitting function is used to determine the relationship between the depth error and the photon counting ratio. Depth error due to different echo energy is calibrated so that the corrected depth accuracy is improved to 1cm.
A Classroom Note on: Modeling Functions with the TI-83/84 Calculator
Lubowsky, Jack
2011-01-01
In Pre-Calculus courses, students are taught the composition and combination of functions to model physical applications. However, when combining two or more functions into a single more complicated one, students may lose sight of the physical picture which they are attempting to model. A block diagram, or flow chart, in which each block…
Psychometric Properties on Lecturers' Beliefs on Teaching Function: Rasch Model Analysis
Mofreh, Samah Ali Mohsen; Ghafar, Mohammed Najib Abdul; Omar, Abdul Hafiz Hj; Mosaku, Monsurat; Ma'ruf, Amar
2014-01-01
This paper focuses on the psychometric analysis of lecturers' beliefs on teaching function (LBTF) survey using Rasch Model analysis. The sample comprised 34 Community Colleges' lecturers. The Rasch Model is applied to produce specific measurements on the lecturers' beliefs on teaching function in order to generalize results and inferential…
A functional integral approach without slave bosons to the Anderson model
International Nuclear Information System (INIS)
Nguyen Ngoc Thuan; Nguyen Toan Thang; Coqblin, B.; Bhattacharjee, A.; Hoang Anh Tuan.
1994-06-01
We developed the technique of the functional integral method without slave bosons for the Periodic Anderson Model (PAM) suggested by Sarker for treating the Hubbard Model. This technique allowed us to obtain an analytical expression of Green functions containing U-dependence that is omitted in the formalism with slave bosons. (author). 9 refs
An exactly solvable model of an oscillator with nonlinear coupling and zeros of Bessel functions
Dodonov, V. V.; Klimov, A. B.
1993-01-01
We consider an oscillator model with nonpolynomial interaction. The model admits exact solutions for two situations: for energy eigenvalues in terms of zeros of Bessel functions, that were considered as functions of the continuous index; and for the corresponding eigenstates in terms of Lommel polynomials.
Group-ICA model order highlights patterns of functional brain connectivity
Directory of Open Access Journals (Sweden)
Ahmed eAbou Elseoud
2011-06-01
Full Text Available Resting-state networks (RSNs can be reliably and reproducibly detected using independent component analysis (ICA at both individual subject and group levels. Altering ICA dimensionality (model order estimation can have a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Recent evidence from several neuroimaging studies suggests that the human brain has a modular hierarchical organization which resembles the hierarchy depicted by different ICA model orders. We hypothesized that functional connectivity between-group differences measured with ICA might be affected by model order selection. We investigated differences in functional connectivity using so-called dual-regression as a function of ICA model order in a group of unmedicated seasonal affective disorder (SAD patients compared to normal healthy controls. The results showed that the detected disease-related differences in functional connectivity alter as a function of ICA model order. The volume of between-group differences altered significantly as a function of ICA model order reaching maximum at model order 70 (which seems to be an optimal point that conveys the largest between-group difference then stabilized afterwards. Our results show that fine-grained RSNs enable better detection of detailed disease-related functional connectivity changes. However, high model orders show an increased risk of false positives that needs to be overcome. Our findings suggest that multilevel ICA exploration of functional connectivity enables optimization of sensitivity to brain disorders.
Why are you telling me that? A conceptual model of the social function of autobiographical memory.
Alea, Nicole; Bluck, Susan
2003-03-01
In an effort to stimulate and guide empirical work within a functional framework, this paper provides a conceptual model of the social functions of autobiographical memory (AM) across the lifespan. The model delineates the processes and variables involved when AMs are shared to serve social functions. Components of the model include: lifespan contextual influences, the qualitative characteristics of memory (emotionality and level of detail recalled), the speaker's characteristics (age, gender, and personality), the familiarity and similarity of the listener to the speaker, the level of responsiveness during the memory-sharing process, and the nature of the social relationship in which the memory sharing occurs (valence and length of the relationship). These components are shown to influence the type of social function served and/or, the extent to which social functions are served. Directions for future empirical work to substantiate the model and hypotheses derived from the model are provided.
Nucleon deep-inelastic structure functions in a quark model with factorizability assumptions
International Nuclear Information System (INIS)
Linkevich, A.D.; Skachkov, N.B.
1979-01-01
Formula for structure functions of deep-inelastic electron scattering on nucleon is derived. For this purpose the dynamic model of factorizing quark amplitudes is used. It has been found that with increase of Q 2 transferred pulse square at great values of x kinemastic variable the decrease of structure function values is observed. At x single values the increase of structure function values is found. The comparison With experimental data shows a good agreement of the model with experiment
Endothelial Function in a Mouse Model of Myeloperoxidase Deficiency
Directory of Open Access Journals (Sweden)
Veronika Golubinskaya
2014-01-01
Full Text Available Myeloperoxidase (MPO activity is suggested to reduce the function of vascular nitric oxide, thereby contributing to endothelial dysfunction, although data in rodents are inconclusive. We examined vascular contractile and relaxant responses in MPO-deficient (MPO-/- and wild-type mice to investigate the role for myeloperoxidase in the development of endothelial dysfunction. Carotid and saphenous arteries were taken from 8-month-old mice and studied in a myograph. Responses of carotid arteries to phenylephrine, high potassium, or acetylcholine (Ach were statistically not different from controls. Treatment with lipopolysaccharide (LPS; to enhance endothelial dysfunction reduced responses to Ach in MPO-/- but did not affect responses in wild-type. In response to high concentrations of Ach, carotid arteries responded with transient contractions, which were not different between the groups and not affected by LPS treatment. Saphenous arteries from MPO-/- had smaller normalized diameters and developed less contractile force. Vessels from MPO-/- were less sensitive to Ach than controls. These data suggest that mature MPO-deficient mice do not show enhanced endothelial function compared to wild-type mice, even when provoked with LPS treatment. The EDHF response appears to be reduced in MPO deficiency.
Modelling human musculoskeletal functional movements using ultrasound imaging
Directory of Open Access Journals (Sweden)
Stenlund Hans
2010-05-01
Full Text Available Abstract Background A widespread and fundamental assumption in the health sciences is that muscle functions are related to a wide variety of conditions, for example pain, ischemic and neurological disorder, exercise and injury. It is therefore highly desirable to study musculoskeletal contributions in clinical applications such as the treatment of muscle injuries, post-surgery evaluations, monitoring of progressive degeneration in neuromuscular disorders, and so on. The spatial image resolution in ultrasound systems has improved tremendously in the last few years and nowadays provides detailed information about tissue characteristics. It is now possible to study skeletal muscles in real-time during activity. Methods The ultrasound images are transformed to be congruent and are effectively compressed and stacked in order to be analysed with multivariate techniques. The method is applied to a relevant clinical orthopaedic research field, namely to describe the dynamics in the Achilles tendon and the calf during real-time movements. Results This study introduces a novel method to medical applications that can be used to examine ultrasound image sequences and to detect, visualise and quantify skeletal muscle dynamics and functions. Conclusions This new objective method is a powerful tool to use when visualising tissue activity and dynamics of musculoskeletal ultrasound registrations.
A Model-Based Approach to Constructing Music Similarity Functions
Directory of Open Access Journals (Sweden)
Lamere Paul
2007-01-01
Full Text Available Several authors have presented systems that estimate the audio similarity of two pieces of music through the calculation of a distance metric, such as the Euclidean distance, between spectral features calculated from the audio, related to the timbre or pitch of the signal. These features can be augmented with other, temporally or rhythmically based features such as zero-crossing rates, beat histograms, or fluctuation patterns to form a more well-rounded music similarity function. It is our contention that perceptual or cultural labels, such as the genre, style, or emotion of the music, are also very important features in the perception of music. These labels help to define complex regions of similarity within the available feature spaces. We demonstrate a machine-learning-based approach to the construction of a similarity metric, which uses this contextual information to project the calculated features into an intermediate space where a music similarity function that incorporates some of the cultural information may be calculated.
Nekouei Shahraki, M.; Haala, N.
2015-09-01
To ensure making valid decisions with high accuracy in machine vision systems such as driver-assistant systems, a primary key factor is to have accurate measurements, which means that we need accurate camera calibration for various optical designs and a very fast approach to analyse the calibration data in real-time. Conventional methods have specific limitations such as limited accuracy, instability by using complex models, difficulties to model the local lens distortions and limitation in real-time calculations that altogether show the necessity to introduce new solutions. We introduce a new model for lens distortion modelling with high accuracies beyond conventional models while yet allowing real-time calculation. The concept is based on Free-Function modelling in a posterior calibration step using the initial distortion estimation and the corresponding residuals on the observations as input information. Free-Function model is the technique of numerically and locally modelling the lens distortion field by assuming unknown functions in our calibration model. This increases the model's flexibility to fit to different optical designs and be able to model the very local lens distortions. Using the Free-Function model one can observe great enhancements in accuracy (in comparison with classical models). Furthermore, by increasing the number of control points and improving their distribution the quality of lens modelling would be improved; a characteristic which is not present in the classical methods.
Approaches to Modelling the Dynamical Activity of Brain Function Based on the Electroencephalogram
Liley, David T. J.; Frascoli, Federico
The brain is arguably the quintessential complex system as indicated by the patterns of behaviour it produces. Despite many decades of concentrated research efforts, we remain largely ignorant regarding the essential processes that regulate and define its function. While advances in functional neuroimaging have provided welcome windows into the coarse organisation of the neuronal networks that underlie a range of cognitive functions, they have largely ignored the fact that behaviour, and by inference brain function, unfolds dynamically. Modelling the brain's dynamics is therefore a critical step towards understanding the underlying mechanisms of its functioning. To date, models have concentrated on describing the sequential organisation of either abstract mental states (functionalism, hard AI) or the objectively measurable manifestations of the brain's ongoing activity (rCBF, EEG, MEG). While the former types of modelling approach may seem to better characterise brain function, they do so at the expense of not making a definite connection with the actual physical brain. Of the latter, only models of the EEG (or MEG) offer a temporal resolution well matched to the anticipated temporal scales of brain (mental processes) function. This chapter will outline the most pertinent of these modelling approaches, and illustrate, using the electrocortical model of Liley et al, how the detailed application of the methods of nonlinear dynamics and bifurcation theory is central to exploring and characterising their various dynamical features. The rich repertoire of dynamics revealed by such dynamical systems approaches arguably represents a critical step towards an understanding of the complexity of brain function.
A statistical model of structure functions and quantum chromodynamics
International Nuclear Information System (INIS)
Mac, E.; Ugaz, E.; Universidad Nacional de Ingenieria, Lima
1989-01-01
We consider a model for the x-dependence of the quark distributions in the proton. Within the context of simple statistical assumptions, we obtain the parton densities in the infinite momentum frame. In a second step lowest order QCD corrections are incorporated to these distributions. Crude, but reasonable, agreement with experiment is found for the F 2 , valence and q, anti q distributions for x> or approx.0.2. (orig.)
Functional mathematical model of dual pathway AV nodal conduction.
Climent, A M; Guillem, M S; Zhang, Y; Millet, J; Mazgalev, T N
2011-04-01
Dual atrioventricular (AV) nodal pathway physiology is described as two different wave fronts that propagate from the atria to the His bundle: one with a longer effective refractory period [fast pathway (FP)] and a second with a shorter effective refractory period [slow pathway (SP)]. By using His electrogram alternance, we have developed a mathematical model of AV conduction that incorporates dual AV nodal pathway physiology. Experiments were performed on five rabbit atrial-AV nodal preparations to develop and test the presented model. His electrogram alternances from the inferior margin of the His bundle were used to identify fast and slow wave front propagations. The ability to predict AV conduction time and the interaction between FP and SP wave fronts have been analyzed during regular and irregular atrial rhythms (e.g., atrial fibrillation). In addition, the role of dual AV nodal pathway wave fronts in the generation of Wenckebach periodicities has been illustrated. Finally, AV node ablative modifications have been evaluated. The model accurately reproduced interactions between FP and SP during regular and irregular atrial pacing protocols. In all experiments, specificity and sensitivity higher than 85% were obtained in the prediction of the pathway responsible for conduction. It has been shown that, during atrial fibrillation, the SP ablation significantly increased the mean HH interval (204 ± 39 vs. 274 ± 50 ms, P AV node mechanisms and should be considered as a step forward in the studies of AV nodal conduction.
Evaluation of mammary gland development and function in mouse models.
Plante, Isabelle; Stewart, Michael K G; Laird, Dale W
2011-07-21
The human mammary gland is composed of 15-20 lobes that secrete milk into a branching duct system opening at the nipple. Those lobes are themselves composed of a number of terminal duct lobular units made of secretory alveoli and converging ducts. In mice, a similar architecture is observed at pregnancy in which ducts and alveoli are interspersed within the connective tissue stroma. The mouse mammary gland epithelium is a tree like system of ducts composed of two layers of cells, an inner layer of luminal cells surrounded by an outer layer of myoepithelial cells denoted by the confines of a basement membrane. At birth, only a rudimental ductal tree is present, composed of a primary duct and 15-20 branches. Branch elongation and amplification start at the beginning of puberty, around 4 weeks old, under the influence of hormones. At 10 weeks, most of the stroma is invaded by a complex system of ducts that will undergo cycles of branching and regression in each estrous cycle until pregnancy. At the onset of pregnancy, a second phase of development begins, with the proliferation and differentiation of the epithelium to form grape-shaped milk secretory structures called alveoli. Following parturition and throughout lactation, milk is produced by luminal secretory cells and stored within the lumen of alveoli. Oxytocin release, stimulated by a neural reflex induced by suckling of pups, induces synchronized contractions of the myoepithelial cells around the alveoli and along the ducts, allowing milk to be transported through the ducts to the nipple where it becomes available to the pups. Mammary gland development, differentiation and function are tightly orchestrated and require, not only interactions between the stroma and the epithelium, but also between myoepithelial and luminal cells within the epithelium. Thereby, mutations in many genes implicated in these interactions may impair either ductal elongation during puberty or alveoli formation during early pregnancy
Warren, Jeffrey M; Hanson, Paul J; Iversen, Colleen M; Kumar, Jitendra; Walker, Anthony P; Wullschleger, Stan D
2015-01-01
There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction. No claim to original US Government works. New Phytologist © 2014 New Phytologist Trust.
Elucidation of spin echo small angle neutron scattering correlation functions through model studies.
