A Cross Structured Light Sensor and Stripe Segmentation Method for Visual Tracking of a Wall Climbing Robot

PubMed Central

Zhang, Liguo; Sun, Jianguo; Yin, Guisheng; Zhao, Jing; Han, Qilong

2015-01-01

In non-destructive testing (NDT) of metal welds, weld line tracking is usually performed outdoors, where the structured light sources are always disturbed by various noises, such as sunlight, shadows, and reflections from the weld line surface. In this paper, we design a cross structured light (CSL) to detect the weld line and propose a robust laser stripe segmentation algorithm to overcome the noises in structured light images. An adaptive monochromatic space is applied to preprocess the image with ambient noises. In the monochromatic image, the laser stripe obtained is recovered as a multichannel signal by minimum entropy deconvolution. Lastly, the stripe centre points are extracted from the image. In experiments, the CSL sensor and the proposed algorithm are applied to guide a wall climbing robot inspecting the weld line of a wind power tower. The experimental results show that the CSL sensor can capture the 3D information of the welds with high accuracy, and the proposed algorithm contributes to the weld line inspection and the robot navigation. PMID:26110403

Fault Detection of Roller-Bearings Using Signal Processing and Optimization Algorithms

PubMed Central

Kwak, Dae-Ho; Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2014-01-01

This study presents a fault detection of roller bearings through signal processing and optimization techniques. After the occurrence of scratch-type defects on the inner race of bearings, variations of kurtosis values are investigated in terms of two different data processing techniques: minimum entropy deconvolution (MED), and the Teager-Kaiser Energy Operator (TKEO). MED and the TKEO are employed to qualitatively enhance the discrimination of defect-induced repeating peaks on bearing vibration data with measurement noise. Given the perspective of the execution sequence of MED and the TKEO, the study found that the kurtosis sensitivity towards a defect on bearings could be highly improved. Also, the vibration signal from both healthy and damaged bearings is decomposed into multiple intrinsic mode functions (IMFs), through empirical mode decomposition (EMD). The weight vectors of IMFs become design variables for a genetic algorithm (GA). The weights of each IMF can be optimized through the genetic algorithm, to enhance the sensitivity of kurtosis on damaged bearing signals. Experimental results show that the EMD-GA approach successfully improved the resolution of detectability between a roller bearing with defect, and an intact system. PMID:24368701

Correction for frequency-dependent hydrophone response to nonlinear pressure waves using complex deconvolution and rarefactional filtering: application with fiber optic hydrophones.

PubMed

Wear, Keith; Liu, Yunbo; Gammell, Paul M; Maruvada, Subha; Harris, Gerald R

2015-01-01

Nonlinear acoustic signals contain significant energy at many harmonic frequencies. For many applications, the sensitivity (frequency response) of a hydrophone will not be uniform over such a broad spectrum. In a continuation of a previous investigation involving deconvolution methodology, deconvolution (implemented in the frequency domain as an inverse filter computed from frequency-dependent hydrophone sensitivity) was investigated for improvement of accuracy and precision of nonlinear acoustic output measurements. Timedelay spectrometry was used to measure complex sensitivities for 6 fiber-optic hydrophones. The hydrophones were then used to measure a pressure wave with rich harmonic content. Spectral asymmetry between compressional and rarefactional segments was exploited to design filters used in conjunction with deconvolution. Complex deconvolution reduced mean bias (for 6 fiber-optic hydrophones) from 163% to 24% for peak compressional pressure (p+), from 113% to 15% for peak rarefactional pressure (p-), and from 126% to 29% for pulse intensity integral (PII). Complex deconvolution reduced mean coefficient of variation (COV) (for 6 fiber optic hydrophones) from 18% to 11% (p+), 53% to 11% (p-), and 20% to 16% (PII). Deconvolution based on sensitivity magnitude or the minimum phase model also resulted in significant reductions in mean bias and COV of acoustic output parameters but was less effective than direct complex deconvolution for p+ and p-. Therefore, deconvolution with appropriate filtering facilitates reliable nonlinear acoustic output measurements using hydrophones with frequency-dependent sensitivity.

Maximum entropy deconvolution of the optical jet of 3C 273

NASA Technical Reports Server (NTRS)

Evans, I. N.; Ford, H. C.; Hui, X.

1989-01-01

The technique of maximum entropy image restoration is applied to the problem of deconvolving the point spread function from a deep, high-quality V band image of the optical jet of 3C 273. The resulting maximum entropy image has an approximate spatial resolution of 0.6 arcsec and has been used to study the morphology of the optical jet. Four regularly-spaced optical knots are clearly evident in the data, together with an optical 'extension' at each end of the optical jet. The jet oscillates around its center of gravity, and the spatial scale of the oscillations is very similar to the spacing between the optical knots. The jet is marginally resolved in the transverse direction and has an asymmetric profile perpendicular to the jet axis. The distribution of V band flux along the length of the jet, and accurate astrometry of the optical knot positions are presented.

Maximum and minimum entropy states yielding local continuity bounds

NASA Astrophysics Data System (ADS)

Hanson, Eric P.; Datta, Nilanjana

2018-04-01

Given an arbitrary quantum state (σ), we obtain an explicit construction of a state ρɛ * ( σ ) [respectively, ρ * , ɛ ( σ ) ] which has the maximum (respectively, minimum) entropy among all states which lie in a specified neighborhood (ɛ-ball) of σ. Computing the entropy of these states leads to a local strengthening of the continuity bound of the von Neumann entropy, i.e., the Audenaert-Fannes inequality. Our bound is local in the sense that it depends on the spectrum of σ. The states ρɛ * ( σ ) and ρ * , ɛ (σ) depend only on the geometry of the ɛ-ball and are in fact optimizers for a larger class of entropies. These include the Rényi entropy and the minimum- and maximum-entropies, providing explicit formulas for certain smoothed quantities. This allows us to obtain local continuity bounds for these quantities as well. In obtaining this bound, we first derive a more general result which may be of independent interest, namely, a necessary and sufficient condition under which a state maximizes a concave and Gâteaux-differentiable function in an ɛ-ball around a given state σ. Examples of such a function include the von Neumann entropy and the conditional entropy of bipartite states. Our proofs employ tools from the theory of convex optimization under non-differentiable constraints, in particular Fermat's rule, and majorization theory.

Entropy-Based Registration of Point Clouds Using Terrestrial Laser Scanning and Smartphone GPS.

PubMed

Chen, Maolin; Wang, Siying; Wang, Mingwei; Wan, Youchuan; He, Peipei

2017-01-20

Automatic registration of terrestrial laser scanning point clouds is a crucial but unresolved topic that is of great interest in many domains. This study combines terrestrial laser scanner with a smartphone for the coarse registration of leveled point clouds with small roll and pitch angles and height differences, which is a novel sensor combination mode for terrestrial laser scanning. The approximate distance between two neighboring scan positions is firstly calculated with smartphone GPS coordinates. Then, 2D distribution entropy is used to measure the distribution coherence between the two scans and search for the optimal initial transformation parameters. To this end, we propose a method called Iterative Minimum Entropy (IME) to correct initial transformation parameters based on two criteria: the difference between the average and minimum entropy and the deviation from the minimum entropy to the expected entropy. Finally, the presented method is evaluated using two data sets that contain tens of millions of points from panoramic and non-panoramic, vegetation-dominated and building-dominated cases and can achieve high accuracy and efficiency.

Estimating Fluctuating Pressures From Distorted Measurements

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Leondes, Cornelius T.

1994-01-01

Two algorithms extract estimates of time-dependent input (upstream) pressures from outputs of pressure sensors located at downstream ends of pneumatic tubes. Effect deconvolutions that account for distoring effects of tube upon pressure signal. Distortion of pressure measurements by pneumatic tubes also discussed in "Distortion of Pressure Signals in Pneumatic Tubes," (ARC-12868). Varying input pressure estimated from measured time-varying output pressure by one of two deconvolution algorithms that take account of measurement noise. Algorithms based on minimum-covariance (Kalman filtering) theory.

Least-squares deconvolution of evoked potentials and sequence optimization for multiple stimuli under low-jitter conditions.

PubMed

Bardy, Fabrice; Dillon, Harvey; Van Dun, Bram

2014-04-01

Rapid presentation of stimuli in an evoked response paradigm can lead to overlap of multiple responses and consequently difficulties interpreting waveform morphology. This paper presents a deconvolution method allowing overlapping multiple responses to be disentangled. The deconvolution technique uses a least-squared error approach. A methodology is proposed to optimize the stimulus sequence associated with the deconvolution technique under low-jitter conditions. It controls the condition number of the matrices involved in recovering the responses. Simulations were performed using the proposed deconvolution technique. Multiple overlapping responses can be recovered perfectly in noiseless conditions. In the presence of noise, the amount of error introduced by the technique can be controlled a priori by the condition number of the matrix associated with the used stimulus sequence. The simulation results indicate the need for a minimum amount of jitter, as well as a sufficient number of overlap combinations to obtain optimum results. An aperiodic model is recommended to improve reconstruction. We propose a deconvolution technique allowing multiple overlapping responses to be extracted and a method of choosing the stimulus sequence optimal for response recovery. This technique may allow audiologists, psychologists, and electrophysiologists to optimize their experimental designs involving rapidly presented stimuli, and to recover evoked overlapping responses. Copyright © 2013 International Federation of Clinical Neurophysiology. All rights reserved.

The Conditional Entropy Power Inequality for Bosonic Quantum Systems

NASA Astrophysics Data System (ADS)

De Palma, Giacomo; Trevisan, Dario

2018-06-01

We prove the conditional Entropy Power Inequality for Gaussian quantum systems. This fundamental inequality determines the minimum quantum conditional von Neumann entropy of the output of the beam-splitter or of the squeezing among all the input states where the two inputs are conditionally independent given the memory and have given quantum conditional entropies. We also prove that, for any couple of values of the quantum conditional entropies of the two inputs, the minimum of the quantum conditional entropy of the output given by the conditional Entropy Power Inequality is asymptotically achieved by a suitable sequence of quantum Gaussian input states. Our proof of the conditional Entropy Power Inequality is based on a new Stam inequality for the quantum conditional Fisher information and on the determination of the universal asymptotic behaviour of the quantum conditional entropy under the heat semigroup evolution. The beam-splitter and the squeezing are the central elements of quantum optics, and can model the attenuation, the amplification and the noise of electromagnetic signals. This conditional Entropy Power Inequality will have a strong impact in quantum information and quantum cryptography. Among its many possible applications there is the proof of a new uncertainty relation for the conditional Wehrl entropy.

The Conditional Entropy Power Inequality for Bosonic Quantum Systems

NASA Astrophysics Data System (ADS)

De Palma, Giacomo; Trevisan, Dario

2018-01-01

We prove the conditional Entropy Power Inequality for Gaussian quantum systems. This fundamental inequality determines the minimum quantum conditional von Neumann entropy of the output of the beam-splitter or of the squeezing among all the input states where the two inputs are conditionally independent given the memory and have given quantum conditional entropies. We also prove that, for any couple of values of the quantum conditional entropies of the two inputs, the minimum of the quantum conditional entropy of the output given by the conditional Entropy Power Inequality is asymptotically achieved by a suitable sequence of quantum Gaussian input states. Our proof of the conditional Entropy Power Inequality is based on a new Stam inequality for the quantum conditional Fisher information and on the determination of the universal asymptotic behaviour of the quantum conditional entropy under the heat semigroup evolution. The beam-splitter and the squeezing are the central elements of quantum optics, and can model the attenuation, the amplification and the noise of electromagnetic signals. This conditional Entropy Power Inequality will have a strong impact in quantum information and quantum cryptography. Among its many possible applications there is the proof of a new uncertainty relation for the conditional Wehrl entropy.

Determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution

NASA Technical Reports Server (NTRS)

Ioup, George E.; Ioup, Juliette W.

1991-01-01

The final report for work on the determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution is presented. Papers and theses prepared during the research report period are included. Among all the research results reported, note should be made of the specific investigation of the determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution. A methodology was developed to determine design and operation parameters for error minimization when deconvolution is included in data analysis. An error surface is plotted versus the signal-to-noise ratio (SNR) and all parameters of interest. Instrumental characteristics will determine a curve in this space. The SNR and parameter values which give the projection from the curve to the surface, corresponding to the smallest value for the error, are the optimum values. These values are constrained by the curve and so will not necessarily correspond to an absolute minimum in the error surface.

Image restoration and superresolution as probes of small scale far-IR structure in star forming regions

NASA Technical Reports Server (NTRS)

Lester, D. F.; Harvey, P. M.; Joy, M.; Ellis, H. B., Jr.

1986-01-01

Far-infrared continuum studies from the Kuiper Airborne Observatory are described that are designed to fully exploit the small-scale spatial information that this facility can provide. This work gives the clearest picture to data on the structure of galactic and extragalactic star forming regions in the far infrared. Work is presently being done with slit scans taken simultaneously at 50 and 100 microns, yielding one-dimensional data. Scans of sources in different directions have been used to get certain information on two dimensional structure. Planned work with linear arrays will allow us to generalize our techniques to two dimensional image restoration. For faint sources, spatial information at the diffraction limit of the telescope is obtained, while for brighter sources, nonlinear deconvolution techniques have allowed us to improve over the diffraction limit by as much as a factor of four. Information on the details of the color temperature distribution is derived as well. This is made possible by the accuracy with which the instrumental point-source profile (PSP) is determined at both wavelengths. While these two PSPs are different, data at different wavelengths can be compared by proper spatial filtering. Considerable effort has been devoted to implementing deconvolution algorithms. Nonlinear deconvolution methods offer the potential of superresolution -- that is, inference of power at spatial frequencies that exceed D lambda. This potential is made possible by the implicit assumption by the algorithm of positivity of the deconvolved data, a universally justifiable constraint for photon processes. We have tested two nonlinear deconvolution algorithms on our data; the Richardson-Lucy (R-L) method and the Maximum Entropy Method (MEM). The limits of image deconvolution techniques for achieving spatial resolution are addressed.

Joint Entropy for Space and Spatial Frequency Domains Estimated from Psychometric Functions of Achromatic Discrimination

PubMed Central

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised. PMID:24466158

Joint entropy for space and spatial frequency domains estimated from psychometric functions of achromatic discrimination.

PubMed

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised.

[Specific features in realization of the principle of minimum energy dissipation during individual development].

PubMed

Zotin, A A

2012-01-01

Realization of the principle of minimum energy dissipation (Prigogine's theorem) during individual development has been analyzed. This analysis has suggested the following reformulation of this principle for living objects: when environmental conditions are constant, the living system evolves to a current steady state in such a way that the difference between entropy production and entropy flow (psi(u) function) is positive and constantly decreases near the steady state, approaching zero. In turn, the current steady state tends to a final steady state in such a way that the difference between the specific entropy productions in an organism and its environment tends to be minimal. In general, individual development completely agrees with the law of entropy increase (second law of thermodynamics).

Application of digital image processing techniques to astronomical imagery, 1979

NASA Technical Reports Server (NTRS)

Lorre, J. J.

1979-01-01

Several areas of applications of image processing to astronomy were identified and discussed. These areas include: (1) deconvolution for atmospheric seeing compensation; a comparison between maximum entropy and conventional Wiener algorithms; (2) polarization in galaxies from photographic plates; (3) time changes in M87 and methods of displaying these changes; (4) comparing emission line images in planetary nebulae; and (5) log intensity, hue saturation intensity, and principal component color enhancements of M82. Examples are presented of these techniques applied to a variety of objects.

Entropy considerations applied to shock unsteadiness in hypersonic inlets

NASA Astrophysics Data System (ADS)

Bussey, Gillian Mary Harding

The stability of curved or rectangular shocks in hypersonic inlets in response to flow perturbations can be determined analytically from the principle of minimum entropy. Unsteady shock wave motion can have a significant effect on the flow in a hypersonic inlet or combustor. According to the principle of minimum entropy, a stable thermodynamic state is one with the lowest entropy gain. A model based on piston theory and its limits has been developed for applying the principle of minimum entropy to quasi-steady flow. Relations are derived for analyzing the time-averaged entropy gain flux across a shock for quasi-steady perturbations in atmospheric conditions and angle as a perturbation in entropy gain flux from the steady state. Initial results from sweeping a wedge at Mach 10 through several degrees in AEDC's Tunnel 9 indicates the bow shock becomes unsteady near the predicted normal Mach number. Several curved shocks of varying curvature are compared to a straight shock with the same mean normal Mach number, pressure ratio, or temperature ratio. The present work provides analysis and guidelines for designing an inlet robust to off- design flight or perturbations in flow conditions an inlet is likely to face. It also suggests that inlets with curved shocks are less robust to off-design flight than those with straight shocks such as rectangular inlets. Relations for evaluating entropy perturbations for highly unsteady flow across a shock and limits on their use were also developed. The normal Mach number at which a shock could be stable to high frequency upstream perturbations increases as the speed of the shock motion increases and slightly decreases as the perturbation size increases. The present work advances the principle of minimum entropy theory by providing additional validity for using the theory for time-varying flows and applying it to shocks, specifically those in inlets. While this analytic tool is applied in the present work for evaluating the stability of shocks in hypersonic inlets, it can be used for an arbitrary application with a shock.

Minimum entropy density method for the time series analysis

NASA Astrophysics Data System (ADS)

Lee, Jeong Won; Park, Joongwoo Brian; Jo, Hang-Hyun; Yang, Jae-Suk; Moon, Hie-Tae

2009-01-01

The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.

Minimum and Maximum Entropy Distributions for Binary Systems with Known Means and Pairwise Correlations

DTIC Science & Technology

2017-08-21

distributions, and we discuss some applications for engineered and biological information transmission systems. Keywords: information theory; minimum...of its interpretation as a measure of the amount of information communicable by a neural system to groups of downstream neurons. Previous authors...of the maximum entropy approach. Our results also have relevance for engineered information transmission systems. We show that empirically measured

Comment on: The cancer Warburg effect may be a testable example of the minimum entropy production rate principle.

PubMed

Sadeghi Ghuchani, Mostafa

2018-02-08

This comment argues against the view that cancer cells produce less entropy than normal cells as stated in a recent paper by Marín and Sabater. The basic principle of estimation of entropy production rate in a living cell is discussed, emphasizing the fact that entropy production depends on both the amount of heat exchange during the metabolism and the entropy difference between products and substrates.

Comment on: The cancer Warburg effect may be a testable example of the minimum entropy production rate principle

NASA Astrophysics Data System (ADS)

Sadeghi Ghuchani, Mostafa

2018-03-01

This comment argues against the view that cancer cells produce less entropy than normal cells as stated in a recent paper by Marín and Sabater. The basic principle of estimation of entropy production rate in a living cell is discussed, emphasizing the fact that entropy production depends on both the amount of heat exchange during the metabolism and the entropy difference between products and substrates.

Thyrotropin secretion in mild and severe primary hypothyroidism is distinguished by amplified burst mass and Basal secretion with increased spikiness and approximate entropy.

PubMed

Roelfsema, Ferdinand; Pereira, Alberto M; Adriaanse, Ria; Endert, Erik; Fliers, Eric; Romijn, Johannes A; Veldhuis, Johannes D

2010-02-01

Twenty-four-hour TSH secretion profiles in primary hypothyroidism have been analyzed with methods no longer in use. The insights afforded by earlier methods are limited. We studied TSH secretion in patients with primary hypothyroidism (eight patients with severe and eight patients with mild hypothyroidism) with up-to-date analytical tools and compared the results with outcomes in 38 healthy controls. Patients and controls underwent a 24-h study with 10-min blood sampling. TSH data were analyzed with a newly developed automated deconvolution program, approximate entropy, spikiness assessment, and cosinor regression. Both basal and pulsatile TSH secretion rates were increased in hypothyroid patients, the latter by increased burst mass with unchanged frequency. Secretory regularity (approximate entropy) was diminished, and spikiness was increased only in patients with severe hypothyroidism. A diurnal TSH rhythm was present in all but two patients, although with an earlier acrophase in severe hypothyroidism. The estimated slow component of the TSH half-life was shortened in all patients. Increased TSH concentrations in hypothyroidism are mediated by amplification of basal secretion and burst size. Secretory abnormalities quantitated by approximate entropy and spikiness were only present in patients with severe disease and thus are possibly related to the increased thyrotrope cell mass.

Viscous regularization of the full set of nonequilibrium-diffusion Grey Radiation-Hydrodynamic equations

DOE PAGES

Delchini, Marc O.; Ragusa, Jean C.; Ferguson, Jim

2017-02-17

A viscous regularization technique, based on the local entropy residual, was proposed by Delchini et al. (2015) to stabilize the nonequilibrium-diffusion Grey Radiation-Hydrodynamic equations using an artificial viscosity technique. This viscous regularization is modulated by the local entropy production and is consistent with the entropy minimum principle. However, Delchini et al. (2015) only based their work on the hyperbolic parts of the Grey Radiation-Hydrodynamic equations and thus omitted the relaxation and diffusion terms present in the material energy and radiation energy equations. Here in this paper, we extend the theoretical grounds for the method and derive an entropy minimum principlemore » for the full set of nonequilibrium-diffusion Grey Radiation-Hydrodynamic equations. This further strengthens the applicability of the entropy viscosity method as a stabilization technique for radiation-hydrodynamic shock simulations. Radiative shock calculations using constant and temperature-dependent opacities are compared against semi-analytical reference solutions, and we present a procedure to perform spatial convergence studies of such simulations.« less

Sinusoidal synthesis based adaptive tracking for rotating machinery fault detection

NASA Astrophysics Data System (ADS)

Li, Gang; McDonald, Geoff L.; Zhao, Qing

2017-01-01

This paper presents a novel Sinusoidal Synthesis Based Adaptive Tracking (SSBAT) technique for vibration-based rotating machinery fault detection. The proposed SSBAT algorithm is an adaptive time series technique that makes use of both frequency and time domain information of vibration signals. Such information is incorporated in a time varying dynamic model. Signal tracking is then realized by applying adaptive sinusoidal synthesis to the vibration signal. A modified Least-Squares (LS) method is adopted to estimate the model parameters. In addition to tracking, the proposed vibration synthesis model is mainly used as a linear time-varying predictor. The health condition of the rotating machine is monitored by checking the residual between the predicted and measured signal. The SSBAT method takes advantage of the sinusoidal nature of vibration signals and transfers the nonlinear problem into a linear adaptive problem in the time domain based on a state-space realization. It has low computation burden and does not need a priori knowledge of the machine under the no-fault condition which makes the algorithm ideal for on-line fault detection. The method is validated using both numerical simulation and practical application data. Meanwhile, the fault detection results are compared with the commonly adopted autoregressive (AR) and autoregressive Minimum Entropy Deconvolution (ARMED) method to verify the feasibility and performance of the SSBAT method.

Processing strategy for water-gun seismic data from the Gulf of Mexico

USGS Publications Warehouse

Lee, Myung W.; Hart, Patrick E.; Agena, Warren F.

2000-01-01

In order to study the regional distribution of gas hydrates and their potential relationship to a large-scale sea-fl oor failures, more than 1,300 km of near-vertical-incidence seismic profi les were acquired using a 15-in3 water gun across the upper- and middle-continental slope in the Garden Banks and Green Canyon regions of the Gulf of Mexico. Because of the highly mixed phase water-gun signature, caused mainly by a precursor of the source arriving about 18 ms ahead of the main pulse, a conventional processing scheme based on the minimum phase assumption is not suitable for this data set. A conventional processing scheme suppresses the reverberations and compresses the main pulse, but the failure to suppress precursors results in complex interference between the precursors and primary refl ections, thus obscuring true refl ections. To clearly image the subsurface without interference from the precursors, a wavelet deconvolution based on the mixedphase assumption using variable norm is attempted. This nonminimum- phase wavelet deconvolution compresses a longwave- train water-gun signature into a simple zero-phase wavelet. A second-zero-crossing predictive deconvolution followed by a wavelet deconvolution suppressed variable ghost arrivals attributed to the variable depths of receivers. The processing strategy of using wavelet deconvolution followed by a secondzero- crossing deconvolution resulted in a sharp and simple wavelet and a better defi nition of the polarity of refl ections. Also, the application of dip moveout correction enhanced lateral resolution of refl ections and substantially suppressed coherent noise.

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

Giovannetti, Vittorio; Maccone, Lorenzo; Shapiro, Jeffrey H.

The minimum Renyi and Wehrl output entropies are found for bosonic channels in which the signal photons are either randomly displaced by a Gaussian distribution (classical-noise channel), or coupled to a thermal environment through lossy propagation (thermal-noise channel). It is shown that the Renyi output entropies of integer orders z{>=}2 and the Wehrl output entropy are minimized when the channel input is a coherent state.

Maximum Kolmogorov-Sinai Entropy Versus Minimum Mixing Time in Markov Chains

NASA Astrophysics Data System (ADS)

Mihelich, M.; Dubrulle, B.; Paillard, D.; Kral, Q.; Faranda, D.

2018-01-01

We establish a link between the maximization of Kolmogorov Sinai entropy (KSE) and the minimization of the mixing time for general Markov chains. Since the maximisation of KSE is analytical and easier to compute in general than mixing time, this link provides a new faster method to approximate the minimum mixing time dynamics. It could be interesting in computer sciences and statistical physics, for computations that use random walks on graphs that can be represented as Markov chains.

Free Energy in Introductory Physics

NASA Astrophysics Data System (ADS)

Prentis, Jeffrey J.; Obsniuk, Michael J.

2016-02-01

Energy and entropy are two of the most important concepts in science. For all natural processes where a system exchanges energy with its environment, the energy of the system tends to decrease and the entropy of the system tends to increase. Free energy is the special concept that specifies how to balance the opposing tendencies to minimize energy and maximize entropy. There are many pedagogical articles on energy and entropy. Here we present a simple model to illustrate the concept of free energy and the principle of minimum free energy.

Force-Time Entropy of Isometric Impulse.

PubMed

Hsieh, Tsung-Yu; Newell, Karl M

2016-01-01

The relation between force and temporal variability in discrete impulse production has been viewed as independent (R. A. Schmidt, H. Zelaznik, B. Hawkins, J. S. Frank, & J. T. Quinn, 1979 ) or dependent on the rate of force (L. G. Carlton & K. M. Newell, 1993 ). Two experiments in an isometric single finger force task investigated the joint force-time entropy with (a) fixed time to peak force and different percentages of force level and (b) fixed percentage of force level and different times to peak force. The results showed that the peak force variability increased either with the increment of force level or through a shorter time to peak force that also reduced timing error variability. The peak force entropy and entropy of time to peak force increased on the respective dimension as the parameter conditions approached either maximum force or a minimum rate of force production. The findings show that force error and timing error are dependent but complementary when considered in the same framework with the joint force-time entropy at a minimum in the middle parameter range of discrete impulse.

Multi-GPU maximum entropy image synthesis for radio astronomy

NASA Astrophysics Data System (ADS)

Cárcamo, M.; Román, P. E.; Casassus, S.; Moral, V.; Rannou, F. R.

2018-01-01

The maximum entropy method (MEM) is a well known deconvolution technique in radio-interferometry. This method solves a non-linear optimization problem with an entropy regularization term. Other heuristics such as CLEAN are faster but highly user dependent. Nevertheless, MEM has the following advantages: it is unsupervised, it has a statistical basis, it has a better resolution and better image quality under certain conditions. This work presents a high performance GPU version of non-gridding MEM, which is tested using real and simulated data. We propose a single-GPU and a multi-GPU implementation for single and multi-spectral data, respectively. We also make use of the Peer-to-Peer and Unified Virtual Addressing features of newer GPUs which allows to exploit transparently and efficiently multiple GPUs. Several ALMA data sets are used to demonstrate the effectiveness in imaging and to evaluate GPU performance. The results show that a speedup from 1000 to 5000 times faster than a sequential version can be achieved, depending on data and image size. This allows to reconstruct the HD142527 CO(6-5) short baseline data set in 2.1 min, instead of 2.5 days that takes a sequential version on CPU.

Ratio of shear viscosity to entropy density in multifragmentation of Au + Au

NASA Astrophysics Data System (ADS)

Zhou, C. L.; Ma, Y. G.; Fang, D. Q.; Li, S. X.; Zhang, G. Q.

2012-06-01

The ratio of the shear viscosity (η) to entropy density (s) for the intermediate energy heavy-ion collisions has been calculated by using the Green-Kubo method in the framework of the quantum molecular dynamics model. The theoretical curve of η/s as a function of the incident energy for the head-on Au + Au collisions displays that a minimum region of η/s has been approached at higher incident energies, where the minimum η/s value is about 7 times Kovtun-Son-Starinets (KSS) bound (1/4π). We argue that the onset of minimum η/s region at higher incident energies corresponds to the nuclear liquid gas phase transition in nuclear multifragmentation.

Quantum entropy and uncertainty for two-mode squeezed, coherent and intelligent spin states

NASA Technical Reports Server (NTRS)

Aragone, C.; Mundarain, D.

1993-01-01

We compute the quantum entropy for monomode and two-mode systems set in squeezed states. Thereafter, the quantum entropy is also calculated for angular momentum algebra when the system is either in a coherent or in an intelligent spin state. These values are compared with the corresponding values of the respective uncertainties. In general, quantum entropies and uncertainties have the same minimum and maximum points. However, for coherent and intelligent spin states, it is found that some minima for the quantum entropy turn out to be uncertainty maxima. We feel that the quantum entropy we use provides the right answer, since it is given in an essentially unique way.

Numerical estimation of the relative entropy of entanglement

NASA Astrophysics Data System (ADS)

Zinchenko, Yuriy; Friedland, Shmuel; Gour, Gilad

2010-11-01

We propose a practical algorithm for the calculation of the relative entropy of entanglement (REE), defined as the minimum relative entropy between a state and the set of states with positive partial transpose. Our algorithm is based on a practical semidefinite cutting plane approach. In low dimensions the implementation of the algorithm in matlab provides an estimation for the REE with an absolute error smaller than 10-3.

Fast online deconvolution of calcium imaging data

PubMed Central

Zhou, Pengcheng; Paninski, Liam

2017-01-01

Fluorescent calcium indicators are a popular means for observing the spiking activity of large neuronal populations, but extracting the activity of each neuron from raw fluorescence calcium imaging data is a nontrivial problem. We present a fast online active set method to solve this sparse non-negative deconvolution problem. Importantly, the algorithm 3progresses through each time series sequentially from beginning to end, thus enabling real-time online estimation of neural activity during the imaging session. Our algorithm is a generalization of the pool adjacent violators algorithm (PAVA) for isotonic regression and inherits its linear-time computational complexity. We gain remarkable increases in processing speed: more than one order of magnitude compared to currently employed state of the art convex solvers relying on interior point methods. Unlike these approaches, our method can exploit warm starts; therefore optimizing model hyperparameters only requires a handful of passes through the data. A minor modification can further improve the quality of activity inference by imposing a constraint on the minimum spike size. The algorithm enables real-time simultaneous deconvolution of O(105) traces of whole-brain larval zebrafish imaging data on a laptop. PMID:28291787

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

Giovannetti, Vittorio; Lloyd, Seth; Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139

The Amosov-Holevo-Werner conjecture implies the additivity of the minimum Renyi entropies at the output of a channel. The conjecture is proven true for all Renyi entropies of integer order greater than two in a class of Gaussian bosonic channel where the input signal is randomly displaced or where it is coupled linearly to an external environment.

Aeroacoustic and aerodynamic applications of the theory of nonequilibrium thermodynamics

NASA Technical Reports Server (NTRS)

Horne, W. Clifton; Smith, Charles A.; Karamcheti, Krishnamurty

1991-01-01

Recent developments in the field of nonequilibrium thermodynamics associated with viscous flows are examined and related to developments to the understanding of specific phenomena in aerodynamics and aeroacoustics. A key element of the nonequilibrium theory is the principle of minimum entropy production rate for steady dissipative processes near equilibrium, and variational calculus is used to apply this principle to several examples of viscous flow. A review of nonequilibrium thermodynamics and its role in fluid motion are presented. Several formulations are presented of the local entropy production rate and the local energy dissipation rate, two quantities that are of central importance to the theory. These expressions and the principle of minimum entropy production rate for steady viscous flows are used to identify parallel-wall channel flow and irrotational flow as having minimally dissipative velocity distributions. Features of irrotational, steady, viscous flow near an airfoil, such as the effect of trailing-edge radius on circulation, are also found to be compatible with the minimum principle. Finally, the minimum principle is used to interpret the stability of infinitesimal and finite amplitude disturbances in an initially laminar, parallel shear flow, with results that are consistent with experiment and linearized hydrodynamic stability theory. These results suggest that a thermodynamic approach may be useful in unifying the understanding of many diverse phenomena in aerodynamics and aeroacoustics.

Absolute Equilibrium Entropy

NASA Technical Reports Server (NTRS)

Shebalin, John V.

1997-01-01

The entropy associated with absolute equilibrium ensemble theories of ideal, homogeneous, fluid and magneto-fluid turbulence is discussed and the three-dimensional fluid case is examined in detail. A sigma-function is defined, whose minimum value with respect to global parameters is the entropy. A comparison is made between the use of global functions sigma and phase functions H (associated with the development of various H-theorems of ideal turbulence). It is shown that the two approaches are complimentary though conceptually different: H-theorems show that an isolated system tends to equilibrium while sigma-functions allow the demonstration that entropy never decreases when two previously isolated systems are combined. This provides a more complete picture of entropy in the statistical mechanics of ideal fluids.

Efficient optimization of the quantum relative entropy

NASA Astrophysics Data System (ADS)

Fawzi, Hamza; Fawzi, Omar

2018-04-01

Many quantum information measures can be written as an optimization of the quantum relative entropy between sets of states. For example, the relative entropy of entanglement of a state is the minimum relative entropy to the set of separable states. The various capacities of quantum channels can also be written in this way. We propose a unified framework to numerically compute these quantities using off-the-shelf semidefinite programming solvers, exploiting the approximation method proposed in Fawzi, Saunderson and Parrilo (2017 arXiv: 1705.00812). As a notable application, this method allows us to provide numerical counterexamples for a proposed lower bound on the quantum conditional mutual information in terms of the relative entropy of recovery.

[Study on once sampling quantitation based on information entropy of ISSR amplified bands of Houttuynia cordata].

PubMed

Wang, Haiqin; Liu, Wenlong; He, Fuyuan; Chen, Zuohong; Zhang, Xili; Xie, Xianggui; Zeng, Jiaoli; Duan, Xiaopeng

2012-02-01

To explore the once sampling quantitation of Houttuynia cordata through its DNA polymorphic bands that carried information entropy, from other form that the expression of traditional Chinese medicine polymorphism, genetic polymorphism, of traditional Chinese medicine. The technique of inter simple sequence repeat (ISSR) was applied to analyze genetic polymorphism of H. cordata samples from the same GAP producing area, the DNA genetic bands were transformed its into the information entropy, and the minimum once sampling quantitation with the mathematical mode was measured. One hundred and thirty-four DNA bands were obtained by using 9 screened ISSR primers to amplify from 46 strains DNA samples of H. cordata from the same GAP, the information entropy was H=0.365 6-0.978 6, and RSD was 14.75%. The once sampling quantitation was W=11.22 kg (863 strains). The "once minimum sampling quantitation" were calculated from the angle of the genetic polymorphism of H. cordata, and a great differences between this volume and the amount from the angle of fingerprint were found.

Rényi-Fisher entropy product as a marker of topological phase transitions

NASA Astrophysics Data System (ADS)

Bolívar, J. C.; Nagy, Ágnes; Romera, Elvira

2018-05-01

The combined Rényi-Fisher entropy product of electrons plus holes displays a minimum at the charge neutrality points. The Stam-Rényi difference and the Stam-Rényi uncertainty product of the electrons plus holes, show maxima at the charge neutrality points. Topological quantum numbers capable of detecting the topological insulator and the band insulator phases, are defined. Upper and lower bounds for the position and momentum space Rényi-Fisher entropy products are derived.

Statistical mechanical theory for steady state systems. VI. Variational principles

NASA Astrophysics Data System (ADS)

Attard, Phil

2006-12-01

Several variational principles that have been proposed for nonequilibrium systems are analyzed. These include the principle of minimum rate of entropy production due to Prigogine [Introduction to Thermodynamics of Irreversible Processes (Interscience, New York, 1967)], the principle of maximum rate of entropy production, which is common on the internet and in the natural sciences, two principles of minimum dissipation due to Onsager [Phys. Rev. 37, 405 (1931)] and to Onsager and Machlup [Phys. Rev. 91, 1505 (1953)], and the principle of maximum second entropy due to Attard [J. Chem.. Phys. 122, 154101 (2005); Phys. Chem. Chem. Phys. 8, 3585 (2006)]. The approaches of Onsager and Attard are argued to be the only viable theories. These two are related, although their physical interpretation and mathematical approximations differ. A numerical comparison with computer simulation results indicates that Attard's expression is the only accurate theory. The implications for the Langevin and other stochastic differential equations are discussed.

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

Chen, Pisin; Hsin, Po-Shen; Niu, Yuezhen, E-mail: pisinchen@phys.ntu.edu.tw, E-mail: r01222031@ntu.edu.tw, E-mail: yuezhenniu@gmail.com

We investigate the entropy evolution in the early universe by computing the change of the entanglement entropy in Freedmann-Robertson-Walker quantum cosmology in the presence of particle horizon. The matter is modeled by a Chaplygin gas so as to provide a smooth interpolation between inflationary and radiation epochs, rendering the evolution of entropy from early time to late time trackable. We found that soon after the onset of the inflation, the total entanglement entropy rapidly decreases to a minimum. It then rises monotonically in the remainder of the inflation epoch as well as the radiation epoch. Our result is in qualitativemore » agreement with the area law of Ryu and Takayanagi including the logarithmic correction. We comment on the possible implication of our finding to the cosmological entropy problem.« less

Entropy of adsorption of mixed surfactants from solutions onto the air/water interface

USGS Publications Warehouse

Chen, L.-W.; Chen, J.-H.; Zhou, N.-F.

1995-01-01

The partial molar entropy change for mixed surfactant molecules adsorbed from solution at the air/water interface has been investigated by surface thermodynamics based upon the experimental surface tension isotherms at various temperatures. Results for different surfactant mixtures of sodium dodecyl sulfate and sodium tetradecyl sulfate, decylpyridinium chloride and sodium alkylsulfonates have shown that the partial molar entropy changes for adsorption of the mixed surfactants were generally negative and decreased with increasing adsorption to a minimum near the maximum adsorption and then increased abruptly. The entropy decrease can be explained by the adsorption-orientation of surfactant molecules in the adsorbed monolayer and the abrupt entropy increase at the maximum adsorption is possible due to the strong repulsion between the adsorbed molecules.

Bimodal behavior of post-measured entropy and one-way quantum deficit for two-qubit X states

NASA Astrophysics Data System (ADS)

Yurischev, Mikhail A.

2018-01-01

A method for calculating the one-way quantum deficit is developed. It involves a careful study of post-measured entropy shapes. We discovered that in some regions of X-state space the post-measured entropy \\tilde{S} as a function of measurement angle θ \\in [0,π /2] exhibits a bimodal behavior inside the open interval (0,π /2), i.e., it has two interior extrema: one minimum and one maximum. Furthermore, cases are found when the interior minimum of such a bimodal function \\tilde{S}(θ ) is less than that one at the endpoint θ =0 or π /2. This leads to the formation of a boundary between the phases of one-way quantum deficit via finite jumps of optimal measured angle from the endpoint to the interior minimum. Phase diagram is built up for a two-parameter family of X states. The subregions with variable optimal measured angle are around 1% of the total region, with their relative linear sizes achieving 17.5%, and the fidelity between the states of those subregions can be reduced to F=0.968. In addition, a correction to the one-way deficit due to the interior minimum can achieve 2.3%. Such conditions are favorable to detect the subregions with variable optimal measured angle of one-way quantum deficit in an experiment.

16QAM Blind Equalization via Maximum Entropy Density Approximation Technique and Nonlinear Lagrange Multipliers

PubMed Central

Mauda, R.; Pinchas, M.

2014-01-01

Recently a new blind equalization method was proposed for the 16QAM constellation input inspired by the maximum entropy density approximation technique with improved equalization performance compared to the maximum entropy approach, Godard's algorithm, and others. In addition, an approximated expression for the minimum mean square error (MSE) was obtained. The idea was to find those Lagrange multipliers that bring the approximated MSE to minimum. Since the derivation of the obtained MSE with respect to the Lagrange multipliers leads to a nonlinear equation for the Lagrange multipliers, the part in the MSE expression that caused the nonlinearity in the equation for the Lagrange multipliers was ignored. Thus, the obtained Lagrange multipliers were not those Lagrange multipliers that bring the approximated MSE to minimum. In this paper, we derive a new set of Lagrange multipliers based on the nonlinear expression for the Lagrange multipliers obtained from minimizing the approximated MSE with respect to the Lagrange multipliers. Simulation results indicate that for the high signal to noise ratio (SNR) case, a faster convergence rate is obtained for a channel causing a high initial intersymbol interference (ISI) while the same equalization performance is obtained for an easy channel (initial ISI low). PMID:24723813

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

Guha, Saikat; Shapiro, Jeffrey H.; Erkmen, Baris I.

Previous work on the classical information capacities of bosonic channels has established the capacity of the single-user pure-loss channel, bounded the capacity of the single-user thermal-noise channel, and bounded the capacity region of the multiple-access channel. The latter is a multiple-user scenario in which several transmitters seek to simultaneously and independently communicate to a single receiver. We study the capacity region of the bosonic broadcast channel, in which a single transmitter seeks to simultaneously and independently communicate to two different receivers. It is known that the tightest available lower bound on the capacity of the single-user thermal-noise channel is thatmore » channel's capacity if, as conjectured, the minimum von Neumann entropy at the output of a bosonic channel with additive thermal noise occurs for coherent-state inputs. Evidence in support of this minimum output entropy conjecture has been accumulated, but a rigorous proof has not been obtained. We propose a minimum output entropy conjecture that, if proved to be correct, will establish that the capacity region of the bosonic broadcast channel equals the inner bound achieved using a coherent-state encoding and optimum detection. We provide some evidence that supports this conjecture, but again a full proof is not available.« less

Nonequilibrium Thermodynamics in Biological Systems

NASA Astrophysics Data System (ADS)

Aoki, I.

2005-12-01

1. Respiration Oxygen-uptake by respiration in organisms decomposes macromolecules such as carbohydrate, protein and lipid and liberates chemical energy of high quality, which is then used to chemical reactions and motions of matter in organisms to support lively order in structure and function in organisms. Finally, this chemical energy becomes heat energy of low quality and is discarded to the outside (dissipation function). Accompanying this heat energy, entropy production which inevitably occurs by irreversibility also is discarded to the outside. Dissipation function and entropy production are estimated from data of respiration. 2. Human body From the observed data of respiration (oxygen absorption), the entropy production in human body can be estimated. Entropy production from 0 to 75 years old human has been obtained, and extrapolated to fertilized egg (beginning of human life) and to 120 years old (maximum period of human life). Entropy production show characteristic behavior in human life span : early rapid increase in short growing phase and later slow decrease in long aging phase. It is proposed that this tendency is ubiquitous and constitutes a Principle of Organization in complex biotic systems. 3. Ecological communities From the data of respiration of eighteen aquatic communities, specific (i.e. per biomass) entropy productions are obtained. They show two phase character with respect to trophic diversity : early increase and later decrease with the increase of trophic diversity. The trophic diversity in these aquatic ecosystems is shown to be positively correlated with the degree of eutrophication, and the degree of eutrophication is an "arrow of time" in the hierarchy of aquatic ecosystems. Hence specific entropy production has the two phase: early increase and later decrease with time. 4. Entropy principle for living systems The Second Law of Thermodynamics has been expressed as follows. 1) In isolated systems, entropy increases with time and approaches to a maximum value. This is well-known classical Clausius principle. 2) In open systems near equilibrium entropy production always decreases with time approaching a minimum stationary level. This is the minimum entropy production principle by Prigogine. These two principle are established ones. However, living systems are not isolated and not near to equilibrium. Hence, these two principles can not be applied to living systems. What is entropy principle for living systems? Answer: Entropy production in living systems consists of multi-stages with time: early increasing, later decreasing and/or intermediate stages. This tendency is supported by various living systems.

LES-Modeling of a Partially Premixed Flame using a Deconvolution Turbulence Closure

NASA Astrophysics Data System (ADS)

Wang, Qing; Wu, Hao; Ihme, Matthias

2015-11-01

The modeling of the turbulence/chemistry interaction in partially premixed and multi-stream combustion remains an outstanding issue. By extending a recently developed constrained minimum mean-square error deconvolution (CMMSED) method, to objective of this work is to develop a source-term closure for turbulent multi-stream combustion. In this method, the chemical source term is obtained from a three-stream flamelet model, and CMMSED is used as closure model, thereby eliminating the need for presumed PDF-modeling. The model is applied to LES of a piloted turbulent jet flame with inhomogeneous inlets, and simulation results are compared with experiments. Comparisons with presumed PDF-methods are performed, and issues regarding resolution and conservation of the CMMSED method are examined. The author would like to acknowledge the support of funding from Stanford Graduate Fellowship.

Increased temperature and entropy production in cancer: the role of anti-inflammatory drugs.

PubMed

Pitt, Michael A

2015-02-01

Some cancers have been shown to have a higher temperature than surrounding normal tissue. This higher temperature is due to heat generated internally in the cancer. The higher temperature of cancer (compared to surrounding tissue) enables a thermodynamic analysis to be carried out. Here I show that there is increased entropy production in cancer compared with surrounding tissue. This is termed excess entropy production. The excess entropy production is expressed in terms of heat flow from the cancer to surrounding tissue and enzymic reactions in the cancer and surrounding tissue. The excess entropy production in cancer drives it away from the stationary state that is characterised by minimum entropy production. Treatments that reduce inflammation (and therefore temperature) should drive a cancer towards the stationary state. Anti-inflammatory agents, such as aspirin, other non-steroidal anti-inflammatory drugs, corticosteroids and also thyroxine analogues have been shown (using various criteria) to reduce the progress of cancer.

Tensor distribution function

NASA Astrophysics Data System (ADS)

Leow, Alex D.; Zhu, Siwei

2008-03-01

Diffusion weighted MR imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitizing gradients along a minimum of 6 directions, second-order tensors (represetnted by 3-by-3 positive definiite matrices) can be computed to model dominant diffusion processes. However, it has been shown that conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g. crossing fiber tracts. More recently, High Angular Resolution Diffusion Imaging (HARDI) seeks to address this issue by employing more than 6 gradient directions. To account for fiber crossing when analyzing HARDI data, several methodologies have been introduced. For example, q-ball imaging was proposed to approximate Orientation Diffusion Function (ODF). Similarly, the PAS method seeks to reslove the angular structure of displacement probability functions using the maximum entropy principle. Alternatively, deconvolution methods extract multiple fiber tracts by computing fiber orientations using a pre-specified single fiber response function. In this study, we introduce Tensor Distribution Function (TDF), a probability function defined on the space of symmetric and positive definite matrices. Using calculus of variations, we solve for the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, ODF can easily be computed by analytical integration of the resulting displacement probability function. Moreover, principle fiber directions can also be directly derived from the TDF.

An X-ray image of the violent interstellar medium in 30 Doradus

NASA Technical Reports Server (NTRS)

Wang, Q.; Helfand, D. J.

1991-01-01

A detailed analysis of the X-ray emission from the largest H II region complex in the Local Group, 30 Dor, is presented. Applying a new maximum entropy deconvolution algorithm to the Einstein Observatory data, reveals striking correlations among the X-ray, radio, and optical morphologies of the region, with X-ray-emitting bubbles filling cavities surrounded by H-alpha shells and coextensive diffuse X-ray and radio continuum emission from throughout the region. The total X-ray luminosity in the 0.16-3.5 keV band from an area within 160 pc of the central cluster R136 is about 2 x 10 to the 37th ergs/sec.

Reply to Comment on ‘The cancer Warburg effect may be a testable example of the minimum entropy production rate principle’

NASA Astrophysics Data System (ADS)

Sabater, Bartolomé; Marín, Dolores

2018-03-01

The minimum rate principle is applied to the chemical reaction in a steady-state open cell system where, under constant supply of the glucose precursor, reference to time or to glucose consumption does not affect the conclusions.

Application of a multiscale maximum entropy image restoration algorithm to HXMT observations

NASA Astrophysics Data System (ADS)

Guan, Ju; Song, Li-Ming; Huo, Zhuo-Xi

2016-08-01

This paper introduces a multiscale maximum entropy (MSME) algorithm for image restoration of the Hard X-ray Modulation Telescope (HXMT), which is a collimated scan X-ray satellite mainly devoted to a sensitive all-sky survey and pointed observations in the 1-250 keV range. The novelty of the MSME method is to use wavelet decomposition and multiresolution support to control noise amplification at different scales. Our work is focused on the application and modification of this method to restore diffuse sources detected by HXMT scanning observations. An improved method, the ensemble multiscale maximum entropy (EMSME) algorithm, is proposed to alleviate the problem of mode mixing exiting in MSME. Simulations have been performed on the detection of the diffuse source Cen A by HXMT in all-sky survey mode. The results show that the MSME method is adapted to the deconvolution task of HXMT for diffuse source detection and the improved method could suppress noise and improve the correlation and signal-to-noise ratio, thus proving itself a better algorithm for image restoration. Through one all-sky survey, HXMT could reach a capacity of detecting a diffuse source with maximum differential flux of 0.5 mCrab. Supported by Strategic Priority Research Program on Space Science, Chinese Academy of Sciences (XDA04010300) and National Natural Science Foundation of China (11403014)

An entropy method for induced drag minimization

NASA Technical Reports Server (NTRS)

Greene, George C.

1989-01-01

A fundamentally new approach to the aircraft minimum induced drag problem is presented. The method, a 'viscous lifting line', is based on the minimum entropy production principle and does not require the planar wake assumption. An approximate, closed form solution is obtained for several wing configurations including a comparison of wing extension, winglets, and in-plane wing sweep, with and without a constraint on wing-root bending moment. Like the classical lifting-line theory, this theory predicts that induced drag is proportional to the square of the lift coefficient and inversely proportioinal to the wing aspect ratio. Unlike the classical theory, it predicts that induced drag is Reynolds number dependent and that the optimum spanwise circulation distribution is non-elliptic.

A secure image encryption method based on dynamic harmony search (DHS) combined with chaotic map

NASA Astrophysics Data System (ADS)

Mirzaei Talarposhti, Khadijeh; Khaki Jamei, Mehrzad

2016-06-01

In recent years, there has been increasing interest in the security of digital images. This study focuses on the gray scale image encryption using dynamic harmony search (DHS). In this research, first, a chaotic map is used to create cipher images, and then the maximum entropy and minimum correlation coefficient is obtained by applying a harmony search algorithm on them. This process is divided into two steps. In the first step, the diffusion of a plain image using DHS to maximize the entropy as a fitness function will be performed. However, in the second step, a horizontal and vertical permutation will be applied on the best cipher image, which is obtained in the previous step. Additionally, DHS has been used to minimize the correlation coefficient as a fitness function in the second step. The simulation results have shown that by using the proposed method, the maximum entropy and the minimum correlation coefficient, which are approximately 7.9998 and 0.0001, respectively, have been obtained.

Quantum Entanglement and the Topological Order of Fractional Hall States

NASA Astrophysics Data System (ADS)

Rezayi, Edward

2015-03-01

Fractional quantum Hall states or, more generally, topological phases of matter defy Landau classification based on order parameter and broken symmetry. Instead they have been characterized by their topological order. Quantum information concepts, such as quantum entanglement, appear to provide the most efficient method of detecting topological order solely from the knowledge of the ground state wave function. This talk will focus on real-space bi-partitioning of quantum Hall states and will present both exact diagonalization and quantum Monte Carlo studies of topological entanglement entropy in various geometries. Results on the torus for non-contractible cuts are quite rich and, through the use of minimum entropy states, yield the modular S-matrix and hence uniquely determine the topological order, as shown in recent literature. Concrete examples of minimum entropy states from known quantum Hall wave functions and their corresponding quantum numbers, used in exact diagonalizations, will be given. In collaboration with Clare Abreu and Raul Herrera. Supported by DOE Grant DE-SC0002140.

Minimum energy dissipation required for a logically irreversible operation

NASA Astrophysics Data System (ADS)

Takeuchi, Naoki; Yoshikawa, Nobuyuki

2018-01-01

According to Landauer's principle, the minimum heat emission required for computing is linked to logical entropy, or logical reversibility. The validity of Landauer's principle has been investigated for several decades and was finally demonstrated in recent experiments by showing that the minimum heat emission is associated with the reduction in logical entropy during a logically irreversible operation. Although the relationship between minimum heat emission and logical reversibility is being revealed, it is not clear how much free energy is required to be dissipated for a logically irreversible operation. In the present study, in order to reveal the connection between logical reversibility and free energy dissipation, we numerically demonstrated logically irreversible protocols using adiabatic superconductor logic. The calculation results of work during the protocol showed that, while the minimum heat emission conforms to Landauer's principle, the free energy dissipation can be arbitrarily reduced by performing the protocol quasistatically. The above results show that logical reversibility is not associated with thermodynamic reversibility, and that heat is not only emitted from logic devices but also absorbed by logic devices. We also formulated the heat emission from adiabatic superconductor logic during a logically irreversible operation at a finite operation speed.

Prediction of pKa Values for Neutral and Basic Drugs based on Hybrid Artificial Intelligence Methods.

PubMed

Li, Mengshan; Zhang, Huaijing; Chen, Bingsheng; Wu, Yan; Guan, Lixin

2018-03-05

The pKa value of drugs is an important parameter in drug design and pharmacology. In this paper, an improved particle swarm optimization (PSO) algorithm was proposed based on the population entropy diversity. In the improved algorithm, when the population entropy was higher than the set maximum threshold, the convergence strategy was adopted; when the population entropy was lower than the set minimum threshold the divergence strategy was adopted; when the population entropy was between the maximum and minimum threshold, the self-adaptive adjustment strategy was maintained. The improved PSO algorithm was applied in the training of radial basis function artificial neural network (RBF ANN) model and the selection of molecular descriptors. A quantitative structure-activity relationship model based on RBF ANN trained by the improved PSO algorithm was proposed to predict the pKa values of 74 kinds of neutral and basic drugs and then validated by another database containing 20 molecules. The validation results showed that the model had a good prediction performance. The absolute average relative error, root mean square error, and squared correlation coefficient were 0.3105, 0.0411, and 0.9685, respectively. The model can be used as a reference for exploring other quantitative structure-activity relationships.

Reduced nocturnal ACTH-driven cortisol secretion during critical illness

PubMed Central

Boonen, Eva; Meersseman, Philippe; Vervenne, Hilke; Meyfroidt, Geert; Guïza, Fabian; Wouters, Pieter J.; Veldhuis, Johannes D.

2014-01-01

Recently, during critical illness, cortisol metabolism was found to be reduced. We hypothesize that such reduced cortisol breakdown may suppress pulsatile ACTH and cortisol secretion via feedback inhibition. To test this hypothesis, nocturnal ACTH and cortisol secretory profiles were constructed by deconvolution analysis from plasma concentration time series in 40 matched critically ill patients and eight healthy controls, excluding diseases or drugs that affect the hypothalamic-pituitary-adrenal axis. Blood was sampled every 10 min between 2100 and 0600 to quantify plasma concentrations of ACTH and (free) cortisol. Approximate entropy, an estimation of process irregularity, cross-approximate entropy, a measure of ACTH-cortisol asynchrony, and ACTH-cortisol dose-response relationships were calculated. Total and free plasma cortisol concentrations were higher at all times in patients than in controls (all P < 0.04). Pulsatile cortisol secretion was 54% lower in patients than in controls (P = 0.005), explained by reduced cortisol burst mass (P = 0.03), whereas cortisol pulse frequency (P = 0.35) and nonpulsatile cortisol secretion (P = 0.80) were unaltered. Pulsatile ACTH secretion was 31% lower in patients than in controls (P = 0.03), again explained by a lower ACTH burst mass (P = 0.02), whereas ACTH pulse frequency (P = 0.50) and nonpulsatile ACTH secretion (P = 0.80) were unchanged. ACTH-cortisol dose response estimates were similar in patients and controls. ACTH and cortisol approximate entropy were higher in patients (P ≤ 0.03), as was ACTH-cortisol cross-approximate entropy (P ≤ 0.001). We conclude that hypercortisolism during critical illness coincided with suppressed pulsatile ACTH and cortisol secretion and a normal ACTH-cortisol dose response. Increased irregularity and asynchrony of the ACTH and cortisol time series supported non-ACTH-dependent mechanisms driving hypercortisolism during critical illness. PMID:24569590

[Application of an Adaptive Inertia Weight Particle Swarm Algorithm in the Magnetic Resonance Bias Field Correction].

PubMed

Wang, Chang; Qin, Xin; Liu, Yan; Zhang, Wenchao

2016-06-01

An adaptive inertia weight particle swarm algorithm is proposed in this study to solve the local optimal problem with the method of traditional particle swarm optimization in the process of estimating magnetic resonance(MR)image bias field.An indicator measuring the degree of premature convergence was designed for the defect of traditional particle swarm optimization algorithm.The inertia weight was adjusted adaptively based on this indicator to ensure particle swarm to be optimized globally and to avoid it from falling into local optimum.The Legendre polynomial was used to fit bias field,the polynomial parameters were optimized globally,and finally the bias field was estimated and corrected.Compared to those with the improved entropy minimum algorithm,the entropy of corrected image was smaller and the estimated bias field was more accurate in this study.Then the corrected image was segmented and the segmentation accuracy obtained in this research was 10% higher than that with improved entropy minimum algorithm.This algorithm can be applied to the correction of MR image bias field.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Kim, Y.; Hwang, T.; Vose, J. M.; Martin, K. L.; Band, L. E.

2016-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Keum, J.; Coulibaly, P. D.

2017-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

The cancer Warburg effect may be a testable example of the minimum entropy production rate principle

NASA Astrophysics Data System (ADS)

Marín, Dolores; Sabater, Bartolomé

2017-04-01

Cancer cells consume more glucose by glycolytic fermentation to lactate than by respiration, a characteristic known as the Warburg effect. In contrast with the 36 moles of ATP produced by respiration, fermentation produces two moles of ATP per mole of glucose consumed, which poses a puzzle with regard to the function of the Warburg effect. The production of free energy (ΔG), enthalpy (ΔH), and entropy (ΔS) per mole linearly varies with the fraction (x) of glucose consumed by fermentation that is frequently estimated around 0.9. Hence, calculation shows that, in respect to pure respiration, the predominant fermentative metabolism decreases around 10% the production of entropy per mole of glucose consumed in cancer cells. We hypothesize that increased fermentation could allow cancer cells to accomplish the Prigogine theorem of the trend to minimize the rate of production of entropy. According to the theorem, open cellular systems near the steady state could evolve to minimize the rates of entropy production that may be reached by modified replicating cells producing entropy at a low rate. Remarkably, at CO2 concentrations above 930 ppm, glucose respiration produces less entropy than fermentation, which suggests experimental tests to validate the hypothesis of minimization of the rate of entropy production through the Warburg effect.

The cancer Warburg effect may be a testable example of the minimum entropy production rate principle.

PubMed

Marín, Dolores; Sabater, Bartolomé

2017-04-28

Cancer cells consume more glucose by glycolytic fermentation to lactate than by respiration, a characteristic known as the Warburg effect. In contrast with the 36 moles of ATP produced by respiration, fermentation produces two moles of ATP per mole of glucose consumed, which poses a puzzle with regard to the function of the Warburg effect. The production of free energy (ΔG), enthalpy (ΔH), and entropy (ΔS) per mole linearly varies with the fraction (x) of glucose consumed by fermentation that is frequently estimated around 0.9. Hence, calculation shows that, in respect to pure respiration, the predominant fermentative metabolism decreases around 10% the production of entropy per mole of glucose consumed in cancer cells. We hypothesize that increased fermentation could allow cancer cells to accomplish the Prigogine theorem of the trend to minimize the rate of production of entropy. According to the theorem, open cellular systems near the steady state could evolve to minimize the rates of entropy production that may be reached by modified replicating cells producing entropy at a low rate. Remarkably, at CO 2 concentrations above 930 ppm, glucose respiration produces less entropy than fermentation, which suggests experimental tests to validate the hypothesis of minimization of the rate of entropy production through the Warburg effect.

Minimum relative entropy distributions with a large mean are Gaussian

NASA Astrophysics Data System (ADS)

Smerlak, Matteo

2016-12-01

Entropy optimization principles are versatile tools with wide-ranging applications from statistical physics to engineering to ecology. Here we consider the following constrained problem: Given a prior probability distribution q , find the posterior distribution p minimizing the relative entropy (also known as the Kullback-Leibler divergence) with respect to q under the constraint that mean (p ) is fixed and large. We show that solutions to this problem are approximately Gaussian. We discuss two applications of this result. In the context of dissipative dynamics, the equilibrium distribution of a Brownian particle confined in a strong external field is independent of the shape of the confining potential. We also derive an H -type theorem for evolutionary dynamics: The entropy of the (standardized) distribution of fitness of a population evolving under natural selection is eventually increasing in time.

Use and validity of principles of extremum of entropy production in the study of complex systems

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

Heitor Reis, A., E-mail: ahr@uevora.pt

2014-07-15

It is shown how both the principles of extremum of entropy production, which are often used in the study of complex systems, follow from the maximization of overall system conductivities, under appropriate constraints. In this way, the maximum rate of entropy production (MEP) occurs when all the forces in the system are kept constant. On the other hand, the minimum rate of entropy production (mEP) occurs when all the currents that cross the system are kept constant. A brief discussion on the validity of the application of the mEP and MEP principles in several cases, and in particular to themore » Earth’s climate is also presented. -- Highlights: •The principles of extremum of entropy production are not first principles. •They result from the maximization of conductivities under appropriate constraints. •The conditions of their validity are set explicitly. •Some long-standing controversies are discussed and clarified.« less

Evaluation of spectral entropy to measure anaesthetic depth and antinociception in sevoflurane-anaesthetised Beagle dogs.

PubMed

Morgaz, Juan; Granados, María del Mar; Domínguez, Juan Manuel; Navarrete, Rocío; Fernández, Andrés; Galán, Alba; Muñoz, Pilar; Gómez-Villamandos, Rafael J

2011-06-01

The use of spectral entropy to determine anaesthetic depth and antinociception was evaluated in sevoflurane-anaesthetised Beagle dogs. Dogs were anaesthetised at each of five multiples of their individual minimum alveolar concentrations (MAC; 0.75, 1, 1.25, 1.5 and 1.75 MAC), and response entropy (RE), state entropy (SE), RE-SE difference, burst suppression rate (BSR) and cardiorespiratory parameters were recorded before and after a painful stimulus. RE, SE and RE-SE difference did not change significantly after the stimuli. The correlation between MAC-entropy parameters was weak, but these values increased when 1.75 MAC results were excluded from the analysis. BSR was different to zero at 1.5 and 1.75 MAC. It was concluded that RE and RE-SE differences were not adequate indicators of antinociception and SE and RE were unable to detect deep planes of anaesthesia in dogs, although they both distinguished the awake and unconscious states. Copyright © 2010 Elsevier Ltd. All rights reserved.

Entropy-based artificial viscosity stabilization for non-equilibrium Grey Radiation-Hydrodynamics

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

Delchini, Marc O., E-mail: delchinm@email.tamu.edu; Ragusa, Jean C., E-mail: jean.ragusa@tamu.edu; Morel, Jim, E-mail: jim.morel@tamu.edu

2015-09-01

The entropy viscosity method is extended to the non-equilibrium Grey Radiation-Hydrodynamic equations. The method employs a viscous regularization to stabilize the numerical solution. The artificial viscosity coefficient is modulated by the entropy production and peaks at shock locations. The added dissipative terms are consistent with the entropy minimum principle. A new functional form of the entropy residual, suitable for the Radiation-Hydrodynamic equations, is derived. We demonstrate that the viscous regularization preserves the equilibrium diffusion limit. The equations are discretized with a standard Continuous Galerkin Finite Element Method and a fully implicit temporal integrator within the MOOSE multiphysics framework. The methodmore » of manufactured solutions is employed to demonstrate second-order accuracy in both the equilibrium diffusion and streaming limits. Several typical 1-D radiation-hydrodynamic test cases with shocks (from Mach 1.05 to Mach 50) are presented to establish the ability of the technique to capture and resolve shocks.« less

New Insights into the Fractional Order Diffusion Equation Using Entropy and Kurtosis.

PubMed

Ingo, Carson; Magin, Richard L; Parrish, Todd B

2014-11-01

Fractional order derivative operators offer a concise description to model multi-scale, heterogeneous and non-local systems. Specifically, in magnetic resonance imaging, there has been recent work to apply fractional order derivatives to model the non-Gaussian diffusion signal, which is ubiquitous in the movement of water protons within biological tissue. To provide a new perspective for establishing the utility of fractional order models, we apply entropy for the case of anomalous diffusion governed by a fractional order diffusion equation generalized in space and in time. This fractional order representation, in the form of the Mittag-Leffler function, gives an entropy minimum for the integer case of Gaussian diffusion and greater values of spectral entropy for non-integer values of the space and time derivatives. Furthermore, we consider kurtosis, defined as the normalized fourth moment, as another probabilistic description of the fractional time derivative. Finally, we demonstrate the implementation of anomalous diffusion, entropy and kurtosis measurements in diffusion weighted magnetic resonance imaging in the brain of a chronic ischemic stroke patient.

External and internal guest binding of a highly charged supramolecular host in water: deconvoluting the very different thermodynamics.

PubMed

Sgarlata, Carmelo; Mugridge, Jeffrey S; Pluth, Michael D; Tiedemann, Bryan E F; Zito, Valeria; Arena, Giuseppe; Raymond, Kenneth N

2010-01-27

NMR, UV-vis, and isothermal titration calorimetry (ITC) measurements probe different aspects of competing host-guest equilibria as simple alkylammonium guest molecules interact with both the exterior (ion-association) and interior (encapsulation) of the [Ga(4)L(6)](12-) supramolecular assembly in water. Data obtained by each independent technique measure different components of the host-guest equilibria and only when analyzed together does a complete picture of the solution thermodynamics emerge. Striking differences between the internal and external guest binding are found. External binding is enthalpy driven and mainly due to attractive interactions between the guests and the exterior surface of the assembly while encapsulation is entropy driven as a result of desolvation and release of solvent molecules from the host cavity.

Reaction profiling by ultra high-pressure liquid chromatography/time-of-flight mass spectrometry in support of the synthesis of DNA-encoded libraries.

PubMed

Hargiss, Leonard O; Zipp, G Greg; Jessop, Theodore C; Sun, Xuejun; Keyes, Philip; Rawlins, David B; Liang, Zhi; Park, Kum Joo; Gu, Huizhong

2014-11-15

An ultra high-pressure liquid chromatography/mass spectrometry (UHPLC/MS) separation and analysis method has been devised for open access analysis of synthetic reactions used in the production of DNA-encoded chemical libraries. The aqueous mobile phase is 100mM hexafluoroisopropanol and 8.6mM triethylamine; the organic mobile phase is methanol. The UHPLC separation uses a C18 OST column (50mm×2.1mm×1.7μm) at 60°C, with a flow rate of 0.6mL/min. Gradient concentration is from 10 to 40% B in 1.0min, increasing to 95% B at 1.2min. Cycle time was about 5min. This method provides a detection limit of a 20-mer oligonucleotide by mass spectrometry of better than 1pmol on-column. Linear UV response for 20-mer extends from 2 to 200pmol/μL in concentration, same-day relative average deviations are less than 5% and bias (observed minus expected) is less than 10%. Deconvoluted mass spectra are generated for components in the predicted mass range using a maximum entropy algorithm. Mass accuracy of deconvoluted spectra is typically 20ppm or better for isotopomers of oligonucleotides up to 7000Da. Copyright © 2014 Elsevier B.V. All rights reserved.

Necessary conditions for the optimality of variable rate residual vector quantizers

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Barnes, Christopher F.

1993-01-01

Residual vector quantization (RVQ), or multistage VQ, as it is also called, has recently been shown to be a competitive technique for data compression. The competitive performance of RVQ reported in results from the joint optimization of variable rate encoding and RVQ direct-sum code books. In this paper, necessary conditions for the optimality of variable rate RVQ's are derived, and an iterative descent algorithm based on a Lagrangian formulation is introduced for designing RVQ's having minimum average distortion subject to an entropy constraint. Simulation results for these entropy-constrained RVQ's (EC-RVQ's) are presented for memory less Gaussian, Laplacian, and uniform sources. A Gauss-Markov source is also considered. The performance is superior to that of entropy-constrained scalar quantizers (EC-SQ's) and practical entropy-constrained vector quantizers (EC-VQ's), and is competitive with that of some of the best source coding techniques that have appeared in the literature.

[Quantitative assessment of urban ecosystem services flow based on entropy theory: A case study of Beijing, China].

PubMed

Li, Jing Xin; Yang, Li; Yang, Lei; Zhang, Chao; Huo, Zhao Min; Chen, Min Hao; Luan, Xiao Feng

2018-03-01

Quantitative evaluation of ecosystem service is a primary premise for rational resources exploitation and sustainable development. Examining ecosystem services flow provides a scientific method to quantity ecosystem services. We built an assessment indicator system based on land cover/land use under the framework of four types of ecosystem services. The types of ecosystem services flow were reclassified. Using entropy theory, disorder degree and developing trend of indicators and urban ecosystem were quantitatively assessed. Beijing was chosen as the study area, and twenty-four indicators were selected for evaluation. The results showed that the entropy value of Beijing urban ecosystem during 2004 to 2015 was 0.794 and the entropy flow was -0.024, suggesting a large disordered degree and near verge of non-health. The system got maximum values for three times, while the mean annual variation of the system entropy value increased gradually in three periods, indicating that human activities had negative effects on urban ecosystem. Entropy flow reached minimum value in 2007, implying the environmental quality was the best in 2007. The determination coefficient for the fitting function of total permanent population in Beijing and urban ecosystem entropy flow was 0.921, indicating that urban ecosystem health was highly correlated with total permanent population.