Shew, Chwen-Yang; Chen, Wei-Ren
2012-02-14
Several single-modal Debye correlation functions to approximate part of the overall Debey correlation function of liquids are closely examined for elucidating their behavior in the corresponding spin echo small angle neutron scattering (SESANS) correlation functions. We find that the maximum length scale of a Debye correlation function is identical to that of its SESANS correlation function. For discrete Debye correlation functions, the peak of SESANS correlation function emerges at their first discrete point, whereas for continuous Debye correlation functions with greater width, the peak position shifts to a greater value. In both cases, the intensity and shape of the peak of the SESANS correlation function are determined by the width of the Debye correlation functions. Furthermore, we mimic the intramolecular and intermolecular Debye correlation functions of liquids composed of interacting particles based on a simple model to elucidate their competition in the SESANS correlation function. Our calculations show that the first local minimum of a SESANS correlation function can be negative and positive. By adjusting the spatial distribution of the intermolecular Debye function in the model, the calculated SESANS spectra exhibit the profile consistent with that of hard-sphere and sticky-hard-sphere liquids predicted by more sophisticated liquid state theory and computer simulation. © 2012 American Institute of Physics
Sakschewski, B.; Bloh, von W.; Boit, A.; Rammig, A.; Kattge, J.; Poorter, L.; Peñualeas, J.; Thonicke, K.
2015-01-01
Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant
Impaired Interoception in a Preclinical Model of Functional Dyspepsia.
Winston, John H; Aguirre, Jose E; Shi, Xuan-Zheng; Sarna, Sushil K
2017-09-01
The etiologies of functional dyspepsia symptoms, including postprandial distress syndrome, remain unknown. We tested the hypothesis that neonatal colon inflammation induces postprandial distress syndrome-like symptoms in adult life that associate with increased activation of vagal afferent pathways and forebrain limbic regions. These rats showed a significant decrease in nutrient meal consumption to satiety after an overnight fast, decrease in gastric emptying, decrease in total distance traveled, and decrease in percent distance traveled in midfield versus control rats in open field test, indicating postprandial anxiety- and depression-like behaviors. Adult naïve rats treated with oral iodoacetamide to induce H. pylori-like mild gastritis demonstrated similar postprandial effects as the above rats. We concluded that neonatal colon inflammation is a risk factor for the development of postprandial distress syndrome-like symptoms. While mild gastritis can induce symptoms similar to those of neonatal colon inflammation, gastritis in these rats does not worsen the symptoms.
Energy Technology Data Exchange (ETDEWEB)
Walraven, Jeremy Allen; Blecke, Jill; Baker, Michael Sean; Clemens, Rebecca C.; Mitchell, John Anthony; Brake, Matthew Robert; Epp, David S.; Wittwer, Jonathan W.
2008-10-01
This report summarizes the functional, model validation, and technology readiness testing of the Sandia MEMS Passive Shock Sensor in FY08. Functional testing of a large number of revision 4 parts showed robust and consistent performance. Model validation testing helped tune the models to match data well and identified several areas for future investigation related to high frequency sensitivity and thermal effects. Finally, technology readiness testing demonstrated the integrated elements of the sensor under realistic environments.
Alternative Functional In Vitro Models of Human Intestinal Epithelia
Directory of Open Access Journals (Sweden)
Amanda L Kauffman
2013-07-01
Full Text Available Physiologically relevant sources of absorptive intestinal epithelial cells are crucial for human drug transport studies. Human adenocarcinoma-derived intestinal cell lines, such as Caco-2, offer conveniences of easy culture maintenance and scalability, but do not fully recapitulate in vivo intestinal phenotypes. Additional sources of renewable physiologically relevant human intestinal cells would provide a much needed tool for drug discovery and intestinal physiology. We sought to evaluate and compare two alternative sources of human intestinal cells, commercially available primary human intestinal epithelial cells (hInEpCs and induced pluripotent stem cell (iPSC-derived intestinal cells to Caco-2, for use in in vitro transwell monolayer intestinal transport assays. To achieve this for iPSC-derived cells, our previously described 3-dimensional intestinal organogenesis method was adapted to transwell differentiation. Intestinal cells were assessed by marker expression through immunocytochemical and mRNA expression analyses, monolayer integrity through Transepithelial Electrical Resistance (TEER measurements and molecule permeability, and functionality by taking advantage the well-characterized intestinal transport mechanisms. In most cases, marker expression for primary hInEpCs and iPSC-derived cells appeared to be as good as or better than Caco-2. Furthermore, transwell monolayers exhibited high TEER with low permeability. Primary hInEpCs showed molecule efflux indicative of P-glycoprotein transport. Primary hInEpCs and iPSC-derived cells also showed neonatal Fc receptor-dependent binding of immunoglobulin G variants. Primary hInEpCs and iPSC-derived intestinal cells exhibit expected marker expression and demonstrate basic functional monolayer formation, similar to or better than Caco-2. These cells could offer an alternative source of human intestinal cells for understanding normal intestinal epithelial physiology and drug transport.
Modeling of the over-exposed pixel area of CCD cameras caused by laser dazzling
Benoist, Koen W.; Schleijpen, Ric H. M. A.
2014-10-01
A simple model has been developed and implemented in Matlab code, predicting the over-exposed pixel area of cameras caused by laser dazzling. Inputs of this model are the laser irradiance on the front optics of the camera, the Point Spread Function (PSF) of the used optics, the integration time of the camera, and camera sensor specifications like pixel size, quantum efficiency and full well capacity. Effects of the read-out circuit of the camera are not incorporated. The model was evaluated with laser dazzle experiments on CCD cameras using a 532 nm CW laser dazzler and shows good agreement. For relatively low laser irradiance the model predicts the over-exposed laser spot area quite accurately and shows the cube root dependency of spot diameter on laser irradiance, caused by the PSF as demonstrated before for IR cameras. For higher laser power levels the laser induced spot diameter increases more rapidly than predicted, which probably can be attributed to scatter effects in the camera. Some first attempts to model scatter contributions, using a simple scatter power function f(θ), show good resemblance with experiments. Using this model, a tool is available which can assess the performance of observation sensor systems while being subjected to laser countermeasures.
Can Microbial Ecology and Mycorrhizal Functioning Inform Climate Change Models?
Energy Technology Data Exchange (ETDEWEB)
Hofmockel, Kirsten; Hobbie, Erik
2017-07-31
Our funded research focused on soil organic matter dynamics and plant-microbe interactions by examining the role of belowground processes and mechanisms across scales, including decomposition of organic molecules, microbial interactions, and plant-microbe interactions associated with a changing climate. Research foci included mycorrhizal mediated priming of soil carbon turnover, organic N use and depolymerization by free-living microbes and mycorrhizal fungi, and the use of isotopes as additional constraints for improved modeling of belowground processes. This work complemented the DOE’s mandate to understand both the consequences of atmospheric and climatic change for key ecosystems and the feedbacks on C cycling.
Extreme Compression and Modeling of Bidirectional Texture Function
Czech Academy of Sciences Publication Activity Database
Haindl, Michal; Filip, Jiří
2007-01-01
Roč. 29, č. 10 (2007), s. 1859-1865 ISSN 0162-8828 R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Rough texture * 3D texture * BTF * texture synthesis * texture modeling * data compression Subject RIV: BD - Theory of Information Impact factor: 3.579, year: 2007 http://doi.ieeecomputersociety.org/10.1109/TPAMI.2007.1139
Energy Technology Data Exchange (ETDEWEB)
Olivero, J.; Toxopeus, A.G.; Skidmore, A.K.; Real, R.
2016-07-01
Statistical downscaling is used to improve the knowledge of spatial distributions from broad–scale to fine–scale maps with higher potential for conservation planning. We assessed the effectiveness of downscaling in two commonly used species distribution models: Maximum Entropy (MaxEnt) and the Favourability Function (FF). We used atlas data (10 x 10 km) of the fire salamander Salamandra salamandra distribution in southern Spain to derive models at a 1 x 1 km resolution. Downscaled models were assessed using an independent dataset of the species’ distribution at 1 x 1 km. The Favourability model showed better downscaling performance than the MaxEnt model, and the models that were based on linear combinations of environmental variables performed better than models allowing higher flexibility. The Favourability model minimized model overfitting compared to the MaxEnt model. (Author)
Directory of Open Access Journals (Sweden)
Olivero, J.
2016-03-01
Full Text Available Statistical downscaling is used to improve the knowledge of spatial distributions from broad–scale to fine–scale maps with higher potential for conservation planning. We assessed the effectiveness of downscaling in two commonly used species distribution models: Maximum Entropy (MaxEnt and the Favourability Function (FF. We used atlas data (10 x 10 km of the fire salamander Salamandra salamandra distribution in southern Spain to derive models at a 1 x 1 km resolution. Downscaled models were assessed using an independent dataset of the species’ distribution at 1 x 1 km. The Favourability model showed better downscaling performance than the MaxEnt model, and the models that were based on linear combinations of environmental variables performed better than models allowing higher flexibility. The Favourability model minimized model overfitting compared to the MaxEnt model.
Directory of Open Access Journals (Sweden)
Tetiana A. Vakaliuk
2017-06-01
Full Text Available The article summarizes the essence of the category "model". There are presented the main types of models used in educational research: structural, functional, structural and functional model as well as basic requirements for building these types of models. The national experience in building models and designing cloud-based learning environment of educational institutions (both higher and secondary is analyzed. It is presented structural and functional model of cloud-based learning environment for Bachelor of Informatics. Also we describe each component of cloud-based learning environment model for bachelors of informatics training: target, managerial, organizational, content and methodical, communication, technological and productive. It is summarized, that COLE should solve all major tasks that relate to higher education institutions.
Quantifying functional connectivity in multi-subject fMRI data using component models
DEFF Research Database (Denmark)
Madsen, Kristoffer Hougaard; Churchill, Nathan William; Mørup, Morten
2017-01-01
in the brain among groups of subjects. Component models can be used to define subspace representations of functional connectivity that are more interpretable. It is, however, unclear which component model provides the optimal representation of functional networks for multi-subject fMRI datasets. A flexible......-generalizing models account for subject variability within a common spatial subspace. Within this set of models, spatial Independent Component Analysis (sICA) on concatenated data provides more interpretable brain patterns, whereas a consistent-covariance model that accounts for subject-specific network scaling...
Exact probability distribution function for multifractal random walk models of stocks
Saakian, D. B.; Martirosyan, A.; Hu, Chin-Kun; Struzik, Z. R.
2011-07-01
We investigate the multifractal random walk (MRW) model, popular in the modelling of stock fluctuations in the financial market. The exact probability distribution function (PDF) is derived by employing methods proposed in the derivation of correlation functions in string theory, including the analytical extension of Selberg integrals. We show that the recent results by Y. V. Fyodorov, P. Le Doussal and A. Rosso obtained with the logarithmic Random Energy Model (REM) model are sufficient to derive exact formulas for the PDF of the log returns in the MRW model.
Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data
Zhou, Lan
2010-03-01
Hierarchical functional data are widely seen in complex studies where sub-units are nested within units, which in turn are nested within treatment groups. We propose a general framework of functional mixed effects model for such data: within unit and within sub-unit variations are modeled through two separate sets of principal components; the sub-unit level functions are allowed to be correlated. Penalized splines are used to model both the mean functions and the principal components functions, where roughness penalties are used to regularize the spline fit. An EM algorithm is developed to fit the model, while the specific covariance structure of the model is utilized for computational efficiency to avoid storage and inversion of large matrices. Our dimension reduction with principal components provides an effective solution to the difficult tasks of modeling the covariance kernel of a random function and modeling the correlation between functions. The proposed methodology is illustrated using simulations and an empirical data set from a colon carcinogenesis study. Supplemental materials are available online.
Model approach to starch functionality in bread making.
Goesaert, Hans; Leman, Pedro; Delcour, Jan A
2008-08-13
We used modified wheat starches in gluten-starch flour models to study the role of starch in bread making. Incorporation of hydroxypropylated starch in the recipe reduced loaf volume and initial crumb firmness and increased crumb gas cell size. Firming rate and firmness after storage increased for loaves containing the least hydroxypropylated starch. Inclusion of cross-linked starch had little effect on loaf volume or crumb structure but increased crumb firmness. The firming rate was mostly similar to that of control samples. Presumably, the moment and extent of starch gelatinization and the concomitant water migration influence the structure formation during baking. Initial bread firmness seems determined by the rigidity of the gelatinized granules and leached amylose. Amylopectin retrogradation and strengthening of a long-range network by intensifying the inter- and intramolecular starch-starch and possibly also starch-gluten interactions (presumably because of water incorporation in retrograded amylopectin crystallites) play an important role in firming.
Impaired executive functions in experimental model of temporal lobe epilepsy
Directory of Open Access Journals (Sweden)
Fabiane Ochai Ramos
2016-06-01
Full Text Available ABSTRACT Objective The present study aimed to investigate cognitive and behavioural changes consistent with attention deficit hyperactivity disorder (ADHD -like behavior in male Wistar rats with temporal lobe epilepsy (TLE. Method Male Wistar rats at 25 day of age were submitted to animal model of TLE by pilocarpine injection (350 mg/kg, ip and a control group received saline 0.9%. The animals were continuously video monitored up to the end of experiments. The behavioural tests (open field, elevated plus maze and operant conditioning box started from 60 days postnatal. Results Animals with TLE exhibited elevated locomotor activity, reduced level of anxiety-related behavior, impulsivity and impaired visuospatial working memory. Conclusion Taken as a whole, we concluded that animals with TLE exhibited some cognitive and behavioural changes consistent with ADHD-like behavior.
A Note on the Item Information Function of the Four-Parameter Logistic Model
Magis, David
2013-01-01
This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…
RIM: A Random Item Mixture Model to Detect Differential Item Functioning
Frederickx, Sofie; Tuerlinckx, Francis; De Boeck, Paul; Magis, David
2010-01-01
In this paper we present a new methodology for detecting differential item functioning (DIF). We introduce a DIF model, called the random item mixture (RIM), that is based on a Rasch model with random item difficulties (besides the common random person abilities). In addition, a mixture model is assumed for the item difficulties such that the…
RIM: A random item mixture model to detect Differential Item Functioning
Frederickx, S.; Tuerlinckx, T.; de Boeck, P.; Magis, D.
2010-01-01
In this paper we present a new methodology for detecting differential item functioning (DIF). We introduce a DIF model, called the random item mixture (RIM), that is based on a Rasch model with random item difficulties (besides the common random person abilities). In addition, a mixture model is
International Nuclear Information System (INIS)
Chudnovsky, D.V.; Chudnovsky, G.V.
1981-01-01
We consider general expressions of factorized S-matrices with Abelian symmetry expressed in terms of theta-functions. These expressions arise from representations of the Heisenberg group. New examples of factorized S-matrices lead to a large class of completely integrable models of statistical mechanics which generalize the XYZ-model of the eight-vertex model. (orig.)
A FUNCTIONAL MODEL OF COMPUTER-ORIENTED LEARNING ENVIRONMENT OF A POST-DEGREE PEDAGOGICAL EDUCATION
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Kateryna R. Kolos
2014-06-01
Full Text Available The study substantiates the need for a systematic study of the functioning of computer-oriented learning environment of a post-degree pedagogical education; it is determined the definition of “functional model of computer-oriented learning environment of a post-degree pedagogical education”; it is built a functional model of computer-oriented learning environment of a post-degree pedagogical education in accordance with the functions of business, information and communication technology, academic, administrative staff and peculiarities of training courses teachers.