New paradigm for task switching strategies while performing multiple tasks: entropy and symbolic dynamics analysis of voluntary patterns.

PubMed

Guastello, Stephen J; Gorin, Hillary; Huschen, Samuel; Peters, Natalie E; Fabisch, Megan; Poston, Kirsten

2012-10-01

It has become well established in laboratory experiments that switching tasks, perhaps due to interruptions at work, incur costs in response time to complete the next task. Conditions are also known that exaggerate or lessen the switching costs. Although switching costs can contribute to fatigue, task switching can also be an adaptive response to fatigue. The present study introduces a new research paradigm for studying the emergence of voluntary task switching regimes, self-organizing processes therein, and the possibly conflicting roles of switching costs and minimum entropy. Fifty-four undergraduates performed 7 different computer-based cognitive tasks producing sets of 49 responses under instructional conditions requiring task quotas or no quotas. The sequences of task choices were analyzed using orbital decomposition to extract pattern types and lengths, which were then classified and compared with regard to Shannon entropy, topological entropy, number of task switches involved, and overall performance. Results indicated that similar but different patterns were generated under the two instructional conditions, and better performance was associated with lower topological entropy. Both entropy metrics were associated with the amount of voluntary task switching. Future research should explore conditions affecting the trade-off between switching costs and entropy, levels of automaticity between task elements, and the role of voluntary switching regimes on fatigue.

Optimization of a Circular Microchannel With Entropy Generation Minimization Method

NASA Astrophysics Data System (ADS)

Jafari, Arash; Ghazali, Normah Mohd

2010-06-01

New advances in micro and nano scales are being realized and the contributions of micro and nano heat dissipation devices are of high importance in this novel technology development. Past studies showed that microchannel design depends on its thermal resistance and pressure drop. However, entropy generation minimization (EGM) as a new optimization theory stated that the rate of entropy generation should be also optimized. Application of EGM in microchannel heat sink design is reviewed and discussed in this paper. Latest principles for deriving the entropy generation relations are discussed to present how this approach can be achieved. An optimization procedure using EGM method with the entropy generation rate is derived for a circular microchannel heat sink based upon thermal resistance and pressure drop. The equations are solved using MATLAB and the obtained results are compared to similar past studies. The effects of channel diameter, number of channels, heat flux, and pumping power on the entropy generation rate and Reynolds number are investigated. Analytical correlations are utilized for heat transfer and friction coefficients. A minimum entropy generation has been observed for N = 40 and channel diameter of 90μm. It is concluded that for N = 40 and channel hydraulic diameter of 90μm, the circular microchannel heat sink is on its optimum operating point based on second law of thermodynamics.

ECOSYSTEM GROWTH AND DEVELOPMENT

EPA Science Inventory

Thermodynamically, ecosystem growth and development is the process by which energy throughflow and stored biomass increase. Several proposed hypotheses describe the natural tendencies that occur as an ecosystem matures, and here, we consider five: minimum entropy production, maxi...

Heat capacities and thermodynamic properties of annite (aluminous iron biotite)

USGS Publications Warehouse

Hemingway, B.S.; Robie, R.A.

1990-01-01

The heat capacities have been measured between 7 and 650 K by quasi-adiabatic calorimetry and differential scanning calorimetry. At 298.15 K and 1 bar, the calorimetric entropy for our sample is 354.9??0.7 J/(mol.K). A minimum configurational entropy of 18.7 J/(mol.K) for full disorder of Al/Si in the tetrahedral sites should be added to the calorimetric entropy for third-law calculations. The heat capacity equation [Cp in units of J/mol.K)] Cp0 = 583.586 + 0.075246T - 3420.60T-0.5 - (4.4551 ?? 106)T-2 fits the experimental and estimated heat capacities for our sample (valid range 250 to 1000 K) with an average deviation of 0.37%. -from Authors

Temperature lapse rates at restricted thermodynamic equilibrium. Part II: Saturated air and further discussions

NASA Astrophysics Data System (ADS)

Björnbom, Pehr

2016-03-01

In the first part of this work equilibrium temperature profiles in fluid columns with ideal gas or ideal liquid were obtained by numerically minimizing the column energy at constant entropy, equivalent to maximizing column entropy at constant energy. A minimum in internal plus potential energy for an isothermal temperature profile was obtained in line with Gibbs' classical equilibrium criterion. However, a minimum in internal energy alone for adiabatic temperature profiles was also obtained. This led to a hypothesis that the adiabatic lapse rate corresponds to a restricted equilibrium state, a type of state in fact discussed already by Gibbs. In this paper similar numerical results for a fluid column with saturated air suggest that also the saturated adiabatic lapse rate corresponds to a restricted equilibrium state. The proposed hypothesis is further discussed and amended based on the previous and the present numerical results and a theoretical analysis based on Gibbs' equilibrium theory.

Optimal Binarization of Gray-Scaled Digital Images via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A. (Inventor); Klinko, Steven J. (Inventor)

2007-01-01

A technique for finding an optimal threshold for binarization of a gray scale image employs fuzzy reasoning. A triangular membership function is employed which is dependent on the degree to which the pixels in the image belong to either the foreground class or the background class. Use of a simplified linear fuzzy entropy factor function facilitates short execution times and use of membership values between 0.0 and 1.0 for improved accuracy. To improve accuracy further, the membership function employs lower and upper bound gray level limits that can vary from image to image and are selected to be equal to the minimum and the maximum gray levels, respectively, that are present in the image to be converted. To identify the optimal binarization threshold, an iterative process is employed in which different possible thresholds are tested and the one providing the minimum fuzzy entropy measure is selected.

A MATLAB implementation of the minimum relative entropy method for linear inverse problems

NASA Astrophysics Data System (ADS)

Neupauer, Roseanna M.; Borchers, Brian

2001-08-01

The minimum relative entropy (MRE) method can be used to solve linear inverse problems of the form Gm= d, where m is a vector of unknown model parameters and d is a vector of measured data. The MRE method treats the elements of m as random variables, and obtains a multivariate probability density function for m. The probability density function is constrained by prior information about the upper and lower bounds of m, a prior expected value of m, and the measured data. The solution of the inverse problem is the expected value of m, based on the derived probability density function. We present a MATLAB implementation of the MRE method. Several numerical issues arise in the implementation of the MRE method and are discussed here. We present the source history reconstruction problem from groundwater hydrology as an example of the MRE implementation.

Biomathematical modeling of pulsatile hormone secretion: a historical perspective.

PubMed

Evans, William S; Farhy, Leon S; Johnson, Michael L

2009-01-01

Shortly after the recognition of the profound physiological significance of the pulsatile nature of hormone secretion, computer-based modeling techniques were introduced for the identification and characterization of such pulses. Whereas these earlier approaches defined perturbations in hormone concentration-time series, deconvolution procedures were subsequently employed to separate such pulses into their secretion event and clearance components. Stochastic differential equation modeling was also used to define basal and pulsatile hormone secretion. To assess the regulation of individual components within a hormone network, a method that quantitated approximate entropy within hormone concentration-times series was described. To define relationships within coupled hormone systems, methods including cross-correlation and cross-approximate entropy were utilized. To address some of the inherent limitations of these methods, modeling techniques with which to appraise the strength of feedback signaling between and among hormone-secreting components of a network have been developed. Techniques such as dynamic modeling have been utilized to reconstruct dose-response interactions between hormones within coupled systems. A logical extension of these advances will require the development of mathematical methods with which to approximate endocrine networks exhibiting multiple feedback interactions and subsequently reconstruct their parameters based on experimental data for the purpose of testing regulatory hypotheses and estimating alterations in hormone release control mechanisms.

Isotopic orientational order in acetyl salicylic acid

NASA Astrophysics Data System (ADS)

Schiebel, P.; Prandl, W.; Papoular, R.; Paulus, W.; Detken, A.; Haeberlen, U.; Zimmermann, H.

2000-03-01

Isotopically mixed methyl groups CD xH 3- x with zero averaged deuteron/hydrogen scattering length 0=< a>= xaD+(3- x) aH are expected to be invisible in a neutron diffraction experiment. We find, indeed, in the scattering length density of aspirin-CD xH 3- x, reconstructed by maximum-entropy methods, at room temperature only three very week minima. At 10 K, however, one positive and two negative extrema are visible: unique evidence for orientational isotopic order. From a combination of 1-d-Fourier and algebraic methods we deconvolute < a> and derive the orientational distribution function f( φ) which has three equivalent maxima/minima at 300 K and loses this 3 φ periodicity at 10 K. f( φ) is the basis for the determination of the hindrance potential with cos( φ) as the leading term.

Sample entropy analysis of cervical neoplasia gene-expression signatures

PubMed Central

Botting, Shaleen K; Trzeciakowski, Jerome P; Benoit, Michelle F; Salama, Salama A; Diaz-Arrastia, Concepcion R

2009-01-01

Background We introduce Approximate Entropy as a mathematical method of analysis for microarray data. Approximate entropy is applied here as a method to classify the complex gene expression patterns resultant of a clinical sample set. Since Entropy is a measure of disorder in a system, we believe that by choosing genes which display minimum entropy in normal controls and maximum entropy in the cancerous sample set we will be able to distinguish those genes which display the greatest variability in the cancerous set. Here we describe a method of utilizing Approximate Sample Entropy (ApSE) analysis to identify genes of interest with the highest probability of producing an accurate, predictive, classification model from our data set. Results In the development of a diagnostic gene-expression profile for cervical intraepithelial neoplasia (CIN) and squamous cell carcinoma of the cervix, we identified 208 genes which are unchanging in all normal tissue samples, yet exhibit a random pattern indicative of the genetic instability and heterogeneity of malignant cells. This may be measured in terms of the ApSE when compared to normal tissue. We have validated 10 of these genes on 10 Normal and 20 cancer and CIN3 samples. We report that the predictive value of the sample entropy calculation for these 10 genes of interest is promising (75% sensitivity, 80% specificity for prediction of cervical cancer over CIN3). Conclusion The success of the Approximate Sample Entropy approach in discerning alterations in complexity from biological system with such relatively small sample set, and extracting biologically relevant genes of interest hold great promise. PMID:19232110

A Maximum Entropy Method for Particle Filtering

NASA Astrophysics Data System (ADS)

Eyink, Gregory L.; Kim, Sangil

2006-06-01

Standard ensemble or particle filtering schemes do not properly represent states of low priori probability when the number of available samples is too small, as is often the case in practical applications. We introduce here a set of parametric resampling methods to solve this problem. Motivated by a general H-theorem for relative entropy, we construct parametric models for the filter distributions as maximum-entropy/minimum-information models consistent with moments of the particle ensemble. When the prior distributions are modeled as mixtures of Gaussians, our method naturally generalizes the ensemble Kalman filter to systems with highly non-Gaussian statistics. We apply the new particle filters presented here to two simple test cases: a one-dimensional diffusion process in a double-well potential and the three-dimensional chaotic dynamical system of Lorenz.

Adjusting protein graphs based on graph entropy.

PubMed

Peng, Sheng-Lung; Tsay, Yu-Wei

2014-01-01

Measuring protein structural similarity attempts to establish a relationship of equivalence between polymer structures based on their conformations. In several recent studies, researchers have explored protein-graph remodeling, instead of looking a minimum superimposition for pairwise proteins. When graphs are used to represent structured objects, the problem of measuring object similarity become one of computing the similarity between graphs. Graph theory provides an alternative perspective as well as efficiency. Once a protein graph has been created, its structural stability must be verified. Therefore, a criterion is needed to determine if a protein graph can be used for structural comparison. In this paper, we propose a measurement for protein graph remodeling based on graph entropy. We extend the concept of graph entropy to determine whether a graph is suitable for representing a protein. The experimental results suggest that when applied, graph entropy helps a conformational on protein graph modeling. Furthermore, it indirectly contributes to protein structural comparison if a protein graph is solid.

Adjusting protein graphs based on graph entropy

PubMed Central

2014-01-01

Measuring protein structural similarity attempts to establish a relationship of equivalence between polymer structures based on their conformations. In several recent studies, researchers have explored protein-graph remodeling, instead of looking a minimum superimposition for pairwise proteins. When graphs are used to represent structured objects, the problem of measuring object similarity become one of computing the similarity between graphs. Graph theory provides an alternative perspective as well as efficiency. Once a protein graph has been created, its structural stability must be verified. Therefore, a criterion is needed to determine if a protein graph can be used for structural comparison. In this paper, we propose a measurement for protein graph remodeling based on graph entropy. We extend the concept of graph entropy to determine whether a graph is suitable for representing a protein. The experimental results suggest that when applied, graph entropy helps a conformational on protein graph modeling. Furthermore, it indirectly contributes to protein structural comparison if a protein graph is solid. PMID:25474347

Entropy as a Gene-Like Performance Indicator Promoting Thermoelectric Materials.

PubMed

Liu, Ruiheng; Chen, Hongyi; Zhao, Kunpeng; Qin, Yuting; Jiang, Binbin; Zhang, Tiansong; Sha, Gang; Shi, Xun; Uher, Ctirad; Zhang, Wenqing; Chen, Lidong

2017-10-01

High-throughput explorations of novel thermoelectric materials based on the Materials Genome Initiative paradigm only focus on digging into the structure-property space using nonglobal indicators to design materials with tunable electrical and thermal transport properties. As the genomic units, following the biogene tradition, such indicators include localized crystal structural blocks in real space or band degeneracy at certain points in reciprocal space. However, this nonglobal approach does not consider how real materials differentiate from others. Here, this study successfully develops a strategy of using entropy as the global gene-like performance indicator that shows how multicomponent thermoelectric materials with high entropy can be designed via a high-throughput screening method. Optimizing entropy works as an effective guide to greatly improve the thermoelectric performance through either a significantly depressed lattice thermal conductivity down to its theoretical minimum value and/or via enhancing the crystal structure symmetry to yield large Seebeck coefficients. The entropy engineering using multicomponent crystal structures or other possible techniques provides a new avenue for an improvement of the thermoelectric performance beyond the current methods and approaches. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A survey of the role of thermodynamic stability in viscous flow

NASA Technical Reports Server (NTRS)

Horne, W. C.; Smith, C. A.; Karamcheti, K.

1991-01-01

The stability of near-equilibrium states has been studied as a branch of the general field of nonequilibrium thermodynamics. By treating steady viscous flow as an open thermodynamic system, nonequilibrium principles such as the condition of minimum entropy-production rate for steady, near-equilibrium processes can be used to generate flow distributions from variational analyses. Examples considered in this paper are steady heat conduction, channel flow, and unconstrained three-dimensional flow. The entropy-production-rate condition has also been used for hydrodynamic stability criteria, and calculations of the stability of a laminar wall jet support this interpretation.

Advanced Source Deconvolution Methods for Compton Telescopes

NASA Astrophysics Data System (ADS)

Zoglauer, Andreas

The next generation of space telescopes utilizing Compton scattering for astrophysical observations is destined to one day unravel the mysteries behind Galactic nucleosynthesis, to determine the origin of the positron annihilation excess near the Galactic center, and to uncover the hidden emission mechanisms behind gamma-ray bursts. Besides astrophysics, Compton telescopes are establishing themselves in heliophysics, planetary sciences, medical imaging, accelerator physics, and environmental monitoring. Since the COMPTEL days, great advances in the achievable energy and position resolution were possible, creating an extremely vast, but also extremely sparsely sampled data space. Unfortunately, the optimum way to analyze the data from the next generation of Compton telescopes has not yet been found, which can retrieve all source parameters (location, spectrum, polarization, flux) and achieves the best possible resolution and sensitivity at the same time. This is especially important for all sciences objectives looking at the inner Galaxy: the large amount of expected sources, the high background (internal and Galactic diffuse emission), and the limited angular resolution, make it the most taxing case for data analysis. In general, two key challenges exist: First, what are the best data space representations to answer the specific science questions? Second, what is the best way to deconvolve the data to fully retrieve the source parameters? For modern Compton telescopes, the existing data space representations can either correctly reconstruct the absolute flux (binned mode) or achieve the best possible resolution (list-mode), both together were not possible up to now. Here we propose to develop a two-stage hybrid reconstruction method which combines the best aspects of both. Using a proof-of-concept implementation we can for the first time show that it is possible to alternate during each deconvolution step between a binned-mode approach to get the flux right and a list-mode approach to get the best angular resolution, to get achieve both at the same time! The second open question concerns the best deconvolution algorithm. For example, several algorithms have been investigated for the famous COMPTEL 26Al map which resulted in significantly different images. There is no clear answer as to which approach provides the most accurate result, largely due to the fact that detailed simulations to test and verify the approaches and their limitations were not possible at that time. This has changed, and therefore we propose to evaluate several deconvolution algorithms (e.g. Richardson-Lucy, Maximum-Entropy, MREM, and stochastic origin ensembles) with simulations of typical observations to find the best algorithm for each application and for each stage of the hybrid reconstruction approach. We will adapt, implement, and fully evaluate the hybrid source reconstruction approach as well as the various deconvolution algorithms with simulations of synthetic benchmarks and simulations of key science objectives such as diffuse nuclear line science and continuum science of point sources, as well as with calibrations/observations of the COSI balloon telescope. This proposal for "development of new data analysis methods for future satellite missions" will significantly improve the source deconvolution techniques for modern Compton telescopes and will allow unlocking the full potential of envisioned satellite missions using Compton-scatter technology in astrophysics, heliophysics and planetary sciences, and ultimately help them to "discover how the universe works" and to better "understand the sun". Ultimately it will also benefit ground based applications such as nuclear medicine and environmental monitoring as all developed algorithms will be made publicly available within the open-source Compton telescope analysis framework MEGAlib.

Moisture sorption isotherms and thermodynamic properties of mexican mennonite-style cheese.

PubMed

Martinez-Monteagudo, Sergio I; Salais-Fierro, Fabiola

2014-10-01

Moisture adsorption isotherms of fresh and ripened Mexican Mennonite-style cheese were investigated using the static gravimetric method at 4, 8, and 12 °C in a water activity range (aw) of 0.08-0.96. These isotherms were modeled using GAB, BET, Oswin and Halsey equations through weighed non-linear regression. All isotherms were sigmoid in shape, showing a type II BET isotherm, and the data were best described by GAB model. GAB model coefficients revealed that water adsorption by cheese matrix is a multilayer process characterized by molecules that are strongly bound in the monolayer and molecules that are slightly structured in a multilayer. Using the GAB model, it was possible to estimate thermodynamic functions (net isosteric heat, differential entropy, integral enthalpy and entropy, and enthalpy-entropy compensation) as function of moisture content. For both samples, the isosteric heat and differential entropy decreased with moisture content in exponential fashion. The integral enthalpy gradually decreased with increasing moisture content after reached a maximum value, while the integral entropy decreased with increasing moisture content after reached a minimum value. A linear compensation was found between integral enthalpy and entropy suggesting enthalpy controlled adsorption. Determination of moisture content and aw relationship yields to important information of controlling the ripening, drying and storage operations as well as understanding of the water state within a cheese matrix.

Inverting Monotonic Nonlinearities by Entropy Maximization

PubMed Central

López-de-Ipiña Pena, Karmele; Caiafa, Cesar F.

2016-01-01

This paper proposes a new method for blind inversion of a monotonic nonlinear map applied to a sum of random variables. Such kinds of mixtures of random variables are found in source separation and Wiener system inversion problems, for example. The importance of our proposed method is based on the fact that it permits to decouple the estimation of the nonlinear part (nonlinear compensation) from the estimation of the linear one (source separation matrix or deconvolution filter), which can be solved by applying any convenient linear algorithm. Our new nonlinear compensation algorithm, the MaxEnt algorithm, generalizes the idea of Gaussianization of the observation by maximizing its entropy instead. We developed two versions of our algorithm based either in a polynomial or a neural network parameterization of the nonlinear function. We provide a sufficient condition on the nonlinear function and the probability distribution that gives a guarantee for the MaxEnt method to succeed compensating the distortion. Through an extensive set of simulations, MaxEnt is compared with existing algorithms for blind approximation of nonlinear maps. Experiments show that MaxEnt is able to successfully compensate monotonic distortions outperforming other methods in terms of the obtained Signal to Noise Ratio in many important cases, for example when the number of variables in a mixture is small. Besides its ability for compensating nonlinearities, MaxEnt is very robust, i.e. showing small variability in the results. PMID:27780261

Inverting Monotonic Nonlinearities by Entropy Maximization.

PubMed

Solé-Casals, Jordi; López-de-Ipiña Pena, Karmele; Caiafa, Cesar F

2016-01-01

This paper proposes a new method for blind inversion of a monotonic nonlinear map applied to a sum of random variables. Such kinds of mixtures of random variables are found in source separation and Wiener system inversion problems, for example. The importance of our proposed method is based on the fact that it permits to decouple the estimation of the nonlinear part (nonlinear compensation) from the estimation of the linear one (source separation matrix or deconvolution filter), which can be solved by applying any convenient linear algorithm. Our new nonlinear compensation algorithm, the MaxEnt algorithm, generalizes the idea of Gaussianization of the observation by maximizing its entropy instead. We developed two versions of our algorithm based either in a polynomial or a neural network parameterization of the nonlinear function. We provide a sufficient condition on the nonlinear function and the probability distribution that gives a guarantee for the MaxEnt method to succeed compensating the distortion. Through an extensive set of simulations, MaxEnt is compared with existing algorithms for blind approximation of nonlinear maps. Experiments show that MaxEnt is able to successfully compensate monotonic distortions outperforming other methods in terms of the obtained Signal to Noise Ratio in many important cases, for example when the number of variables in a mixture is small. Besides its ability for compensating nonlinearities, MaxEnt is very robust, i.e. showing small variability in the results.

Application of an NLME-Stochastic Deconvolution Approach to Level A IVIVC Modeling.

PubMed

Kakhi, Maziar; Suarez-Sharp, Sandra; Shepard, Terry; Chittenden, Jason

2017-07-01

Stochastic deconvolution is a parameter estimation method that calculates drug absorption using a nonlinear mixed-effects model in which the random effects associated with absorption represent a Wiener process. The present work compares (1) stochastic deconvolution and (2) numerical deconvolution, using clinical pharmacokinetic (PK) data generated for an in vitro-in vivo correlation (IVIVC) study of extended release (ER) formulations of a Biopharmaceutics Classification System class III drug substance. The preliminary analysis found that numerical and stochastic deconvolution yielded superimposable fraction absorbed (F abs ) versus time profiles when supplied with exactly the same externally determined unit impulse response parameters. In a separate analysis, a full population-PK/stochastic deconvolution was applied to the clinical PK data. Scenarios were considered in which immediate release (IR) data were either retained or excluded to inform parameter estimation. The resulting F abs profiles were then used to model level A IVIVCs. All the considered stochastic deconvolution scenarios, and numerical deconvolution, yielded on average similar results with respect to the IVIVC validation. These results could be achieved with stochastic deconvolution without recourse to IR data. Unlike numerical deconvolution, this also implies that in crossover studies where certain individuals do not receive an IR treatment, their ER data alone can still be included as part of the IVIVC analysis. Published by Elsevier Inc.

An Integrated Theory of Everything (TOE)

NASA Astrophysics Data System (ADS)

Colella, Antonio

2014-03-01

An Integrated TOE unifies all known physical phenomena from the Planck cube to the Super Universe (multiverse). Each matter/force particle is represented by a Planck cube string. Any Super Universe object is a volume of contiguous Planck cubes. Super force Planck cube string singularities existed at the start of all universes. An Integrated TOE foundations are twenty independent existing theories and without sacrificing their integrities, are replaced by twenty interrelated amplified theories. Amplifications of Higgs force theory are key to an Integrated TOE and include: 64 supersymmetric Higgs particles; super force condensations to 17 matter particles/associated Higgs forces; spontaneous symmetry breaking is bidirectional; and the sum of 8 permanent Higgs force energies is dark energy. Stellar black hole theory was amplified to include a quark star (matter) with mass, volume, near zero temperature, and maximum entropy. A black hole (energy) has energy, minimal volume (singularity), near infinite temperature, and minimum entropy. Our precursor universe's super supermassive quark star (matter) evaporated to a super supermassive black hole (energy). This transferred total conserved energy/mass and transformed entropy from maximum to minimum. Integrated Theory of Everything Book Video: https://www.youtube.com/watch?v=4a1c9IvdoGY Research Article Video: http://www.youtube.com/watch?v=CD-QoLeVbSY Research Article: http://toncolella.files.wordpress.com/2012/07/m080112.pdf.

Shock wave induced vaporization of porous solids

NASA Astrophysics Data System (ADS)

Shen, Andy H.; Ahrens, Thomas J.; O'Keefe, John D.

2003-05-01

Strong shock waves generated by hypervelocity impact can induce vaporization in solid materials. To pursue knowledge of the chemical species in the shock-induced vapors, one needs to design experiments that will drive the system to such thermodynamic states that sufficient vapor can be generated for investigation. It is common to use porous media to reach high entropy, vaporized states in impact experiments. We extended calculations by Ahrens [J. Appl. Phys. 43, 2443 (1972)] and Ahrens and O'Keefe [The Moon 4, 214 (1972)] to higher distentions (up to five) and improved their method with a different impedance match calculation scheme and augmented their model with recent thermodynamic and Hugoniot data of metals, minerals, and polymers. Although we reconfirmed the competing effects reported in the previous studies: (1) increase of entropy production and (2) decrease of impedance match, when impacting materials with increasing distentions, our calculations did not exhibit optimal entropy-generating distention. For different materials, very different impact velocities are needed to initiate vaporization. For aluminum at distention (m)<2.2, a minimum impact velocity of 2.7 km/s is required using tungsten projectile. For ionic solids such as NaCl at distention <2.2, 2.5 km/s is needed. For carbonate and sulfate minerals, the minimum impact velocities are much lower, ranging from less than 1 to 1.5 km/s.

The constructal law of design and evolution in nature

PubMed Central

Bejan, Adrian; Lorente, Sylvie

2010-01-01

Constructal theory is the view that (i) the generation of images of design (pattern, rhythm) in nature is a phenomenon of physics and (ii) this phenomenon is covered by a principle (the constructal law): ‘for a finite-size flow system to persist in time (to live) it must evolve such that it provides greater and greater access to the currents that flow through it’. This law is about the necessity of design to occur, and about the time direction of the phenomenon: the tape of the design evolution ‘movie’ runs such that existing configurations are replaced by globally easier flowing configurations. The constructal law has two useful sides: the prediction of natural phenomena and the strategic engineering of novel architectures, based on the constructal law, i.e. not by mimicking nature. We show that the emergence of scaling laws in inanimate (geophysical) flow systems is the same phenomenon as the emergence of allometric laws in animate (biological) flow systems. Examples are lung design, animal locomotion, vegetation, river basins, turbulent flow structure, self-lubrication and natural multi-scale porous media. This article outlines the place of the constructal law as a self-standing law in physics, which covers all the ad hoc (and contradictory) statements of optimality such as minimum entropy generation, maximum entropy generation, minimum flow resistance, maximum flow resistance, minimum time, minimum weight, uniform maximum stresses and characteristic organ sizes. Nature is configured to flow and move as a conglomerate of ‘engine and brake’ designs. PMID:20368252

The constructal law of design and evolution in nature.

PubMed

Bejan, Adrian; Lorente, Sylvie

2010-05-12

Constructal theory is the view that (i) the generation of images of design (pattern, rhythm) in nature is a phenomenon of physics and (ii) this phenomenon is covered by a principle (the constructal law): 'for a finite-size flow system to persist in time (to live) it must evolve such that it provides greater and greater access to the currents that flow through it'. This law is about the necessity of design to occur, and about the time direction of the phenomenon: the tape of the design evolution 'movie' runs such that existing configurations are replaced by globally easier flowing configurations. The constructal law has two useful sides: the prediction of natural phenomena and the strategic engineering of novel architectures, based on the constructal law, i.e. not by mimicking nature. We show that the emergence of scaling laws in inanimate (geophysical) flow systems is the same phenomenon as the emergence of allometric laws in animate (biological) flow systems. Examples are lung design, animal locomotion, vegetation, river basins, turbulent flow structure, self-lubrication and natural multi-scale porous media. This article outlines the place of the constructal law as a self-standing law in physics, which covers all the ad hoc (and contradictory) statements of optimality such as minimum entropy generation, maximum entropy generation, minimum flow resistance, maximum flow resistance, minimum time, minimum weight, uniform maximum stresses and characteristic organ sizes. Nature is configured to flow and move as a conglomerate of 'engine and brake' designs.

Non-Negative Spherical Deconvolution (NNSD) for estimation of fiber Orientation Distribution Function in single-/multi-shell diffusion MRI.

PubMed

Cheng, Jian; Deriche, Rachid; Jiang, Tianzi; Shen, Dinggang; Yap, Pew-Thian

2014-11-01

Spherical Deconvolution (SD) is commonly used for estimating fiber Orientation Distribution Functions (fODFs) from diffusion-weighted signals. Existing SD methods can be classified into two categories: 1) Continuous Representation based SD (CR-SD), where typically Spherical Harmonic (SH) representation is used for convenient analytical solutions, and 2) Discrete Representation based SD (DR-SD), where the signal profile is represented by a discrete set of basis functions uniformly oriented on the unit sphere. A feasible fODF should be non-negative and should integrate to unity throughout the unit sphere S(2). However, to our knowledge, most existing SH-based SD methods enforce non-negativity only on discretized points and not the whole continuum of S(2). Maximum Entropy SD (MESD) and Cartesian Tensor Fiber Orientation Distributions (CT-FOD) are the only SD methods that ensure non-negativity throughout the unit sphere. They are however computational intensive and are susceptible to errors caused by numerical spherical integration. Existing SD methods are also known to overestimate the number of fiber directions, especially in regions with low anisotropy. DR-SD introduces additional error in peak detection owing to the angular discretization of the unit sphere. This paper proposes a SD framework, called Non-Negative SD (NNSD), to overcome all the limitations above. NNSD is significantly less susceptible to the false-positive peaks, uses SH representation for efficient analytical spherical deconvolution, and allows accurate peak detection throughout the whole unit sphere. We further show that NNSD and most existing SD methods can be extended to work on multi-shell data by introducing a three-dimensional fiber response function. We evaluated NNSD in comparison with Constrained SD (CSD), a quadratic programming variant of CSD, MESD, and an L1-norm regularized non-negative least-squares DR-SD. Experiments on synthetic and real single-/multi-shell data indicate that NNSD improves estimation performance in terms of mean difference of angles, peak detection consistency, and anisotropy contrast between isotropic and anisotropic regions. Copyright © 2014 Elsevier Inc. All rights reserved.

Maximum-Entropy Inference with a Programmable Annealer

PubMed Central

Chancellor, Nicholas; Szoke, Szilard; Vinci, Walter; Aeppli, Gabriel; Warburton, Paul A.

2016-01-01

Optimisation problems typically involve finding the ground state (i.e. the minimum energy configuration) of a cost function with respect to many variables. If the variables are corrupted by noise then this maximises the likelihood that the solution is correct. The maximum entropy solution on the other hand takes the form of a Boltzmann distribution over the ground and excited states of the cost function to correct for noise. Here we use a programmable annealer for the information decoding problem which we simulate as a random Ising model in a field. We show experimentally that finite temperature maximum entropy decoding can give slightly better bit-error-rates than the maximum likelihood approach, confirming that useful information can be extracted from the excited states of the annealer. Furthermore we introduce a bit-by-bit analytical method which is agnostic to the specific application and use it to show that the annealer samples from a highly Boltzmann-like distribution. Machines of this kind are therefore candidates for use in a variety of machine learning applications which exploit maximum entropy inference, including language processing and image recognition. PMID:26936311

Sorption isotherms, thermodynamic properties and glass transition temperature of mucilage extracted from chia seeds (Salvia hispanica L.).

PubMed

Velázquez-Gutiérrez, Sandra Karina; Figueira, Ana Cristina; Rodríguez-Huezo, María Eva; Román-Guerrero, Angélica; Carrillo-Navas, Hector; Pérez-Alonso, César

2015-05-05

Freeze-dried chia mucilage adsorption isotherms were determined at 25, 35 and 40°C and fitted with the Guggenheim-Anderson-de Boer model. The integral thermodynamic properties (enthalpy and entropy) were estimated with the Clausius-Clapeyron equation. Pore radius of the mucilage, calculated with the Kelvin equation, varied from 0.87 to 6.44 nm in the temperature range studied. The point of maximum stability (minimum integral entropy) ranged between 7.56 and 7.63kg H2O per 100 kg of dry solids (d.s.) (water activity of 0.34-0.53). Enthalpy-entropy compensation for the mucilage showed two isokinetic temperatures: (i) one occurring at low moisture contents (0-7.56 kg H2O per 100 kg d.s.), controlled by changes in water entropy; and (ii) another happening in the moisture interval of 7.56-24 kg H2O per 100 kg d.s. and was enthalpy driven. The glass transition temperature Tg of the mucilage fluctuated between 42.93 and 57.93°C. Copyright © 2015 Elsevier Ltd. All rights reserved.

Study of thermodynamic properties of liquid binary alloys by a pseudopotential method

NASA Astrophysics Data System (ADS)

Vora, Aditya M.

2010-11-01

On the basis of the Percus-Yevick hard-sphere model as a reference system and the Gibbs-Bogoliubov inequality, a thermodynamic perturbation method is applied with the use of the well-known model potential. By applying a variational method, the hard-core diameters are found which correspond to a minimum free energy. With this procedure, the thermodynamic properties such as the internal energy, entropy, Helmholtz free energy, entropy of mixing, and heat of mixing are computed for liquid NaK binary systems. The influence of the local-field correction functions of Hartree, Taylor, Ichimaru-Utsumi, Farid-Heine-Engel-Robertson, and Sarkar-Sen-Haldar-Roy is also investigated. The computed excess entropy is in agreement with available experimental data in the case of liquid alloys, whereas the agreement for the heat of mixing is poor. This may be due to the sensitivity of the latter to the potential parameters and dielectric function.

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

Luis, Alfredo

The use of Renyi entropy as an uncertainty measure alternative to variance leads to the study of states with quantum fluctuations below the levels established by Gaussian states, which are the position-momentum minimum uncertainty states according to variance. We examine the quantum properties of states with exponential wave functions, which combine reduced fluctuations with practical feasibility.

Information dynamics in living systems: prokaryotes, eukaryotes, and cancer.

PubMed

Frieden, B Roy; Gatenby, Robert A

2011-01-01

Living systems use information and energy to maintain stable entropy while far from thermodynamic equilibrium. The underlying first principles have not been established. We propose that stable entropy in living systems, in the absence of thermodynamic equilibrium, requires an information extremum (maximum or minimum), which is invariant to first order perturbations. Proliferation and death represent key feedback mechanisms that promote stability even in a non-equilibrium state. A system moves to low or high information depending on its energy status, as the benefit of information in maintaining and increasing order is balanced against its energy cost. Prokaryotes, which lack specialized energy-producing organelles (mitochondria), are energy-limited and constrained to an information minimum. Acquisition of mitochondria is viewed as a critical evolutionary step that, by allowing eukaryotes to achieve a sufficiently high energy state, permitted a phase transition to an information maximum. This state, in contrast to the prokaryote minima, allowed evolution of complex, multicellular organisms. A special case is a malignant cell, which is modeled as a phase transition from a maximum to minimum information state. The minimum leads to a predicted power-law governing the in situ growth that is confirmed by studies measuring growth of small breast cancers. We find living systems achieve a stable entropic state by maintaining an extreme level of information. The evolutionary divergence of prokaryotes and eukaryotes resulted from acquisition of specialized energy organelles that allowed transition from information minima to maxima, respectively. Carcinogenesis represents a reverse transition: of an information maximum to minimum. The progressive information loss is evident in accumulating mutations, disordered morphology, and functional decline characteristics of human cancers. The findings suggest energy restriction is a critical first step that triggers the genetic mutations that drive somatic evolution of the malignant phenotype.

Investigation of radio astronomy image processing techniques for use in the passive millimetre-wave security screening environment

NASA Astrophysics Data System (ADS)

Taylor, Christopher T.; Hutchinson, Simon; Salmon, Neil A.; Wilkinson, Peter N.; Cameron, Colin D.

2014-06-01

Image processing techniques can be used to improve the cost-effectiveness of future interferometric Passive MilliMetre Wave (PMMW) imagers. The implementation of such techniques will allow for a reduction in the number of collecting elements whilst ensuring adequate image fidelity is maintained. Various techniques have been developed by the radio astronomy community to enhance the imaging capability of sparse interferometric arrays. The most prominent are Multi- Frequency Synthesis (MFS) and non-linear deconvolution algorithms, such as the Maximum Entropy Method (MEM) and variations of the CLEAN algorithm. This investigation focuses on the implementation of these methods in the defacto standard for radio astronomy image processing, the Common Astronomy Software Applications (CASA) package, building upon the discussion presented in Taylor et al., SPIE 8362-0F. We describe the image conversion process into a CASA suitable format, followed by a series of simulations that exploit the highlighted deconvolution and MFS algorithms assuming far-field imagery. The primary target application used for this investigation is an outdoor security scanner for soft-sided Heavy Goods Vehicles. A quantitative analysis of the effectiveness of the aforementioned image processing techniques is presented, with thoughts on the potential cost-savings such an approach could yield. Consideration is also given to how the implementation of these techniques in CASA might be adapted to operate in a near-field target environment. This may enable a much wider usability by the imaging community outside of radio astronomy and thus would be directly relevant to portal screening security systems in the microwave and millimetre wave bands.

Application of genetic algorithms in nonlinear heat conduction problems.

PubMed

Kadri, Muhammad Bilal; Khan, Waqar A

2014-01-01

Genetic algorithms are employed to optimize dimensionless temperature in nonlinear heat conduction problems. Three common geometries are selected for the analysis and the concept of minimum entropy generation is used to determine the optimum temperatures under the same constraints. The thermal conductivity is assumed to vary linearly with temperature while internal heat generation is assumed to be uniform. The dimensionless governing equations are obtained for each selected geometry and the dimensionless temperature distributions are obtained using MATLAB. It is observed that GA gives the minimum dimensionless temperature in each selected geometry.

Hybrid Imaging for Extended Depth of Field Microscopy

NASA Astrophysics Data System (ADS)

Zahreddine, Ramzi Nicholas

An inverse relationship exists in optical systems between the depth of field (DOF) and the minimum resolvable feature size. This trade-off is especially detrimental in high numerical aperture microscopy systems where resolution is pushed to the diffraction limit resulting in a DOF on the order of 500 nm. Many biological structures and processes of interest span over micron scales resulting in significant blurring during imaging. This thesis explores a two-step computational imaging technique known as hybrid imaging to create extended DOF (EDF) microscopy systems with minimal sacrifice in resolution. In the first step a mask is inserted at the pupil plane of the microscope to create a focus invariant system over 10 times the traditional DOF, albeit with reduced contrast. In the second step the contrast is restored via deconvolution. Several EDF pupil masks from the literature are quantitatively compared in the context of biological microscopy. From this analysis a new mask is proposed, the incoherently partitioned pupil with binary phase modulation (IPP-BPM), that combines the most advantageous properties from the literature. Total variation regularized deconvolution models are derived for the various noise conditions and detectors commonly used in biological microscopy. State of the art algorithms for efficiently solving the deconvolution problem are analyzed for speed, accuracy, and ease of use. The IPP-BPM mask is compared with the literature and shown to have the highest signal-to-noise ratio and lowest mean square error post-processing. A prototype of the IPP-BPM mask is fabricated using a combination of 3D femtosecond glass etching and standard lithography techniques. The mask is compared against theory and demonstrated in biological imaging applications.

Partial Deconvolution with Inaccurate Blur Kernel.

PubMed

Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

2017-10-17

Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.

Texture descriptions of lunar surface derived from LOLA data: Kilometer-scale roughness and entropy maps

NASA Astrophysics Data System (ADS)

Li, Bo; Ling, Zongcheng; Zhang, Jiang; Chen, Jian; Wu, Zhongchen; Ni, Yuheng; Zhao, Haowei

2015-11-01

The lunar global texture maps of roughness and entropy are derived at kilometer scales from Digital Elevation Models (DEMs) data obtained by Lunar Orbiter Laser Altimeter (LOLA) aboard on Lunar Reconnaissance Orbiter (LRO) spacecraft. We use statistical moments of a gray-level histogram of elevations in a neighborhood to compute the roughness and entropy value. Our texture descriptors measurements are shown in global maps at multi-sized square neighborhoods, whose length of side is 3, 5, 10, 20, 40 and 80 pixels, respectively. We found that large-scale topographical changes can only be displayed in maps with longer side of neighborhood, but the small scale global texture maps are more disorderly and unsystematic because of more complicated textures' details. Then, the frequency curves of texture maps are made out, whose shapes and distributions are changing as the spatial scales increases. Entropy frequency curve with minimum 3-pixel scale has large fluctuations and six peaks. According to this entropy curve we can classify lunar surface into maria, highlands, different parts of craters preliminarily. The most obvious textures in the middle-scale roughness and entropy maps are the two typical morphological units, smooth maria and rough highlands. For the impact crater, its roughness and entropy value are characterized by a multiple-ring structure obviously, and its different parts have different texture results. In the last, we made a 2D scatter plot between the two texture results of typical lunar maria and highlands. There are two clusters with largest dot density which are corresponded to the lunar highlands and maria separately. In the lunar mare regions (cluster A), there is a high correlation between roughness and entropy, but in the highlands (Cluster B), the entropy shows little change. This could be subjected to different geological processes of maria and highlands forming different landforms.

Deconvolution method for accurate determination of overlapping peak areas in chromatograms.

PubMed

Nelson, T J

1991-12-20

A method is described for deconvoluting chromatograms which contain overlapping peaks. Parameters can be selected to ensure that attenuation of peak areas is uniform over any desired range of peak widths. A simple extension of the method greatly reduces the negative overshoot frequently encountered with deconvolutions. The deconvoluted chromatograms are suitable for integration by conventional methods.

An information-theoretical perspective on weighted ensemble forecasts

NASA Astrophysics Data System (ADS)

Weijs, Steven V.; van de Giesen, Nick

2013-08-01

This paper presents an information-theoretical method for weighting ensemble forecasts with new information. Weighted ensemble forecasts can be used to adjust the distribution that an existing ensemble of time series represents, without modifying the values in the ensemble itself. The weighting can, for example, add new seasonal forecast information in an existing ensemble of historically measured time series that represents climatic uncertainty. A recent article in this journal compared several methods to determine the weights for the ensemble members and introduced the pdf-ratio method. In this article, a new method, the minimum relative entropy update (MRE-update), is presented. Based on the principle of minimum discrimination information, an extension of the principle of maximum entropy (POME), the method ensures that no more information is added to the ensemble than is present in the forecast. This is achieved by minimizing relative entropy, with the forecast information imposed as constraints. From this same perspective, an information-theoretical view on the various weighting methods is presented. The MRE-update is compared with the existing methods and the parallels with the pdf-ratio method are analysed. The paper provides a new, information-theoretical justification for one version of the pdf-ratio method that turns out to be equivalent to the MRE-update. All other methods result in sets of ensemble weights that, seen from the information-theoretical perspective, add either too little or too much (i.e. fictitious) information to the ensemble.

Deconvolution of continuous paleomagnetic data from pass-through magnetometer: A new algorithm to restore geomagnetic and environmental information based on realistic optimization

NASA Astrophysics Data System (ADS)

Oda, Hirokuni; Xuan, Chuang

2014-10-01

development of pass-through superconducting rock magnetometers (SRM) has greatly promoted collection of paleomagnetic data from continuous long-core samples. The output of pass-through measurement is smoothed and distorted due to convolution of magnetization with the magnetometer sensor response. Although several studies could restore high-resolution paleomagnetic signal through deconvolution of pass-through measurement, difficulties in accurately measuring the magnetometer sensor response have hindered the application of deconvolution. We acquired reliable sensor response of an SRM at the Oregon State University based on repeated measurements of a precisely fabricated magnetic point source. In addition, we present an improved deconvolution algorithm based on Akaike's Bayesian Information Criterion (ABIC) minimization, incorporating new parameters to account for errors in sample measurement position and length. The new algorithm was tested using synthetic data constructed by convolving "true" paleomagnetic signal containing an "excursion" with the sensor response. Realistic noise was added to the synthetic measurement using Monte Carlo method based on measurement noise distribution acquired from 200 repeated measurements of a u-channel sample. Deconvolution of 1000 synthetic measurements with realistic noise closely resembles the "true" magnetization, and successfully restored fine-scale magnetization variations including the "excursion." Our analyses show that inaccuracy in sample measurement position and length significantly affects deconvolution estimation, and can be resolved using the new deconvolution algorithm. Optimized deconvolution of 20 repeated measurements of a u-channel sample yielded highly consistent deconvolution results and estimates of error in sample measurement position and length, demonstrating the reliability of the new deconvolution algorithm for real pass-through measurements.

UDECON: deconvolution optimization software for restoring high-resolution records from pass-through paleomagnetic measurements

NASA Astrophysics Data System (ADS)

Xuan, Chuang; Oda, Hirokuni

2015-11-01

The rapid accumulation of continuous paleomagnetic and rock magnetic records acquired from pass-through measurements on superconducting rock magnetometers (SRM) has greatly contributed to our understanding of the paleomagnetic field and paleo-environment. Pass-through measurements are inevitably smoothed and altered by the convolution effect of SRM sensor response, and deconvolution is needed to restore high-resolution paleomagnetic and environmental signals. Although various deconvolution algorithms have been developed, the lack of easy-to-use software has hindered the practical application of deconvolution. Here, we present standalone graphical software UDECON as a convenient tool to perform optimized deconvolution for pass-through paleomagnetic measurements using the algorithm recently developed by Oda and Xuan (Geochem Geophys Geosyst 15:3907-3924, 2014). With the preparation of a format file, UDECON can directly read pass-through paleomagnetic measurement files collected at different laboratories. After the SRM sensor response is determined and loaded to the software, optimized deconvolution can be conducted using two different approaches (i.e., "Grid search" and "Simplex method") with adjustable initial values or ranges for smoothness, corrections of sample length, and shifts in measurement position. UDECON provides a suite of tools to view conveniently and check various types of original measurement and deconvolution data. Multiple steps of measurement and/or deconvolution data can be compared simultaneously to check the consistency and to guide further deconvolution optimization. Deconvolved data together with the loaded original measurement and SRM sensor response data can be saved and reloaded for further treatment in UDECON. Users can also export the optimized deconvolution data to a text file for analysis in other software.

Free Energy Landscape of Protein-Protein Encounter Resulting from Brownian Dynamics Simulations of Barnase:Barstar.

PubMed

Spaar, Alexander; Helms, Volkhard

2005-07-01

Over the past years Brownian dynamics (BD) simulations have been proven to be a suitable tool for the analysis of protein-protein association. The computed rates and relative trends for protein mutants and different ionic strength are generally in good agreement with experimental results, e.g. see ref 1. By design, BD simulations correspond to an intensive sampling over energetically favorable states, rather than to a systematic sampling over all possible states which is feasible only at rather low resolution. On the example of barnase and barstar, a well characterized model system of electrostatically steered diffusional encounter, we report here the computation of the 6-dimensional free energy landscape for the encounter process of two proteins by a novel, careful analysis of the trajectories from BD simulations. The aim of these studies was the clarification of the encounter state. Along the trajectories, the individual positions and orientations of one protein (relative to the other) are recorded and stored in so-called occupancy maps. Since the number of simulated trajectories is sufficiently high, these occupancy maps can be interpreted as a probability distribution which allows the calculation of the entropy landscape by the use of a locally defined entropy function. Additionally, the configuration dependent electrostatic and desolvation energies are recorded in separate maps. The free energy landscape of protein-protein encounter is finally obtained by summing the energy and entropy contributions. In the free energy profile along the reaction path, which is defined as the path along the minima in the free energy landscape, a minimum shows up suggesting this to be used as the definition of the encounter state. This minimum describes a state of reduced diffusion velocity where the electrostatic attraction is compensated by the repulsion due to the unfavorable desolvation of the charged residues and the entropy loss due to the increasing restriction of the motional freedom. In the simulations the orientational degrees of freedom at the encounter state are found to be less restricted than the translational degrees of freedom. Therefore, the orientational alignment of the two binding partners seems to take place beyond this free energy minimum. The free energy profiles along the reaction pathway are compared for different ionic strength and temperature. This novel analysis technique facilitates mechanistic interpretation of protein-protein encounter pathways which should be useful for interpretation of experimental results as well.

A neural network approach for the blind deconvolution of turbulent flows

NASA Astrophysics Data System (ADS)

Maulik, R.; San, O.

2017-11-01

We present a single-layer feedforward artificial neural network architecture trained through a supervised learning approach for the deconvolution of flow variables from their coarse grained computations such as those encountered in large eddy simulations. We stress that the deconvolution procedure proposed in this investigation is blind, i.e. the deconvolved field is computed without any pre-existing information about the filtering procedure or kernel. This may be conceptually contrasted to the celebrated approximate deconvolution approaches where a filter shape is predefined for an iterative deconvolution process. We demonstrate that the proposed blind deconvolution network performs exceptionally well in the a-priori testing of both two-dimensional Kraichnan and three-dimensional Kolmogorov turbulence and shows promise in forming the backbone of a physics-augmented data-driven closure for the Navier-Stokes equations.

Efficient Computation of Small-Molecule Configurational Binding Entropy and Free Energy Changes by Ensemble Enumeration

PubMed Central

2013-01-01

Here we present a novel, end-point method using the dead-end-elimination and A* algorithms to efficiently and accurately calculate the change in free energy, enthalpy, and configurational entropy of binding for ligand–receptor association reactions. We apply the new approach to the binding of a series of human immunodeficiency virus (HIV-1) protease inhibitors to examine the effect ensemble reranking has on relative accuracy as well as to evaluate the role of the absolute and relative ligand configurational entropy losses upon binding in affinity differences for structurally related inhibitors. Our results suggest that most thermodynamic parameters can be estimated using only a small fraction of the full configurational space, and we see significant improvement in relative accuracy when using an ensemble versus single-conformer approach to ligand ranking. We also find that using approximate metrics based on the single-conformation enthalpy differences between the global minimum energy configuration in the bound as well as unbound states also correlates well with experiment. Using a novel, additive entropy expansion based on conditional mutual information, we also analyze the source of ligand configurational entropy loss upon binding in terms of both uncoupled per degree of freedom losses as well as changes in coupling between inhibitor degrees of freedom. We estimate entropic free energy losses of approximately +24 kcal/mol, 12 kcal/mol of which stems from loss of translational and rotational entropy. Coupling effects contribute only a small fraction to the overall entropy change (1–2 kcal/mol) but suggest differences in how inhibitor dihedral angles couple to each other in the bound versus unbound states. The importance of accounting for flexibility in drug optimization and design is also discussed. PMID:24250277

Statistical physics of self-replication.

PubMed

England, Jeremy L

2013-09-28

Self-replication is a capacity common to every species of living thing, and simple physical intuition dictates that such a process must invariably be fueled by the production of entropy. Here, we undertake to make this intuition rigorous and quantitative by deriving a lower bound for the amount of heat that is produced during a process of self-replication in a system coupled to a thermal bath. We find that the minimum value for the physically allowed rate of heat production is determined by the growth rate, internal entropy, and durability of the replicator, and we discuss the implications of this finding for bacterial cell division, as well as for the pre-biotic emergence of self-replicating nucleic acids.

Benford's law and the FSD distribution of economic behavioral micro data

NASA Astrophysics Data System (ADS)

Villas-Boas, Sofia B.; Fu, Qiuzi; Judge, George

2017-11-01

In this paper, we focus on the first significant digit (FSD) distribution of European micro income data and use information theoretic-entropy based methods to investigate the degree to which Benford's FSD law is consistent with the nature of these economic behavioral systems. We demonstrate that Benford's law is not an empirical phenomenon that occurs only in important distributions in physical statistics, but that it also arises in self-organizing dynamic economic behavioral systems. The empirical likelihood member of the minimum divergence-entropy family, is used to recover country based income FSD probability density functions and to demonstrate the implications of using a Benford prior reference distribution in economic behavioral system information recovery.

Scaling laws for ignition at the National Ignition Facility from first principles.

PubMed

Cheng, Baolian; Kwan, Thomas J T; Wang, Yi-Ming; Batha, Steven H

2013-10-01

We have developed an analytical physics model from fundamental physics principles and used the reduced one-dimensional model to derive a thermonuclear ignition criterion and implosion energy scaling laws applicable to inertial confinement fusion capsules. The scaling laws relate the fuel pressure and the minimum implosion energy required for ignition to the peak implosion velocity and the equation of state of the pusher and the hot fuel. When a specific low-entropy adiabat path is used for the cold fuel, our scaling laws recover the ignition threshold factor dependence on the implosion velocity, but when a high-entropy adiabat path is chosen, the model agrees with recent measurements.

Minimax Quantum Tomography: Estimators and Relative Entropy Bounds.

PubMed

Ferrie, Christopher; Blume-Kohout, Robin

2016-03-04

A minimax estimator has the minimum possible error ("risk") in the worst case. We construct the first minimax estimators for quantum state tomography with relative entropy risk. The minimax risk of nonadaptive tomography scales as O(1/sqrt[N])-in contrast to that of classical probability estimation, which is O(1/N)-where N is the number of copies of the quantum state used. We trace this deficiency to sampling mismatch: future observations that determine risk may come from a different sample space than the past data that determine the estimate. This makes minimax estimators very biased, and we propose a computationally tractable alternative with similar behavior in the worst case, but superior accuracy on most states.

Consistent description of kinetic equation with triangle anomaly

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

Pu Shi; Gao Jianhua; Wang Qun

2011-05-01

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

Crowded field photometry with deconvolved images.

NASA Astrophysics Data System (ADS)

Linde, P.; Spännare, S.

A local implementation of the Lucy-Richardson algorithm has been used to deconvolve a set of crowded stellar field images. The effects of deconvolution on detection limits as well as on photometric and astrometric properties have been investigated as a function of the number of deconvolution iterations. Results show that deconvolution improves detection of faint stars, although artifacts are also found. Deconvolution provides more stars measurable without significant degradation of positional accuracy. The photometric precision is affected by deconvolution in several ways. Errors due to unresolved images are notably reduced, while flux redistribution between stars and background increases the errors.

Towards the minimization of thermodynamic irreversibility in an electrically actuated microflow of a viscoelastic fluid under electrical double layer phenomenon

NASA Astrophysics Data System (ADS)

Sarma, Rajkumar; Jain, Manish; Mondal, Pranab Kumar

2017-10-01

We discuss the entropy generation minimization for electro-osmotic flow of a viscoelastic fluid through a parallel plate microchannel under the combined influences of interfacial slip and conjugate transport of heat. We use in this study the simplified Phan-Thien-Tanner model to describe the rheological behavior of the viscoelastic fluid. Using Navier's slip law and thermal boundary conditions of the third kind, we solve the transport equations analytically and evaluate the global entropy generation rate of the system. We examine the influential role of the following parameters on the entropy generation rate of the system, viz., the viscoelastic parameter (ɛDe2), Debye-Hückel parameter ( κ ¯ ) , channel wall thickness (δ), thermal conductivity of the wall (γ), Biot number (Bi), Peclet number (Pe), and axial temperature gradient (B). This investigation finally establishes the optimum values of the abovementioned parameters, leading to the minimum entropy generation of the system. We believe that results of this analysis could be helpful in optimizing the second-law performance of microscale thermal management devices, including the micro-heat exchangers, micro-reactors, and micro-heat pipes.

Improving ground-penetrating radar data in sedimentary rocks using deterministic deconvolution

USGS Publications Warehouse

Xia, J.; Franseen, E.K.; Miller, R.D.; Weis, T.V.; Byrnes, A.P.

2003-01-01

Resolution is key to confidently identifying unique geologic features using ground-penetrating radar (GPR) data. Source wavelet "ringing" (related to bandwidth) in a GPR section limits resolution because of wavelet interference, and can smear reflections in time and/or space. The resultant potential for misinterpretation limits the usefulness of GPR. Deconvolution offers the ability to compress the source wavelet and improve temporal resolution. Unlike statistical deconvolution, deterministic deconvolution is mathematically simple and stable while providing the highest possible resolution because it uses the source wavelet unique to the specific radar equipment. Source wavelets generated in, transmitted through and acquired from air allow successful application of deterministic approaches to wavelet suppression. We demonstrate the validity of using a source wavelet acquired in air as the operator for deterministic deconvolution in a field application using "400-MHz" antennas at a quarry site characterized by interbedded carbonates with shale partings. We collected GPR data on a bench adjacent to cleanly exposed quarry faces in which we placed conductive rods to provide conclusive groundtruth for this approach to deconvolution. The best deconvolution results, which are confirmed by the conductive rods for the 400-MHz antenna tests, were observed for wavelets acquired when the transmitter and receiver were separated by 0.3 m. Applying deterministic deconvolution to GPR data collected in sedimentary strata at our study site resulted in an improvement in resolution (50%) and improved spatial location (0.10-0.15 m) of geologic features compared to the same data processed without deterministic deconvolution. The effectiveness of deterministic deconvolution for increased resolution and spatial accuracy of specific geologic features is further demonstrated by comparing results of deconvolved data with nondeconvolved data acquired along a 30-m transect immediately adjacent to a fresh quarry face. The results at this site support using deterministic deconvolution, which incorporates the GPR instrument's unique source wavelet, as a standard part of routine GPR data processing. ?? 2003 Elsevier B.V. All rights reserved.

Perspective: Maximum caliber is a general variational principle for dynamical systems

NASA Astrophysics Data System (ADS)

Dixit, Purushottam D.; Wagoner, Jason; Weistuch, Corey; Pressé, Steve; Ghosh, Kingshuk; Dill, Ken A.

2018-01-01

We review here Maximum Caliber (Max Cal), a general variational principle for inferring distributions of paths in dynamical processes and networks. Max Cal is to dynamical trajectories what the principle of maximum entropy is to equilibrium states or stationary populations. In Max Cal, you maximize a path entropy over all possible pathways, subject to dynamical constraints, in order to predict relative path weights. Many well-known relationships of non-equilibrium statistical physics—such as the Green-Kubo fluctuation-dissipation relations, Onsager's reciprocal relations, and Prigogine's minimum entropy production—are limited to near-equilibrium processes. Max Cal is more general. While it can readily derive these results under those limits, Max Cal is also applicable far from equilibrium. We give examples of Max Cal as a method of inference about trajectory distributions from limited data, finding reaction coordinates in bio-molecular simulations, and modeling the complex dynamics of non-thermal systems such as gene regulatory networks or the collective firing of neurons. We also survey its basis in principle and some limitations.

Divalent cation shrinks DNA but inhibits its compaction with trivalent cation.

PubMed

Tongu, Chika; Kenmotsu, Takahiro; Yoshikawa, Yuko; Zinchenko, Anatoly; Chen, Ning; Yoshikawa, Kenichi

2016-05-28

Our observation reveals the effects of divalent and trivalent cations on the higher-order structure of giant DNA (T4 DNA 166 kbp) by fluorescence microscopy. It was found that divalent cations, Mg(2+) and Ca(2+), inhibit DNA compaction induced by a trivalent cation, spermidine (SPD(3+)). On the other hand, in the absence of SPD(3+), divalent cations cause the shrinkage of DNA. As the control experiment, we have confirmed the minimum effect of monovalent cation, Na(+) on the DNA higher-order structure. We interpret the competition between 2+ and 3+ cations in terms of the change in the translational entropy of the counterions. For the compaction with SPD(3+), we consider the increase in translational entropy due to the ion-exchange of the intrinsic monovalent cations condensing on a highly charged polyelectrolyte, double-stranded DNA, by the 3+ cations. In contrast, the presence of 2+ cation decreases the gain of entropy contribution by the ion-exchange between monovalent and 3+ ions.

Perspective: Maximum caliber is a general variational principle for dynamical systems.

PubMed

Dixit, Purushottam D; Wagoner, Jason; Weistuch, Corey; Pressé, Steve; Ghosh, Kingshuk; Dill, Ken A

2018-01-07

We review here Maximum Caliber (Max Cal), a general variational principle for inferring distributions of paths in dynamical processes and networks. Max Cal is to dynamical trajectories what the principle of maximum entropy is to equilibrium states or stationary populations. In Max Cal, you maximize a path entropy over all possible pathways, subject to dynamical constraints, in order to predict relative path weights. Many well-known relationships of non-equilibrium statistical physics-such as the Green-Kubo fluctuation-dissipation relations, Onsager's reciprocal relations, and Prigogine's minimum entropy production-are limited to near-equilibrium processes. Max Cal is more general. While it can readily derive these results under those limits, Max Cal is also applicable far from equilibrium. We give examples of Max Cal as a method of inference about trajectory distributions from limited data, finding reaction coordinates in bio-molecular simulations, and modeling the complex dynamics of non-thermal systems such as gene regulatory networks or the collective firing of neurons. We also survey its basis in principle and some limitations.

Fast analytical spectral filtering methods for magnetic resonance perfusion quantification.

PubMed

Reddy, Kasireddy V; Mitra, Abhishek; Yalavarthy, Phaneendra K

2016-08-01

The deconvolution in the perfusion weighted imaging (PWI) plays an important role in quantifying the MR perfusion parameters. The PWI application to stroke and brain tumor studies has become a standard clinical practice. The standard approach for this deconvolution is oscillatory-limited singular value decomposition (oSVD) and frequency domain deconvolution (FDD). The FDD is widely recognized as the fastest approach currently available for deconvolution of MR perfusion data. In this work, two fast deconvolution methods (namely analytical fourier filtering and analytical showalter spectral filtering) are proposed. Through systematic evaluation, the proposed methods are shown to be computationally efficient and quantitatively accurate compared to FDD and oSVD.

Optimized Deconvolution for Maximum Axial Resolution in Three-Dimensional Aberration-Corrected Scanning Transmission Electron Microscopy

PubMed Central

Ramachandra, Ranjan; de Jonge, Niels

2012-01-01

Three-dimensional (3D) data sets were recorded of gold nanoparticles placed on both sides of silicon nitride membranes using focal series aberration-corrected scanning transmission electron microscopy (STEM). The deconvolution of the 3D datasets was optimized to obtain the highest possible axial resolution. The deconvolution involved two different point spread function (PSF)s, each calculated iteratively via blind deconvolution.. Supporting membranes of different thicknesses were tested to study the effect of beam broadening on the deconvolution. It was found that several iterations of deconvolution was efficient in reducing the imaging noise. With an increasing number of iterations, the axial resolution was increased, and most of the structural information was preserved. Additional iterations improved the axial resolution by maximal a factor of 4 to 6, depending on the particular dataset, and up to 8 nm maximal, but at the cost of a reduction of the lateral size of the nanoparticles in the image. Thus, the deconvolution procedure optimized for highest axial resolution is best suited for applications where one is interested in the 3D locations of nanoparticles only. PMID:22152090

Covariance hypotheses for LANDSAT data

NASA Technical Reports Server (NTRS)

Decell, H. P.; Peters, C.

1983-01-01

Two covariance hypotheses are considered for LANDSAT data acquired by sampling fields, one an autoregressive covariance structure and the other the hypothesis of exchangeability. A minimum entropy approximation of the first structure by the second is derived and shown to have desirable properties for incorporation into a mixture density estimation procedure. Results of a rough test of the exchangeability hypothesis are presented.

Minimum Entropy Autofocus Correction of Residual Range Cell Migration

DTIC Science & Technology

2017-03-02

reduced the residual to effectively a slowly varying bias on the order of a wavelength ( ∼ 3 cm ) which has negligible impact on the image focus. Fig...Fitzgerrell, and J. Beaver , “Two- dimensional phase gradient autofocus,” Proc. SPIE, vol. 4123, pp. 162– 173, 2000. [6] D. H. Brandwood, “A complex gradient

Constrained signal reconstruction from wavelet transform coefficients

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

Brislawn, C.M.

1991-12-31

A new method is introduced for reconstructing a signal from an incomplete sampling of its Discrete Wavelet Transform (DWT). The algorithm yields a minimum-norm estimate satisfying a priori upper and lower bounds on the signal. The method is based on a finite-dimensional representation theory for minimum-norm estimates of bounded signals developed by R.E. Cole. Cole`s work has its origins in earlier techniques of maximum-entropy spectral estimation due to Lang and McClellan, which were adapted by Steinhardt, Goodrich and Roberts for minimum-norm spectral estimation. Cole`s extension of their work provides a representation for minimum-norm estimates of a class of generalized transformsmore » in terms of general correlation data (not just DFT`s of autocorrelation lags, as in spectral estimation). One virtue of this great generality is that it includes the inverse DWT. 20 refs.« less

Comparison between deterministic and statistical wavelet estimation methods through predictive deconvolution: Seismic to well tie example from the North Sea

NASA Astrophysics Data System (ADS)

de Macedo, Isadora A. S.; da Silva, Carolina B.; de Figueiredo, J. J. S.; Omoboya, Bode

2017-01-01

Wavelet estimation as well as seismic-to-well tie procedures are at the core of every seismic interpretation workflow. In this paper we perform a comparative study of wavelet estimation methods for seismic-to-well tie. Two approaches to wavelet estimation are discussed: a deterministic estimation, based on both seismic and well log data, and a statistical estimation, based on predictive deconvolution and the classical assumptions of the convolutional model, which provides a minimum-phase wavelet. Our algorithms, for both wavelet estimation methods introduce a semi-automatic approach to determine the optimum parameters of deterministic wavelet estimation and statistical wavelet estimation and, further, to estimate the optimum seismic wavelets by searching for the highest correlation coefficient between the recorded trace and the synthetic trace, when the time-depth relationship is accurate. Tests with numerical data show some qualitative conclusions, which are probably useful for seismic inversion and interpretation of field data, by comparing deterministic wavelet estimation and statistical wavelet estimation in detail, especially for field data example. The feasibility of this approach is verified on real seismic and well data from Viking Graben field, North Sea, Norway. Our results also show the influence of the washout zones on well log data on the quality of the well to seismic tie.

Molecular mechanism of direct proflavine-DNA intercalation: evidence for drug-induced minimum base-stacking penalty pathway.

PubMed

Sasikala, Wilbee D; Mukherjee, Arnab

2012-10-11

DNA intercalation, a biophysical process of enormous clinical significance, has surprisingly eluded molecular understanding for several decades. With appropriate configurational restraint (to prevent dissociation) in all-atom metadynamics simulations, we capture the free energy surface of direct intercalation from minor groove-bound state for the first time using an anticancer agent proflavine. Mechanism along the minimum free energy path reveals that intercalation happens through a minimum base stacking penalty pathway where nonstacking parameters (Twist→Slide/Shift) change first, followed by base stacking parameters (Buckle/Roll→Rise). This mechanism defies the natural fluctuation hypothesis and provides molecular evidence for the drug-induced cavity formation hypothesis. The thermodynamic origin of the barrier is found to be a combination of entropy and desolvation energy.

SU-F-T-478: Effect of Deconvolution in Analysis of Mega Voltage Photon Beam Profiles

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

Muthukumaran, M; Manigandan, D; Murali, V

2016-06-15

Purpose: To study and compare the penumbra of 6 MV and 15 MV photon beam profiles after deconvoluting different volume ionization chambers. Methods: 0.125cc Semi-Flex chamber, Markus Chamber and PTW Farmer chamber were used to measure the in-plane and cross-plane profiles at 5 cm depth for 6 MV and 15 MV photons. The profiles were measured for various field sizes starting from 2×2 cm till 30×30 cm. PTW TBA scan software was used for the measurements and the “deconvolution” functionality in the software was used to remove the volume averaging effect due to finite volume of the chamber along lateralmore » and longitudinal directions for all the ionization chambers. The predicted true profile was compared and the change in penumbra before and after deconvolution was studied. Results: After deconvoluting the penumbra decreased by 1 mm for field sizes ranging from 2 × 2 cm till 20 x20 cm. This is observed for along both lateral and longitudinal directions. However for field sizes from 20 × 20 till 30 ×30 cm the difference in penumbra was around 1.2 till 1.8 mm. This was observed for both 6 MV and 15 MV photon beams. The penumbra was always lesser in the deconvoluted profiles for all the ionization chambers involved in the study. The variation in difference in penumbral values were in the order of 0.1 till 0.3 mm between the deconvoluted profile along lateral and longitudinal directions for all the chambers under study. Deconvolution of the profiles along longitudinal direction for Farmer chamber was not good and is not comparable with other deconvoluted profiles. Conclusion: The results of the deconvoluted profiles for 0.125cc and Markus chamber was comparable and the deconvolution functionality can be used to overcome the volume averaging effect.« less

An adaptive sparse deconvolution method for distinguishing the overlapping echoes of ultrasonic guided waves for pipeline crack inspection

NASA Astrophysics Data System (ADS)

Chang, Yong; Zi, Yanyang; Zhao, Jiyuan; Yang, Zhe; He, Wangpeng; Sun, Hailiang

2017-03-01

In guided wave pipeline inspection, echoes reflected from closely spaced reflectors generally overlap, meaning useful information is lost. To solve the overlapping problem, sparse deconvolution methods have been developed in the past decade. However, conventional sparse deconvolution methods have limitations in handling guided wave signals, because the input signal is directly used as the prototype of the convolution matrix, without considering the waveform change caused by the dispersion properties of the guided wave. In this paper, an adaptive sparse deconvolution (ASD) method is proposed to overcome these limitations. First, the Gaussian echo model is employed to adaptively estimate the column prototype of the convolution matrix instead of directly using the input signal as the prototype. Then, the convolution matrix is constructed upon the estimated results. Third, the split augmented Lagrangian shrinkage (SALSA) algorithm is introduced to solve the deconvolution problem with high computational efficiency. To verify the effectiveness of the proposed method, guided wave signals obtained from pipeline inspection are investigated numerically and experimentally. Compared to conventional sparse deconvolution methods, e.g. the {{l}1} -norm deconvolution method, the proposed method shows better performance in handling the echo overlap problem in the guided wave signal.