The polarized structure function of the nucleons with a non-extensive statistical quark model
Energy Technology Data Exchange (ETDEWEB)
Trevisan, Luis A. [Departamento de Matematica e Estatistica, Universidade Estadual de Ponta Grossa, 84010-790, Ponta Grossa, PR (Brazil); Mirez, Carlos [Instituto de Ciencia, Engenharia e Tecnologia - ICET, Universidade Federal dos Vales do Jequitinhonha e Mucuri - UFVJM, Campus do Mucuri, Rua do Cruzeiro 01, Jardim Sao Paulo, 39803-371, Teofilo Otoni, Minas Gerais (Brazil)
2013-05-06
We studied an application of nonextensive thermodynamics to describe the polarized structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution, often used in the statistical models, were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and the chemical potentials given by the corresponding up (u) and down (d) quark normalization in the nucleon and by {Delta}u and {Delta}d of the polarized functions.
DEFF Research Database (Denmark)
Karunarathna, Anurudda Kumara; Kawamoto, Ken; Møldrup, Per
2010-01-01
WR(θ) models is still lacking. In this study, a simple empirical beta function was suggested to describe the effect of changing soil-water content on the change of WR given as apparent contact angle (α) measured by the molarity of ethanol droplet (MED) method. The beta function for predicting α......Soil-water content (θ) and soil organic carbon (SOC) are key factors controlling the occurrence and magnitude of soil-water repellency (WR). Although expressions have recently been proposed to describe the nonlinear variation of WR with θ, the inclusion of easily measurable parameters in predictive......(θ) is based on measurement of WR on air-dry soil and three additional model parameters: the water contents at which the maximum WR (highest α) occurs and where WR ceases (α = 90 degrees), and the maximum α value. The MED data for three data sets from literature comprising WR measurements across moisture...
Hou, Likun; de la Torre, Jimmy; Nandakumar, Ratna
2014-01-01
Analyzing examinees' responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This study…
Azzopardi, George; Petkov, Nicolai
Simple cells in primary visual cortex are believed to extract local contour information from a visual scene. The 2D Gabor function (GF) model has gained particular popularity as a computational model of a simple cell. However, it short-cuts the LGN, it cannot reproduce a number of properties of real
The distance-decay function of geographical gravity model: Power law or exponential law?
International Nuclear Information System (INIS)
Chen, Yanguang
2015-01-01
Highlights: •The distance-decay exponent of the gravity model is a fractal dimension. •Entropy maximization accounts for the gravity model based on power law decay. •Allometric scaling relations relate gravity models with spatial interaction models. •The four-parameter gravity models have dual mathematical expressions. •The inverse power law is the most probable distance-decay function. -- Abstract: The distance-decay function of the geographical gravity model is originally an inverse power law, which suggests a scaling process in spatial interaction. However, the distance exponent of the model cannot be reasonably explained with the ideas from Euclidean geometry. This results in a dimension dilemma in geographical analysis. Consequently, a negative exponential function was used to replace the inverse power function to serve for a distance-decay function. But a new puzzle arose that the exponential-based gravity model goes against the first law of geography. This paper is devoted for solving these kinds of problems by mathematical reasoning and empirical analysis. New findings are as follows. First, the distance exponent of the gravity model is demonstrated to be a fractal dimension using the geometric measure relation. Second, the similarities and differences between the gravity models and spatial interaction models are revealed using allometric relations. Third, a four-parameter gravity model possesses a symmetrical expression, and we need dual gravity models to describe spatial flows. The observational data of China's cities and regions (29 elements indicative of 841 data points) in 2010 are employed to verify the theoretical inferences. A conclusion can be reached that the geographical gravity model based on power-law decay is more suitable for analyzing large, complex, and scale-free regional and urban systems. This study lends further support to the suggestion that the underlying rationale of fractal structure is entropy maximization. Moreover
A more general model for testing measurement invariance and differential item functioning.
Bauer, Daniel J
2017-09-01
The evaluation of measurement invariance is an important step in establishing the validity and comparability of measurements across individuals. Most commonly, measurement invariance has been examined using 1 of 2 primary latent variable modeling approaches: the multiple groups model or the multiple-indicator multiple-cause (MIMIC) model. Both approaches offer opportunities to detect differential item functioning within multi-item scales, and thereby to test measurement invariance, but both approaches also have significant limitations. The multiple groups model allows 1 to examine the invariance of all model parameters but only across levels of a single categorical individual difference variable (e.g., ethnicity). In contrast, the MIMIC model permits both categorical and continuous individual difference variables (e.g., sex and age) but permits only a subset of the model parameters to vary as a function of these characteristics. The current article argues that moderated nonlinear factor analysis (MNLFA) constitutes an alternative, more flexible model for evaluating measurement invariance and differential item functioning. We show that the MNLFA subsumes and combines the strengths of the multiple group and MIMIC models, allowing for a full and simultaneous assessment of measurement invariance and differential item functioning across multiple categorical and/or continuous individual difference variables. The relationships between the MNLFA model and the multiple groups and MIMIC models are shown mathematically and via an empirical demonstration. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
A hypothetical universal model of cerebellar function: reconsideration of the current dogma.
Magal, Ari
2013-10-01
The cerebellum is commonly studied in the context of the classical eyeblink conditioning model, which attributes an adaptive motor function to cerebellar learning processes. This model of cerebellar function has quite a few shortcomings and may in fact be somewhat deficient in explaining the myriad functions attributed to the cerebellum, functions ranging from motor sequencing to emotion and cognition. The involvement of the cerebellum in these motor and non-motor functions has been demonstrated in both animals and humans in electrophysiological, behavioral, tracing, functional neuroimaging, and PET studies, as well as in clinical human case studies. A closer look at the cerebellum's evolutionary origin provides a clue to its underlying purpose as a tool which evolved to aid predation rather than as a tool for protection. Based upon this evidence, an alternative model of cerebellar function is proposed, one which might more comprehensively account both for the cerebellum's involvement in a myriad of motor, affective, and cognitive functions and for the relative simplicity and ubiquitous repetitiveness of its circuitry. This alternative model suggests that the cerebellum has the ability to detect coincidences of events, be they sensory, motor, affective, or cognitive in nature, and, after having learned to associate these, it can then trigger (or "mirror") these events after having temporally adjusted their onset based on positive/negative reinforcement. The model also provides for the cerebellum's direction of the proper and uninterrupted sequence of events resulting from this learning through the inhibition of efferent structures (as demonstrated in our lab).
Analysis and Application of Mechanical System Reliability Model Based on Copula Function
Directory of Open Access Journals (Sweden)
An Hai
2016-10-01
Full Text Available There is complicated correlations in mechanical system. By using the advantages of copula function to solve the related issues, this paper proposes the mechanical system reliability model based on copula function. And makes a detailed research for the serial and parallel mechanical system model and gets their reliability function respectively. Finally, the application research is carried out for serial mechanical system reliability model to prove its validity by example. Using Copula theory to make mechanical system reliability modeling and its expectation, studying the distribution of the random variables (marginal distribution of the mechanical product’ life and associated structure of variables separately, can reduce the difficulty of multivariate probabilistic modeling and analysis to make the modeling and analysis process more clearly.
DEFF Research Database (Denmark)
Saleem, Arshad
2007-01-01
The purpose of this paper is to present a Multilevel Flow Model (MFM) of an industrial heat pump system and its use for diagnostic reasoning. MFM is functional modeling language supporting an explicit means-ends intelligent control strategy for large industrial process plants. The model is used...... in several diagnostic experiments analyzing different fault scenarios. The model and results of the experiments are explained and it is shown how MFM based intelligent modeling and automated reasoning can improve the fault diagnosis process significantly....
International Nuclear Information System (INIS)
Mueller, A.
1985-01-01
The advantage of the Gauss-function-based models doubtlessly consists in their proven propagation parameter sets and empirical stack plume rise formulas and in their easy matchability and handability. However, grid models based on trace matter transport equation are more convincing concerning their fundamental principle. Grid models of the MODIS type are to acquire a practical applicability comparable to Gauss models by developing techniques allowing to consider the vertical self-movement of the plumes in grid models and to secure improved diffusion co-efficient determination. (orig./PW) [de
Orakanya Kanjanatarakul; Komsan Suriya
2012-01-01
This paper compares the accuracy of sales forecasting between Bass model (Bass, 1969) and Logistic function (Stoneman, 2010). It uses several ways to estimate the models; least squares with quadratic interpolation, least squares with quasi-Newton, maximum likelihood with quadratic interpolation and maximum likelihood with quasi-Newton. It applies the technique to an innovative agro-industrial product, feta cheese from buffalo milk. Then it compares the performance of the models by Mean Absolu...
Identification of hidden failures in control systems: a functional modelling approach
International Nuclear Information System (INIS)
Jalashgar, A.; Modarres, M.
1996-01-01
This paper presents a model which encompasses knowledge about a process control system's functionalities in a function-oriented failure analysis task. The technique called Hybrid MFM-GTST, mainly utilizes two different function - oriented methods (MFM and GTST) to identify all functions of the system components, and hence possible sources of hidden failures in process control systems. Hidden failures are referred to incipient failures within the system that in long term may lead to loss of major functions. The features of the method are described and demonstrated by using an example of a process control system
DEFF Research Database (Denmark)
Kjeldsen, Tinne Hoff; Blomhøj, Morten
2013-01-01
Mathematical models and mathematical modeling play different roles in the different areas and problems in which they are used. The function and status of mathematical modeling and models in the different areas depend on the scientific practice as well as the underlying philosophical and theoretical...... position held by the modeler(s) and the practitioners in the extra-mathematical domain. For students to experience the significance of different scientific practices and cultures for the function and status of mathematical modeling in other sciences, students need to be placed in didactical situations...... where such differences are exposed and made into explicit objects of their reflections. It can be difficult to create such situations in the teaching of contemporary science in which modeling is part of the culture. In this paper we show how history can serve as a means for students to be engaged...
Improvement of wall condensation modeling with suction wall functions for containment application
Energy Technology Data Exchange (ETDEWEB)
Lehmkuhl, Jan, E-mail: j.lehmkuhl@fz-juelich.de [RWTH Aachen University, Aachen (Germany); Kelm, Stephan, E-mail: s.kelm@fz-juelich.de [Forschungszentrum Jülich GmbH, Jülich (Germany); Bucci, Matteo [Commissariat à l’énergie atomique et aux énergies alternatives, Paris (France); Allelein, Hans-Josef [RWTH Aachen University, Aachen (Germany); Forschungszentrum Jülich GmbH, Jülich (Germany)
2016-04-01
Highlights: • Assessment of wall functions for single phase condensation models for large scale application. • Identification of modeling errors related to standard log-law due to buoyancy and wall normal mass transfer (suction). • Modeling of wall normal mass transfer by literature formulation (Sucec, 1999) and in-house approach (FIBULA). • Validation against isothermal Favre experimental data. • Comparison against reference fine grid solution for condensing conditions. - Abstract: To simulate wall condensation on containment scale with CFD methods at reasonable computational cost, a single phase approach has to be applied and wall functions have to be used. However, standard wall functions were derived for flows without heat and mass transfer and their fundamental simplifications are not appropriate to deal with condensation. This paper discusses the limitations of standard wall functions and proposes two wall functions for the momentum equation dealing with mass transfer normal to the sheared wall (suction). The first proposed suction wall function is an algebraic modification based on the standard wall function concept. The second proposed wall function is an in-house developed suction wall function with the potential to cover also heat and mass transfer effects by storing the complex solutions of the RANS-Equations in a lookup table. The wall function approaches are compared to experimental results for boundary layer flows with suction and to the reference results obtained using a refined grid in order to resolve the condensing boundary layer.
Links, Jonathan M; Schwartz, Brian S; Lin, Sen; Kanarek, Norma; Mitrani-Reiser, Judith; Sell, Tara Kirk; Watson, Crystal R; Ward, Doug; Slemp, Cathy; Burhans, Robert; Gill, Kimberly; Igusa, Tak; Zhao, Xilei; Aguirre, Benigno; Trainor, Joseph; Nigg, Joanne; Inglesby, Thomas; Carbone, Eric; Kendra, James M
2018-02-01
Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster. We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties. The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature. The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127-137).
Flexible parametric modelling of the cause-specific cumulative incidence function.
Lambert, Paul C; Wilkes, Sally R; Crowther, Michael J
2017-04-30
Competing risks arise with time-to-event data when individuals are at risk of more than one type of event and the occurrence of one event precludes the occurrence of all other events. A useful measure with competing risks is the cause-specific cumulative incidence function (CIF), which gives the probability of experiencing a particular event as a function of follow-up time, accounting for the fact that some individuals may have a competing event. When modelling the cause-specific CIF, the most common model is a semi-parametric proportional subhazards model. In this paper, we propose the use of flexible parametric survival models to directly model the cause-specific CIF where the effect of follow-up time is modelled using restricted cubic splines. The models provide smooth estimates of the cause-specific CIF with the important advantage that the approach is easily extended to model time-dependent effects. The models can be fitted using standard survival analysis tools by a combination of data expansion and introducing time-dependent weights. Various link functions are available that allow modelling on different scales and have proportional subhazards, proportional odds and relative absolute risks as particular cases. We conduct a simulation study to evaluate how well the spline functions approximate subhazard functions with complex shapes. The methods are illustrated using data from the European Blood and Marrow Transplantation Registry showing excellent agreement between parametric estimates of the cause-specific CIF and those obtained from a semi-parametric model. We also fit models relaxing the proportional subhazards assumption using alternative link functions and/or including time-dependent effects. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Wismueller, Axel; Lange, Oliver; Auer, Dorothee; Leinsinger, Gerda
2010-03-01
Slowly varying temporally correlated activity fluctuations between functionally related brain areas have been identified by functional magnetic resonance imaging (fMRI) research in recent years. These low-frequency oscillations of less than 0.08 Hz appear to play a major role in various dynamic functional brain networks, such as the so-called 'default mode' network. They also have been observed as a property of symmetric cortices, and they are known to be present in the motor cortex among others. These low-frequency data are difficult to detect and quantify in fMRI. Traditionally, user-based regions of interests (ROI) or 'seed clusters' have been the primary analysis method. In this paper, we propose unsupervised clustering algorithms based on various distance measures to detect functional connectivity in resting state fMRI. The achieved results are evaluated quantitatively for different distance measures. The Euclidian metric implemented by standard unsupervised clustering approaches is compared with a non-metric topographic mapping of proximities based on the the mutual prediction error between pixel-specific signal dynamics time-series. It is shown that functional connectivity in the motor cortex of the human brain can be detected based on such model-free analysis methods for resting state fMRI.