Hybrid sparse blind deconvolution: an implementation of SOOT algorithm to real data

NASA Astrophysics Data System (ADS)

Pakmanesh, Parvaneh; Goudarzi, Alireza; Kourki, Meisam

2018-06-01

Getting information of seismic data depends on deconvolution as an important processing step; it provides the reflectivity series by signal compression. This compression can be obtained by removing the wavelet effects on the traces. The recently blind deconvolution has provided reliable performance for sparse signal recovery. In this study, two deconvolution methods have been implemented to the seismic data; the convolution of these methods provides a robust spiking deconvolution approach. This hybrid deconvolution is applied using the sparse deconvolution (MM algorithm) and the Smoothed-One-Over-Two algorithm (SOOT) in a chain. The MM algorithm is based on the minimization of the cost function defined by standards l1 and l2. After applying the two algorithms to the seismic data, the SOOT algorithm provided well-compressed data with a higher resolution than the MM algorithm. The SOOT algorithm requires initial values to be applied for real data, such as the wavelet coefficients and reflectivity series that can be achieved through the MM algorithm. The computational cost of the hybrid method is high, and it is necessary to be implemented on post-stack or pre-stack seismic data of complex structure regions.

Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin; Razavi, Tara; Tapsoba, Dominique; Gobena, Adam; Weber, Frank; Pietroniro, Alain

2018-06-01

Snow has a unique characteristic in the water cycle, that is, snow falls during the entire winter season, but the discharge from snowmelt is typically delayed until the melting period and occurs in a relatively short period. Therefore, reliable observations from an optimal snow monitoring network are necessary for an efficient management of snowmelt water for flood prevention and hydropower generation. The Dual Entropy and Multiobjective Optimization is applied to design snow monitoring networks in La Grande River Basin in Québec and Columbia River Basin in British Columbia. While the networks are optimized to have the maximum amount of information with minimum redundancy based on entropy concepts, this study extends the traditional entropy applications to the hydrometric network design by introducing several improvements. First, several data quantization cases and their effects on the snow network design problems were explored. Second, the applicability the Snow Data Assimilation System (SNODAS) products as synthetic datasets of potential stations was demonstrated in the design of the snow monitoring network of the Columbia River Basin. Third, beyond finding the Pareto-optimal networks from the entropy with multi-objective optimization, the networks obtained for La Grande River Basin were further evaluated by applying three hydrologic models. The calibrated hydrologic models simulated discharges using the updated snow water equivalent data from the Pareto-optimal networks. Then, the model performances for high flows were compared to determine the best optimal network for enhanced spring runoff forecasting.

Systematic investigation of NLTE phenomena in the limit of small departures from LTE

NASA Astrophysics Data System (ADS)

Libby, S. B.; Graziani, F. R.; More, R. M.; Kato, T.

1997-04-01

In this paper, we begin a systematic study of Non-Local Thermal Equilibrium (NLTE) phenomena in near equilibrium (LTE) high energy density, highly radiative plasmas. It is shown that the principle of minimum entropy production rate characterizes NLTE steady states for average atom rate equations in the case of small departures form LTE. With the aid of a novel hohlraum-reaction box thought experiment, we use the principles of minimum entropy production and detailed balance to derive Onsager reciprocity relations for the NLTE responses of a near equilibrium sample to non-Planckian perturbations in different frequency groups. This result is a significant symmetry constraint on the linear corrections to Kirchoff's law. We envisage applying our strategy to a number of test problems which include: the NLTE corrections to the ionization state of an ion located near the edge of an otherwise LTE medium; the effect of a monochromatic radiation field perturbation on an LTE medium; the deviation of Rydberg state populations from LTE in recombining or ionizing plasmas; multi-electron temperature models such as that of Busquet; and finally, the effect of NLTE population shifts on opacity models.

Characterization of separability and entanglement in (2xD)- and (3xD)-dimensional systems by single-qubit and single-qutrit unitary transformations

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

Giampaolo, Salvatore M.; CNR-INFM Coherentia, Naples; CNISM Unita di Salerno and INFN Sezione di Napoli, Gruppo collegato di Salerno, Baronissi

2007-10-15

We investigate the geometric characterization of pure state bipartite entanglement of (2xD)- and (3xD)-dimensional composite quantum systems. To this aim, we analyze the relationship between states and their images under the action of particular classes of local unitary operations. We find that invariance of states under the action of single-qubit and single-qutrit transformations is a necessary and sufficient condition for separability. We demonstrate that in the (2xD)-dimensional case the von Neumann entropy of entanglement is a monotonic function of the minimum squared Euclidean distance between states and their images over the set of single qubit unitary transformations. Moreover, both inmore » the (2xD)- and in the (3xD)-dimensional cases the minimum squared Euclidean distance exactly coincides with the linear entropy [and thus as well with the tangle measure of entanglement in the (2xD)-dimensional case]. These results provide a geometric characterization of entanglement measures originally established in informational frameworks. Consequences and applications of the formalism to quantum critical phenomena in spin systems are discussed.« less

Post-processing of adaptive optics images based on frame selection and multi-frame blind deconvolution

NASA Astrophysics Data System (ADS)

Tian, Yu; Rao, Changhui; Wei, Kai

2008-07-01

The adaptive optics can only partially compensate the image blurred by atmospheric turbulence due to the observing condition and hardware restriction. A post-processing method based on frame selection and multi-frames blind deconvolution to improve images partially corrected by adaptive optics is proposed. The appropriate frames which are suitable for blind deconvolution from the recorded AO close-loop frames series are selected by the frame selection technique and then do the multi-frame blind deconvolution. There is no priori knowledge except for the positive constraint in blind deconvolution. It is benefit for the use of multi-frame images to improve the stability and convergence of the blind deconvolution algorithm. The method had been applied in the image restoration of celestial bodies which were observed by 1.2m telescope equipped with 61-element adaptive optical system at Yunnan Observatory. The results show that the method can effectively improve the images partially corrected by adaptive optics.

Thermodynamics of an ideal generalized gas: II. Means of order alpha.

PubMed

Lavenda, B H

2005-11-01

The property that power means are monotonically increasing functions of their order is shown to be the basis of the second laws not only for processes involving heat conduction, but also for processes involving deformations. This generalizes earlier work involving only pure heat conduction and underlines the incomparability of the internal energy and adiabatic potentials when expressed as powers of the adiabatic variable. In an L-potential equilibration, the final state will be one of maximum entropy, whereas in an entropy equilibration, the final state will be one of minimum L. Unlike classical equilibrium thermodynamic phase space, which lacks an intrinsic metric structure insofar as distances and other geometrical concepts do not have an intrinsic thermodynamic significance in such spaces, a metric space can be constructed for the power means: the distance between means of different order is related to the Carnot efficiency. In the ideal classical gas limit, the average change in the entropy is shown to be proportional to the difference between the Shannon and Rényi entropies for nonextensive systems that are multifractal in nature. The L potential, like the internal energy, is a Schur convex function of the empirical temperature, which satisfies Jensen's inequality, and serves as a measure of the tendency to uniformity in processes involving pure thermal conduction.

Characterizing Protease Specificity: How Many Substrates Do We Need?

PubMed Central

Schauperl, Michael; Fuchs, Julian E.; Waldner, Birgit J.; Huber, Roland G.; Kramer, Christian; Liedl, Klaus R.

2015-01-01

Calculation of cleavage entropies allows to quantify, map and compare protease substrate specificity by an information entropy based approach. The metric intrinsically depends on the number of experimentally determined substrates (data points). Thus a statistical analysis of its numerical stability is crucial to estimate the systematic error made by estimating specificity based on a limited number of substrates. In this contribution, we show the mathematical basis for estimating the uncertainty in cleavage entropies. Sets of cleavage entropies are calculated using experimental cleavage data and modeled extreme cases. By analyzing the underlying mathematics and applying statistical tools, a linear dependence of the metric in respect to 1/n was found. This allows us to extrapolate the values to an infinite number of samples and to estimate the errors. Analyzing the errors, a minimum number of 30 substrates was found to be necessary to characterize substrate specificity, in terms of amino acid variability, for a protease (S4-S4’) with an uncertainty of 5 percent. Therefore, we encourage experimental researchers in the protease field to record specificity profiles of novel proteases aiming to identify at least 30 peptide substrates of maximum sequence diversity. We expect a full characterization of protease specificity helpful to rationalize biological functions of proteases and to assist rational drug design. PMID:26559682

Entropy studies on beam distortion by atmospheric turbulence

NASA Astrophysics Data System (ADS)

Wu, Chensheng; Ko, Jonathan; Davis, Christopher C.

2015-09-01

When a beam propagates through atmospheric turbulence over a known distance, the target beam profile deviates from the projected profile of the beam on the receiver. Intuitively, the unwanted distortion provides information about the atmospheric turbulence. This information is crucial for guiding adaptive optic systems and improving beam propagation results. In this paper, we propose an entropy study based on the image from a plenoptic sensor to provide a measure of information content of atmospheric turbulence. In general, lower levels of atmospheric turbulence will have a smaller information size while higher levels of atmospheric turbulence will cause significant expansion of the information size, which may exceed the maximum capacity of a sensing system and jeopardize the reliability of an AO system. Therefore, the entropy function can be used to analyze the turbulence distortion and evaluate performance of AO systems. In fact, it serves as a metric that can tell the improvement of beam correction in each iteration step. In addition, it points out the limitation of an AO system at optimized correction as well as the minimum information needed for wavefront sensing to achieve certain levels of correction. In this paper, we will demonstrate the definition of the entropy function and how it is related to evaluating information (randomness) carried by atmospheric turbulence.

Blind source deconvolution for deep Earth seismology

NASA Astrophysics Data System (ADS)

Stefan, W.; Renaut, R.; Garnero, E. J.; Lay, T.

2007-12-01

We present an approach to automatically estimate an empirical source characterization of deep earthquakes recorded teleseismically and subsequently remove the source from the recordings by applying regularized deconvolution. A principle goal in this work is to effectively deblur the seismograms, resulting in more impulsive and narrower pulses, permitting better constraints in high resolution waveform analyses. Our method consists of two stages: (1) we first estimate the empirical source by automatically registering traces to their 1st principal component with a weighting scheme based on their deviation from this shape, we then use this shape as an estimation of the earthquake source. (2) We compare different deconvolution techniques to remove the source characteristic from the trace. In particular Total Variation (TV) regularized deconvolution is used which utilizes the fact that most natural signals have an underlying spareness in an appropriate basis, in this case, impulsive onsets of seismic arrivals. We show several examples of deep focus Fiji-Tonga region earthquakes for the phases S and ScS, comparing source responses for the separate phases. TV deconvolution is compared to the water level deconvolution, Tikenov deconvolution, and L1 norm deconvolution, for both data and synthetics. This approach significantly improves our ability to study subtle waveform features that are commonly masked by either noise or the earthquake source. Eliminating source complexities improves our ability to resolve deep mantle triplications, waveform complexities associated with possible double crossings of the post-perovskite phase transition, as well as increasing stability in waveform analyses used for deep mantle anisotropy measurements.

Thermodynamical transcription of density functional theory with minimum Fisher information

NASA Astrophysics Data System (ADS)

Nagy, Á.

2018-03-01

Ghosh, Berkowitz and Parr designed a thermodynamical transcription of the ground-state density functional theory and introduced a local temperature that varies from point to point. The theory, however, is not unique because the kinetic energy density is not uniquely defined. Here we derive the expression of the phase-space Fisher information in the GBP theory taking the inverse temperature as the Fisher parameter. It is proved that this Fisher information takes its minimum for the case of constant temperature. This result is consistent with the recently proven theorem that the phase-space Shannon information entropy attains its maximum at constant temperature.

Developing Soil Moisture Profiles Utilizing Remotely Sensed MW and TIR Based SM Estimates Through Principle of Maximum Entropy

NASA Astrophysics Data System (ADS)

Mishra, V.; Cruise, J. F.; Mecikalski, J. R.

2015-12-01

Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Earlier studies show that the principle of maximum entropy (POME) can be utilized to develop vertical soil moisture profiles with accuracy (MAE of about 1% for a monotonically dry profile; nearly 2% for monotonically wet profiles and 3.8% for mixed profiles) with minimum constraints (surface, mean and bottom soil moisture contents). In this study, the constraints for the vertical soil moisture profiles were obtained from remotely sensed data. Low resolution (25 km) MW soil moisture estimates (AMSR-E) were downscaled to 4 km using a soil evaporation efficiency index based disaggregation approach. The downscaled MW soil moisture estimates served as a surface boundary condition, while 4 km resolution TIR based Atmospheric Land Exchange Inverse (ALEXI) estimates provided the required mean root-zone soil moisture content. Bottom soil moisture content is assumed to be a soil dependent constant. Mulit-year (2002-2011) gridded profiles were developed for the southeastern United States using the POME method. The soil moisture profiles were compared to those generated in land surface models (Land Information System (LIS) and an agricultural model DSSAT) along with available NRCS SCAN sites in the study region. The end product, spatial soil moisture profiles, can be assimilated into agricultural and hydrologic models in lieu of precipitation for data scarce regions.Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Previous studies have shown that the principle of maximum entropy (POME) can be utilized with minimal constraints to develop vertical soil moisture profiles with accuracy (MAE = 1% for monotonically dry profiles; MAE = 2% for monotonically wet profiles and MAE = 3.8% for mixed profiles) when compared to laboratory and field data. In this study, vertical soil moisture profiles were developed using the POME model to evaluate an irrigation schedule over a maze field in north central Alabama (USA). The model was validated using both field data and a physically based mathematical model. The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles within the field area for 6 different soil types. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with loss of about 1.9% of the total applied irrigation water. However, areas of fine-textured soil (i.e. silty clay) resulted in plant stress of nearly 30% of the available moisture content due to insufficient water supply on the last day of the drying phase of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, with minimum input requirements.

Liquid chromatography with diode array detection combined with spectral deconvolution for the analysis of some diterpene esters in Arabica coffee brew.

PubMed

Erny, Guillaume L; Moeenfard, Marzieh; Alves, Arminda

2015-02-01

In this manuscript, the separation of kahweol and cafestol esters from Arabica coffee brews was investigated using liquid chromatography with a diode array detector. When detected in conjunction, cafestol, and kahweol esters were eluted together, but, after optimization, the kahweol esters could be selectively detected by setting the wavelength at 290 nm to allow their quantification. Such an approach was not possible for the cafestol esters, and spectral deconvolution was used to obtain deconvoluted chromatograms. In each of those chromatograms, the four esters were baseline separated allowing for the quantification of the eight targeted compounds. Because kahweol esters could be quantified either using the chromatogram obtained by setting the wavelength at 290 nm or using the deconvoluted chromatogram, those compounds were used to compare the analytical performances. Slightly better limits of detection were obtained using the deconvoluted chromatogram. Identical concentrations were found in a real sample with both approaches. The peak areas in the deconvoluted chromatograms were repeatable (intraday repeatability of 0.8%, interday repeatability of 1.0%). This work demonstrates the accuracy of spectral deconvolution when using liquid chromatography to mathematically separate coeluting compounds using the full spectra recorded by a diode array detector. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space

PubMed Central

Lonardi, Stefano; Duma, Denisa; Alpert, Matthew; Cordero, Francesca; Beccuti, Marco; Bhat, Prasanna R.; Wu, Yonghui; Ciardo, Gianfranco; Alsaihati, Burair; Ma, Yaqin; Wanamaker, Steve; Resnik, Josh; Bozdag, Serdar; Luo, Ming-Cheng; Close, Timothy J.

2013-01-01

For the vast majority of species – including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding. PMID:23592960

Combinatorial pooling enables selective sequencing of the barley gene space.

PubMed

Lonardi, Stefano; Duma, Denisa; Alpert, Matthew; Cordero, Francesca; Beccuti, Marco; Bhat, Prasanna R; Wu, Yonghui; Ciardo, Gianfranco; Alsaihati, Burair; Ma, Yaqin; Wanamaker, Steve; Resnik, Josh; Bozdag, Serdar; Luo, Ming-Cheng; Close, Timothy J

2013-04-01

For the vast majority of species - including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

Calibration of Wide-Field Deconvolution Microscopy for Quantitative Fluorescence Imaging

PubMed Central

Lee, Ji-Sook; Wee, Tse-Luen (Erika); Brown, Claire M.

2014-01-01

Deconvolution enhances contrast in fluorescence microscopy images, especially in low-contrast, high-background wide-field microscope images, improving characterization of features within the sample. Deconvolution can also be combined with other imaging modalities, such as confocal microscopy, and most software programs seek to improve resolution as well as contrast. Quantitative image analyses require instrument calibration and with deconvolution, necessitate that this process itself preserves the relative quantitative relationships between fluorescence intensities. To ensure that the quantitative nature of the data remains unaltered, deconvolution algorithms need to be tested thoroughly. This study investigated whether the deconvolution algorithms in AutoQuant X3 preserve relative quantitative intensity data. InSpeck Green calibration microspheres were prepared for imaging, z-stacks were collected using a wide-field microscope, and the images were deconvolved using the iterative deconvolution algorithms with default settings. Afterwards, the mean intensities and volumes of microspheres in the original and the deconvolved images were measured. Deconvolved data sets showed higher average microsphere intensities and smaller volumes than the original wide-field data sets. In original and deconvolved data sets, intensity means showed linear relationships with the relative microsphere intensities given by the manufacturer. Importantly, upon normalization, the trend lines were found to have similar slopes. In original and deconvolved images, the volumes of the microspheres were quite uniform for all relative microsphere intensities. We were able to show that AutoQuant X3 deconvolution software data are quantitative. In general, the protocol presented can be used to calibrate any fluorescence microscope or image processing and analysis procedure. PMID:24688321

Detection of cracks in shafts with the Approximated Entropy algorithm

NASA Astrophysics Data System (ADS)

Sampaio, Diego Luchesi; Nicoletti, Rodrigo

2016-05-01

The Approximate Entropy is a statistical calculus used primarily in the fields of Medicine, Biology, and Telecommunication for classifying and identifying complex signal data. In this work, an Approximate Entropy algorithm is used to detect cracks in a rotating shaft. The signals of the cracked shaft are obtained from numerical simulations of a de Laval rotor with breathing cracks modelled by the Fracture Mechanics. In this case, one analysed the vertical displacements of the rotor during run-up transients. The results show the feasibility of detecting cracks from 5% depth, irrespective of the unbalance of the rotating system and crack orientation in the shaft. The results also show that the algorithm can differentiate the occurrence of crack only, misalignment only, and crack + misalignment in the system. However, the algorithm is sensitive to intrinsic parameters p (number of data points in a sample vector) and f (fraction of the standard deviation that defines the minimum distance between two sample vectors), and good results are only obtained by appropriately choosing their values according to the sampling rate of the signal.

Minimax Quantum Tomography: Estimators and Relative Entropy Bounds

DOE PAGES

Ferrie, Christopher; Blume-Kohout, Robin

2016-03-04

A minimax estimator has the minimum possible error (“risk”) in the worst case. Here we construct the first minimax estimators for quantum state tomography with relative entropy risk. The minimax risk of nonadaptive tomography scales as O (1/more » $$\\sqrt{N}$$ ) —in contrast to that of classical probability estimation, which is O (1/N) —where N is the number of copies of the quantum state used. We trace this deficiency to sampling mismatch: future observations that determine risk may come from a different sample space than the past data that determine the estimate. Lastly, this makes minimax estimators very biased, and we propose a computationally tractable alternative with similar behavior in the worst case, but superior accuracy on most states.« less

Gamma-Ray Simulated Spectrum Deconvolution of a LaBr₃ 1-in. x 1-in. Scintillator for Nondestructive ATR Fuel Burnup On-Site Predictions

DOE PAGES

Navarro, Jorge; Ring, Terry A.; Nigg, David W.

2015-03-01

A deconvolution method for a LaBr₃ 1"x1" detector for nondestructive Advanced Test Reactor (ATR) fuel burnup applications was developed. The method consisted of obtaining the detector response function, applying a deconvolution algorithm to 1”x1” LaBr₃ simulated, data along with evaluating the effects that deconvolution have on nondestructively determining ATR fuel burnup. The simulated response function of the detector was obtained using MCNPX as well with experimental data. The Maximum-Likelihood Expectation Maximization (MLEM) deconvolution algorithm was selected to enhance one-isotope source-simulated and fuel- simulated spectra. The final evaluation of the study consisted of measuring the performance of the fuel burnup calibrationmore » curve for the convoluted and deconvoluted cases. The methodology was developed in order to help design a reliable, high resolution, rugged and robust detection system for the ATR fuel canal capable of collecting high performance data for model validation, along with a system that can calculate burnup and using experimental scintillator detector data.« less

Seismic interferometry by multidimensional deconvolution as a means to compensate for anisotropic illumination

NASA Astrophysics Data System (ADS)

Wapenaar, K.; van der Neut, J.; Ruigrok, E.; Draganov, D.; Hunziker, J.; Slob, E.; Thorbecke, J.; Snieder, R.

2008-12-01

It is well-known that under specific conditions the crosscorrelation of wavefields observed at two receivers yields the impulse response between these receivers. This principle is known as 'Green's function retrieval' or 'seismic interferometry'. Recently it has been recognized that in many situations it can be advantageous to replace the correlation process by deconvolution. One of the advantages is that deconvolution compensates for the waveform emitted by the source; another advantage is that it is not necessary to assume that the medium is lossless. The approaches that have been developed to date employ a 1D deconvolution process. We propose a method for seismic interferometry by multidimensional deconvolution and show that under specific circumstances the method compensates for irregularities in the source distribution. This is an important difference with crosscorrelation methods, which rely on the condition that waves are equipartitioned. This condition is for example fulfilled when the sources are regularly distributed along a closed surface and the power spectra of the sources are identical. The proposed multidimensional deconvolution method compensates for anisotropic illumination, without requiring knowledge about the positions and the spectra of the sources.

Iterative and function-continuation Fourier deconvolution methods for enhancing mass spectrometer resolution

NASA Technical Reports Server (NTRS)

Ioup, J. W.; Ioup, G. E.; Rayborn, G. H., Jr.; Wood, G. M., Jr.; Upchurch, B. T.

1984-01-01

Mass spectrometer data in the form of ion current versus mass-to-charge ratio often include overlapping mass peaks, especially in low- and medium-resolution instruments. Numerical deconvolution of such data effectively enhances the resolution by decreasing the overlap of mass peaks. In this paper two approaches to deconvolution are presented: a function-domain iterative technique and a Fourier transform method which uses transform-domain function-continuation. Both techniques include data smoothing to reduce the sensitivity of the deconvolution to noise. The efficacy of these methods is demonstrated through application to representative mass spectrometer data and the deconvolved results are discussed and compared to data obtained from a spectrometer with sufficient resolution to achieve separation of the mass peaks studied. A case for which the deconvolution is seriously affected by Gibbs oscillations is analyzed.

Broadband ion mobility deconvolution for rapid analysis of complex mixtures.

PubMed

Pettit, Michael E; Brantley, Matthew R; Donnarumma, Fabrizio; Murray, Kermit K; Solouki, Touradj

2018-05-04

High resolving power ion mobility (IM) allows for accurate characterization of complex mixtures in high-throughput IM mass spectrometry (IM-MS) experiments. We previously demonstrated that pure component IM-MS data can be extracted from IM unresolved post-IM/collision-induced dissociation (CID) MS data using automated ion mobility deconvolution (AIMD) software [Matthew Brantley, Behrooz Zekavat, Brett Harper, Rachel Mason, and Touradj Solouki, J. Am. Soc. Mass Spectrom., 2014, 25, 1810-1819]. In our previous reports, we utilized a quadrupole ion filter for m/z-isolation of IM unresolved monoisotopic species prior to post-IM/CID MS. Here, we utilize a broadband IM-MS deconvolution strategy to remove the m/z-isolation requirement for successful deconvolution of IM unresolved peaks. Broadband data collection has throughput and multiplexing advantages; hence, elimination of the ion isolation step reduces experimental run times and thus expands the applicability of AIMD to high-throughput bottom-up proteomics. We demonstrate broadband IM-MS deconvolution of two separate and unrelated pairs of IM unresolved isomers (viz., a pair of isomeric hexapeptides and a pair of isomeric trisaccharides) in a simulated complex mixture. Moreover, we show that broadband IM-MS deconvolution improves high-throughput bottom-up characterization of a proteolytic digest of rat brain tissue. To our knowledge, this manuscript is the first to report successful deconvolution of pure component IM and MS data from an IM-assisted data-independent analysis (DIA) or HDMSE dataset.

Optimization of rainfall networks using information entropy and temporal variability analysis

NASA Astrophysics Data System (ADS)

Wang, Wenqi; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-04-01

Rainfall networks are the most direct sources of precipitation data and their optimization and evaluation are essential and important. Information entropy can not only represent the uncertainty of rainfall distribution but can also reflect the correlation and information transmission between rainfall stations. Using entropy this study performs optimization of rainfall networks that are of similar size located in two big cities in China, Shanghai (in Yangtze River basin) and Xi'an (in Yellow River basin), with respect to temporal variability analysis. Through an easy-to-implement greedy ranking algorithm based on the criterion called, Maximum Information Minimum Redundancy (MIMR), stations of the networks in the two areas (each area is further divided into two subareas) are ranked during sliding inter-annual series and under different meteorological conditions. It is found that observation series with different starting days affect the ranking, alluding to the temporal variability during network evaluation. We propose a dynamic network evaluation framework for considering temporal variability, which ranks stations under different starting days with a fixed time window (1-year, 2-year, and 5-year). Therefore, we can identify rainfall stations which are temporarily of importance or redundancy and provide some useful suggestions for decision makers. The proposed framework can serve as a supplement for the primary MIMR optimization approach. In addition, during different periods (wet season or dry season) the optimal network from MIMR exhibits differences in entropy values and the optimal network from wet season tended to produce higher entropy values. Differences in spatial distribution of the optimal networks suggest that optimizing the rainfall network for changing meteorological conditions may be more recommended.

Ovarian Cancer Differential Interactome and Network Entropy Analysis Reveal New Candidate Biomarkers.

PubMed

Ayyildiz, Dilara; Gov, Esra; Sinha, Raghu; Arga, Kazim Yalcin

2017-05-01

Ovarian cancer is one of the most common cancers and has a high mortality rate due to insidious symptoms and lack of robust diagnostics. A hitherto understudied concept in cancer pathogenesis may offer new avenues for innovation in ovarian cancer biomarker development. Cancer cells are characterized by an increase in network entropy, and several studies have exploited this concept to identify disease-associated gene and protein modules. We report in this study the changes in protein-protein interactions (PPIs) in ovarian cancer within a differential network (interactome) analysis framework utilizing the entropy concept and gene expression data. A compendium of six transcriptome datasets that included 140 samples from laser microdissected epithelial cells of ovarian cancer patients and 51 samples from healthy population was obtained from Gene Expression Omnibus, and the high confidence human protein interactome (31,465 interactions among 10,681 proteins) was used. The uncertainties of the up- or downregulation of PPIs in ovarian cancer were estimated through an entropy formulation utilizing combined expression levels of genes, and the interacting protein pairs with minimum uncertainty were identified. We identified 105 proteins with differential PPI patterns scattered in 11 modules, each indicating significantly affected biological pathways in ovarian cancer such as DNA repair, cell proliferation-related mechanisms, nucleoplasmic translocation of estrogen receptor, extracellular matrix degradation, and inflammation response. In conclusion, we suggest several PPIs as biomarker candidates for ovarian cancer and discuss their future biological implications as potential molecular targets for pharmaceutical development as well. In addition, network entropy analysis is a concept that deserves greater research attention for diagnostic innovation in oncology and tumor pathogenesis.

Using deconvolution to improve the metrological performance of the grid method

NASA Astrophysics Data System (ADS)

Grédiac, Michel; Sur, Frédéric; Badulescu, Claudiu; Mathias, Jean-Denis

2013-06-01

The use of various deconvolution techniques to enhance strain maps obtained with the grid method is addressed in this study. Since phase derivative maps obtained with the grid method can be approximated by their actual counterparts convolved by the envelope of the kernel used to extract phases and phase derivatives, non-blind restoration techniques can be used to perform deconvolution. Six deconvolution techniques are presented and employed to restore a synthetic phase derivative map, namely direct deconvolution, regularized deconvolution, the Richardson-Lucy algorithm and Wiener filtering, the last two with two variants concerning their practical implementations. Obtained results show that the noise that corrupts the grid images must be thoroughly taken into account to limit its effect on the deconvolved strain maps. The difficulty here is that the noise on the grid image yields a spatially correlated noise on the strain maps. In particular, numerical experiments on synthetic data show that direct and regularized deconvolutions are unstable when noisy data are processed. The same remark holds when Wiener filtering is employed without taking into account noise autocorrelation. On the other hand, the Richardson-Lucy algorithm and Wiener filtering with noise autocorrelation provide deconvolved maps where the impact of noise remains controlled within a certain limit. It is also observed that the last technique outperforms the Richardson-Lucy algorithm. Two short examples of actual strain fields restoration are finally shown. They deal with asphalt and shape memory alloy specimens. The benefits and limitations of deconvolution are presented and discussed in these two cases. The main conclusion is that strain maps are correctly deconvolved when the signal-to-noise ratio is high and that actual noise in the actual strain maps must be more specifically characterized than in the current study to address higher noise levels with Wiener filtering.

Least-squares (LS) deconvolution of a series of overlapping cortical auditory evoked potentials: a simulation and experimental study

NASA Astrophysics Data System (ADS)

Bardy, Fabrice; Van Dun, Bram; Dillon, Harvey; Cowan, Robert

2014-08-01

Objective. To evaluate the viability of disentangling a series of overlapping ‘cortical auditory evoked potentials’ (CAEPs) elicited by different stimuli using least-squares (LS) deconvolution, and to assess the adaptation of CAEPs for different stimulus onset-asynchronies (SOAs). Approach. Optimal aperiodic stimulus sequences were designed by controlling the condition number of matrices associated with the LS deconvolution technique. First, theoretical considerations of LS deconvolution were assessed in simulations in which multiple artificial overlapping responses were recovered. Second, biological CAEPs were recorded in response to continuously repeated stimulus trains containing six different tone-bursts with frequencies 8, 4, 2, 1, 0.5, 0.25 kHz separated by SOAs jittered around 150 (120-185), 250 (220-285) and 650 (620-685) ms. The control condition had a fixed SOA of 1175 ms. In a second condition, using the same SOAs, trains of six stimuli were separated by a silence gap of 1600 ms. Twenty-four adults with normal hearing (<20 dB HL) were assessed. Main results. Results showed disentangling of a series of overlapping responses using LS deconvolution on simulated waveforms as well as on real EEG data. The use of rapid presentation and LS deconvolution did not however, allow the recovered CAEPs to have a higher signal-to-noise ratio than for slowly presented stimuli. The LS deconvolution technique enables the analysis of a series of overlapping responses in EEG. Significance. LS deconvolution is a useful technique for the study of adaptation mechanisms of CAEPs for closely spaced stimuli whose characteristics change from stimulus to stimulus. High-rate presentation is necessary to develop an understanding of how the auditory system encodes natural speech or other intrinsically high-rate stimuli.

Enhancing multi-spot structured illumination microscopy with fluorescence difference

NASA Astrophysics Data System (ADS)

Ward, Edward N.; Torkelsen, Frida H.; Pal, Robert

2018-03-01

Structured illumination microscopy is a super-resolution technique used extensively in biological research. However, this technique is limited in the maximum possible resolution increase. Here we report the results of simulations of a novel enhanced multi-spot structured illumination technique. This method combines the super-resolution technique of difference microscopy with structured illumination deconvolution. Initial results give at minimum a 1.4-fold increase in resolution over conventional structured illumination in a low-noise environment. This new technique also has the potential to be expanded to further enhance axial resolution with three-dimensional difference microscopy. The requirement for precise pattern determination in this technique also led to the development of a new pattern estimation algorithm which proved more efficient and reliable than other methods tested.

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

PubMed

Chen, Zhaoxue; Chen, Hao

2014-01-01

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

HMM for hyperspectral spectrum representation and classification with endmember entropy vectors

NASA Astrophysics Data System (ADS)

Arabi, Samir Y. W.; Fernandes, David; Pizarro, Marco A.

2015-10-01

The Hyperspectral images due to its good spectral resolution are extensively used for classification, but its high number of bands requires a higher bandwidth in the transmission data, a higher data storage capability and a higher computational capability in processing systems. This work presents a new methodology for hyperspectral data classification that can work with a reduced number of spectral bands and achieve good results, comparable with processing methods that require all hyperspectral bands. The proposed method for hyperspectral spectra classification is based on the Hidden Markov Model (HMM) associated to each Endmember (EM) of a scene and the conditional probabilities of each EM belongs to each other EM. The EM conditional probability is transformed in EM vector entropy and those vectors are used as reference vectors for the classes in the scene. The conditional probability of a spectrum that will be classified is also transformed in a spectrum entropy vector, which is classified in a given class by the minimum ED (Euclidian Distance) among it and the EM entropy vectors. The methodology was tested with good results using AVIRIS spectra of a scene with 13 EM considering the full 209 bands and the reduced spectral bands of 128, 64 and 32. For the test area its show that can be used only 32 spectral bands instead of the original 209 bands, without significant loss in the classification process.

Scalar flux modeling in turbulent flames using iterative deconvolution

NASA Astrophysics Data System (ADS)

Nikolaou, Z. M.; Cant, R. S.; Vervisch, L.

2018-04-01

In the context of large eddy simulations, deconvolution is an attractive alternative for modeling the unclosed terms appearing in the filtered governing equations. Such methods have been used in a number of studies for non-reacting and incompressible flows; however, their application in reacting flows is limited in comparison. Deconvolution methods originate from clearly defined operations, and in theory they can be used in order to model any unclosed term in the filtered equations including the scalar flux. In this study, an iterative deconvolution algorithm is used in order to provide a closure for the scalar flux term in a turbulent premixed flame by explicitly filtering the deconvoluted fields. The assessment of the method is conducted a priori using a three-dimensional direct numerical simulation database of a turbulent freely propagating premixed flame in a canonical configuration. In contrast to most classical a priori studies, the assessment is more stringent as it is performed on a much coarser mesh which is constructed using the filtered fields as obtained from the direct simulations. For the conditions tested in this study, deconvolution is found to provide good estimates both of the scalar flux and of its divergence.

Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization

NASA Astrophysics Data System (ADS)

Raghunath, N.; Faber, T. L.; Suryanarayanan, S.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.

Rapid perfusion quantification using Welch-Satterthwaite approximation and analytical spectral filtering

NASA Astrophysics Data System (ADS)

Krishnan, Karthik; Reddy, Kasireddy V.; Ajani, Bhavya; Yalavarthy, Phaneendra K.

2017-02-01

CT and MR perfusion weighted imaging (PWI) enable quantification of perfusion parameters in stroke studies. These parameters are calculated from the residual impulse response function (IRF) based on a physiological model for tissue perfusion. The standard approach for estimating the IRF is deconvolution using oscillatory-limited singular value decomposition (oSVD) or Frequency Domain Deconvolution (FDD). FDD is widely recognized as the fastest approach currently available for deconvolution of CT Perfusion/MR PWI. In this work, three faster methods are proposed. The first is a direct (model based) crude approximation to the final perfusion quantities (Blood flow, Blood volume, Mean Transit Time and Delay) using the Welch-Satterthwaite approximation for gamma fitted concentration time curves (CTC). The second method is a fast accurate deconvolution method, we call Analytical Fourier Filtering (AFF). The third is another fast accurate deconvolution technique using Showalter's method, we call Analytical Showalter's Spectral Filtering (ASSF). Through systematic evaluation on phantom and clinical data, the proposed methods are shown to be computationally more than twice as fast as FDD. The two deconvolution based methods, AFF and ASSF, are also shown to be quantitatively accurate compared to FDD and oSVD.