Functional Freedom: A Psychological Model of Freedom in Decision-Making.
Lau, Stephan; Hiemisch, Anette
2017-07-05
The freedom of a decision is not yet sufficiently described as a psychological variable. We present a model of functional decision freedom that aims to fill that role. The model conceptualizes functional freedom as a capacity of people that varies depending on certain conditions of a decision episode. It denotes an inner capability to consciously shape complex decisions according to one's own values and needs. Functional freedom depends on three compensatory dimensions: it is greatest when the decision-maker is highly rational, when the structure of the decision is highly underdetermined, and when the decision process is strongly based on conscious thought and reflection. We outline possible research questions, argue for psychological benefits of functional decision freedom, and explicate the model's implications on current knowledge and research. In conclusion, we show that functional freedom is a scientific variable, permitting an additional psychological foothold in research on freedom, and that is compatible with a deterministic worldview.
Dynamics of a Fractional Order HIV Infection Model with Specific Functional Response and Cure Rate
Directory of Open Access Journals (Sweden)
Adnane Boukhouima
2017-01-01
Full Text Available We propose a fractional order model in this paper to describe the dynamics of human immunodeficiency virus (HIV infection. In the model, the infection transmission process is modeled by a specific functional response. First, we show that the model is mathematically and biologically well posed. Second, the local and global stabilities of the equilibria are investigated. Finally, some numerical simulations are presented in order to illustrate our theoretical results.
Directory of Open Access Journals (Sweden)
Y. Kakinami
2009-08-01
Full Text Available Empirical models of Total Electron Content (TEC based on functional fitting over Taiwan (120° E, 24° N have been constructed using data of the Global Positioning System (GPS from 1998 to 2007 during geomagnetically quiet condition (D_{st}>−30 nT. The models provide TEC as functions of local time (LT, day of year (DOY and the solar activity (F, which are represented by 1–162 days mean of F10.7 and EUV. Other models based on median values have been also constructed and compared with the models based on the functional fitting. Under same values of F parameter, the models based on the functional fitting show better accuracy than those based on the median values in all cases. The functional fitting model using daily EUV is the most accurate with 9.2 TECu of root mean square error (RMS than the 15-days running median with 10.4 TECu RMS and the model of International Reference Ionosphere 2007 (IRI2007 with 14.7 TECu RMS. IRI2007 overestimates TEC when the solar activity is low, and underestimates TEC when the solar activity is high. Though average of 81 days centered running mean of F10.7 and daily F10.7 is often used as indicator of EUV, our result suggests that average of F10.7 mean from 1 to 54 day prior and current day is better than the average of 81 days centered running mean for reproduction of TEC. This paper is for the first time comparing the median based model with the functional fitting model. Results indicate the functional fitting model yielding a better performance than the median based one. Meanwhile we find that the EUV radiation is essential to derive an optimal TEC.
Functional modelling for integration of human-software-hardware in complex physical systems
International Nuclear Information System (INIS)
Modarres, M.
1996-01-01
A framework describing the properties of complex physical systems composed of human-software-hardware interactions in terms of their functions is described. It is argued that such a framework is domain-general, so that functional primitives present a language that is more general than most other modeling methods such as mathematical simulation. The characteristics and types of functional models are described. Examples of uses of the framework in modeling physical systems composed of human-software-hardware (hereby we refer to them as only physical systems) are presented. It is concluded that a function-centered model of a physical system provides a capability for generating a high-level simulation of the system for intelligent diagnostic, control or other similar applications
DEFF Research Database (Denmark)
Vafamand, Navid; Asemani, Mohammad Hassan; Khayatiyan, Alireza
2018-01-01
criterion, new robust controller design conditions in terms of linear matrix inequalities are derived. Three practical case studies, electric power steering system, a helicopter model and servo-mechanical system, are presented to demonstrate the importance of such class of nonlinear systems comprising......This paper proposes a novel robust controller design for a class of nonlinear systems including hard nonlinearity functions. The proposed approach is based on Takagi-Sugeno (TS) fuzzy modeling, nonquadratic Lyapunov function, and nonparallel distributed compensation scheme. In this paper, a novel...... TS modeling of the nonlinear dynamics with signum functions is proposed. This model can exactly represent the original nonlinear system with hard nonlinearity while the discontinuous signum functions are not approximated. Based on the bounded-input-bounded-output stability scheme and L₁ performance...
A Model for Evaluating Mental Health Programs: The Functional Baseline System.
Krowinski, William J.; Fitt, David X.
1978-01-01
This paper presents an evaluation model for a partial hospitalization program. The evaluation instrument, the Functional Baseline System (FBS), is presented with its use in assessing program effectiveness and efficiency. (Author)
Real-time Estimation of UAS Performance Using Efficient Sampling of Functional Models, Phase I
National Aeronautics and Space Administration — Numerica proposes to developed advanced algorithms for constructing a UAS vehicle model from ATC surveillance data in real-time. Using functional descriptions of...
Resolving Microzooplankton Functional Groups In A Size-Structured Planktonic Model
Taniguchi, D.; Dutkiewicz, S.; Follows, M. J.; Jahn, O.; Menden-Deuer, S.
2016-02-01
Microzooplankton are important marine grazers, often consuming a large fraction of primary productivity. They consist of a great diversity of organisms with different behaviors, characteristics, and rates. This functional diversity, and its consequences, are not currently reflected in large-scale ocean ecological simulations. How should these organisms be represented, and what are the implications for their biogeography? We develop a size-structured, trait-based model to characterize a diversity of microzooplankton functional groups. We compile and examine size-based laboratory data on the traits, revealing some patterns with size and functional group that we interpret with mechanistic theory. Fitting the model to the data provides parameterizations of key rates and properties, which we employ in a numerical ocean model. The diversity of grazing preference, rates, and trophic strategies enables the coexistence of different functional groups of micro-grazers under various environmental conditions, and the model produces testable predictions of the biogeography.
Wan, Songlin; Zhang, Xiangchao; He, Xiaoying; Xu, Min
2016-12-20
Computer controlled optical surfacing requires an accurate tool influence function (TIF) for reliable path planning and deterministic fabrication. Near the edge of the workpieces, the TIF has a nonlinear removal behavior, which will cause a severe edge-roll phenomenon. In the present paper, a new edge pressure model is developed based on the finite element analysis results. The model is represented as the product of a basic pressure function and a correcting function. The basic pressure distribution is calculated according to the surface shape of the polishing pad, and the correcting function is used to compensate the errors caused by the edge effect. Practical experimental results demonstrate that the new model can accurately predict the edge TIFs with different overhang ratios. The relative error of the new edge model can be reduced to 15%.
International Nuclear Information System (INIS)
Lind, M.
2005-10-01
Multilevel Flow Modeling (MFM) has proven to be an effective modeling tool for reasoning about plant failure and control strategies and is currently exploited for operator support in diagnosis and on-line alarm analysis. Previous MFM research was focussed on representing goals and functions of process plants which generate, transform and distribute mass and energy. However, only a limited consideration has been given to the problems of modeling the control systems. Control functions are indispensable for operating any industrial plant. But modeling of control system functions has proven to be a more challenging problem than modeling functions of energy and mass processes. The problems were discussed by Lind and tentative solutions has been proposed but have not been investigated in depth until recently, partly due to the lack of an appropriate theoretical foundation. The purposes of the present report are to show that such a theoretical foundation for modeling goals and functions of control systems can be built from concepts and theories of action developed by Von Wright and to show how the theoretical foundation can be used to extend MFM with concepts for modeling control systems. The theoretical foundations has been presented in detail elsewhere by the present author without the particular focus on modeling control actions and MFM adopted here. (au)
Energy Technology Data Exchange (ETDEWEB)
Lind, M. [Oersted - DTU, Kgs. Lyngby (Denmark)
2005-10-01
Multilevel Flow Modeling (MFM) has proven to be an effective modeling tool for reasoning about plant failure and control strategies and is currently exploited for operator support in diagnosis and on-line alarm analysis. Previous MFM research was focussed on representing goals and functions of process plants which generate, transform and distribute mass and energy. However, only a limited consideration has been given to the problems of modeling the control systems. Control functions are indispensable for operating any industrial plant. But modeling of control system functions has proven to be a more challenging problem than modeling functions of energy and mass processes. The problems were discussed by Lind and tentative solutions has been proposed but have not been investigated in depth until recently, partly due to the lack of an appropriate theoretical foundation. The purposes of the present report are to show that such a theoretical foundation for modeling goals and functions of control systems can be built from concepts and theories of action developed by Von Wright and to show how the theoretical foundation can be used to extend MFM with concepts for modeling control systems. The theoretical foundations has been presented in detail elsewhere by the present author without the particular focus on modeling control actions and MFM adopted here. (au)
Directory of Open Access Journals (Sweden)
Mapopa Chipofya
2015-01-01
Full Text Available This paper presents a solution to stability and trajectory tracking of a quadrotor system using a model predictive controller designed using a type of orthonormal functions called Laguerre functions. A linear model of the quadrotor is derived and used. To check the performance of the controller we compare it with a linear quadratic regulator and a more traditional linear state space MPC. Simulations for trajectory tracking and stability are performed in MATLAB and results provided in this paper.
One-loop beta functions for the orientable non-commutative Gross Neveu model TH1"-->
Lakhoua, A.; Vignes-Tourneret, F.; Wallet, J.-C.
2007-11-01
We compute at the one-loop order the β-functions for a renormalisable non-commutative analog of the Gross Neveu model defined on the Moyal plane. The calculation is performed within the so called x-space formalism. We find that this non-commutative field theory exhibits asymptotic freedom for any number of colors. The β-function for the non-commutative counterpart of the Thirring model is found to be non vanishing.
3D finite element model of the chinchilla ear for characterizing middle ear functions
Wang, Xuelin; Gan, Rong Z.
2016-01-01
Chinchilla is a commonly used animal model for research of sound transmission through the ear. Experimental measurements of the middle ear transfer function in chinchillas have shown that the middle ear cavity greatly affects the tympanic membrane (TM) and stapes footplate (FP) displacements. However, there is no finite element (FE) model of the chinchilla ear available in the literature to characterize the middle ear functions with the anatomical features of the chinchilla ear. This paper re...
REQUIREMENTS PARTICLE NETWORKS: AN APPROACH TO FORMAL SOFTWARE FUNCTIONAL REQUIREMENTS MODELLING
Wiwat Vatanawood; Wanchai Rivepiboon
2001-01-01
In this paper, an approach to software functional requirements modelling using requirements particle networks is presented. In our approach, a set of requirements particles is defined as an essential tool to construct a visual model of software functional requirements specification during the software analysis phase and the relevant formal specification is systematically generated without the experience of writing formal specification. A number of algorithms are presented to perform these for...
Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons
Czech Academy of Sciences Publication Activity Database
Bustince, H.; Pagola, M.; Mesiar, Radko; Hullermeier, E.; Herrera, F.
2012-01-01
Roč. 20, č. 3 (2012), s. 405-415 ISSN 1063-6706 R&D Projects: GA ČR GAP402/11/0378 Institutional support: RVO:67985556 Keywords : decision making * grouping function * overlap function Subject RIV: BA - General Mathematics Impact factor: 5.484, year: 2012 http://library.utia.cas.cz/separaty/2012/E/mesiar-grouping overlap and general bientropic functions for fuzzy modelling of pairwise comparisons.pdf
Analytic properties of the Ruelle ζ-function for mean field models of phase transition
International Nuclear Information System (INIS)
Hallerberg, Sarah; Just, Wolfram; Radons, Guenter
2005-01-01
We evaluate by analytical means the Ruelle ζ-function for a spin model with global coupling. The implications of the ferromagnetic phase transitions for the analytical properties of the ζ-function are discussed in detail. In the paramagnetic phase the ζ-function develops a single branch point. In the low-temperature regime two branch points appear which correspond to the ferromagnetic state and the metastable state. The results are typical for any Ginsburg-Landau-type phase transition
Pion-nucleon vertex function and the Chew-Low model
International Nuclear Information System (INIS)
Nutt, W.T.
1977-01-01
We provide an interpretation of the cutoff function used in the Chew-Low theory of pion-nucleon scattering. It is shown that this function may be related to the pion-pion interaction which is not explicitly considered in the Chew-Low approach. Using a previously developed model for the pion-nucleon vertex function, we then perform a ''parameter-free'' Chew-Low calculation which predicts the P 33 resonance quite well
Training Public School Special Educators to Implement Two Functional Analysis Models
Rispoli, Mandy; Neely, Leslie; Healy, Olive; Gregori, Emily
2016-01-01
The purpose of this study was to investigate the efficacy and efficiency of a training package to teach public school special educators to conduct functional analyses of challenging behavior. Six public school educators were divided into two cohorts of three and were taught two models of functional analysis of challenging behavior: traditional and…
An Integrated Agent Model Addressing Situation Awareness and Functional State in Decision Making
Hoogendoorn, M.; van Lambalgen, R.M.; Treur, J.
2011-01-01
In this paper, an integrated agent model is introduced addressing mutually interacting Situation Awareness and Functional State dynamics in decision making. This shows how a human's functional state, more specific a human's exhaustion and power, can influence a human's situation awareness, and in
Giesbertz, K.J.H.; van Leeuwen, Robert; von Barth, Ulf
We put forward an approach for the development of a nonlocal density functional by a direct modeling of the shape of exchange-correlation (xc) hole in inhomogeneous systems. The functional is aimed at giving an accurate xc energy and an accurate corresponding xc potential even in difficult
A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.
Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F
2017-11-01
The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach
Finite element model updating of the UCF grid benchmark using measured frequency response functions
Sipple, Jesse D.; Sanayei, Masoud
2014-05-01
A frequency response function based finite element model updating method is presented and used to perform parameter estimation of the University of Central Florida Grid Benchmark Structure. The proposed method is used to calibrate the initial finite element model using measured frequency response functions from the undamaged, intact structure. Stiffness properties, mass properties, and boundary conditions of the initial model were estimated and updated. Model updating was then performed using measured frequency response functions from the damaged structure to detect physical structural change. Grouping and ungrouping were utilized to determine the exact location and magnitude of the damage. The fixity in rotation of two boundary condition nodes was accurately and successfully estimated. The usefulness of the proposed method for finite element model updating is shown by being able to detect, locate, and quantify change in structural properties.
Dynamics of a generalized Gause-type predator-prey model with a seasonal functional response
International Nuclear Information System (INIS)
Moghadas, S.M.; Alexander, M.E.
2005-01-01
We extend a previous Gause-type predator-prey model to include a general monotonic and bounded seasonally varying functional response. The model exhibits rich dynamical behaviour not encountered when the functional response is not seasonally forced. A theoretical analysis is performed on the model to investigate the global stability of the boundary equilibria and the existence of periodic solutions. It is shown that, under certain well-defined conditions, the Poincare map of the model undergoes a Hopf bifurcation leading to the appearance of a quasi-periodic solution. Numerical results are given for the Poincare sections and bifurcation diagrams for Holling-types II and III functional responses, using the amplitude of seasonal variation as bifurcation parameter. The model shows a rich variety of behaviour, including period doubling, quasi-periodicity, chaos, transient chaos, and windows of periodicity
Modelling of Multi Input Transfer Function for Rainfall Forecasting in Batu City
Directory of Open Access Journals (Sweden)
Priska Arindya Purnama
2017-11-01
Full Text Available The aim of this research is to model and forecast the rainfall in Batu City using multi input transfer function model based on air temperature, humidity, wind speed and cloud. Transfer function model is a multivariate time series model which consists of an output series (Yt sequence expected to be effected by an input series (Xt and other inputs in a group called a noise series (Nt. Multi input transfer function model obtained is (b1,s1,r1 (b2,s2,r2 (b3,s3,r3 (b4,s4,r4(pn,qn = (0,0,0 (23,0,0 (1,2,0 (0,0,0 ([5,8],2 and shows that air temperature on t-day affects rainfall on t-day, rainfall on t-day is influenced by air humidity in the previous 23 days, rainfall on t-day is affected by wind speed in the previous day , and rainfall on day t is affected by clouds on day t. The results of rainfall forecasting in Batu City with multi input transfer function model can be said to be accurate, because it produces relatively small RMSE value. The value of RMSE data forecasting training is 7.7921 while forecasting data testing is 4.2184. Multi-input transfer function model is suitable for rainfall in Batu City.
Hallin, Sara; Welsh, Allana; Stenström, John; Hallet, Stephanie; Enwall, Karin; Bru, David; Philippot, Laurent
2012-01-01
Soil microorganisms are key players in biogeochemical cycles. Yet, there is no consistent view on the significance of microbial biodiversity for soil ecosystem functioning. According to the insurance hypothesis, declines in ecosystem functioning due to reduced biodiversity are more likely to occur under fluctuating, extreme or rapidly changing environmental conditions. Here, we compare the functional operating range, a new concept defined as the complete range of environmental conditions under which soil microbial communities are able to maintain their functions, between four naturally assembled soil communities from a long-term fertilization experiment. A functional trait approach was adopted with denitrifiers involved in nitrogen cycling as our model soil community. Using short-term temperature and salt gradients, we show that the functional operating range was broader and process rates were higher when the soil community was phylogenetically more diverse. However, key bacterial genotypes played an important role for maintaining denitrification as an ecosystem functioning under certain conditions.
International Nuclear Information System (INIS)
Ghoshal, D.; Sen, A.
1991-01-01
We calculate the partition function of the (ρ, ρ + 1) minimal model, perturbed by the operators φ 1.3 and φ 3.1 , to leading order in 1/ρ, and show that the result agrees with the partition functions of the (ρ-1, ρ) and (ρ+1, ρ+2) minimal models respectively. We also relate the change in the partition function of a conformal field theory under a perturbation to a change in the free energy of appropriate string field theory due to a change in the background. (orig.)
DEFF Research Database (Denmark)
Rytter, Hana Malá; Mogensen, Jesper
The REF (Reorganization of Elementary Functions) model suggests mechanisms of posttraumatic reorganization, and resolves the contradiction between localization and functional recovery. In the process of developing this model, we have reconceptualised the term ‘function’ and introduced a concept...... as ‘function’. After brain injury, the EFs of the affected structure are irreversibly lost. However, during neurorehabilitation, the remaining EFs are reorganized into novel ASs. Creation and utilization of these novel ASs constitutes the basis for functional recovery. The degree to which recovery appears...
Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model
Directory of Open Access Journals (Sweden)
Yazid Edwar
2014-07-01
Full Text Available This paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA. The accuracy and practicability of the proposed method are then assessed experimentally from a scaled 1:100 model of a prototype truss spar platform. Identification results in time and frequency domain are presented and coherent functions are performed to check the quality of the identification results. It is shown that results between experimental data and proposed method are in good agreement.
On the structure of Gaussian pricing models and Gaussian Markov functional models
C.D.D. Neumann
2002-01-01
textabstractThis article investigates the structure of Gaussian pricing models (that is, models in which future returns are normally distributed). Although much is already known about such models, this article differs in that it is based on a formulation of the theory of derivative pricing in which
COCOA code for creating mock observations of star cluster models
Askar, Abbas; Giersz, Mirek; Pych, Wojciech; Dalessandro, Emanuele
2018-04-01
We introduce and present results from the COCOA (Cluster simulatiOn Comparison with ObservAtions) code that has been developed to create idealized mock photometric observations using results from numerical simulations of star cluster evolution. COCOA is able to present the output of realistic numerical simulations of star clusters carried out using Monte Carlo or N-body codes in a way that is useful for direct comparison with photometric observations. In this paper, we describe the COCOA code and demonstrate its different applications by utilizing globular cluster (GC) models simulated with the MOCCA (MOnte Carlo Cluster simulAtor) code. COCOA is used to synthetically observe these different GC models with optical telescopes, perform point spread function photometry, and subsequently produce observed colour-magnitude diagrams. We also use COCOA to compare the results from synthetic observations of a cluster model that has the same age and metallicity as the Galactic GC NGC 2808 with observations of the same cluster carried out with a 2.2 m optical telescope. We find that COCOA can effectively simulate realistic observations and recover photometric data. COCOA has numerous scientific applications that maybe be helpful for both theoreticians and observers that work on star clusters. Plans for further improving and developing the code are also discussed in this paper.
Integrative approaches for modeling regulation and function of the respiratory system.
Ben-Tal, Alona; Tawhai, Merryn H
2013-01-01
Mathematical models have been central to understanding the interaction between neural control and breathing. Models of the entire respiratory system-which comprises the lungs and the neural circuitry that controls their ventilation-have been derived using simplifying assumptions to compartmentalize each component of the system and to define the interactions between components. These full system models often rely-through necessity-on empirically derived relationships or parameters, in addition to physiological values. In parallel with the development of whole respiratory system models are mathematical models that focus on furthering a detailed understanding of the neural control network, or of the several functions that contribute to gas exchange within the lung. These models are biophysically based, and rely on physiological parameters. They include single-unit models for a breathing lung or neural circuit, through to spatially distributed models of ventilation and perfusion, or multicircuit models for neural control. The challenge is to bring together these more recent advances in models of neural control with models of lung function, into a full simulation for the respiratory system that builds upon the more detailed models but remains computationally tractable. This requires first understanding the mathematical models that have been developed for the respiratory system at different levels, and which could be used to study how physiological levels of O2 and CO2 in the blood are maintained. Copyright © 2013 Wiley Periodicals, Inc.
Kamis-Gould, Edna; And Others
1991-01-01
A model for quality assurance (QA) in psychiatric hospitals is described. Its functions (general QA, utilization review, clinical records, evaluation, management information systems, risk management, and infection control), subfunctions, and corresponding staffing requirements are reviewed. This model was designed to foster standardization in QA…
Approximation of N(k)(infinity)-functions II : Convergence of Models
Dijksma, Aad; Luger, Annemarie; Shondin, Yuri; Behrndt, J; Forster, KH; Trunk, C
2010-01-01
This paper is a continuation of Part I, [9] in the list of references, where models for N(k)(infinity)-functions have been studied in detail. In the present paper we investigate the convergence of the corresponding models as a singular N(k)(infinity)-functionis approximated by regular
A Functional Model of the Digital Extensor Mechanism: Demonstrating Biomechanics with Hair Bands
Cloud, Beth A.; Youdas, James W.; Hellyer, Nathan J.; Krause, David A.
2010-01-01
The action of muscles about joints can be explained through analysis of their spatial relationship. A functional model of these relationships can be valuable in learning and understanding the muscular action about a joint. A model can be particularly helpful when examining complex actions across multiple joints such as in the digital extensor…
DEFF Research Database (Denmark)
Péguin-Feissolle, Anne; Strikholm, Birgit; Teräsvirta, Timo
In this paper we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in the sample space. We study the performance of our tests...
A Comparison of Single Factor Markov-Functional and Multi Factor Market Models
R. Pietersz (Raoul); A.A.J. Pelsser (Antoon)
2005-01-01
textabstractWe compare single factor Markov-functional and multi factor market models for hedging performance of Bermudan swaptions. We show that hedging performance of both models is comparable, thereby supporting the claim that Bermudan swaptions can be adequately riskmanaged with single factor
Thomas E. Dilts; Peter J. Weisberg; Camie M. Dencker; Jeanne C. Chambers
2015-01-01
We have three goals. (1) To develop a suite of functionally relevant climate variables for modelling vegetation distribution on arid and semi-arid landscapes of the Great Basin, USA. (2) To compare the predictive power of vegetation distribution models based on mechanistically proximate factors (water deficit variables) and factors that are more mechanistically removed...
Comparison of Geophysical Model Functions for SAR Wind Speed Retrieval in Japanese Coastal Waters
DEFF Research Database (Denmark)
Takeyama, Yuko; Ohsawa, Teruo; Kozai, Katsutoshi
2013-01-01
from two validation sites, Hiratsuka and Shirahama, are used for comparison of the retrieved sea surface wind speeds using CMOD (C-band model)4, CMOD_IFR2, CMOD5 and CMOD5.N. Of all the geophysical model functions (GMFs), the latest C-band GMF, CMOD5.N, has the smallest bias and root mean square error...
1981-01-01
This document specifies the functional requirements for the AGT-SOS Feeder Systems Model (FSM), the type of hardware required, and the modeling techniques employed by the FSM. The objective of the FSM is to map the zone-to-zone transit patronage dema...
Evaluation of a Digital Library by Means of Quality Function Deployment (QFD) and the Kano Model
Garibay, Cecilia; Gutierrez, Humberto; Figueroa, Arturo
2010-01-01
This paper proposes utilizing a combination of the Quality Function Deployment (QFD)-Kano model as a useful tool to evaluate service quality. The digital library of the University of Guadalajara (Mexico) is presented as a case study. Data to feed the QFD-Kano model was gathered by an online questionnaire that was made available to users on the…
Wijk, van M.T.
2007-01-01
Ecosystem functioning is the result of processes working at a hierarchy of scales. The representation of these processes in a model that is mathematically tractable and ecologically meaningful is a big challenge. In this paper I describe an individual based model (PLACO¿PLAnt COmpetition) that
Developing the multi-level functioning interface framework for DER models
DEFF Research Database (Denmark)
Han, Xue; Bindner, Henrik W.; You, Shi
2013-01-01
The paper summarises several modelling applications of distributed energy resources (DERs) for various purposes, and describes the related operational issues regarding the complexity of the future distribution grid. Furthermore, a multi-level functioning interface framework is proposed for DER mo....... The information mapping for photovoltaic panel (PV) modelling is also provided as an example....
S.I. Birbil (Ilker); J.B.G. Frenk (Hans); Z.P. Bayindir (Pelin)
2004-01-01
textabstractWe present a thorough analysis of the economic order quantity model with shortages under a general inventory cost rate function and concave production costs. By using some standard results from convex analysis, we show that the model exhibits a composite concave-convex structure.
Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks
DEFF Research Database (Denmark)
Postnov, D.E.; Koreshkov, R.N.; Brazhe, N.A.
2009-01-01
We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission...
3D finite element model of the chinchilla ear for characterizing middle ear functions.
Wang, Xuelin; Gan, Rong Z
2016-10-01
Chinchilla is a commonly used animal model for research of sound transmission through the ear. Experimental measurements of the middle ear transfer function in chinchillas have shown that the middle ear cavity greatly affects the tympanic membrane (TM) and stapes footplate (FP) displacements. However, there is no finite element (FE) model of the chinchilla ear available in the literature to characterize the middle ear functions with the anatomical features of the chinchilla ear. This paper reports a recently completed 3D FE model of the chinchilla ear based on X-ray micro-computed tomography images of a chinchilla bulla. The model consisted of the ear canal, TM, middle ear ossicles and suspensory ligaments, and the middle ear cavity. Two boundary conditions of the middle ear cavity wall were simulated in the model as the rigid structure and the partially flexible surface, and the acoustic-mechanical coupled analysis was conducted with these two conditions to characterize the middle ear function. The model results were compared with experimental measurements reported in the literature including the TM and FP displacements and the middle ear input admittance in chinchilla ear. An application of this model was presented to identify the acoustic role of the middle ear septa-a unique feature of chinchilla middle ear cavity. This study provides the first 3D FE model of the chinchilla ear for characterizing the middle ear functions through the acoustic-mechanical coupled FE analysis.
Item Purification in Differential Item Functioning Using Generalized Linear Mixed Models
Liu, Qian
2011-01-01
For this dissertation, four item purification procedures were implemented onto the generalized linear mixed model for differential item functioning (DIF) analysis, and the performance of these item purification procedures was investigated through a series of simulations. Among the four procedures, forward and generalized linear mixed model (GLMM)…
Delta-function Approximation SSC Model in 3C 273 S. J. Kang1 ...
Indian Academy of Sciences (India)
Abstract. We obtain an approximate analytical solution using δ approximate calculation on the traditional one-zone synchrotron self-. Compton (SSC) model. In this model, we describe the electron energy distribution by a broken power-law function with a sharp cut-off, and non- thermal photons are produced by both ...
Davis, James; Leslie, Ray; Billington, Susan; Slater, Peter R.
2010-01-01
The use of "Origami" is presented as an accessible and transferable modeling system through which to convey the intricacies of molecular shape and highlight structure-function relationships. The implementation of origami has been found to be a versatile alternative to conventional ball-and-stick models, possessing the key advantages of being both…
An Entropy-Assisted Shielding Function in DDES Formulation for the SST Turbulence Model
Directory of Open Access Journals (Sweden)
Ling Zhou
2017-02-01
Full Text Available The intent of shielding functions in delayed detached-eddy simulation methods (DDES is to preserve the wall boundary layers as Reynolds-averaged Navier–Strokes (RANS mode, avoiding possible modeled stress depletion (MSD or even unphysical separation due to grid refinement. An entropy function fs is introduced to construct a DDES formulation for the k-ω shear stress transport (SST model, whose performance is extensively examined on a range of attached and separated flows (flat-plate flow, circular cylinder flow, and supersonic cavity-ramp flow. Two more forms of shielding functions are also included for comparison: one that uses the blending function F2 of SST, the other which adopts the recalibrated shielding function fd_cor of the DDES version based on the Spalart-Allmaras (SA model. In general, all of the shielding functions do not impair the vortex in fully separated flows. However, for flows including attached boundary layer, both F2 and the recalibrated fd_cor are found to be too conservative to resolve the unsteady flow content. On the other side, fs is proposed on the theory of energy dissipation and independent on from any particular turbulence model, showing the generic priority by properly balancing the need of reserving the RANS modeled regions for wall boundary layers and generating the unsteady turbulent structures in detached areas.