Highly Entangled, Non-random Subspaces of Tensor Products from Quantum Groups

NASA Astrophysics Data System (ADS)

Brannan, Michael; Collins, Benoît

2018-03-01

In this paper we describe a class of highly entangled subspaces of a tensor product of finite-dimensional Hilbert spaces arising from the representation theory of free orthogonal quantum groups. We determine their largest singular values and obtain lower bounds for the minimum output entropy of the corresponding quantum channels. An application to the construction of d-positive maps on matrix algebras is also presented.

Maximum nonlocality and minimum uncertainty using magic states

NASA Astrophysics Data System (ADS)

Howard, Mark

2015-04-01

We prove that magic states from the Clifford hierarchy give optimal solutions for tasks involving nonlocality and entropic uncertainty with respect to Pauli measurements. For both the nonlocality and uncertainty tasks, stabilizer states are the worst possible pure states, so our solutions have an operational interpretation as being highly nonstabilizer. The optimal strategy for a qudit version of the Clauser-Horne-Shimony-Holt game in prime dimensions is achieved by measuring maximally entangled states that are isomorphic to single-qudit magic states. These magic states have an appealingly simple form, and our proof shows that they are "balanced" with respect to all but one of the mutually unbiased stabilizer bases. Of all equatorial qudit states, magic states minimize the average entropic uncertainties for collision entropy and also, for small prime dimensions, min-entropy, a fact that may have implications for cryptography.

Seismic interferometry by crosscorrelation and by multidimensional deconvolution: a systematic comparison

NASA Astrophysics Data System (ADS)

Wapenaar, Kees; van der Neut, Joost; Ruigrok, Elmer; Draganov, Deyan; Hunziker, Juerg; Slob, Evert; Thorbecke, Jan; Snieder, Roel

2010-05-01

In recent years, seismic interferometry (or Green's function retrieval) has led to many applications in seismology (exploration, regional and global), underwater acoustics and ultrasonics. One of the explanations for this broad interest lies in the simplicity of the methodology. In passive data applications a simple crosscorrelation of responses at two receivers gives the impulse response (Green's function) at one receiver as if there were a source at the position of the other. In controlled-source applications the procedure is similar, except that it involves in addition a summation along the sources. It has also been recognized that the simple crosscorrelation approach has its limitations. From the various theoretical models it follows that there are a number of underlying assumptions for retrieving the Green's function by crosscorrelation. The most important assumptions are that the medium is lossless and that the waves are equipartitioned. In heuristic terms the latter condition means that the receivers are illuminated isotropically from all directions, which is for example achieved when the sources are regularly distributed along a closed surface, the sources are mutually uncorrelated and their power spectra are identical. Despite the fact that in practical situations these conditions are at most only partly fulfilled, the results of seismic interferometry are generally quite robust, but the retrieved amplitudes are unreliable and the results are often blurred by artifacts. Several researchers have proposed to address some of the shortcomings by replacing the correlation process by deconvolution. In most cases the employed deconvolution procedure is essentially 1-D (i.e., trace-by-trace deconvolution). This compensates the anelastic losses, but it does not account for the anisotropic illumination of the receivers. To obtain more accurate results, seismic interferometry by deconvolution should acknowledge the 3-D nature of the seismic wave field. Hence, from a theoretical point of view, the trace-by-trace process should be replaced by a full 3-D wave field deconvolution process. Interferometry by multidimensional deconvolution is more accurate than the trace-by-trace correlation and deconvolution approaches but the processing is more involved. In the presentation we will give a systematic analysis of seismic interferometry by crosscorrelation versus multi-dimensional deconvolution and discuss applications of both approaches.

An optimized algorithm for multiscale wideband deconvolution of radio astronomical images

NASA Astrophysics Data System (ADS)

Offringa, A. R.; Smirnov, O.

2017-10-01

We describe a new multiscale deconvolution algorithm that can also be used in a multifrequency mode. The algorithm only affects the minor clean loop. In single-frequency mode, the minor loop of our improved multiscale algorithm is over an order of magnitude faster than the casa multiscale algorithm, and produces results of similar quality. For multifrequency deconvolution, a technique named joined-channel cleaning is used. In this mode, the minor loop of our algorithm is two to three orders of magnitude faster than casa msmfs. We extend the multiscale mode with automated scale-dependent masking, which allows structures to be cleaned below the noise. We describe a new scale-bias function for use in multiscale cleaning. We test a second deconvolution method that is a variant of the moresane deconvolution technique, and uses a convex optimization technique with isotropic undecimated wavelets as dictionary. On simple well-calibrated data, the convex optimization algorithm produces visually more representative models. On complex or imperfect data, the convex optimization algorithm has stability issues.

New regularization scheme for blind color image deconvolution

NASA Astrophysics Data System (ADS)

Chen, Li; He, Yu; Yap, Kim-Hui

2011-01-01

This paper proposes a new regularization scheme to address blind color image deconvolution. Color images generally have a significant correlation among the red, green, and blue channels. Conventional blind monochromatic deconvolution algorithms handle each color image channels independently, thereby ignoring the interchannel correlation present in the color images. In view of this, a unified regularization scheme for image is developed to recover edges of color images and reduce color artifacts. In addition, by using the color image properties, a spectral-based regularization operator is adopted to impose constraints on the blurs. Further, this paper proposes a reinforcement regularization framework that integrates a soft parametric learning term in addressing blind color image deconvolution. A blur modeling scheme is developed to evaluate the relevance of manifold parametric blur structures, and the information is integrated into the deconvolution scheme. An optimization procedure called alternating minimization is then employed to iteratively minimize the image- and blur-domain cost functions. Experimental results show that the method is able to achieve satisfactory restored color images under different blurring conditions.

Methods and Apparatus for Reducing Multipath Signal Error Using Deconvolution

NASA Technical Reports Server (NTRS)

Kumar, Rajendra (Inventor); Lau, Kenneth H. (Inventor)

1999-01-01

A deconvolution approach to adaptive signal processing has been applied to the elimination of signal multipath errors as embodied in one preferred embodiment in a global positioning system receiver. The method and receiver of the present invention estimates then compensates for multipath effects in a comprehensive manner. Application of deconvolution, along with other adaptive identification and estimation techniques, results in completely novel GPS (Global Positioning System) receiver architecture.

Improving space debris detection in GEO ring using image deconvolution

NASA Astrophysics Data System (ADS)

Núñez, Jorge; Núñez, Anna; Montojo, Francisco Javier; Condominas, Marta

2015-07-01

In this paper we present a method based on image deconvolution to improve the detection of space debris, mainly in the geostationary ring. Among the deconvolution methods we chose the iterative Richardson-Lucy (R-L), as the method that achieves better goals with a reasonable amount of computation. For this work, we used two sets of real 4096 × 4096 pixel test images obtained with the Telescope Fabra-ROA at Montsec (TFRM). Using the first set of data, we establish the optimal number of iterations in 7, and applying the R-L method with 7 iterations to the images, we show that the astrometric accuracy does not vary significantly while the limiting magnitude of the deconvolved images increases significantly compared to the original ones. The increase is in average about 1.0 magnitude, which means that objects up to 2.5 times fainter can be detected after deconvolution. The application of the method to the second set of test images, which includes several faint objects, shows that, after deconvolution, up to four previously undetected faint objects are detected in a single frame. Finally, we carried out a study of some economic aspects of applying the deconvolution method, showing that an important economic impact can be envisaged.

Richardson-Lucy deconvolution as a general tool for combining images with complementary strengths.

PubMed

Ingaramo, Maria; York, Andrew G; Hoogendoorn, Eelco; Postma, Marten; Shroff, Hari; Patterson, George H

2014-03-17

We use Richardson-Lucy (RL) deconvolution to combine multiple images of a simulated object into a single image in the context of modern fluorescence microscopy techniques. RL deconvolution can merge images with very different point-spread functions, such as in multiview light-sheet microscopes,1, 2 while preserving the best resolution information present in each image. We show that RL deconvolution is also easily applied to merge high-resolution, high-noise images with low-resolution, low-noise images, relevant when complementing conventional microscopy with localization microscopy. We also use RL deconvolution to merge images produced by different simulated illumination patterns, relevant to structured illumination microscopy (SIM)3, 4 and image scanning microscopy (ISM). The quality of our ISM reconstructions is at least as good as reconstructions using standard inversion algorithms for ISM data, but our method follows a simpler recipe that requires no mathematical insight. Finally, we apply RL deconvolution to merge a series of ten images with varying signal and resolution levels. This combination is relevant to gated stimulated-emission depletion (STED) microscopy, and shows that merges of high-quality images are possible even in cases for which a non-iterative inversion algorithm is unknown. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dense deconvolution net: Multi path fusion and dense deconvolution for high resolution skin lesion segmentation.

PubMed

He, Xinzi; Yu, Zhen; Wang, Tianfu; Lei, Baiying; Shi, Yiyan

2018-01-01

Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region. To handle these challenges, we propose a novel skin lesion segmentation network via a very deep dense deconvolution network based on dermoscopic images. Specifically, the deep dense layer and generic multi-path Deep RefineNet are combined to improve the segmentation performance. The deep representation of all available layers is aggregated to form the global feature maps using skip connection. Also, the dense deconvolution layer is leveraged to capture diverse appearance features via the contextual information. Finally, we apply the dense deconvolution layer to smooth segmentation maps and obtain final high-resolution output. Our proposed method shows the superiority over the state-of-the-art approaches based on the public available 2016 and 2017 skin lesion challenge dataset and achieves the accuracy of 96.0% and 93.9%, which obtained a 6.0% and 1.2% increase over the traditional method, respectively. By utilizing Dense Deconvolution Net, the average time for processing one testing images with our proposed framework was 0.253 s.

Dissipated energy and entropy production for an unconventional heat engine: the stepwise `circular cycle'

NASA Astrophysics Data System (ADS)

di Liberto, Francesco; Pastore, Raffaele; Peruggi, Fulvio

2011-05-01

When some entropy is transferred, by means of a reversible engine, from a hot heat source to a colder one, the maximum efficiency occurs, i.e. the maximum available work is obtained. Similarly, a reversible heat pumps transfer entropy from a cold heat source to a hotter one with the minimum expense of energy. In contrast, if we are faced with non-reversible devices, there is some lost work for heat engines, and some extra work for heat pumps. These quantities are both related to entropy production. The lost work, i.e. ? , is also called 'degraded energy' or 'energy unavailable to do work'. The extra work, i.e. ? , is the excess of work performed on the system in the irreversible process with respect to the reversible one (or the excess of heat given to the hotter source in the irreversible process). Both quantities are analysed in detail and are evaluated for a complex process, i.e. the stepwise circular cycle, which is similar to the stepwise Carnot cycle. The stepwise circular cycle is a cycle performed by means of N small weights, dw, which are first added and then removed from the piston of the vessel containing the gas or vice versa. The work performed by the gas can be found as the increase of the potential energy of the dw's. Each single dw is identified and its increase, i.e. its increase in potential energy, evaluated. In such a way it is found how the energy output of the cycle is distributed among the dw's. The size of the dw's affects entropy production and therefore the lost and extra work. The distribution of increases depends on the chosen removal process.

Irreversibility and entropy production in transport phenomena, IV: Symmetry, integrated intermediate processes and separated variational principles for multi-currents

NASA Astrophysics Data System (ADS)

Suzuki, Masuo

2013-10-01

The mechanism of entropy production in transport phenomena is discussed again by emphasizing the role of symmetry of non-equilibrium states and also by reformulating Einstein’s theory of Brownian motion to derive entropy production from it. This yields conceptual reviews of the previous papers [M. Suzuki, Physica A 390 (2011) 1904; 391 (2012) 1074; 392 (2013) 314]. Separated variational principles of steady states for multi external fields {Xi} and induced currents {Ji} are proposed by extending the principle of minimum integrated entropy production found by the present author for a single external field. The basic strategy of our theory on steady states is to take in all the intermediate processes from the equilibrium state to the final possible steady states in order to study the irreversible physics even in the steady states. As an application of this principle, Gransdorff-Prigogine’s evolution criterion inequality (or stability condition) dXP≡∫dr∑iJidXi≤0 is derived in the stronger form dQi≡∫drJidXi≤0 for individual force Xi and current Ji even in nonlinear responses which depend on all the external forces {Xk} nonlinearly. This is called “separated evolution criterion”. Some explicit demonstrations of the present general theory to simple electric circuits with multi external fields are given in order to clarify the physical essence of our new theory and to realize the condition of its validity concerning the existence of the solutions of the simultaneous equations obtained by the separated variational principles. It is also instructive to compare the two results obtained by the new variational theory and by the old scheme based on the instantaneous entropy production. This seems to be suggestive even to the energy problem in the world.

Pituitary-hormone secretion by thyrotropinomas.

PubMed

Roelfsema, Ferdinand; Kok, Simon; Kok, Petra; Pereira, Alberto M; Biermasz, Nienke R; Smit, Jan W; Frolich, Marijke; Keenan, Daniel M; Veldhuis, Johannes D; Romijn, Johannes A

2009-01-01

Hormone secretion by somatotropinomas, corticotropinomas and prolactinomas exhibits increased pulse frequency, basal and pulsatile secretion, accompanied by greater disorderliness. Increased concentrations of growth hormone (GH) or prolactin (PRL) are observed in about 30% of thyrotropinomas leading to acromegaly or disturbed sexual functions beyond thyrotropin (TSH)-induced hyperthyroidism. Regulation of non-TSH pituitary hormones in this context is not well understood. We there therefore evaluated TSH, GH and PRL secretion in 6 patients with up-to-date analytical and mathematical tools by 24-h blood sampling at 10-min intervals in a clinical research laboratory. The profiles were analyzed with a new deconvolution method, approximate entropy, cross-approximate entropy, cross-correlation and cosinor regression. TSH burst frequency and basal and pulsatile secretion were increased in patients compared with controls. TSH secretion patterns in patients were more irregular, but the diurnal rhythm was preserved at a higher mean with a 2.5 h phase delay. Although only one patient had clinical acromegaly, GH secretion and IGF-I levels were increased in two other patients and all three had a significant cross-correlation between the GH and TSH. PRL secretion was increased in one patient, but all patients had a significant cross-correlation with TSH and showed decreased PRL regularity. Cross-ApEn synchrony between TSH and GH did not differ between patients and controls, but TSH and PRL synchrony was reduced in patients. We conclude that TSH secretion by thyrotropinomas shares many characteristics of other pituitary hormone-secreting adenomas. In addition, abnormalities in GH and PRL secretion exist ranging from decreased (joint) regularity to overt hypersecretion, although not always clinically obvious, suggesting tumoral transformation of thyrotrope lineage cells.

An accelerated non-Gaussianity based multichannel predictive deconvolution method with the limited supporting region of filters

NASA Astrophysics Data System (ADS)

Li, Zhong-xiao; Li, Zhen-chun

2016-09-01

The multichannel predictive deconvolution can be conducted in overlapping temporal and spatial data windows to solve the 2D predictive filter for multiple removal. Generally, the 2D predictive filter can better remove multiples at the cost of more computation time compared with the 1D predictive filter. In this paper we first use the cross-correlation strategy to determine the limited supporting region of filters where the coefficients play a major role for multiple removal in the filter coefficient space. To solve the 2D predictive filter the traditional multichannel predictive deconvolution uses the least squares (LS) algorithm, which requires primaries and multiples are orthogonal. To relax the orthogonality assumption the iterative reweighted least squares (IRLS) algorithm and the fast iterative shrinkage thresholding (FIST) algorithm have been used to solve the 2D predictive filter in the multichannel predictive deconvolution with the non-Gaussian maximization (L1 norm minimization) constraint of primaries. The FIST algorithm has been demonstrated as a faster alternative to the IRLS algorithm. In this paper we introduce the FIST algorithm to solve the filter coefficients in the limited supporting region of filters. Compared with the FIST based multichannel predictive deconvolution without the limited supporting region of filters the proposed method can reduce the computation burden effectively while achieving a similar accuracy. Additionally, the proposed method can better balance multiple removal and primary preservation than the traditional LS based multichannel predictive deconvolution and FIST based single channel predictive deconvolution. Synthetic and field data sets demonstrate the effectiveness of the proposed method.

Studing Regional Wave Source Time Functions Using A Massive Automated EGF Deconvolution Procedure

NASA Astrophysics Data System (ADS)

Xie, J. "; Schaff, D. P.

2010-12-01

Reliably estimated source time functions (STF) from high-frequency regional waveforms, such as Lg, Pn and Pg, provide important input for seismic source studies, explosion detection, and minimization of parameter trade-off in attenuation studies. The empirical Green’s function (EGF) method can be used for estimating STF, but it requires a strict recording condition. Waveforms from pairs of events that are similar in focal mechanism, but different in magnitude must be on-scale recorded on the same stations for the method to work. Searching for such waveforms can be very time consuming, particularly for regional waves that contain complex path effects and have reduced S/N ratios due to attenuation. We have developed a massive, automated procedure to conduct inter-event waveform deconvolution calculations from many candidate event pairs. The procedure automatically evaluates the “spikiness” of the deconvolutions by calculating their “sdc”, which is defined as the peak divided by the background value. The background value is calculated as the mean absolute value of the deconvolution, excluding 10 s around the source time function. When the sdc values are about 10 or higher, the deconvolutions are found to be sufficiently spiky (pulse-like), indicating similar path Green’s functions and good estimates of the STF. We have applied this automated procedure to Lg waves and full regional wavetrains from 989 M ≥ 5 events in and around China, calculating about a million deconvolutions. Of these we found about 2700 deconvolutions with sdc greater than 9, which, if having a sufficiently broad frequency band, can be used to estimate the STF of the larger events. We are currently refining our procedure, as well as the estimated STFs. We will infer the source scaling using the STFs. We will also explore the possibility that the deconvolution procedure could complement cross-correlation in a real time event-screening process.

A novel partial volume effects correction technique integrating deconvolution associated with denoising within an iterative PET image reconstruction

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

Merlin, Thibaut, E-mail: thibaut.merlin@telecom-bretagne.eu; Visvikis, Dimitris; Fernandez, Philippe

2015-02-15

Purpose: Partial volume effect (PVE) plays an important role in both qualitative and quantitative PET image accuracy, especially for small structures. A previously proposed voxelwise PVE correction method applied on PET reconstructed images involves the use of Lucy–Richardson deconvolution incorporating wavelet-based denoising to limit the associated propagation of noise. The aim of this study is to incorporate the deconvolution, coupled with the denoising step, directly inside the iterative reconstruction process to further improve PVE correction. Methods: The list-mode ordered subset expectation maximization (OSEM) algorithm has been modified accordingly with the application of the Lucy–Richardson deconvolution algorithm to the current estimationmore » of the image, at each reconstruction iteration. Acquisitions of the NEMA NU2-2001 IQ phantom were performed on a GE DRX PET/CT system to study the impact of incorporating the deconvolution inside the reconstruction [with and without the point spread function (PSF) model] in comparison to its application postreconstruction and to standard iterative reconstruction incorporating the PSF model. The impact of the denoising step was also evaluated. Images were semiquantitatively assessed by studying the trade-off between the intensity recovery and the noise level in the background estimated as relative standard deviation. Qualitative assessments of the developed methods were additionally performed on clinical cases. Results: Incorporating the deconvolution without denoising within the reconstruction achieved superior intensity recovery in comparison to both standard OSEM reconstruction integrating a PSF model and application of the deconvolution algorithm in a postreconstruction process. The addition of the denoising step permitted to limit the SNR degradation while preserving the intensity recovery. Conclusions: This study demonstrates the feasibility of incorporating the Lucy–Richardson deconvolution associated with a wavelet-based denoising in the reconstruction process to better correct for PVE. Future work includes further evaluations of the proposed method on clinical datasets and the use of improved PSF models.« less

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

Khosla, D.; Singh, M.

The estimation of three-dimensional dipole current sources on the cortical surface from the measured magnetoencephalogram (MEG) is a highly under determined inverse problem as there are many {open_quotes}feasible{close_quotes} images which are consistent with the MEG data. Previous approaches to this problem have concentrated on the use of weighted minimum norm inverse methods. While these methods ensure a unique solution, they often produce overly smoothed solutions and exhibit severe sensitivity to noise. In this paper we explore the maximum entropy approach to obtain better solutions to the problem. This estimation technique selects that image from the possible set of feasible imagesmore » which has the maximum entropy permitted by the information available to us. In order to account for the presence of noise in the data, we have also incorporated a noise rejection or likelihood term into our maximum entropy method. This makes our approach mirror a Bayesian maximum a posteriori (MAP) formulation. Additional information from other functional techniques like functional magnetic resonance imaging (fMRI) can be incorporated in the proposed method in the form of a prior bias function to improve solutions. We demonstrate the method with experimental phantom data from a clinical 122 channel MEG system.« less

Is There a Direct Correlation Between Microvascular Wall Structure and k-Trans Values Obtained From Perfusion CT Measurements in Lymphomas?

PubMed

Horger, Marius; Fallier-Becker, Petra; Thaiss, Wolfgang M; Sauter, Alexander; Bösmüller, Hans; Martella, Manuela; Preibsch, Heike; Fritz, Jan; Nikolaou, Konstantin; Kloth, Christopher

2018-05-03

This study aimed to test the hypothesis that ultrastructural wall abnormalities of lymphoma vessels correlate with perfusion computed tomography (PCT) kinetics. Our local institutional review board approved this prospective study. Between February 2013 and June 2016, we included 23 consecutive subjects with newly diagnosed lymphoma, who were referred for computed tomography-guided biopsy (6 women, 17 men; mean age, 60.61 ± 12.43 years; range, 28-74 years) and additionally agreed to undergo PCT of the target lymphoma tissues. PCT was obtained for 40 seconds using 80 kV, 120 mAs, 64 × 0.6-mm collimation, 6.9-cm z-axis coverage, and 26 volume measurements. Mean and maximum k-trans (mL/100 mL/min), blood flow (BF; mL/100 mL/min) and blood volume (BV) were quantified using the deconvolution and the maximum slope + Patlak calculation models. Immunohistochemical staining was performed for microvessel density quantification (vessels/m 2 ), and electron microscopy was used to determine the presence or absence of tight junctions, endothelial fenestration, basement membrane, and pericytes, and to measure extracellular matrix thickness. Extracellular matrix thickness as well as the presence or absence of tight junctions, basal lamina, and pericytes did not correlate with computed tomography perfusion parameters. Endothelial fenestrations correlated significantly with mean BF deconvolution (P = .047, r = 0.418) and additionally was significantly associated with higher mean BV deconvolution (P < .005). Mean k-trans Patlak correlated strongly with mean k-trans deconvolution (r = 0.939, P = .001), and both correlated with mean BF deconvolution (P = .001, r = 0.748), max BF deconvolution (P = .028, r = 0.564), mean BV deconvolution (P = .001, r = 0.752), and max BV deconvolution (P = .001, r = 0.771). Microvessel density correlated with max k-trans deconvolution (r = 0.564, P = .023). Vascular endothelial growth factor receptor-3 expression (receptor specific for lymphatics) correlated significantly with max k-trans Patlak (P = .041, r = 0.686) and mean BF deconvolution (P = .038, r = 0.695). k-Trans values of PCT do not correlate with ultrastructural microvessel features, whereas endothelial fenestrations correlate with increased intra-tumoral BVs. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Potential of mean force between two hydrophobic solutes in water.

PubMed

Southall, Noel T; Dill, Ken A

2002-12-10

We study the potential of mean force between two nonpolar solutes in the Mercedes Benz model of water. Using NPT Monte Carlo simulations, we find that the solute size determines the relative preference of two solute molecules to come into contact ('contact minimum') or to be separated by a single layer of water ('solvent-separated minimum'). Larger solutes more strongly prefer the contacting state, while smaller solutes have more tendency to become solvent-separated, particularly in cold water. The thermal driving forces oscillate with solute separation. Contacts are stabilized by entropy, whereas solvent-separated solute pairing is stabilized by enthalpy. The free energy of interaction for small solutes is well-approximated by scaled-particle theory. Copyright 2002 Elsevier Science B.V.

Data enhancement and analysis through mathematical deconvolution of signals from scientific measuring instruments

NASA Technical Reports Server (NTRS)

Wood, G. M.; Rayborn, G. H.; Ioup, J. W.; Ioup, G. E.; Upchurch, B. T.; Howard, S. J.

1981-01-01

Mathematical deconvolution of digitized analog signals from scientific measuring instruments is shown to be a means of extracting important information which is otherwise hidden due to time-constant and other broadening or distortion effects caused by the experiment. Three different approaches to deconvolution and their subsequent application to recorded data from three analytical instruments are considered. To demonstrate the efficacy of deconvolution, the use of these approaches to solve the convolution integral for the gas chromatograph, magnetic mass spectrometer, and the time-of-flight mass spectrometer are described. Other possible applications of these types of numerical treatment of data to yield superior results from analog signals of the physical parameters normally measured in aerospace simulation facilities are suggested and briefly discussed.

Multi-frame partially saturated images blind deconvolution

NASA Astrophysics Data System (ADS)

Ye, Pengzhao; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting

2016-12-01

When blurred images have saturated or over-exposed pixels, conventional blind deconvolution approaches often fail to estimate accurate point spread function (PSF) and will introduce local ringing artifacts. In this paper, we propose a method to deal with the problem under the modified multi-frame blind deconvolution framework. First, in the kernel estimation step, a light streak detection scheme using multi-frame blurred images is incorporated into the regularization constraint. Second, we deal with image regions affected by the saturated pixels separately by modeling a weighted matrix during each multi-frame deconvolution iteration process. Both synthetic and real-world examples show that more accurate PSFs can be estimated and restored images have richer details and less negative effects compared to state of art methods.

Parallelization of a blind deconvolution algorithm

NASA Astrophysics Data System (ADS)

Matson, Charles L.; Borelli, Kathy J.

2006-09-01

Often it is of interest to deblur imagery in order to obtain higher-resolution images. Deblurring requires knowledge of the blurring function - information that is often not available separately from the blurred imagery. Blind deconvolution algorithms overcome this problem by jointly estimating both the high-resolution image and the blurring function from the blurred imagery. Because blind deconvolution algorithms are iterative in nature, they can take minutes to days to deblur an image depending how many frames of data are used for the deblurring and the platforms on which the algorithms are executed. Here we present our progress in parallelizing a blind deconvolution algorithm to increase its execution speed. This progress includes sub-frame parallelization and a code structure that is not specialized to a specific computer hardware architecture.

Improved deconvolution of very weak confocal signals.

PubMed

Day, Kasey J; La Rivière, Patrick J; Chandler, Talon; Bindokas, Vytas P; Ferrier, Nicola J; Glick, Benjamin S

2017-01-01

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal of background noise. This approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.

Enhancing multi-spot structured illumination microscopy with fluorescence difference

PubMed Central

Torkelsen, Frida H.

2018-01-01

Structured illumination microscopy is a super-resolution technique used extensively in biological research. However, this technique is limited in the maximum possible resolution increase. Here we report the results of simulations of a novel enhanced multi-spot structured illumination technique. This method combines the super-resolution technique of difference microscopy with structured illumination deconvolution. Initial results give at minimum a 1.4-fold increase in resolution over conventional structured illumination in a low-noise environment. This new technique also has the potential to be expanded to further enhance axial resolution with three-dimensional difference microscopy. The requirement for precise pattern determination in this technique also led to the development of a new pattern estimation algorithm which proved more efficient and reliable than other methods tested. PMID:29657751

Experimental feasibility of the airborne measurement of absolute oil fluorescence spectral conversion efficiency

NASA Technical Reports Server (NTRS)

Hoge, F. E.; Swift, R. N.

1983-01-01

Airborne lidar oil spill experiments carried out to determine the practicability of the AOFSCE (absolute oil fluorescence spectral conversion efficiency) computational model are described. The results reveal that the model is suitable over a considerable range of oil film thicknesses provided the fluorescence efficiency of the oil does not approach the minimum detection sensitivity limitations of the lidar system. Separate airborne lidar experiments to demonstrate measurement of the water column Raman conversion efficiency are also conducted to ascertain the ultimate feasibility of converting such relative oil fluorescence to absolute values. Whereas the AOFSCE model is seen as highly promising, further airborne water column Raman conversion efficiency experiments with improved temporal or depth-resolved waveform calibration and software deconvolution techniques are thought necessary for a final determination of suitability.

Septal penetration correction in I-131 imaging following thyroid cancer treatment

NASA Astrophysics Data System (ADS)

Barrack, Fiona; Scuffham, James; McQuaid, Sarah

2018-04-01

Whole body gamma camera images acquired after I-131 treatment for thyroid cancer can suffer from collimator septal penetration artefacts because of the high energy of the gamma photons. This results in the appearance of ‘spoke’ artefacts, emanating from regions of high activity concentration, caused by the non-isotropic attenuation of the collimator. Deconvolution has the potential to reduce such artefacts, by taking into account the non-Gaussian point-spread-function (PSF) of the system. A Richardson–Lucy deconvolution algorithm, with and without prior scatter-correction was tested as a method of reducing septal penetration in planar gamma camera images. Phantom images (hot spheres within a warm background) were acquired and deconvolution using a measured PSF was applied. The results were evaluated through region-of-interest and line profile analysis to determine the success of artefact reduction and the optimal number of deconvolution iterations and damping parameter (λ). Without scatter-correction, the optimal results were obtained with 15 iterations and λ  =  0.01, with the counts in the spokes reduced to 20% of the original value, indicating a substantial decrease in their prominence. When a triple-energy-window scatter-correction was applied prior to deconvolution, the optimal results were obtained with six iterations and λ  =  0.02, which reduced the spoke counts to 3% of the original value. The prior application of scatter-correction therefore produced the best results, with a marked change in the appearance of the images. The optimal settings were then applied to six patient datasets, to demonstrate its utility in the clinical setting. In all datasets, spoke artefacts were substantially reduced after the application of scatter-correction and deconvolution, with the mean spoke count being reduced to 10% of the original value. This indicates that deconvolution is a promising technique for septal penetration artefact reduction that could potentially improve the diagnostic accuracy of I-131 imaging. Novelty and significance This work has demonstrated that scatter correction combined with deconvolution can be used to substantially reduce the appearance of septal penetration artefacts in I-131 phantom and patient gamma camera planar images, enable improved visualisation of the I-131 distribution. Deconvolution with symmetric PSF has previously been used to reduce artefacts in gamma camera images however this work details the novel use of an asymmetric PSF to remove the angularly dependent septal penetration artefacts.

Systems analysis of a closed loop ECLSS using the ASPEN simulation tool. Thermodynamic efficiency analysis of ECLSS components. M.S. Thesis

NASA Technical Reports Server (NTRS)

Chatterjee, Sharmista

1993-01-01

Our first goal in this project was to perform a systems analysis of a closed loop Environmental Control Life Support System (ECLSS). This pertains to the development of a model of an existing real system from which to assess the state or performance of the existing system. Systems analysis is applied to conceptual models obtained from a system design effort. For our modelling purposes we used a simulator tool called ASPEN (Advanced System for Process Engineering). Our second goal was to evaluate the thermodynamic efficiency of the different components comprising an ECLSS. Use is made of the second law of thermodynamics to determine the amount of irreversibility of energy loss of each component. This will aid design scientists in selecting the components generating the least entropy, as our penultimate goal is to keep the entropy generation of the whole system at a minimum.

A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection

NASA Astrophysics Data System (ADS)

Li, Yongbo; Yang, Yuantao; Li, Guoyan; Xu, Minqiang; Huang, Wenhu

2017-07-01

Health condition identification of planetary gearboxes is crucial to reduce the downtime and maximize productivity. This paper aims to develop a novel fault diagnosis method based on modified multi-scale symbolic dynamic entropy (MMSDE) and minimum redundancy maximum relevance (mRMR) to identify the different health conditions of planetary gearbox. MMSDE is proposed to quantify the regularity of time series, which can assess the dynamical characteristics over a range of scales. MMSDE has obvious advantages in the detection of dynamical changes and computation efficiency. Then, the mRMR approach is introduced to refine the fault features. Lastly, the obtained new features are fed into the least square support vector machine (LSSVM) to complete the fault pattern identification. The proposed method is numerically and experimentally demonstrated to be able to recognize the different fault types of planetary gearboxes.

Recurrence plots of discrete-time Gaussian stochastic processes

NASA Astrophysics Data System (ADS)

Ramdani, Sofiane; Bouchara, Frédéric; Lagarde, Julien; Lesne, Annick

2016-09-01

We investigate the statistical properties of recurrence plots (RPs) of data generated by discrete-time stationary Gaussian random processes. We analytically derive the theoretical values of the probabilities of occurrence of recurrence points and consecutive recurrence points forming diagonals in the RP, with an embedding dimension equal to 1. These results allow us to obtain theoretical values of three measures: (i) the recurrence rate (REC) (ii) the percent determinism (DET) and (iii) RP-based estimation of the ε-entropy κ(ε) in the sense of correlation entropy. We apply these results to two Gaussian processes, namely first order autoregressive processes and fractional Gaussian noise. For these processes, we simulate a number of realizations and compare the RP-based estimations of the three selected measures to their theoretical values. These comparisons provide useful information on the quality of the estimations, such as the minimum required data length and threshold radius used to construct the RP.

Source Pulse Estimation of Mine Shock by Blind Deconvolution

NASA Astrophysics Data System (ADS)

Makowski, R.

The objective of seismic signal deconvolution is to extract from the signal information concerning the rockmass or the signal in the source of the shock. In the case of blind deconvolution, we have to extract information regarding both quantities. Many methods of deconvolution made use of in prospective seismology were found to be of minor utility when applied to shock-induced signals recorded in the mines of the Lubin Copper District. The lack of effectiveness should be attributed to the inadequacy of the model on which the methods are based, with respect to the propagation conditions for that type of signal. Each of the blind deconvolution methods involves a number of assumptions; hence, only if these assumptions are fulfilled, we may expect reliable results.Consequently, we had to formulate a different model for the signals recorded in the copper mines of the Lubin District. The model is based on the following assumptions: (1) The signal emitted by the sh ock source is a short-term signal. (2) The signal transmitting system (rockmass) constitutes a parallel connection of elementary systems. (3) The elementary systems are of resonant type. Such a model seems to be justified by the geological structure as well as by the positions of the shock foci and seismometers. The results of time-frequency transformation also support the dominance of resonant-type propagation.Making use of the model, a new method for the blind deconvolution of seismic signals has been proposed. The adequacy of the new model, as well as the efficiency of the proposed method, has been confirmed by the results of blind deconvolution. The slight approximation errors obtained with a small number of approximating elements additionally corroborate the adequacy of the model.

Improving Range Estimation of a 3-Dimensional Flash Ladar via Blind Deconvolution

DTIC Science & Technology

2010-09-01

12 2.1.4 Optical Imaging as a Linear and Nonlinear System 15 2.1.5 Coherence Theory and Laser Light Statistics . . . 16 2.2 Deconvolution...rather than deconvolution. 2.1.5 Coherence Theory and Laser Light Statistics. Using [24] and [25], this section serves as background on coherence theory...the laser light incident on the detector surface. The image intensity related to different types of coherence is governed by the laser light’s spatial

Evaluation of deconvolution modelling applied to numerical combustion

NASA Astrophysics Data System (ADS)

Mehl, Cédric; Idier, Jérôme; Fiorina, Benoît

2018-01-01

A possible modelling approach in the large eddy simulation (LES) of reactive flows is to deconvolve resolved scalars. Indeed, by inverting the LES filter, scalars such as mass fractions are reconstructed. This information can be used to close budget terms of filtered species balance equations, such as the filtered reaction rate. Being ill-posed in the mathematical sense, the problem is very sensitive to any numerical perturbation. The objective of the present study is to assess the ability of this kind of methodology to capture the chemical structure of premixed flames. For that purpose, three deconvolution methods are tested on a one-dimensional filtered laminar premixed flame configuration: the approximate deconvolution method based on Van Cittert iterative deconvolution, a Taylor decomposition-based method, and the regularised deconvolution method based on the minimisation of a quadratic criterion. These methods are then extended to the reconstruction of subgrid scale profiles. Two methodologies are proposed: the first one relies on subgrid scale interpolation of deconvolved profiles and the second uses parametric functions to describe small scales. Conducted tests analyse the ability of the method to capture the chemical filtered flame structure and front propagation speed. Results show that the deconvolution model should include information about small scales in order to regularise the filter inversion. a priori and a posteriori tests showed that the filtered flame propagation speed and structure cannot be captured if the filter size is too large.

Faceting for direction-dependent spectral deconvolution

NASA Astrophysics Data System (ADS)

Tasse, C.; Hugo, B.; Mirmont, M.; Smirnov, O.; Atemkeng, M.; Bester, L.; Hardcastle, M. J.; Lakhoo, R.; Perkins, S.; Shimwell, T.

2018-04-01

The new generation of radio interferometers is characterized by high sensitivity, wide fields of view and large fractional bandwidth. To synthesize the deepest images enabled by the high dynamic range of these instruments requires us to take into account the direction-dependent Jones matrices, while estimating the spectral properties of the sky in the imaging and deconvolution algorithms. In this paper we discuss and implement a wideband wide-field spectral deconvolution framework (DDFacet) based on image plane faceting, that takes into account generic direction-dependent effects. Specifically, we present a wide-field co-planar faceting scheme, and discuss the various effects that need to be taken into account to solve for the deconvolution problem (image plane normalization, position-dependent Point Spread Function, etc). We discuss two wideband spectral deconvolution algorithms based on hybrid matching pursuit and sub-space optimisation respectively. A few interesting technical features incorporated in our imager are discussed, including baseline dependent averaging, which has the effect of improving computing efficiency. The version of DDFacet presented here can account for any externally defined Jones matrices and/or beam patterns.

Intrinsic fluorescence spectroscopy of glutamate dehydrogenase: Integrated behavior and deconvolution analysis

NASA Astrophysics Data System (ADS)

Pompa, P. P.; Cingolani, R.; Rinaldi, R.

2003-07-01

In this paper, we present a deconvolution method aimed at spectrally resolving the broad fluorescence spectra of proteins, namely, of the enzyme bovine liver glutamate dehydrogenase (GDH). The analytical procedure is based on the deconvolution of the emission spectra into three distinct Gaussian fluorescing bands Gj. The relative changes of the Gj parameters are directly related to the conformational changes of the enzyme, and provide interesting information about the fluorescence dynamics of the individual emitting contributions. Our deconvolution method results in an excellent fitting of all the spectra obtained with GDH in a number of experimental conditions (various conformational states of the protein) and describes very well the dynamics of a variety of phenomena, such as the dependence of hexamers association on protein concentration, the dynamics of thermal denaturation, and the interaction process between the enzyme and external quenchers. The investigation was carried out by means of different optical experiments, i.e., native enzyme fluorescence, thermal-induced unfolding, and fluorescence quenching studies, utilizing both the analysis of the “average” behavior of the enzyme and the proposed deconvolution approach.

4Pi microscopy deconvolution with a variable point-spread function.

PubMed

Baddeley, David; Carl, Christian; Cremer, Christoph

2006-09-20

To remove the axial sidelobes from 4Pi images, deconvolution forms an integral part of 4Pi microscopy. As a result of its high axial resolution, the 4Pi point spread function (PSF) is particularly susceptible to imperfect optical conditions within the sample. This is typically observed as a shift in the position of the maxima under the PSF envelope. A significantly varying phase shift renders deconvolution procedures based on a spatially invariant PSF essentially useless. We present a technique for computing the forward transformation in the case of a varying phase at a computational expense of the same order of magnitude as that of the shift invariant case, a method for the estimation of PSF phase from an acquired image, and a deconvolution procedure built on these techniques.

Improved deconvolution of very weak confocal signals

PubMed Central

Day, Kasey J.; La Rivière, Patrick J.; Chandler, Talon; Bindokas, Vytas P.; Ferrier, Nicola J.; Glick, Benjamin S.

2017-01-01

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal of background noise. This approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage. PMID:28868135

Improved deconvolution of very weak confocal signals

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

Day, Kasey J.; La Riviere, Patrick J.; Chandler, Talon

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal ofmore » background noise. Here, this approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.« less

Improved deconvolution of very weak confocal signals

DOE PAGES

Day, Kasey J.; La Riviere, Patrick J.; Chandler, Talon; ...

2017-06-06

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal ofmore » background noise. Here, this approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.« less

Deconvolution of Thermal Emissivity Spectra of Mercury to their Endmember Counterparts measured in Simulated Mercury Surface Conditions

NASA Astrophysics Data System (ADS)

Varatharajan, I.; D'Amore, M.; Maturilli, A.; Helbert, J.; Hiesinger, H.

2017-12-01

The Mercury Radiometer and Thermal Imaging Spectrometer (MERTIS) payload of ESA/JAXA Bepicolombo mission to Mercury will map the thermal emissivity at wavelength range of 7-14 μm and spatial resolution of 500 m/pixel [1]. Mercury was also imaged at the same wavelength range using the Boston University's Mid-Infrared Spectrometer and Imager (MIRSI) mounted on the NASA Infrared Telescope Facility (IRTF) on Mauna Kea, Hawaii with the minimum spatial coverage of 400-600km/spectra which blends all rocks, minerals, and soil types [2]. Therefore, the study [2] used quantitative deconvolution algorithm developed by [3] for spectral unmixing of this composite thermal emissivity spectrum from telescope to their respective areal fractions of endmember spectra; however, the thermal emissivity of endmembers used in [2] is the inverted reflectance measurements (Kirchhoff's law) of various samples measured at room temperature and pressure. Over a decade, the Planetary Spectroscopy Laboratory (PSL) at the Institute of Planetary Research (PF) at the German Aerospace Center (DLR) facilitates the thermal emissivity measurements under controlled and simulated surface conditions of Mercury by taking emissivity measurements at varying temperatures from 100-500°C under vacuum conditions supporting MERTIS payload. The measured thermal emissivity endmember spectral library therefore includes major silicates such as bytownite, anorthoclase, synthetic glass, olivine, enstatite, nepheline basanite, rocks like komatiite, tektite, Johnson Space Center lunar simulant (1A), and synthetic powdered sulfides which includes MgS, FeS, CaS, CrS, TiS, NaS, and MnS. Using such specialized endmember spectral library created under Mercury's conditions significantly increases the accuracy of the deconvolution model results. In this study, we revisited the available telescope spectra and redeveloped the algorithm by [3] by only choosing the endmember spectral library created at PSL for unbiased model accuracy with the RMS value of 0.03-0.04. Currently, the telescope spectra are investigated for its calibrations and the results will be presented at AGU. References: [1] Hiesinger, H. and J. Helbert (2010) PSS, 58(1-2): 144-165. [2] Sprague, A.L. et al (2009) PSS, 57, 364-383. [3] Ramsey and Christiansen (1998) JGR, 103, 577-596

Kinetic analysis of hyperpolarized data with minimum a priori knowledge: Hybrid maximum entropy and nonlinear least squares method (MEM/NLS).

PubMed

Mariotti, Erika; Veronese, Mattia; Dunn, Joel T; Southworth, Richard; Eykyn, Thomas R

2015-06-01

To assess the feasibility of using a hybrid Maximum-Entropy/Nonlinear Least Squares (MEM/NLS) method for analyzing the kinetics of hyperpolarized dynamic data with minimum a priori knowledge. A continuous distribution of rates obtained through the Laplace inversion of the data is used as a constraint on the NLS fitting to derive a discrete spectrum of rates. Performance of the MEM/NLS algorithm was assessed through Monte Carlo simulations and validated by fitting the longitudinal relaxation time curves of hyperpolarized [1-(13) C] pyruvate acquired at 9.4 Tesla and at three different flip angles. The method was further used to assess the kinetics of hyperpolarized pyruvate-lactate exchange acquired in vitro in whole blood and to re-analyze the previously published in vitro reaction of hyperpolarized (15) N choline with choline kinase. The MEM/NLS method was found to be adequate for the kinetic characterization of hyperpolarized in vitro time-series. Additional insights were obtained from experimental data in blood as well as from previously published (15) N choline experimental data. The proposed method informs on the compartmental model that best approximate the biological system observed using hyperpolarized (13) C MR especially when the metabolic pathway assessed is complex or a new hyperpolarized probe is used. © 2014 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc.

Blind deconvolution post-processing of images corrected by adaptive optics

NASA Astrophysics Data System (ADS)

Christou, Julian C.

1995-08-01

Experience with the adaptive optics system at the Starfire Optical Range has shown that the point spread function is non-uniform and varies both spatially and temporally as well as being object dependent. Because of this, the application of a standard linear and non-linear deconvolution algorithms make it difficult to deconvolve out the point spread function. In this paper we demonstrate the application of a blind deconvolution algorithm to adaptive optics compensated data where a separate point spread function is not needed.

Computerised curve deconvolution of TL/OSL curves using a popular spreadsheet program.

PubMed

Afouxenidis, D; Polymeris, G S; Tsirliganis, N C; Kitis, G

2012-05-01

This paper exploits the possibility of using commercial software for thermoluminescence and optically stimulated luminescence curve deconvolution analysis. The widely used software package Microsoft Excel, with the Solver utility has been used to perform deconvolution analysis to both experimental and reference glow curves resulted from the GLOw Curve ANalysis INtercomparison project. The simple interface of this programme combined with the powerful Solver utility, allows the analysis of complex stimulated luminescence curves into their components and the evaluation of the associated luminescence parameters.

Deconvolution of noisy transient signals: a Kalman filtering application

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

Candy, J.V.; Zicker, J.E.

The deconvolution of transient signals from noisy measurements is a common problem occuring in various tests at Lawrence Livermore National Laboratory. The transient deconvolution problem places atypical constraints on algorithms presently available. The Schmidt-Kalman filter, a time-varying, tunable predictor, is designed using a piecewise constant model of the transient input signal. A simulation is developed to test the algorithm for various input signal bandwidths and different signal-to-noise ratios for the input and output sequences. The algorithm performance is reasonable.

Range resolution improvement in passive bistatic radars using nested FM channels and least squares approach

NASA Astrophysics Data System (ADS)

Arslan, Musa T.; Tofighi, Mohammad; Sevimli, Rasim A.; ćetin, Ahmet E.

2015-05-01

One of the main disadvantages of using commercial broadcasts in a Passive Bistatic Radar (PBR) system is the range resolution. Using multiple broadcast channels to improve the radar performance is offered as a solution to this problem. However, it suffers from detection performance due to the side-lobes that matched filter creates for using multiple channels. In this article, we introduce a deconvolution algorithm to suppress the side-lobes. The two-dimensional matched filter output of a PBR is further analyzed as a deconvolution problem. The deconvolution algorithm is based on making successive projections onto the hyperplanes representing the time delay of a target. Resulting iterative deconvolution algorithm is globally convergent because all constraint sets are closed and convex. Simulation results in an FM based PBR system are presented.

Simulation Study of Effects of the Blind Deconvolution on Ultrasound Image

NASA Astrophysics Data System (ADS)

He, Xingwu; You, Junchen

2018-03-01

Ultrasonic image restoration is an essential subject in Medical Ultrasound Imaging. However, without enough and precise system knowledge, some traditional image restoration methods based on the system prior knowledge often fail to improve the image quality. In this paper, we use the simulated ultrasound image to find the effectiveness of the blind deconvolution method for ultrasound image restoration. Experimental results demonstrate that the blind deconvolution method can be applied to the ultrasound image restoration and achieve the satisfactory restoration results without the precise prior knowledge, compared with the traditional image restoration method. And with the inaccurate small initial PSF, the results shows blind deconvolution could improve the overall image quality of ultrasound images, like much better SNR and image resolution, and also show the time consumption of these methods. it has no significant increasing on GPU platform.

Imaging resolution and properties analysis of super resolution microscopy with parallel detection under different noise, detector and image restoration conditions

NASA Astrophysics Data System (ADS)

Yu, Zhongzhi; Liu, Shaocong; Sun, Shiyi; Kuang, Cuifang; Liu, Xu

2018-06-01

Parallel detection, which can use the additional information of a pinhole plane image taken at every excitation scan position, could be an efficient method to enhance the resolution of a confocal laser scanning microscope. In this paper, we discuss images obtained under different conditions and using different image restoration methods with parallel detection to quantitatively compare the imaging quality. The conditions include different noise levels and different detector array settings. The image restoration methods include linear deconvolution and pixel reassignment with Richard-Lucy deconvolution and with maximum-likelihood estimation deconvolution. The results show that the linear deconvolution share properties such as high-efficiency and the best performance under all different conditions, and is therefore expected to be of use for future biomedical routine research.

Energy landscapes and properties of biomolecules.

PubMed

Wales, David J

2005-11-09

Thermodynamic and dynamic properties of biomolecules can be calculated using a coarse-grained approach based upon sampling stationary points of the underlying potential energy surface. The superposition approximation provides an overall partition function as a sum of contributions from the local minima, and hence functions such as internal energy, entropy, free energy and the heat capacity. To obtain rates we must also sample transition states that link the local minima, and the discrete path sampling method provides a systematic means to achieve this goal. A coarse-grained picture is also helpful in locating the global minimum using the basin-hopping approach. Here we can exploit a fictitious dynamics between the basins of attraction of local minima, since the objective is to find the lowest minimum, rather than to reproduce the thermodynamics or dynamics.

Principles of time evolution in classical physics

NASA Astrophysics Data System (ADS)

Güémez, J.; Fiolhais, M.

2018-07-01

We address principles of time evolution in classical mechanical/thermodynamical systems in translational and rotational motion, in three cases: when there is conservation of mechanical energy, when there is energy dissipation and when there is mechanical energy production. In the first case, the time derivative of the Hamiltonian vanishes. In the second one, when dissipative forces are present, the time evolution is governed by the minimum potential energy principle, or, equivalently, maximum increase of the entropy of the universe. Finally, in the third situation, when internal sources of work are available to the system, it evolves in time according to the principle of minimum Gibbs function. We apply the Lagrangian formulation to the systems, dealing with the non-conservative forces using restriction functions such as the Rayleigh dissipative function.

Application of deconvolution interferometry with both Hi-net and KiK-net data

NASA Astrophysics Data System (ADS)

Nakata, N.

2013-12-01

Application of deconvolution interferometry to wavefields observed by KiK-net, a strong-motion recording network in Japan, is useful for estimating wave velocities and S-wave splitting in the near surface. Using this technique, for example, Nakata and Snieder (2011, 2012) found changed in velocities caused by Tohoku-Oki earthquake in Japan. At the location of the borehole accelerometer of each KiK-net station, a velocity sensor is also installed as a part of a high-sensitivity seismograph network (Hi-net). I present a technique that uses both Hi-net and KiK-net records for computing deconvolution interferometry. The deconvolved waveform obtained from the combination of Hi-net and KiK-net data is similar to the waveform computed from KiK-net data only, which indicates that one can use Hi-net wavefields for deconvolution interferometry. Because Hi-net records have a high signal-to-noise ratio (S/N) and high dynamic resolution, the S/N and the quality of amplitude and phase of deconvolved waveforms can be improved with Hi-net data. These advantages are especially important for short-time moving-window seismic interferometry and deconvolution interferometry using later coda waves.

The Small-scale Structure of Photospheric Convection Retrieved by a Deconvolution Technique Applied to Hinode/SP Data

NASA Astrophysics Data System (ADS)

Oba, T.; Riethmüller, T. L.; Solanki, S. K.; Iida, Y.; Quintero Noda, C.; Shimizu, T.

2017-11-01

Solar granules are bright patterns surrounded by dark channels, called intergranular lanes, in the solar photosphere and are a manifestation of overshooting convection. Observational studies generally find stronger upflows in granules and weaker downflows in intergranular lanes. This trend is, however, inconsistent with the results of numerical simulations in which downflows are stronger than upflows through the joint action of gravitational acceleration/deceleration and pressure gradients. One cause of this discrepancy is the image degradation caused by optical distortion and light diffraction and scattering that takes place in an imaging instrument. We apply a deconvolution technique to Hinode/SP data in an attempt to recover the original solar scene. Our results show a significant enhancement in both the convective upflows and downflows but particularly for the latter. After deconvolution, the up- and downflows reach maximum amplitudes of -3.0 km s-1 and +3.0 km s-1 at an average geometrical height of roughly 50 km, respectively. We found that the velocity distributions after deconvolution match those derived from numerical simulations. After deconvolution, the net LOS velocity averaged over the whole field of view lies close to zero as expected in a rough sense from mass balance.

Application of deterministic deconvolution of ground-penetrating radar data in a study of carbonate strata

USGS Publications Warehouse

Xia, J.; Franseen, E.K.; Miller, R.D.; Weis, T.V.

2004-01-01

We successfully applied deterministic deconvolution to real ground-penetrating radar (GPR) data by using the source wavelet that was generated in and transmitted through air as the operator. The GPR data were collected with 400-MHz antennas on a bench adjacent to a cleanly exposed quarry face. The quarry site is characterized by horizontally bedded carbonate strata with shale partings. In order to provide groundtruth for this deconvolution approach, 23 conductive rods were drilled into the quarry face at key locations. The steel rods provided critical information for: (1) correlation between reflections on GPR data and geologic features exposed in the quarry face, (2) GPR resolution limits, (3) accuracy of velocities calculated from common midpoint data and (4) identifying any multiples. Comparing the results of deconvolved data with non-deconvolved data demonstrates the effectiveness of deterministic deconvolution in low dielectric-loss media for increased accuracy of velocity models (improved at least 10-15% in our study after deterministic deconvolution), increased vertical and horizontal resolution of specific geologic features and more accurate representation of geologic features as confirmed from detailed study of the adjacent quarry wall. ?? 2004 Elsevier B.V. All rights reserved.

Peptide de novo sequencing of mixture tandem mass spectra

PubMed Central

Hotta, Stéphanie Yuki Kolbeck; Verano‐Braga, Thiago; Kjeldsen, Frank

2016-01-01

The impact of mixture spectra deconvolution on the performance of four popular de novo sequencing programs was tested using artificially constructed mixture spectra as well as experimental proteomics data. Mixture fragmentation spectra are recognized as a limitation in proteomics because they decrease the identification performance using database search engines. De novo sequencing approaches are expected to be even more sensitive to the reduction in mass spectrum quality resulting from peptide precursor co‐isolation and thus prone to false identifications. The deconvolution approach matched complementary b‐, y‐ions to each precursor peptide mass, which allowed the creation of virtual spectra containing sequence specific fragment ions of each co‐isolated peptide. Deconvolution processing resulted in equally efficient identification rates but increased the absolute number of correctly sequenced peptides. The improvement was in the range of 20–35% additional peptide identifications for a HeLa lysate sample. Some correct sequences were identified only using unprocessed spectra; however, the number of these was lower than those where improvement was obtained by mass spectral deconvolution. Tight candidate peptide score distribution and high sensitivity to small changes in the mass spectrum introduced by the employed deconvolution method could explain some of the missing peptide identifications. PMID:27329701

Deconvolution using a neural network

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

Lehman, S.K.

1990-11-15

Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

Parameter Estimation as a Problem in Statistical Thermodynamics.

PubMed

Earle, Keith A; Schneider, David J

2011-03-14

In this work, we explore the connections between parameter fitting and statistical thermodynamics using the maxent principle of Jaynes as a starting point. In particular, we show how signal averaging may be described by a suitable one particle partition function, modified for the case of a variable number of particles. These modifications lead to an entropy that is extensive in the number of measurements in the average. Systematic error may be interpreted as a departure from ideal gas behavior. In addition, we show how to combine measurements from different experiments in an unbiased way in order to maximize the entropy of simultaneous parameter fitting. We suggest that fit parameters may be interpreted as generalized coordinates and the forces conjugate to them may be derived from the system partition function. From this perspective, the parameter fitting problem may be interpreted as a process where the system (spectrum) does work against internal stresses (non-optimum model parameters) to achieve a state of minimum free energy/maximum entropy. Finally, we show how the distribution function allows us to define a geometry on parameter space, building on previous work[1, 2]. This geometry has implications for error estimation and we outline a program for incorporating these geometrical insights into an automated parameter fitting algorithm.

Query construction, entropy, and generalization in neural-network models

NASA Astrophysics Data System (ADS)

Sollich, Peter

1994-05-01

We study query construction algorithms, which aim at improving the generalization ability of systems that learn from examples by choosing optimal, nonredundant training sets. We set up a general probabilistic framework for deriving such algorithms from the requirement of optimizing a suitable objective function; specifically, we consider the objective functions entropy (or information gain) and generalization error. For two learning scenarios, the high-low game and the linear perceptron, we evaluate the generalization performance obtained by applying the corresponding query construction algorithms and compare it to training on random examples. We find qualitative differences between the two scenarios due to the different structure of the underlying rules (nonlinear and ``noninvertible'' versus linear); in particular, for the linear perceptron, random examples lead to the same generalization ability as a sequence of queries in the limit of an infinite number of examples. We also investigate learning algorithms which are ill matched to the learning environment and find that, in this case, minimum entropy queries can in fact yield a lower generalization ability than random examples. Finally, we study the efficiency of single queries and its dependence on the learning history, i.e., on whether the previous training examples were generated randomly or by querying, and the difference between globally and locally optimal query construction.

Computational method for the correction of proximity effect in electron-beam lithography (Poster Paper)

NASA Astrophysics Data System (ADS)

Chang, Chih-Yuan; Owen, Gerry; Pease, Roger Fabian W.; Kailath, Thomas

1992-07-01

Dose correction is commonly used to compensate for the proximity effect in electron lithography. The computation of the required dose modulation is usually carried out using 'self-consistent' algorithms that work by solving a large number of simultaneous linear equations. However, there are two major drawbacks: the resulting correction is not exact, and the computation time is excessively long. A computational scheme, as shown in Figure 1, has been devised to eliminate this problem by the deconvolution of the point spread function in the pattern domain. The method is iterative, based on a steepest descent algorithm. The scheme has been successfully tested on a simple pattern with a minimum feature size 0.5 micrometers , exposed on a MEBES tool at 10 KeV in 0.2 micrometers of PMMA resist on a silicon substrate.

Deconvolution of gas chromatographic data

NASA Technical Reports Server (NTRS)

Howard, S.; Rayborn, G. H.

1980-01-01

The use of deconvolution methods on gas chromatographic data to obtain an accurate determination of the relative amounts of each material present by mathematically separating the merged peaks is discussed. Data were obtained on a gas chromatograph with a flame ionization detector. Chromatograms of five xylenes with differing degrees of separation were generated by varying the column temperature at selected rates. The merged peaks were then successfully separated by deconvolution. The concept of function continuation in the frequency domain was introduced in striving to reach the theoretical limit of accuracy, but proved to be only partially successful.

Detailed interpretation of aeromagnetic data from the Patagonia Mountains area, southeastern Arizona

USGS Publications Warehouse

Bultman, Mark W.

2015-01-01

Euler deconvolution depth estimates derived from aeromagnetic data with a structural index of 0 show that mapped faults on the northern margin of the Patagonia Mountains generally agree with the depth estimates in the new geologic model. The deconvolution depth estimates also show that the concealed Patagonia Fault southwest of the Patagonia Mountains is more complex than recent geologic mapping represents. Additionally, Euler deconvolution depth estimates with a structural index of 2 locate many potential intrusive bodies that might be associated with known and unknown mineralization.

[Glossary of terms used by radiologists in image processing].

PubMed

Rolland, Y; Collorec, R; Bruno, A; Ramée, A; Morcet, N; Haigron, P

1995-01-01

We give the definition of 166 words used in image processing. Adaptivity, aliazing, analog-digital converter, analysis, approximation, arc, artifact, artificial intelligence, attribute, autocorrelation, bandwidth, boundary, brightness, calibration, class, classification, classify, centre, cluster, coding, color, compression, contrast, connectivity, convolution, correlation, data base, decision, decomposition, deconvolution, deduction, descriptor, detection, digitization, dilation, discontinuity, discretization, discrimination, disparity, display, distance, distorsion, distribution dynamic, edge, energy, enhancement, entropy, erosion, estimation, event, extrapolation, feature, file, filter, filter floaters, fitting, Fourier transform, frequency, fusion, fuzzy, Gaussian, gradient, graph, gray level, group, growing, histogram, Hough transform, Houndsfield, image, impulse response, inertia, intensity, interpolation, interpretation, invariance, isotropy, iterative, JPEG, knowledge base, label, laplacian, learning, least squares, likelihood, matching, Markov field, mask, matching, mathematical morphology, merge (to), MIP, median, minimization, model, moiré, moment, MPEG, neural network, neuron, node, noise, norm, normal, operator, optical system, optimization, orthogonal, parametric, pattern recognition, periodicity, photometry, pixel, polygon, polynomial, prediction, pulsation, pyramidal, quantization, raster, reconstruction, recursive, region, rendering, representation space, resolution, restoration, robustness, ROC, thinning, transform, sampling, saturation, scene analysis, segmentation, separable function, sequential, smoothing, spline, split (to), shape, threshold, tree, signal, speckle, spectrum, spline, stationarity, statistical, stochastic, structuring element, support, syntaxic, synthesis, texture, truncation, variance, vision, voxel, windowing.

SU-G-IeP3-08: Image Reconstruction for Scanning Imaging System Based On Shape-Modulated Point Spreading Function

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

Wang, Ruixing; Yang, LV; Xu, Kele

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 -more » 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.« less

Spectral identification of a 90Sr source in the presence of masking nuclides using Maximum-Likelihood deconvolution

NASA Astrophysics Data System (ADS)

Neuer, Marcus J.

2013-11-01

A technique for the spectral identification of strontium-90 is shown, utilising a Maximum-Likelihood deconvolution. Different deconvolution approaches are discussed and summarised. Based on the intensity distribution of the beta emission and Geant4 simulations, a combined response matrix is derived, tailored to the β- detection process in sodium iodide detectors. It includes scattering effects and attenuation by applying a base material decomposition extracted from Geant4 simulations with a CAD model for a realistic detector system. Inversion results of measurements show the agreement between deconvolution and reconstruction. A detailed investigation with additional masking sources like 40K, 226Ra and 131I shows that a contamination of strontium can be found in the presence of these nuisance sources. Identification algorithms for strontium are presented based on the derived technique. For the implementation of blind identification, an exemplary masking ratio is calculated.

A frequency-domain seismic blind deconvolution based on Gini correlations

NASA Astrophysics Data System (ADS)

Wang, Zhiguo; Zhang, Bing; Gao, Jinghuai; Huo Liu, Qing

2018-02-01

In reflection seismic processing, the seismic blind deconvolution is a challenging problem, especially when the signal-to-noise ratio (SNR) of the seismic record is low and the length of the seismic record is short. As a solution to this ill-posed inverse problem, we assume that the reflectivity sequence is independent and identically distributed (i.i.d.). To infer the i.i.d. relationships from seismic data, we first introduce the Gini correlations (GCs) to construct a new criterion for the seismic blind deconvolution in the frequency-domain. Due to a unique feature, the GCs are robust in their higher tolerance of the low SNR data and less dependent on record length. Applications of the seismic blind deconvolution based on the GCs show their capacity in estimating the unknown seismic wavelet and the reflectivity sequence, whatever synthetic traces or field data, even with low SNR and short sample record.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis.

PubMed

Carnevale Neto, Fausto; Pilon, Alan C; Selegato, Denise M; Freire, Rafael T; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis

PubMed Central

Carnevale Neto, Fausto; Pilon, Alan C.; Selegato, Denise M.; Freire, Rafael T.; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P.; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts. PMID:27747213

A method of PSF generation for 3D brightfield deconvolution.

PubMed

Tadrous, P J

2010-02-01

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

A digital algorithm for spectral deconvolution with noise filtering and peak picking: NOFIPP-DECON

NASA Technical Reports Server (NTRS)

Edwards, T. R.; Settle, G. L.; Knight, R. D.

1975-01-01

Noise-filtering, peak-picking deconvolution software incorporates multiple convoluted convolute integers and multiparameter optimization pattern search. The two theories are described and three aspects of the software package are discussed in detail. Noise-filtering deconvolution was applied to a number of experimental cases ranging from noisy, nondispersive X-ray analyzer data to very noisy photoelectric polarimeter data. Comparisons were made with published infrared data, and a man-machine interactive language has evolved for assisting in very difficult cases. A modified version of the program is being used for routine preprocessing of mass spectral and gas chromatographic data.

The Small-scale Structure of Photospheric Convection Retrieved by a Deconvolution Technique Applied to Hinode /SP Data

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

Oba, T.; Riethmüller, T. L.; Solanki, S. K.

Solar granules are bright patterns surrounded by dark channels, called intergranular lanes, in the solar photosphere and are a manifestation of overshooting convection. Observational studies generally find stronger upflows in granules and weaker downflows in intergranular lanes. This trend is, however, inconsistent with the results of numerical simulations in which downflows are stronger than upflows through the joint action of gravitational acceleration/deceleration and pressure gradients. One cause of this discrepancy is the image degradation caused by optical distortion and light diffraction and scattering that takes place in an imaging instrument. We apply a deconvolution technique to Hinode /SP data inmore » an attempt to recover the original solar scene. Our results show a significant enhancement in both the convective upflows and downflows but particularly for the latter. After deconvolution, the up- and downflows reach maximum amplitudes of −3.0 km s{sup −1} and +3.0 km s{sup −1} at an average geometrical height of roughly 50 km, respectively. We found that the velocity distributions after deconvolution match those derived from numerical simulations. After deconvolution, the net LOS velocity averaged over the whole field of view lies close to zero as expected in a rough sense from mass balance.« less

Toxoplasma Modulates Signature Pathways of Human Epilepsy, Neurodegeneration & Cancer.

PubMed

Ngô, Huân M; Zhou, Ying; Lorenzi, Hernan; Wang, Kai; Kim, Taek-Kyun; Zhou, Yong; El Bissati, Kamal; Mui, Ernest; Fraczek, Laura; Rajagopala, Seesandra V; Roberts, Craig W; Henriquez, Fiona L; Montpetit, Alexandre; Blackwell, Jenefer M; Jamieson, Sarra E; Wheeler, Kelsey; Begeman, Ian J; Naranjo-Galvis, Carlos; Alliey-Rodriguez, Ney; Davis, Roderick G; Soroceanu, Liliana; Cobbs, Charles; Steindler, Dennis A; Boyer, Kenneth; Noble, A Gwendolyn; Swisher, Charles N; Heydemann, Peter T; Rabiah, Peter; Withers, Shawn; Soteropoulos, Patricia; Hood, Leroy; McLeod, Rima

2017-09-13

One third of humans are infected lifelong with the brain-dwelling, protozoan parasite, Toxoplasma gondii. Approximately fifteen million of these have congenital toxoplasmosis. Although neurobehavioral disease is associated with seropositivity, causality is unproven. To better understand what this parasite does to human brains, we performed a comprehensive systems analysis of the infected brain: We identified susceptibility genes for congenital toxoplasmosis in our cohort of infected humans and found these genes are expressed in human brain. Transcriptomic and quantitative proteomic analyses of infected human, primary, neuronal stem and monocytic cells revealed effects on neurodevelopment and plasticity in neural, immune, and endocrine networks. These findings were supported by identification of protein and miRNA biomarkers in sera of ill children reflecting brain damage and T. gondii infection. These data were deconvoluted using three systems biology approaches: "Orbital-deconvolution" elucidated upstream, regulatory pathways interconnecting human susceptibility genes, biomarkers, proteomes, and transcriptomes. "Cluster-deconvolution" revealed visual protein-protein interaction clusters involved in processes affecting brain functions and circuitry, including lipid metabolism, leukocyte migration and olfaction. Finally, "disease-deconvolution" identified associations between the parasite-brain interactions and epilepsy, movement disorders, Alzheimer's disease, and cancer. This "reconstruction-deconvolution" logic provides templates of progenitor cells' potentiating effects, and components affecting human brain parasitism and diseases.

Peptide de novo sequencing of mixture tandem mass spectra.

PubMed

Gorshkov, Vladimir; Hotta, Stéphanie Yuki Kolbeck; Verano-Braga, Thiago; Kjeldsen, Frank

2016-09-01

The impact of mixture spectra deconvolution on the performance of four popular de novo sequencing programs was tested using artificially constructed mixture spectra as well as experimental proteomics data. Mixture fragmentation spectra are recognized as a limitation in proteomics because they decrease the identification performance using database search engines. De novo sequencing approaches are expected to be even more sensitive to the reduction in mass spectrum quality resulting from peptide precursor co-isolation and thus prone to false identifications. The deconvolution approach matched complementary b-, y-ions to each precursor peptide mass, which allowed the creation of virtual spectra containing sequence specific fragment ions of each co-isolated peptide. Deconvolution processing resulted in equally efficient identification rates but increased the absolute number of correctly sequenced peptides. The improvement was in the range of 20-35% additional peptide identifications for a HeLa lysate sample. Some correct sequences were identified only using unprocessed spectra; however, the number of these was lower than those where improvement was obtained by mass spectral deconvolution. Tight candidate peptide score distribution and high sensitivity to small changes in the mass spectrum introduced by the employed deconvolution method could explain some of the missing peptide identifications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Variation principle in calculating the flow of a two-phase mixture in the pipes of the cooling systems in high-rise buildings

NASA Astrophysics Data System (ADS)

Aksenov, Andrey; Malysheva, Anna

2018-03-01

The analytical solution of one of the urgent problems of modern hydromechanics and heat engineering about the distribution of gas and liquid phases along the channel cross-section, the thickness of the annular layer and their connection with the mass content of the gas phase in the gas-liquid flow is given in the paper.The analytical method is based on the fundamental laws of theoretical mechanics and thermophysics on the minimum of energy dissipation and the minimum rate of increase in the system entropy, which determine the stability of stationary states and processes. Obtained dependencies disclose the physical laws of the motion of two-phase media and can be used in hydraulic calculations during the design and operation of refrigeration and air conditioning systems.