Canine intrahepatic vasculature: is a functional anatomic model relevant to the dog?
Hall, Jon L; Mannion, Paddy; Ladlow, Jane F
2015-01-01
To clarify canine intrahepatic portal and hepatic venous system anatomy using corrosion casting and advanced imaging and to devise a novel functional anatomic model of the canine liver to investigate whether this could help guide the planning and surgical procedure of partial hepatic lobectomy and interventional radiological procedures. Prospective experimental study. Adult Greyhound cadavers (n = 8). Portal and hepatic vein corrosion casts of healthy livers were assessed using computed tomography (CT). The hepatic lobes have a consistent hilar hepatic and portal vein supply with some variation in the number of intrahepatic branches. For all specimens, 3 surgically resectable areas were identified in the left lateral lobe and 2 surgically resectable areas were identified in the right medial lobe as defined by a functional anatomic model. CT of detailed acrylic casts allowed complex intrahepatic vascular relationships to be investigated and compared with previous studies. Improving understanding of the intrahepatic vascular supply facilitates interpretation of advanced images in clinical patients, the planning and performance of surgical procedures, and may facilitate interventional vascular procedures, such as intravenous embolization of portosystemic shunts. Functional division of the canine liver similar to human models is possible. The left lateral and right medial lobes can be consistently divided into surgically resectable functional areas and partial lobectomies can be performed following a functional model; further study in clinically affected animals would be required to investigate the relevance of this functional model in the dog. © Copyright 2014 by The American College of Veterinary Surgeons.
International Nuclear Information System (INIS)
Khalid, S.; Alam, A.
2016-01-01
Collaborative Virtual Environments (CVEs) falls under Virtual Reality (VR) where two or more users manipulate objects collaboratively. In this paper we have made some experiments to make assembly from constituents parts scattered in Virtual Environment (VE) based on task distribution model using assistance functions for checking and enhancing user performance. The CVEs subjects setting on distinct connected machines via local area network. In this perspective, we consider the effects of assistance function with oral communication on collaboration, co-presence and users performance. Twenty subjects performed collaboratively an assembly task on static and dynamic based task distribution. We examine the degree of influence of assistance function with oral communications on user's performance based on task distribution model. The results show that assistance functions with oral communication based on task distribution model not only increase user performance but also enhance the sense of copresence and awareness. (author)
Development and Validation of Functional Model of a Cruise Control System
Directory of Open Access Journals (Sweden)
Avinash Visagan Varadarajan
2016-03-01
Full Text Available Modern automobiles can be considered as a collection of many subsystems working with each other to realize safe transportation of the occupants. Innovative technologies that make transportation easier are increasingly incorporated into the automobile in the form of functionalities. These new functionalities in turn increase the complexity of the system framework present and traceability is lost or becomes very tricky in the process. This hugely impacts the development phase of an automobile, in which, the safety and reliability of the automobile design should be ensured. Hence, there is a need to ensure operational safety of the vehicles while adding new functionalities to the vehicle. To address this issue, functional models of such systems are created and analysed. The main purpose of developing a functional model is to improve the traceability and reusability of a system which reduces development time and cost. Operational safety of the system is ensured by analysing the system with respect to random and systematic failures and including safety mechanism to prevent such failures. This paper discusses the development and validation of a functional model of a conventional cruise control system in a passenger vehicle based on the ISO 26262 Road Vehicles - Functional Safety standard. A methodology for creating functional architectures and an architecture of a cruise control system developed using the methodology are presented.
Directory of Open Access Journals (Sweden)
Hahnbeom Park
Full Text Available Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.
DEFF Research Database (Denmark)
Kirwan, L; Connolly, J; Finn, J A
2009-01-01
We develop a modeling framework that estimates the effects of species identity and diversity on ecosystem function and permits prediction of the diversity-function relationship across different types of community composition. Rather than just measure an overall effect of diversity, we separately...... estimate the contributions of different species interactions. This is especially important when both positive and negative interactions occur or where there are patterns in the interactions. Based on different biological assumptions, we can test for different patterns of interaction that correspond...... to the roles of evenness, functional groups, and functional redundancy. These more parsimonious descriptions can be especially useful in identifying general diversity-function relationships in communities with large numbers of species. We provide an example of the application of the modeling framework...
A numerical study of the string function using a primitive equation ocean model
Tyler, R. H.; Käse, R.
We use results from a primitive-equation ocean numerical model (SCRUM) to test a theoretical 'string function' formulation put forward by Tyler and Käse in another article in this issue. The string function acts as a stream function for the large-scale potential energy flow under the combined beta and topographic effects. The model results verify that large-scale anomalies propagate along the string function contours with a speed correctly given by the cross-string gradient. For anomalies having a scale similar to the Rossby radius, material rates of change in the layer mass following the string velocity are balanced by material rates of change in relative vorticity following the flow velocity. It is shown that large-amplitude anomalies can be generated when wind stress is resonant with the string function configuration.
A Functional Analysis Framework for Modeling, Estimation and Control in Science and Engineering
Banks, HT
2012-01-01
A Modern Framework Based on Time-Tested Material A Functional Analysis Framework for Modeling, Estimation and Control in Science and Engineering presents functional analysis as a tool for understanding and treating distributed parameter systems. Drawing on his extensive research and teaching from the past 20 years, the author explains how functional analysis can be the basis of modern partial differential equation (PDE) and delay differential equation (DDE) techniques. Recent Examples of Functional Analysis in Biology, Electromagnetics, Materials, and Mechanics Through numerous application exa
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A. Kuceyeski
2016-01-01
Full Text Available Following severe injuries that result in disorders of consciousness, recovery can occur over many months or years post-injury. While post-injury synaptogenesis, axonal sprouting and functional reorganization are known to occur, the network-level processes underlying recovery are poorly understood. Here, we test a network-level functional rerouting hypothesis in recovery of patients with disorders of consciousness following severe brain injury. This hypothesis states that the brain recovers from injury by restoring normal functional connections via alternate structural pathways that circumvent impaired white matter connections. The so-called network diffusion model, which relates an individual's structural and functional connectomes by assuming that functional activation diffuses along structural pathways, is used here to capture this functional rerouting. We jointly examined functional and structural connectomes extracted from MRIs of 12 healthy and 16 brain-injured subjects. Connectome properties were quantified via graph theoretic measures and network diffusion model parameters. While a few graph metrics showed groupwise differences, they did not correlate with patients' level of consciousness as measured by the Coma Recovery Scale — Revised. There was, however, a strong and significant partial Pearson's correlation (accounting for age and years post-injury between level of consciousness and network diffusion model propagation time (r = 0.76, p < 0.05, corrected, i.e. the time functional activation spends traversing the structural network. We concluded that functional rerouting via alternate (and less efficient pathways leads to increases in network diffusion model propagation time. Simulations of injury and recovery in healthy connectomes confirmed these results. This work establishes the feasibility for using the network diffusion model to capture network-level mechanisms in recovery of consciousness after severe brain injury.
Aircraft/Air Traffic Management Functional Analysis Model: Technical Description. 2.0
Etheridge, Melvin; Plugge, Joana; Retina, Nusrat
1998-01-01
The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) under a National Aeronautics and Space Administration (NASA) contract. This document provides a technical description of FAM 2.0 and its computer files to enable the modeler and programmer to make enhancements or modifications to the model. Those interested in a guide for using the model in analysis should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Users Manual.
Isgur-Wise function in a QCD-inspired potential model with WKB approximation
International Nuclear Information System (INIS)
Hazarika, Bhaskar Jyoti; Choudhury, D.K.
2017-01-01
We use Wentzel-Kramers-Brillouin (WKB) approximation for calculating the slope and curvature of Isgur-Wise function in a QCD-inspired potential model. This work is an extension of the approximation methods to the QCD-inspired potential model. The approach hints at an effective range of distance for calculating the slope and curvature of Isgur-Wise function. Comparison is also made with those of Dalgarno method and variationally improved perturbation theory (VIPT) as well as other models to show the advantages of using WKB approximation. (author)
Cammi, Roberto
2013-01-01
This Brief presents the main aspects of the response functions theory (RFT) for molecular solutes described within the framework of the Polarizable Continuum Model (PCM). PCM is a solvation model for a Quantum Mechanical molecular system in which the solvent is represented as a continuum distribution of matter. Particular attention is devoted to the description of the basic features of the PCM model, and to the problems characterizing the study of the response function theory for molecules in solution with respect to the analogous theory on isolated molecules.
A discrete stress-strength interference model based on universal generating function
International Nuclear Information System (INIS)
An Zongwen; Huang Hongzhong; Liu Yu
2008-01-01
Continuous stress-strength interference (SSI) model regards stress and strength as continuous random variables with known probability density function. This, to some extent, results in a limitation of its application. In this paper, stress and strength are treated as discrete random variables, and a discrete SSI model is presented by using the universal generating function (UGF) method. Finally, case studies demonstrate the validity of the discrete model in a variety of circumstances, in which stress and strength can be represented by continuous random variables, discrete random variables, or two groups of experimental data
The Perspective on Data and Control Flow Analysis in Topological Functioning Models by Petri Nets
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Asnina Erika
2014-12-01
Full Text Available The perspective on integration of two mathematical formalisms, i.e., Colored Petri Nets (CPNs and Topological Functioning Model (TFM, is discussed in the paper. The roots of CPNs are in modeling system functionality. The TFM joins principles of system theory and algebraic topology, and formally bridges the solution domain with the problem domain. It is a base for further automated construction of software design models. The paper discusses a perspective on check of control and data flows in the TFM by CPNs formalism. The research result is definition of mappings from TFMs to CPNs.
Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.
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Hau-Tieng Wu
Full Text Available We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features.
A prototype symbolic model of canonical functional neuroanatomy of the motor system.
Talos, Ion-Florin; Rubin, Daniel L; Halle, Michael; Musen, Mark; Kikinis, Ron
2008-04-01
Recent advances in bioinformatics have opened entire new avenues for organizing, integrating and retrieving neuroscientific data, in a digital, machine-processable format, which can be at the same time understood by humans, using ontological, symbolic data representations. Declarative information stored in ontological format can be perused and maintained by domain experts, interpreted by machines, and serve as basis for a multitude of decision support, computerized simulation, data mining, and teaching applications. We have developed a prototype symbolic model of canonical neuroanatomy of the motor system. Our symbolic model is intended to support symbolic look up, logical inference and mathematical modeling by integrating descriptive, qualitative and quantitative functional neuroanatomical knowledge. Furthermore, we show how our approach can be extended to modeling impaired brain connectivity in disease states, such as common movement disorders. In developing our ontology, we adopted a disciplined modeling approach, relying on a set of declared principles, a high-level schema, Aristotelian definitions, and a frame-based authoring system. These features, along with the use of the Unified Medical Language System (UMLS) vocabulary, enable the alignment of our functional ontology with an existing comprehensive ontology of human anatomy, and thus allow for combining the structural and functional views of neuroanatomy for clinical decision support and neuroanatomy teaching applications. Although the scope of our current prototype ontology is limited to a particular functional system in the brain, it may be possible to adapt this approach for modeling other brain functional systems as well.
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Meriel Bloor
2008-04-01
Full Text Available This article reports on research into the variation of texts across disciplines and considers the implications of this work for the teaching of writing. The research was motivated by the need to improve students’ academic writing skills in English and the limitations of some current pedagogic advice. The analysis compares Methods sections of research articles across four disciplines, including applied and hard sciences, on a cline, or gradient, termed slow to fast. The analysis considers the characteristics the texts share, but more importantly identifies the variation between sets of linguistic features. Working within a systemic functional framework, the texts are analysed for length, sentence length, lexical density, readability, grammatical metaphor, Thematic choice, as well as various rhetorical functions. Contextually relevant reasons for the differences are considered and the implications of the findings are related to models of text and discourse. Recommendations are made for developing domain models that relate clusters of features to positions on a cline. This article reports on research into the variation of texts across disciplines and considers the implications of this work for the teaching of writing. The research was motivated by the need to improve students’ academic writing skills in English and the limitations of some current pedagogic advice. The analysis compares Methods sections of research articles across four disciplines, including applied and hard sciences, on a cline, or gradient, termed slow to fast. The analysis considers the characteristics the texts share, but more importantly identifies the variation between sets of linguistic features. Working within a systemic functional framework, the texts are analysed for length, sentence length, lexical density, readability, grammatical metaphor, Thematic choice, as well as various rhetorical functions. Contextually relevant reasons for the differences are considered
Angelov, Kiril; Kaynakchieva, Vesela
2017-12-01
The aim of the current study is to research and analyze Mathematical model for research and analyze of relations and functions between enterprises, members of cluster, and its approbation in given cluster. Subject of the study are theoretical mechanisms for the definition of mathematical models for research and analyze of relations and functions between enterprises, members of cluster. Object of the study are production enterprises, members of cluster. Results of this study show that described theoretical mathematical model is applicable for research and analyze of functions and relations between enterprises, members of cluster from different industrial sectors. This circumstance creates alternatives for election of cluster, where is experimented this model for interaction improvement between enterprises, members of cluster.
Redefining the Attraction Measure, Scaling Exponent and Impedance Function of the Gravity Model
Chen, Yanguang; Xu, Feng
2013-01-01
The attraction measure, scaling exponent, and impedance function of the gravity model are redefined using the concepts from fractals and spatial complexity. Firstly, the attraction measure of spatial interaction in human systems is defined by the product of traffic inflow and outflow. Based on the new definition, the gravity model originating from the Newtonian analogy is differentiated from Wilson's spatial interaction model deriving from entropy-maximizing principle. Secondly, the scaling e...
Gorgoso-Varela, J. Javier; Rojo-Alboreca, Alberto
2014-01-01
International audience; & Context Families of the Gumbel (type I), Fréchet (type II) and Weibull (type III) distributions can be combined in the generalized extreme value (GEV) family of distributions. Maximum and minimum values of diameters in forest stands can be used in forest modelling, mainly to define parameters of the functions used in diameter class models as well as in some practical cases, such as modelling maximum diameters for sawing and processing purposes. & Aims The purpose of ...
Flocking of the Motsch-Tadmor Model with a Cut-Off Interaction Function
Jin, Chunyin
2018-04-01
In this paper, we study the flocking behavior of the Motsch-Tadmor model with a cut-off interaction function. Our analysis shows that connectedness is important for flocking of this kind of model. Fortunately, we get a sufficient condition imposed only on the model parameters and initial data to guarantee the connectedness of the neighbor graph associated with the system. Then we present a theoretical analysis for flocking, and show that the system achieves consensus at an exponential rate.
A functional-dynamic reflection on participatory processes in modeling projects.
Seidl, Roman
2015-12-01
The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.
Takagi-Sugeno fuzzy models in the framework of orthonormal basis functions.
Machado, Jeremias B; Campello, Ricardo J G B; Amaral, Wagner Caradori
2013-06-01
An approach to obtain Takagi-Sugeno (TS) fuzzy models of nonlinear dynamic systems using the framework of orthonormal basis functions (OBFs) is presented in this paper. This approach is based on an architecture in which local linear models with ladder-structured generalized OBFs (GOBFs) constitute the fuzzy rule consequents and the outputs of the corresponding GOBF filters are input variables for the rule antecedents. The resulting GOBF-TS model is characterized by having only real-valued parameters that do not depend on any user specification about particular types of functions to be used in the orthonormal basis. The fuzzy rules of the model are initially obtained by means of a well-known technique based on fuzzy clustering and least squares. Those rules are then simplified, and the model parameters (GOBF poles, GOBF expansion coefficients, and fuzzy membership functions) are subsequently adjusted by using a nonlinear optimization algorithm. The exact gradients of an error functional with respect to the parameters to be optimized are computed analytically. Those gradients provide exact search directions for the optimization process, which relies solely on input-output data measured from the system to be modeled. An example is presented to illustrate the performance of this approach in the modeling of a complex nonlinear dynamic system.
Functional outcome measures in a surgical model of hip osteoarthritis in dogs.
Little, Dianne; Johnson, Stephen; Hash, Jonathan; Olson, Steven A; Estes, Bradley T; Moutos, Franklin T; Lascelles, B Duncan X; Guilak, Farshid
2016-12-01
The hip is one of the most common sites of osteoarthritis in the body, second only to the knee in prevalence. However, current animal models of hip osteoarthritis have not been assessed using many of the functional outcome measures used in orthopaedics, a characteristic that could increase their utility in the evaluation of therapeutic interventions. The canine hip shares similarities with the human hip, and functional outcome measures are well documented in veterinary medicine, providing a baseline for pre-clinical evaluation of therapeutic strategies for the treatment of hip osteoarthritis. The purpose of this study was to evaluate a surgical model of hip osteoarthritis in a large laboratory animal model and to evaluate functional and end-point outcome measures. Seven dogs were subjected to partial surgical debridement of cartilage from one femoral head. Pre- and postoperative pain and functional scores, gait analysis, radiographs, accelerometry, goniometry and limb circumference were evaluated through a 20-week recovery period, followed by histological evaluation of cartilage and synovium. Animals developed histological and radiographic evidence of osteoarthritis, which was correlated with measurable functional impairment. For example, Mankin scores in operated limbs were positively correlated to radiographic scores but negatively correlated to range of motion, limb circumference and 20-week peak vertical force. This study demonstrates that multiple relevant functional outcome measures can be used successfully in a large laboratory animal model of hip osteoarthritis. These measures could be used to evaluate relative efficacy of therapeutic interventions relevant to human clinical care.
Jonny, Zagloed, Teuku Yuri M.
2017-11-01
This paper aims to present an integrated health care model for Indonesian health care industry. Based on previous researches, there are two health care models in the industry such as decease- and patient-centered care models. In their developments, the patient-centered care model is widely applied due to its capability in reducing cost and improving quality simultaneously. However, there is still no comprehensive model resulting in cost reduction, quality improvement, patient satisfaction and hospital profitability simultaneously. Therefore, this research is intended to develop that model. In doing so, first, a conceptual model using Kano's Model, Quality Function Deployment (QFD) and Balanced Scorecard (BSC) is developed to generate several important elements of the model as required by stakeholders. Then, a case study of an Indonesian hospital is presented to evaluate the validity of the model using correlation analysis. As a result, it can be concluded that the model is validated implying several managerial insights among its elements such as l) leadership (r=0.85) and context of the organization (r=0.77) improve operations; 2) planning (r=0.96), support process (r=0.87) and continual improvement (r=0.95) also improve operations; 3) operations improve customer satisfaction (r=0.89) and financial performance (r=0.93) and 4) customer satisfaction improves the financial performance (0.98).
Sparse generalized functional linear model for predicting remission status of depression patients.
Liu, Yashu; Nie, Zhi; Zhou, Jiayu; Farnum, Michael; Narayan, Vaibhav A; Wittenberg, Gayle; Ye, Jieping
2014-01-01
Complex diseases such as major depression affect people over time in complicated patterns. Longitudinal data analysis is thus crucial for understanding and prognosis of such diseases and has received considerable attention in the biomedical research community. Traditional classification and regression methods have been commonly applied in a simple (controlled) clinical setting with a small number of time points. However, these methods cannot be easily extended to the more general setting for longitudinal analysis, as they are not inherently built for time-dependent data. Functional regression, in contrast, is capable of identifying the relationship between features and outcomes along with time information by assuming features and/or outcomes as random functions over time rather than independent random variables. In this paper, we propose a novel sparse generalized functional linear model for the prediction of treatment remission status of the depression participants with longitudinal features. Compared to traditional functional regression models, our model enables high-dimensional learning, smoothness of functional coefficients, longitudinal feature selection and interpretable estimation of functional coefficients. Extensive experiments have been conducted on the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) data set and the results show that the proposed sparse functional regression method achieves significantly higher prediction power than existing approaches.
Directory of Open Access Journals (Sweden)
Miguel Flores
2016-11-01
Full Text Available This work aims to classify the DNA sequences of healthy and malignant cancer respectively. For this, supervised and unsupervised classification methods from a functional context are used; i.e. each strand of DNA is an observation. The observations are discretized, for that reason different ways to represent these observations with functions are evaluated. In addition, an exploratory study is done: estimating the mean and variance of each functional type of cancer. For the unsupervised classification method, hierarchical clustering with different measures of functional distance is used. On the other hand, for the supervised classification method, a functional generalized linear model is used. For this model the first and second derivatives are used which are included as discriminating variables. It has been verified that one of the advantages of working in the functional context is to obtain a model to correctly classify cancers by 100%. For the implementation of the methods it has been used the fda.usc R package that includes all the techniques of functional data analysis used in this work. In addition, some that have been developed in recent decades. For more details of these techniques can be consulted Ramsay, J. O. and Silverman (2005 and Ferraty et al. (2006.
Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models
Klotz, D.; Herrnegger, M.; Schulz, K.
2017-11-01
Current concepts for parameter regionalization of spatially distributed rainfall-runoff models rely on the a priori definition of transfer functions that globally map land surface characteristics (such as soil texture, land use, and digital elevation) into the model parameter space. However, these transfer functions are often chosen ad hoc or derived from small-scale experiments. This study proposes and tests an approach for inferring the structure and parametrization of possible transfer functions from runoff data to potentially circumvent these difficulties. The concept uses context-free grammars to generate possible proposition for transfer functions. The resulting structure can then be parametrized with classical optimization techniques. Several virtual experiments are performed to examine the potential for an appropriate estimation of transfer function, all of them using a very simple conceptual rainfall-runoff model with data from the Austrian Mur catchment. The results suggest that a priori defined transfer functions are in general well identifiable by the method. However, the deduction process might be inhibited, e.g., by noise in the runoff observation data, often leading to transfer function estimates of lower structural complexity.
Application of ANFIS for analytical modeling of tensile strength of functionally graded steels
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Ali Nazari
2012-06-01
Full Text Available In the present study, the tensile strength of ferritic and austenitic functionally graded steels produced by electroslag remelting has been modeled. To produce functionally graded steels, two slices of plain carbon steel and austenitic stainless steels were spot welded and used as electroslag remelting electrode. Functionally graded steel containing graded layers of ferrite and austenite may be fabricated via diffusion of alloying elements during remelting stage. Vickers microhardness profile of the specimen has been obtained experimentally and modeled with adaptive network-based fuzzy inference systems (ANFIS. To build the model for graded ferritic and austenitic steels, training, testing and validation using respectively 174 and 120 experimental data were conducted. According to the input parameters, in the ANFIS model, the Vickers microhardness of each layer was predicted. A good fit equation which correlates the Vickers microhardness of each layer to its corresponding chemical composition was achieved by the optimized network for both ferritic and austenitic graded steels. Afterwards; the Vickers microhardness of each layer in functionally graded steels was related to the yield stress of the corresponding layer and by assuming Holloman relation for stress-strain curve of each layer, they were acquired. Finally, by applying the rule of mixtures, tensile strength of functionally graded steels configuration was found through a numerical method. The obtained results from the proposed model are in good agreement with those acquired from the experiments.
Estimation of parameters of constant elasticity of substitution production functional model
Mahaboob, B.; Venkateswarlu, B.; Sankar, J. Ravi
2017-11-01
Nonlinear model building has become an increasing important powerful tool in mathematical economics. In recent years the popularity of applications of nonlinear models has dramatically been rising up. Several researchers in econometrics are very often interested in the inferential aspects of nonlinear regression models [6]. The present research study gives a distinct method of estimation of more complicated and highly nonlinear model viz Constant Elasticity of Substitution (CES) production functional model. Henningen et.al [5] proposed three solutions to avoid serious problems when estimating CES functions in 2012 and they are i) removing discontinuities by using the limits of the CES function and its derivative. ii) Circumventing large rounding errors by local linear approximations iii) Handling ill-behaved objective functions by a multi-dimensional grid search. Joel Chongeh et.al [7] discussed the estimation of the impact of capital and labour inputs to the gris output agri-food products using constant elasticity of substitution production function in Tanzanian context. Pol Antras [8] presented new estimates of the elasticity of substitution between capital and labour using data from the private sector of the U.S. economy for the period 1948-1998.
Harris, Michelle A.; Chang, Wesley S.; Dent, Erik W.; Nordheim, Erik V.; Franzen, Margaret A.
2016-01-01
Abstract Understanding how basic structural units influence function is identified as a foundational/core concept for undergraduate biological and biochemical literacy. It is essential for students to understand this concept at all size scales, but it is often more difficult for students to understand structure–function relationships at the molecular level, which they cannot as effectively visualize. Students need to develop accurate, 3‐dimensional mental models of biomolecules to understand how biomolecular structure affects cellular functions at the molecular level, yet most traditional curricular tools such as textbooks include only 2‐dimensional representations. We used a controlled, backward design approach to investigate how hand‐held physical molecular model use affected students' ability to logically predict structure–function relationships. Brief (one class period) physical model use increased quiz score for females, whereas there was no significant increase in score for males using physical models. Females also self‐reported higher learning gains in their understanding of context‐specific protein function. Gender differences in spatial visualization may explain the gender‐specific benefits of physical model use observed. © 2016 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology, 44(4):326–335, 2016. PMID:26923186
Forbes-Lorman, Robin M; Harris, Michelle A; Chang, Wesley S; Dent, Erik W; Nordheim, Erik V; Franzen, Margaret A
2016-07-08
Understanding how basic structural units influence function is identified as a foundational/core concept for undergraduate biological and biochemical literacy. It is essential for students to understand this concept at all size scales, but it is often more difficult for students to understand structure-function relationships at the molecular level, which they cannot as effectively visualize. Students need to develop accurate, 3-dimensional mental models of biomolecules to understand how biomolecular structure affects cellular functions at the molecular level, yet most traditional curricular tools such as textbooks include only 2-dimensional representations. We used a controlled, backward design approach to investigate how hand-held physical molecular model use affected students' ability to logically predict structure-function relationships. Brief (one class period) physical model use increased quiz score for females, whereas there was no significant increase in score for males using physical models. Females also self-reported higher learning gains in their understanding of context-specific protein function. Gender differences in spatial visualization may explain the gender-specific benefits of physical model use observed. © 2016 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology, 44(4):326-335, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.
NCACO-score: An effective main-chain dependent scoring function for structure modeling
Directory of Open Access Journals (Sweden)
Dong Xiaoxi
2011-05-01
Full Text Available Abstract Background Development of effective scoring functions is a critical component to the success of protein structure modeling. Previously, many efforts have been dedicated to the development of scoring functions. Despite these efforts, development of an effective scoring function that can achieve both good accuracy and fast speed still presents a grand challenge. Results Based on a coarse-grained representation of a protein structure by using only four main-chain atoms: N, Cα, C and O, we develop a knowledge-based scoring function, called NCACO-score, that integrates different structural information to rapidly model protein structure from sequence. In testing on the Decoys'R'Us sets, we found that NCACO-score can effectively recognize native conformers from their decoys. Furthermore, we demonstrate that NCACO-score can effectively guide fragment assembly for protein structure prediction, which has achieved a good performance in building the structure models for hard targets from CASP8 in terms of both accuracy and speed. Conclusions Although NCACO-score is developed based on a coarse-grained model, it is able to discriminate native conformers from decoy conformers with high accuracy. NCACO is a very effective scoring function for structure modeling.
Carton, David; Brinchmann, Jarle; Shirazi, Maryam; Contini, Thierry; Epinat, Benoît; Erroz-Ferrer, Santiago; Marino, Raffaella A.; Martinsson, Thomas P. K.; Richard, Johan; Patrício, Vera
2017-06-01
We present a method to recover the gas-phase metallicity gradients from integral field spectroscopic (IFS) observations of barely resolved galaxies. We take a forward modelling approach and compare our models to the observed spatial distribution of emission-line fluxes, accounting for the degrading effects of seeing and spatial binning. The method is flexible and is not limited to particular emission lines or instruments. We test the model through comparison to synthetic observations and use downgraded observations of nearby galaxies to validate this work. As a proof of concept, we also apply the model to real IFS observations of high-redshift galaxies. From our testing, we show that the inferred metallicity gradients and central metallicities are fairly insensitive to the assumptions made in the model and that they are reliably recovered for galaxies with sizes approximately equal to the half width at half-maximum of the point spread function. However, we also find that the presence of star-forming clumps can significantly complicate the interpretation of metallicity gradients in moderately resolved high-redshift galaxies. Therefore, we emphasize that care should be taken when comparing nearby well-resolved observations to high-redshift observations of partially resolved galaxies.
Asymptotic behaviour of two-point functions in multi-species models
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Karol K. Kozlowski
2016-05-01
Full Text Available We extract the long-distance asymptotic behaviour of two-point correlation functions in massless quantum integrable models containing multi-species excitations. For such a purpose, we extend to these models the method of a large-distance regime re-summation of the form factor expansion of correlation functions. The key feature of our analysis is a technical hypothesis on the large-volume behaviour of the form factors of local operators in such models. We check the validity of this hypothesis on the example of the SU(3-invariant XXX magnet by means of the determinant representations for the form factors of local operators in this model. Our approach confirms the structure of the critical exponents obtained previously for numerous models solvable by the nested Bethe Ansatz.
Semi-analytical wave functions in relativistic average atom model for high-temperature plasmas
International Nuclear Information System (INIS)
Guo Yonghui; Duan Yaoyong; Kuai Bin
2007-01-01
The semi-analytical method is utilized for solving a relativistic average atom model for high-temperature plasmas. Semi-analytical wave function and the corresponding energy eigenvalue, containing only a numerical factor, are obtained by fitting the potential function in the average atom into hydrogen-like one. The full equations for the model are enumerated, and more attentions are paid upon the detailed procedures including the numerical techniques and computer code design. When the temperature of plasmas is comparatively high, the semi-analytical results agree quite well with those obtained by using a full numerical method for the same model and with those calculated by just a little different physical models, and the result's accuracy and computation efficiency are worthy of note. The drawbacks for this model are also analyzed. (authors)
Modeling and Circumventing the Effect of Sediments and Water Column on Receiver Functions
Audet, P.
2017-12-01
Teleseismic P-wave receiver functions are routinely used to resolve crust and mantle structure in various geologic settings. Receiver functions are approximations to the Earth's Green's functions and are composed of various scattered phase arrivals, depending on the complexity of the underlying Earth structure. For simple structure, the dominant arrivals (converted and back-scattered P-to-S phases) are well separated in time and can be reliably used in estimating crustal velocity structure. In the presence of sedimentary layers, strong reverberations typically produce high-amplitude oscillations that contaminate the early part of the wave train and receiver functions can be difficult to interpret in terms of underlying structure. The effect of a water column also limits the interpretability of under-water receiver functions due to the additional acoustic wave propagating within the water column that can contaminate structural arrivals. We perform numerical modeling of teleseismic Green's functions and receiver functions using a reflectivity technique for a range of Earth models that include thin sedimentary layers and overlying water column. These modeling results indicate that, as expected, receiver functions are difficult to interpret in the presence of sediments, but the contaminating effect of the water column is dependent on the thickness of the water layer. To circumvent these effects and recover source-side structure, we propose using an approach based on transfer function modeling that bypasses receiver functions altogether and estimates crustal properties directly from the waveforms (Frederiksen and Delayney, 2015). Using this approach, reasonable assumptions about the properties of the sedimentary layer can be included in forward calculations of the Green's functions that are convolved with radial waveforms to predict vertical waveforms. Exploration of model space using Monte Carlo-style search and least-square waveform misfits can be performed to
Parameterizing Dose-Response Models to Estimate Relative Potency Functions Directly
Dinse, Gregg E.
2012-01-01
Many comparative analyses of toxicity assume that the potency of a test chemical relative to a reference chemical is constant, but employing such a restrictive assumption uncritically may generate misleading conclusions. Recent efforts to characterize non-constant relative potency rely on relative potency functions and estimate them secondarily after fitting dose-response models for the test and reference chemicals. We study an alternative approach of specifying a relative potency model a priori and estimating it directly using the dose-response data from both chemicals. We consider a power function in dose as a relative potency model and find that it keeps the two chemicals’ dose-response functions within the same family of models for families typically used in toxicology. When differences in the response limits for the test and reference chemicals are attributable to the chemicals themselves, the older two-stage approach is the more convenient. When differences in response limits are attributable to other features of the experimental protocol or when response limits do not differ, the direct approach is straightforward to apply with nonlinear regression methods and simplifies calculation of simultaneous confidence bands. We illustrate the proposed approach using Hill models with dose-response data from U.S. National Toxicology Program bioassays. Though not universally applicable, this method of estimating relative potency functions directly can be profitably applied to a broad family of dose-response models commonly used in toxicology. PMID:22700543
A perturbative approach to the redshift space correlation function: beyond the Standard Model
Energy Technology Data Exchange (ETDEWEB)
Bose, Benjamin; Koyama, Kazuya, E-mail: benjamin.bose@port.ac.uk, E-mail: kazuya.koyama@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Burnaby Road, Portsmouth, Hampshire, PO1 3FX (United Kingdom)
2017-08-01
We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with ≤ 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpc h ≤ s ≤ 180Mpc/ h . Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.
A perturbative approach to the redshift space correlation function: beyond the Standard Model
Bose, Benjamin; Koyama, Kazuya
2017-08-01
We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with <= 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpch <= s <= 180Mpc/h. Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.
Directory of Open Access Journals (Sweden)
Kitzig Andreas
2017-09-01
Full Text Available Development of preparation-free functionalized furniture based patient monitoring systems for use in the area of home- or stationary- care is often empirically driven. In particular, functionalization of furniture by means of different sensors is strongly affected by this development methodology. As a result, the systems are often not extensive-ly extendable or cannot be optimized because basic mechanisms are not comprehensible. In order to support development or optimization, a modelling approach is often useful. Thus, using a more comprehensive approach the required sensitivity of the sensors as well as their position in the system can be derived from a simulation model. In order to solve this problem, a multi-stage model was introduced at the BMT conference in 2014 by the authors, which allows the designer to model the entire system. The model has been extended and improved in the meantime and the achieved progress is presented in this work. The presented modelling approach can be divided into three main components. These are the person under supervision, the furniture (in our case a nursing bed and the sensors (force measuring cells which are modelled separately. In this work the main focus will be on improving the modelling of the human movement process and its implementation. Furthermore, the modelling of the sensor behavior in the nursing bed is described in detail with regard to their oscillation behavior and the influence on the model.
Model etch profiles for ion energy distribution functions in an inductively coupled plasma reactor
International Nuclear Information System (INIS)
Chen, W.; Abraham-Shrauner, B.; Woodworth, J.R.
1999-01-01
Rectangular trench profiles are modeled with analytic etch rates determined from measured ion distribution functions. The pattern transfer step for this plasma etch is for trilayer lithography. Argon and chlorine angular ion energy distribution functions measured by a spherical collector ring analyzer are fit to a sum of drifting Maxwellian velocity distribution functions with anisotropic temperatures. The fit of the model ion distribution functions by a simulated annealing optimization procedure converges adequately for only two drifting Maxwellians. The etch rates are proportional to analytic expressions for the ion energy flux. Numerical computation of the etch profiles by integration of the characteristic equations for profile points and connection of the profiles points is efficient. copyright 1999 American Vacuum Society
Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G
2015-12-01
The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer's disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM.
Determinants of functioning and well-being among individuals with schizophrenia: An integrated model
Yanos, P.T.; Moos, R.H.
2006-01-01
Outcomes for health conditions are typically the result of multiple factors; however, studies tend to focus on a narrow class of variables. Functioning and well-being outcomes for schizophrenia are diverse and have resisted simple explanation; however, prior research has not offered an integrated understanding of the relative contributions of enduring and episodic environmental factors, personal resources and psychiatric factors, and cognitive appraisal and coping, on functioning and well-being outcomes in schizophrenia. The present article sets out an integrated model of the determinants of functioning and well-being among individuals with schizophrenia. To examine evidence that bears on the model, literature on hypothesized relationships is reviewed to identify areas for which there is strong evidence and areas where more research is needed. The article suggests areas for further research, and directs researchers and practitioners toward areas of intervention that can enhance functioning and well-being for persons diagnosed with schizophrenia. PMID:16480804
Asymmetric and Non–Positive Definite Distance Functions Part II: Modeling
Directory of Open Access Journals (Sweden)
H. Sánchez–Larios
2009-01-01
Full Text Available Traditionally the distance functions involved in problems of Operations Research have been modeled using positive linear combinations of metrics Lp. Thus, the resulting distance functions are symmetric, uniforms and positive definite. Starting from a new definition of arc length, we propose a method formo deling generalized distance functions, that we call premetrics, which can be asymmetric, non uniform, and non positive definite. We show that every distance function satisfying the triangle inequality and having a continuous one–sided directional derivative can be modeled as a problem of calculus of variations. The "length" of a d–geodesic arc C(a,b from a to b with respect to the premetric d (the d–length can be negative, and therefore the d–distance from a to b may represent the minimum energy needed to move a mobile object from a to b. We illustrate our method with two examples.
Moeys, J.; Larsbo, M.; Bergström, L.; Brown, C. D.; Coquet, Y.; Jarvis, N. J.
2012-07-01
Estimating pesticide leaching risks at the regional scale requires the ability to completely parameterise a pesticide fate model using only survey data, such as soil and land-use maps. Such parameterisations usually rely on a set of lookup tables and (pedo)transfer functions, relating elementary soil and site properties to model parameters. The aim of this paper is to describe and test a complete set of parameter estimation algorithms developed for the pesticide fate model MACRO, which accounts for preferential flow in soil macropores. We used tracer monitoring data from 16 lysimeter studies, carried out in three European countries, to evaluate the ability of MACRO and this "blind parameterisation" scheme to reproduce measured solute leaching at the base of each lysimeter. We focused on the prediction of early tracer breakthrough due to preferential flow, because this is critical for pesticide leaching. We then calibrated a selected number of parameters in order to assess to what extent the prediction of water and solute leaching could be improved. Our results show that water flow was generally reasonably well predicted (median model efficiency, ME, of 0.42). Although the general pattern of solute leaching was reproduced well by the model, the overall model efficiency was low (median ME = -0.26) due to errors in the timing and magnitude of some peaks. Preferential solute leaching at early pore volumes was also systematically underestimated. Nonetheless, the ranking of soils according to solute loads at early pore volumes was reasonably well estimated (concordance correlation coefficient, CCC, between 0.54 and 0.72). Moreover, we also found that ignoring macropore flow leads to a significant deterioration in the ability of the model to reproduce the observed leaching pattern, and especially the early breakthrough in some soils. Finally, the calibration procedure showed that improving the estimation of solute transport parameters is probably more important than the
Directory of Open Access Journals (Sweden)
J. Moeys
2012-07-01
Full Text Available Estimating pesticide leaching risks at the regional scale requires the ability to completely parameterise a pesticide fate model using only survey data, such as soil and land-use maps. Such parameterisations usually rely on a set of lookup tables and (pedotransfer functions, relating elementary soil and site properties to model parameters. The aim of this paper is to describe and test a complete set of parameter estimation algorithms developed for the pesticide fate model MACRO, which accounts for preferential flow in soil macropores. We used tracer monitoring data from 16 lysimeter studies, carried out in three European countries, to evaluate the ability of MACRO and this "blind parameterisation" scheme to reproduce measured solute leaching at the base of each lysimeter. We focused on the prediction of early tracer breakthrough due to preferential flow, because this is critical for pesticide leaching. We then calibrated a selected number of parameters in order to assess to what extent the prediction of water and solute leaching could be improved.
Our results show that water flow was generally reasonably well predicted (median model efficiency, ME, of 0.42. Although the general pattern of solute leaching was reproduced well by the model, the overall model efficiency was low (median ME = −0.26 due to errors in the timing and magnitude of some peaks. Preferential solute leaching at early pore volumes was also systematically underestimated. Nonetheless, the ranking of soils according to solute loads at early pore volumes was reasonably well estimated (concordance correlation coefficient, CCC, between 0.54 and 0.72. Moreover, we also found that ignoring macropore flow leads to a significant deterioration in the ability of the model to reproduce the observed leaching pattern, and especially the early breakthrough in some soils. Finally, the calibration procedure showed that improving the estimation of solute transport parameters is
Iwadate, Mitsuo; Kanou, Kazuhiko; Terashi, Genki; Umeyama, Hideaki; Takeda-Shitaka, Mayuko
2010-01-01
We have devised a power function (PF) that can predict the accuracy of a three-dimensional (3D) structure model of a protein using only amino acid sequence alignments. This Power Function (PF) consists of three parts; (1) the length of a model, (2) a homology identity percent value and (3) the agreement rate between PSI-PRED secondary structure prediction and the secondary structure judgment of a reference protein. The PF value is mathematically computed from the execution process of homology search tools, such as FASTA or various BLAST programs, to obtain the amino acid sequence alignments. There is a high correlation between the global distance test-total score (GDT_TS) value of the protein model based upon the PF score and the GDT_TS(MAX) value used as an index of protein modeling accuracy in the international contest Critical Assessment of Techniques for Protein Structure Prediction (CASP). Accordingly, the PF method is valuable for constructing a highly accurate model without wasteful calculations of homology modeling that is normally performed by an iterative method to move the main chain and side chains in the modeling process. Moreover, a model with higher accuracy can be obtained by combining the models ordered by the PF score with models sorted by the size of the CIRCLE score. The CIRCLE software is a 3D-1D program, in which energetic stabilization is estimated based upon the experimental environment of each amino acid residue in the protein solution or protein crystals.
Mendoza, P. A.; Clark, M. P.; Rajagopalan, B.
2012-12-01
The increasing availability of hydrometeorological data and computational resources has allowed the evolution of hydrological models from lumped, conceptual to fully distributed. However, principal catchment behavioral functions are poorly understood, mainly because model evaluation has been typically based on the comparison of simulated and observed time series of model outputs (e.g., streamflow), ignoring the possibility that we may be getting the right results because of a compensation of errors in model structure, parameters and data. In recent years the hydrological community has redirected its efforts to look for a better understanding of hydrological models from a functional point of view (e.g. water balance, vertical redistribution of soil moisture and redistribution of runoff in time, among others). In this research, we evaluate the ability of three hydrological models (PRMS, VIC and Noah-MP) to skillfully reproduce relevant watershed processes in the Animas River basin, which is a sub-basin of the Colorado River Basin. A suite of signature measures that have diagnostic power of model behaviors is developed and analyzed in order to diagnose the model deficiency. All model simulations were run with the same spatial discretization and forcing data to enable fair comparison of model structures
Dixit, Anshuman; Verkhivker, Gennady M
2012-01-01
Deciphering functional mechanisms of the Hsp90 chaperone machinery is an important objective in cancer biology aiming to facilitate discovery of targeted anti-cancer therapies. Despite significant advances in understanding structure and function of molecular chaperones, organizing molecular principles that control the relationship between conformational diversity and functional mechanisms of the Hsp90 activity lack a sufficient quantitative characterization. We combined molecular dynamics simulations, principal component analysis, the energy landscape model and structure-functional analysis of Hsp90 regulatory interactions to systematically investigate functional dynamics of the molecular chaperone. This approach has identified a network of conserved regions common to the Hsp90 chaperones that could play a universal role in coordinating functional dynamics, principal collective motions and allosteric signaling of Hsp90. We have found that these functional motifs may be utilized by the molecular chaperone machinery to act collectively as central regulators of Hsp90 dynamics and activity, including the inter-domain communications, control of ATP hydrolysis, and protein client binding. These findings have provided support to a long-standing assertion that allosteric regulation and catalysis may have emerged via common evolutionary routes. The interaction networks regulating functional motions of Hsp90 may be determined by the inherent structural architecture of the molecular chaperone. At the same time, the thermodynamics-based "conformational selection" of functional states is likely to be activated based on the nature of the binding partner. This mechanistic model of Hsp90 dynamics and function is consistent with the notion that allosteric networks orchestrating cooperative protein motions can be formed by evolutionary conserved and sparsely connected residue clusters. Hence, allosteric signaling through a small network of distantly connected residue clusters may be