Heat engine by exorcism of Maxwell Demon using spin angular momentum reservoir

NASA Astrophysics Data System (ADS)

Bedkihal, Salil; Wright, Jackson; Vaccaro, Joan; Gould, Tim

Landauer's erasure principle is a hallmark in thermodynamics and information theory. According to this principle, erasing one bit of information incurs a minimum energy cost. Recently, Vaccaro and Barnett (VB) have explored the role of multiple conserved quantities in memory erasure. They further illustrated that for the energy degenerate spin reservoirs, the cost of erasure can be solely in terms of spin angular momentum and no energy. Motivated by the VB erasure, in this work we propose a novel optical heat engine that operates under a single thermal reservoir and a spin angular momentum reservoir. The novel heat engine exploits ultrafast processes of phonon absorption to convert thermal phonon energy to coherent light. The entropy generated in this process then corresponds to a mixture of spin up and spin down populations of energy degenerate electronic ground states which acts as demon's memory. This information is then erased using a polarised spin reservoir that acts as an entropy sink. The proposed heat engines goes beyond the traditional Carnot engine.

System Mass Variation and Entropy Generation in 100k We Closed-Brayton-Cycle Space Power Systems

NASA Technical Reports Server (NTRS)

Barrett, Michael J.; Reid, Bryan M.

2004-01-01

State-of-the-art closed-Brayton-cycle (CBC) space power systems were modeled to study performance trends in a trade space characteristic of interplanetary orbiters. For working-fluid molar masses of 48.6, 39.9, and 11.9 kg/kmol, peak system pressures of 1.38 and 3.0 MPa and compressor pressure ratios ranging from 1.6 to 2.4, total system masses were estimated. System mass increased as peak operating pressure increased for all compressor pressure ratios and molar mass values examined. Minimum mass point comparison between 72 percent He at 1.38 MPa peak and 94 percent He at 3.0 MPa peak showed an increase in system mass of 14 percent. Converter flow loop entropy generation rates were calculated for 1.38 and 3.0 MPa peak pressure cases. Physical system behavior was approximated using a pedigreed NASA Glenn modeling code, Closed Cycle Engine Program (CCEP), which included realistic performance prediction for heat exchangers, radiators and turbomachinery.

System Mass Variation and Entropy Generation in 100-kWe Closed-Brayton-Cycle Space Power Systems

NASA Technical Reports Server (NTRS)

Barrett, Michael J.; Reid, Bryan M.

2004-01-01

State-of-the-art closed-Brayton-cycle (CBC) space power systems were modeled to study performance trends in a trade space characteristic of interplanetary orbiters. For working-fluid molar masses of 48.6, 39.9, and 11.9 kg/kmol, peak system pressures of 1.38 and 3.0 MPa and compressor pressure ratios ranging from 1.6 to 2.4, total system masses were estimated. System mass increased as peak operating pressure increased for all compressor pressure ratios and molar mass values examined. Minimum mass point comparison between 72 percent He at 1.38 MPa peak and 94 percent He at 3.0 MPa peak showed an increase in system mass of 14 percent. Converter flow loop entropy generation rates were calculated for 1.38 and 3.0 MPa peak pressure cases. Physical system behavior was approximated using a pedigreed NASA Glenn modeling code, Closed Cycle Engine Program (CCEP), which included realistic performance prediction for heat exchangers, radiators and turbomachinery.

Study of Thermodynamics of Liquid Noble-Metals Alloys Through a Pseudopotential Theory

NASA Astrophysics Data System (ADS)

Vora, Aditya M.

2010-09-01

The Gibbs-Bogoliubov (GB) inequality is applied to investigate the thermodynamic properties of some equiatomic noble metal alloys in liquid phase such as Au-Cu, Ag-Cu, and Ag-Au using well recognized pseudopotential formalism. For description of the structure, well known Percus-Yevick (PY) hard sphere model is used as a reference system. By applying a variation method the best hard core diameters have been found which correspond to minimum free energy. With this procedure the thermodynamic properties such as entropy and heat of mixing have been computed. The influence of local field correction function viz; Hartree (H), Taylor (T), Ichimaru-Utsumi (IU), Farid et al. (F), and Sarkar et al. (S) is also investigated. The computed results of the excess entropy compares favourably in the case of liquid alloys while the agreement with experiment is poor in the case of heats of mixing. This may be due to the sensitivity of the heats of mixing with the potential parameters and the dielectric function.

Minimum entropy principle-based solar cell operation without a pn-junction and a thin CdS layer to extract the holes from the emitter

NASA Astrophysics Data System (ADS)

Böer, Karl W.

2016-10-01

The solar cell does not use a pn-junction to separate electrons from holes, but uses an undoped CdS layer that is p-type inverted when attached to a p-type collector and collects the holes while rejecting the backflow of electrons and thereby prevents junction leakage. The operation of the solar cell is determined by the minimum entropy principle of the cell and its external circuit that determines the electrochemical potential, i.e., the Fermi-level of the base electrode to the operating (maximum power point) voltage. It leaves the Fermi level of the metal electrode of the CdS unchanged, since CdS does not participate in the photo-emf. All photoelectric actions are generated by the holes excited from the light that causes the shift of the quasi-Fermi levels in the generator and supports the diffusion current in operating conditions. It is responsible for the measured solar maximum power current. The open circuit voltage (Voc) can approach its theoretical limit of the band gap of the collector at 0 K and the cell increases the efficiency at AM1 to 21% for a thin-film CdS/CdTe that is given as an example here. However, a series resistance of the CdS forces a limitation of its thickness to preferably below 200 Å to avoid unnecessary reduction in efficiency or Voc. The operation of the CdS solar cell does not involve heated carriers. It is initiated by the field at the CdS/CdTe interface that exceeds 20 kV/cm that is sufficient to cause extraction of holes by the CdS that is inverted to become p-type. Here a strong doubly charged intrinsic donor can cause a negative differential conductivity that switches-on a high-field domain that is stabilized by the minimum entropy principle and permits an efficient transport of the holes from the CdTe to the base electrode. Experimental results of the band model of CdS/CdTe solar cells are given and show that the conduction bands are connected in the dark, where the electron current must be continuous, and the valence bands are connected with light where the hole currents are dominant and must be continuous through the junction. The major shifts of the bands in operating conditions are self-adjusting by a change in the junction dipole momentum.

Towards robust deconvolution of low-dose perfusion CT: sparse perfusion deconvolution using online dictionary learning.

PubMed

Fang, Ruogu; Chen, Tsuhan; Sanelli, Pina C

2013-05-01

Computed tomography perfusion (CTP) is an important functional imaging modality in the evaluation of cerebrovascular diseases, particularly in acute stroke and vasospasm. However, the post-processed parametric maps of blood flow tend to be noisy, especially in low-dose CTP, due to the noisy contrast enhancement profile and the oscillatory nature of the results generated by the current computational methods. In this paper, we propose a robust sparse perfusion deconvolution method (SPD) to estimate cerebral blood flow in CTP performed at low radiation dose. We first build a dictionary from high-dose perfusion maps using online dictionary learning and then perform deconvolution-based hemodynamic parameters estimation on the low-dose CTP data. Our method is validated on clinical data of patients with normal and pathological CBF maps. The results show that we achieve superior performance than existing methods, and potentially improve the differentiation between normal and ischemic tissue in the brain. Copyright © 2013 Elsevier B.V. All rights reserved.

Deconvolution of azimuthal mode detection measurements

NASA Astrophysics Data System (ADS)

Sijtsma, Pieter; Brouwer, Harry

2018-05-01

Unequally spaced transducer rings make it possible to extend the range of detectable azimuthal modes. The disadvantage is that the response of the mode detection algorithm to a single mode is distributed over all detectable modes, similarly to the Point Spread Function of Conventional Beamforming with microphone arrays. With multiple modes the response patterns interfere, leading to a relatively high "noise floor" of spurious modes in the detected mode spectrum, in other words, to a low dynamic range. In this paper a deconvolution strategy is proposed for increasing this dynamic range. It starts with separating the measured sound into shaft tones and broadband noise. For broadband noise modes, a standard Non-Negative Least Squares solver appeared to be a perfect deconvolution tool. For shaft tones a Matching Pursuit approach is proposed, taking advantage of the sparsity of dominant modes. The deconvolution methods were applied to mode detection measurements in a fan rig. An increase in dynamic range of typically 10-15 dB was found.

Joint deconvolution and classification with applications to passive acoustic underwater multipath.

PubMed

Anderson, Hyrum S; Gupta, Maya R

2008-11-01

This paper addresses the problem of classifying signals that have been corrupted by noise and unknown linear time-invariant (LTI) filtering such as multipath, given labeled uncorrupted training signals. A maximum a posteriori approach to the deconvolution and classification is considered, which produces estimates of the desired signal, the unknown channel, and the class label. For cases in which only a class label is needed, the classification accuracy can be improved by not committing to an estimate of the channel or signal. A variant of the quadratic discriminant analysis (QDA) classifier is proposed that probabilistically accounts for the unknown LTI filtering, and which avoids deconvolution. The proposed QDA classifier can work either directly on the signal or on features whose transformation by LTI filtering can be analyzed; as an example a classifier for subband-power features is derived. Results on simulated data and real Bowhead whale vocalizations show that jointly considering deconvolution with classification can dramatically improve classification performance over traditional methods over a range of signal-to-noise ratios.

Application of Fourier-wavelet regularized deconvolution for improving image quality of free space propagation x-ray phase contrast imaging.

PubMed

Zhou, Zhongxing; Gao, Feng; Zhao, Huijuan; Zhang, Lixin

2012-11-21

New x-ray phase contrast imaging techniques without using synchrotron radiation confront a common problem from the negative effects of finite source size and limited spatial resolution. These negative effects swamp the fine phase contrast fringes and make them almost undetectable. In order to alleviate this problem, deconvolution procedures should be applied to the blurred x-ray phase contrast images. In this study, three different deconvolution techniques, including Wiener filtering, Tikhonov regularization and Fourier-wavelet regularized deconvolution (ForWaRD), were applied to the simulated and experimental free space propagation x-ray phase contrast images of simple geometric phantoms. These algorithms were evaluated in terms of phase contrast improvement and signal-to-noise ratio. The results demonstrate that the ForWaRD algorithm is most appropriate for phase contrast image restoration among above-mentioned methods; it can effectively restore the lost information of phase contrast fringes while reduce the amplified noise during Fourier regularization.

A new scoring function for top-down spectral deconvolution

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

Kou, Qiang; Wu, Si; Liu, Xiaowen

2014-12-18

Background: Top-down mass spectrometry plays an important role in intact protein identification and characterization. Top-down mass spectra are more complex than bottom-up mass spectra because they often contain many isotopomer envelopes from highly charged ions, which may overlap with one another. As a result, spectral deconvolution, which converts a complex top-down mass spectrum into a monoisotopic mass list, is a key step in top-down spectral interpretation. Results: In this paper, we propose a new scoring function, L-score, for evaluating isotopomer envelopes. By combining L-score with MS-Deconv, a new software tool, MS-Deconv+, was developed for top-down spectral deconvolution. Experimental results showedmore » that MS-Deconv+ outperformed existing software tools in top-down spectral deconvolution. Conclusions: L-score shows high discriminative ability in identification of isotopomer envelopes. Using L-score, MS-Deconv+ reports many correct monoisotopic masses missed by other software tools, which are valuable for proteoform identification and characterization.« less

Bayesian Deconvolution for Angular Super-Resolution in Forward-Looking Scanning Radar

PubMed Central

Zha, Yuebo; Huang, Yulin; Sun, Zhichao; Wang, Yue; Yang, Jianyu

2015-01-01

Scanning radar is of notable importance for ground surveillance, terrain mapping and disaster rescue. However, the angular resolution of a scanning radar image is poor compared to the achievable range resolution. This paper presents a deconvolution algorithm for angular super-resolution in scanning radar based on Bayesian theory, which states that the angular super-resolution can be realized by solving the corresponding deconvolution problem with the maximum a posteriori (MAP) criterion. The algorithm considers that the noise is composed of two mutually independent parts, i.e., a Gaussian signal-independent component and a Poisson signal-dependent component. In addition, the Laplace distribution is used to represent the prior information about the targets under the assumption that the radar image of interest can be represented by the dominant scatters in the scene. Experimental results demonstrate that the proposed deconvolution algorithm has higher precision for angular super-resolution compared with the conventional algorithms, such as the Tikhonov regularization algorithm, the Wiener filter and the Richardson–Lucy algorithm. PMID:25806871

Towards robust deconvolution of low-dose perfusion CT: Sparse perfusion deconvolution using online dictionary learning

PubMed Central

Fang, Ruogu; Chen, Tsuhan; Sanelli, Pina C.

2014-01-01

Computed tomography perfusion (CTP) is an important functional imaging modality in the evaluation of cerebrovascular diseases, particularly in acute stroke and vasospasm. However, the post-processed parametric maps of blood flow tend to be noisy, especially in low-dose CTP, due to the noisy contrast enhancement profile and the oscillatory nature of the results generated by the current computational methods. In this paper, we propose a robust sparse perfusion deconvolution method (SPD) to estimate cerebral blood flow in CTP performed at low radiation dose. We first build a dictionary from high-dose perfusion maps using online dictionary learning and then perform deconvolution-based hemodynamic parameters estimation on the low-dose CTP data. Our method is validated on clinical data of patients with normal and pathological CBF maps. The results show that we achieve superior performance than existing methods, and potentially improve the differentiation between normal and ischemic tissue in the brain. PMID:23542422

Entropy measures detect increased movement variability in resistance training when elite rugby players use the ball.

PubMed

Moras, Gerard; Fernández-Valdés, Bruno; Vázquez-Guerrero, Jairo; Tous-Fajardo, Julio; Exel, Juliana; Sampaio, Jaime

2018-05-24

This study described the variability in acceleration during a resistance training task, performed in horizontal inertial flywheels without (NOBALL) or with the constraint of catching and throwing a rugby ball (BALL). Twelve elite rugby players (mean±SD: age 25.6±3.0years, height 1.82±0.07m, weight 94.0±9.9kg) performed a resistance training task in both conditions (NOBALL AND BALL). Players had five minutes of a standardized warm-up, followed by two series of six repetitions of both conditions: at the first three repetitions the intensity was progressively increased while the last three were performed at maximal voluntary effort. Thereafter, the participants performed two series of eight repetitions from each condition for two days and in a random order, with a minimum of 10min between series. The structure of variability was analysed using non-linear measures of entropy. Mean changes (%; ±90% CL) of 4.64; ±3.1g for mean acceleration and 39.48; ±36.63a.u. for sample entropy indicated likely and very likely increase when in BALL condition. Multiscale entropy also showed higher unpredictability of acceleration under the BALL condition, especially at higher time scales. The application of match specific constraints in resistance training for rugby players elicit different amount of variability of body acceleration across multiple physiological time scales. Understanding the non-linear process inherent to the manipulation of resistance training variables with constraints and its motor adaptations may help coaches and trainers to enhance the effectiveness of physical training and, ultimately, better understand and maximize sports performance. Copyright © 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Studies in astronomical time series analysis. IV - Modeling chaotic and random processes with linear filters

NASA Technical Reports Server (NTRS)

Scargle, Jeffrey D.

1990-01-01

While chaos arises only in nonlinear systems, standard linear time series models are nevertheless useful for analyzing data from chaotic processes. This paper introduces such a model, the chaotic moving average. This time-domain model is based on the theorem that any chaotic process can be represented as the convolution of a linear filter with an uncorrelated process called the chaotic innovation. A technique, minimum phase-volume deconvolution, is introduced to estimate the filter and innovation. The algorithm measures the quality of a model using the volume covered by the phase-portrait of the innovation process. Experiments on synthetic data demonstrate that the algorithm accurately recovers the parameters of simple chaotic processes. Though tailored for chaos, the algorithm can detect both chaos and randomness, distinguish them from each other, and separate them if both are present. It can also recover nonminimum-delay pulse shapes in non-Gaussian processes, both random and chaotic.

Systematic approach to cutoff frequency selection in continuous-wave electron paramagnetic resonance imaging

NASA Astrophysics Data System (ADS)

Hirata, Hiroshi; Itoh, Toshiharu; Hosokawa, Kouichi; Deng, Yuanmu; Susaki, Hitoshi

2005-08-01

This article describes a systematic method for determining the cutoff frequency of the low-pass window function that is used for deconvolution in two-dimensional continuous-wave electron paramagnetic resonance (EPR) imaging. An evaluation function for the criterion used to select the cutoff frequency is proposed, and is the product of the effective width of the point spread function for a localized point signal and the noise amplitude of a resultant EPR image. The present method was applied to EPR imaging for a phantom, and the result of cutoff frequency selection was compared with that based on a previously reported method for the same projection data set. The evaluation function has a global minimum point that gives the appropriate cutoff frequency. Images with reasonably good resolution and noise suppression can be obtained from projections with an automatically selected cutoff frequency based on the present method.

Achieving high spatial resolution using a microchannel plate detector with an economic and scalable approach

NASA Astrophysics Data System (ADS)

Wiggins, B. B.; deSouza, Z. O.; Vadas, J.; Alexander, A.; Hudan, S.; deSouza, R. T.

2017-11-01

A second generation position-sensitive microchannel plate detector using the induced signal approach has been realized. This detector is presently capable of measuring the incident position of electrons, photons, or ions. To assess the spatial resolution, the masked detector was illuminated by electrons. The initial, measured spatial resolution of 276 μm FWHM was improved by requiring a minimum signal amplitude on the anode and by employing digital signal processing techniques. The resulting measured spatial resolution of 119 μm FWHM corresponds to an intrinsic resolution of 98 μm FWHM when the effect of the finite slit width is de-convoluted. This measurement is a substantial improvement from the last reported spatial resolution of 466 μm FWHM using the induced signal approach. To understand the factors that limit the measured resolution, the performance of the detector is simulated.

Development of a compact E ? B microchannel plate detector for beam imaging

DOE PAGES

Wiggins, B. B.; Singh, Varinderjit; Vadas, J.; ...

2017-06-17

A beam imaging detector was developed by coupling a multi-strip anode with delay line readout to an E×B microchannel plate (MCP) detector. This detector is capable of measuring the incident position of the beam particles in one-dimension. To assess the spatial resolution, the detector was illuminated by an α-source with an intervening mask that consists of a series of precisely-machined slits. The measured spatial resolution was 520 um source FWHM, which was improved to 413 um FWHM by performing an FFT of the signals, rejecting spurious signals on the delay line, and requiring a minimum signal amplitude. This measured spatialmore » resolution of 413 um FWHM corresponds to an intrinsic resolution of 334 um FWHM when the effect of the finite slit width is de-convoluted. To understand the measured resolution, the performance of the detector is simulated with the ion-trajectory code SIMION.« less

Development of a compact E ? B microchannel plate detector for beam imaging

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

Wiggins, B. B.; Singh, Varinderjit; Vadas, J.

A beam imaging detector was developed by coupling a multi-strip anode with delay line readout to an E×B microchannel plate (MCP) detector. This detector is capable of measuring the incident position of the beam particles in one-dimension. To assess the spatial resolution, the detector was illuminated by an α-source with an intervening mask that consists of a series of precisely-machined slits. The measured spatial resolution was 520 um source FWHM, which was improved to 413 um FWHM by performing an FFT of the signals, rejecting spurious signals on the delay line, and requiring a minimum signal amplitude. This measured spatialmore » resolution of 413 um FWHM corresponds to an intrinsic resolution of 334 um FWHM when the effect of the finite slit width is de-convoluted. To understand the measured resolution, the performance of the detector is simulated with the ion-trajectory code SIMION.« less

Waveform LiDAR processing: comparison of classic approaches and optimized Gold deconvolution to characterize vegetation structure and terrain elevation

NASA Astrophysics Data System (ADS)

Zhou, T.; Popescu, S. C.; Krause, K.

2016-12-01

Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: 1) direct decomposition, 2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms - the Richardson Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from discrete LiDAR data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference (<1.22 m for DTMs, < 0.77 m for CHMs) and root mean square error (RMSE) (<1.26 m for DTMs, < 1.93 m for CHMs). More specifically, the Gold algorithm is superior to others with smaller root mean square error (RMSE) (< 1.01m), while the direct decomposition approach works better in terms of the percentage of spatial difference within 0.5 and 1 m. The parameter uncertainty analysis demonstrates that the Gold algorithm outperforms other approaches in dense vegetation areas, with the smallest RMSE, and the RL algorithm performs better in sparse vegetation areas in terms of RMSE.

Processing of single channel air and water gun data for imaging an impact structure at the Chesapeake Bay

USGS Publications Warehouse

Lee, Myung W.

1999-01-01

Processing of 20 seismic profiles acquired in the Chesapeake Bay area aided in analysis of the details of an impact structure and allowed more accurate mapping of the depression caused by a bolide impact. Particular emphasis was placed on enhancement of seismic reflections from the basement. Application of wavelet deconvolution after a second zero-crossing predictive deconvolution improved the resolution of shallow reflections, and application of a match filter enhanced the basement reflections. The use of deconvolution and match filtering with a two-dimensional signal enhancement technique (F-X filtering) significantly improved the interpretability of seismic sections.

Handling of computational in vitro/in vivo correlation problems by Microsoft Excel: III. Convolution and deconvolution.

PubMed

Langenbucher, Frieder

2003-11-01

Convolution and deconvolution are the classical in-vitro-in-vivo correlation tools to describe the relationship between input and weighting/response in a linear system, where input represents the drug release in vitro, weighting/response any body response in vivo. While functional treatment, e.g. in terms of polyexponential or Weibull distribution, is more appropriate for general survey or prediction, numerical algorithms are useful for treating actual experimental data. Deconvolution is not considered an algorithm by its own, but the inversion of a corresponding convolution. MS Excel is shown to be a useful tool for all these applications.

Generating Multivariate Ordinal Data via Entropy Principles.

PubMed

Lee, Yen; Kaplan, David

2018-03-01

When conducting robustness research where the focus of attention is on the impact of non-normality, the marginal skewness and kurtosis are often used to set the degree of non-normality. Monte Carlo methods are commonly applied to conduct this type of research by simulating data from distributions with skewness and kurtosis constrained to pre-specified values. Although several procedures have been proposed to simulate data from distributions with these constraints, no corresponding procedures have been applied for discrete distributions. In this paper, we present two procedures based on the principles of maximum entropy and minimum cross-entropy to estimate the multivariate observed ordinal distributions with constraints on skewness and kurtosis. For these procedures, the correlation matrix of the observed variables is not specified but depends on the relationships between the latent response variables. With the estimated distributions, researchers can study robustness not only focusing on the levels of non-normality but also on the variations in the distribution shapes. A simulation study demonstrates that these procedures yield excellent agreement between specified parameters and those of estimated distributions. A robustness study concerning the effect of distribution shape in the context of confirmatory factor analysis shows that shape can affect the robust [Formula: see text] and robust fit indices, especially when the sample size is small, the data are severely non-normal, and the fitted model is complex.

High quality image-pair-based deblurring method using edge mask and improved residual deconvolution

NASA Astrophysics Data System (ADS)

Cui, Guangmang; Zhao, Jufeng; Gao, Xiumin; Feng, Huajun; Chen, Yueting

2017-04-01

Image deconvolution problem is a challenging task in the field of image process. Using image pairs could be helpful to provide a better restored image compared with the deblurring method from a single blurred image. In this paper, a high quality image-pair-based deblurring method is presented using the improved RL algorithm and the gain-controlled residual deconvolution technique. The input image pair includes a non-blurred noisy image and a blurred image captured for the same scene. With the estimated blur kernel, an improved RL deblurring method based on edge mask is introduced to obtain the preliminary deblurring result with effective ringing suppression and detail preservation. Then the preliminary deblurring result is served as the basic latent image and the gain-controlled residual deconvolution is utilized to recover the residual image. A saliency weight map is computed as the gain map to further control the ringing effects around the edge areas in the residual deconvolution process. The final deblurring result is obtained by adding the preliminary deblurring result with the recovered residual image. An optical experimental vibration platform is set up to verify the applicability and performance of the proposed algorithm. Experimental results demonstrate that the proposed deblurring framework obtains a superior performance in both subjective and objective assessments and has a wide application in many image deblurring fields.

Windprofiler optimization using digital deconvolution procedures

NASA Astrophysics Data System (ADS)

Hocking, W. K.; Hocking, A.; Hocking, D. G.; Garbanzo-Salas, M.

2014-10-01

Digital improvements to data acquisition procedures used for windprofiler radars have the potential for improving the height coverage at optimum resolution, and permit improved height resolution. A few newer systems already use this capability. Real-time deconvolution procedures offer even further optimization, and this has not been effectively employed in recent years. In this paper we demonstrate the advantages of combining these features, with particular emphasis on the advantages of real-time deconvolution. Using several multi-core CPUs, we have been able to achieve speeds of up to 40 GHz from a standard commercial motherboard, allowing data to be digitized and processed without the need for any type of hardware except for a transmitter (and associated drivers), a receiver and a digitizer. No Digital Signal Processor chips are needed, allowing great flexibility with analysis algorithms. By using deconvolution procedures, we have then been able to not only optimize height resolution, but also have been able to make advances in dealing with spectral contaminants like ground echoes and other near-zero-Hz spectral contamination. Our results also demonstrate the ability to produce fine-resolution measurements, revealing small-scale structures within the backscattered echoes that were previously not possible to see. Resolutions of 30 m are possible for VHF radars. Furthermore, our deconvolution technique allows the removal of range-aliasing effects in real time, a major bonus in many instances. Results are shown using new radars in Canada and Costa Rica.

Geometric characterization of separability and entanglement in pure Gaussian states by single-mode unitary operations

NASA Astrophysics Data System (ADS)

Adesso, Gerardo; Giampaolo, Salvatore M.; Illuminati, Fabrizio

2007-10-01

We present a geometric approach to the characterization of separability and entanglement in pure Gaussian states of an arbitrary number of modes. The analysis is performed adapting to continuous variables a formalism based on single subsystem unitary transformations that has been recently introduced to characterize separability and entanglement in pure states of qubits and qutrits [S. M. Giampaolo and F. Illuminati, Phys. Rev. A 76, 042301 (2007)]. In analogy with the finite-dimensional case, we demonstrate that the 1×M bipartite entanglement of a multimode pure Gaussian state can be quantified by the minimum squared Euclidean distance between the state itself and the set of states obtained by transforming it via suitable local symplectic (unitary) operations. This minimum distance, corresponding to a , uniquely determined, extremal local operation, defines an entanglement monotone equivalent to the entropy of entanglement, and amenable to direct experimental measurement with linear optical schemes.

Dirac dispersion generates unusually large Nernst effect in Weyl semimetals

NASA Astrophysics Data System (ADS)

Watzman, Sarah J.; McCormick, Timothy M.; Shekhar, Chandra; Wu, Shu-Chun; Sun, Yan; Prakash, Arati; Felser, Claudia; Trivedi, Nandini; Heremans, Joseph P.

2018-04-01

Weyl semimetals contain linearly dispersing electronic states, offering interesting features in transport yet to be thoroughly explored thermally. Here we show how the Nernst effect, combining entropy with charge transport, gives a unique signature for the presence of Dirac bands and offers a diagnostic to determine if trivial pockets play a role in this transport. The Nernst thermopower of NbP exceeds its conventional thermopower by a 100-fold, and the temperature dependence of the Nernst effect has a pronounced maximum. The charge-neutrality condition dictates that the Fermi level shifts with increasing temperature toward the energy that has the minimum density of states (DOS). In NbP, the agreement of the Nernst and Seebeck data with a model that assumes this minimum DOS resides at the Dirac points is taken as strong experimental evidence that the trivial (non-Dirac) bands play no role in high-temperature transport.

Strehl-constrained iterative blind deconvolution for post-adaptive-optics data

NASA Astrophysics Data System (ADS)

Desiderà, G.; Carbillet, M.

2009-12-01

Aims: We aim to improve blind deconvolution applied to post-adaptive-optics (AO) data by taking into account one of their basic characteristics, resulting from the necessarily partial AO correction: the Strehl ratio. Methods: We apply a Strehl constraint in the framework of iterative blind deconvolution (IBD) of post-AO near-infrared images simulated in a detailed end-to-end manner and considering a case that is as realistic as possible. Results: The results obtained clearly show the advantage of using such a constraint, from the point of view of both performance and stability, especially for poorly AO-corrected data. The proposed algorithm has been implemented in the freely-distributed and CAOS-based Software Package AIRY.

Calibration of a polarimetric imaging SAR

NASA Technical Reports Server (NTRS)

Sarabandi, K.; Pierce, L. E.; Ulaby, F. T.

1991-01-01

Calibration of polarimetric imaging Synthetic Aperture Radars (SAR's) using point calibration targets is discussed. The four-port network calibration technique is used to describe the radar error model. The polarimetric ambiguity function of the SAR is then found using a single point target, namely a trihedral corner reflector. Based on this, an estimate for the backscattering coefficient of the terrain is found by a deconvolution process. A radar image taken by the JPL Airborne SAR (AIRSAR) is used for verification of the deconvolution calibration method. The calibrated responses of point targets in the image are compared both with theory and the POLCAL technique. Also, response of a distributed target are compared using the deconvolution and POLCAL techniques.

First-order irreversible thermodynamic approach to a simple energy converter

NASA Astrophysics Data System (ADS)

Arias-Hernandez, L. A.; Angulo-Brown, F.; Paez-Hernandez, R. T.

2008-01-01

Several authors have shown that dissipative thermal cycle models based on finite-time thermodynamics exhibit loop-shaped curves of power output versus efficiency, such as it occurs with actual dissipative thermal engines. Within the context of first-order irreversible thermodynamics (FOIT), in this work we show that for an energy converter consisting of two coupled fluxes it is also possible to find loop-shaped curves of both power output and the so-called ecological function versus efficiency. In a previous work Stucki [J. W. Stucki, Eur. J. Biochem. 109, 269 (1980)] used a FOIT approach to describe the modes of thermodynamic performance of oxidative phosphorylation involved in adenosine triphosphate (ATP) synthesis within mithochondrias. In that work the author did not use the mentioned loop-shaped curves and he proposed that oxidative phosphorylation operates in a steady state at both minimum entropy production and maximum efficiency simultaneously, by means of a conductance matching condition between extreme states of zero and infinite conductances, respectively. In the present work we show that all Stucki’s results about the oxidative phosphorylation energetics can be obtained without the so-called conductance matching condition. On the other hand, we also show that the minimum entropy production state implies both null power output and efficiency and therefore this state is not fulfilled by the oxidative phosphorylation performance. Our results suggest that actual efficiency values of oxidative phosphorylation performance are better described by a mode of operation consisting of the simultaneous maximization of both the so-called ecological function and the efficiency.

Information-theoretic measures of hydrogen-like ions in weakly coupled Debye plasmas

NASA Astrophysics Data System (ADS)

Zan, Li Rong; Jiao, Li Guang; Ma, Jia; Ho, Yew Kam

2017-12-01

Recent development of information theory provides researchers an alternative and useful tool to quantitatively investigate the variation of the electronic structure when atoms interact with the external environment. In this work, we make systematic studies on the information-theoretic measures for hydrogen-like ions immersed in weakly coupled plasmas modeled by Debye-Hückel potential. Shannon entropy, Fisher information, and Fisher-Shannon complexity in both position and momentum spaces are quantified in high accuracy for the hydrogen atom in a large number of stationary states. The plasma screening effect on embedded atoms can significantly affect the electronic density distributions, in both conjugate spaces, and it is quantified by the variation of information quantities. It is shown that the composite quantities (the Shannon entropy sum and the Fisher information product in combined spaces and Fisher-Shannon complexity in individual space) give a more comprehensive description of the atomic structure information than single ones. The nodes of wave functions play a significant role in the changes of composite information quantities caused by plasmas. With the continuously increasing screening strength, all composite quantities in circular states increase monotonously, while in higher-lying excited states where nodal structures exist, they first decrease to a minimum and then increase rapidly before the bound state approaches the continuum limit. The minimum represents the most reduction of uncertainty properties of the atom in plasmas. The lower bounds for the uncertainty product of the system based on composite information quantities are discussed. Our research presents a comprehensive survey in the investigation of information-theoretic measures for simple atoms embedded in Debye model plasmas.

Histogram deconvolution - An aid to automated classifiers

NASA Technical Reports Server (NTRS)

Lorre, J. J.

1983-01-01

It is shown that N-dimensional histograms are convolved by the addition of noise in the picture domain. Three methods are described which provide the ability to deconvolve such noise-affected histograms. The purpose of the deconvolution is to provide automated classifiers with a higher quality N-dimensional histogram from which to obtain classification statistics.

Study of one- and two-dimensional filtering and deconvolution algorithms for a streaming array computer

NASA Technical Reports Server (NTRS)

Ioup, G. E.

1985-01-01

Appendix 5 of the Study of One- and Two-Dimensional Filtering and Deconvolution Algorithms for a Streaming Array Computer includes a resume of the professional background of the Principal Investigator on the project, lists of this publications and research papers, graduate thesis supervised, and grants received.

Blind Deconvolution for Distributed Parameter Systems with Unbounded Input and Output and Determining Blood Alcohol Concentration from Transdermal Biosensor Data.

PubMed

Rosen, I G; Luczak, Susan E; Weiss, Jordan

2014-03-15

We develop a blind deconvolution scheme for input-output systems described by distributed parameter systems with boundary input and output. An abstract functional analytic theory based on results for the linear quadratic control of infinite dimensional systems with unbounded input and output operators is presented. The blind deconvolution problem is then reformulated as a series of constrained linear and nonlinear optimization problems involving infinite dimensional dynamical systems. A finite dimensional approximation and convergence theory is developed. The theory is applied to the problem of estimating blood or breath alcohol concentration (respectively, BAC or BrAC) from biosensor-measured transdermal alcohol concentration (TAC) in the field. A distributed parameter model with boundary input and output is proposed for the transdermal transport of ethanol from the blood through the skin to the sensor. The problem of estimating BAC or BrAC from the TAC data is formulated as a blind deconvolution problem. A scheme to identify distinct drinking episodes in TAC data based on a Hodrick Prescott filter is discussed. Numerical results involving actual patient data are presented.

Calculation of the static in-flight telescope-detector response by deconvolution applied to point-spread function for the geostationary earth radiation budget experiment.

PubMed

Matthews, Grant

2004-12-01

The Geostationary Earth Radiation Budget (GERB) experiment is a broadband satellite radiometer instrument program intended to resolve remaining uncertainties surrounding the effect of cloud radiative feedback on future climate change. By use of a custom-designed diffraction-aberration telescope model, the GERB detector spatial response is recovered by deconvolution applied to the ground calibration point-spread function (PSF) measurements. An ensemble of randomly generated white-noise test scenes, combined with the measured telescope transfer function results in the effect of noise on the deconvolution being significantly reduced. With the recovered detector response as a base, the same model is applied in construction of the predicted in-flight field-of-view response of each GERB pixel to both short- and long-wave Earth radiance. The results of this study can now be used to simulate and investigate the instantaneous sampling errors incurred by GERB. Also, the developed deconvolution method may be highly applicable in enhancing images or PSF data for any telescope system for which a wave-front error measurement is available.

Point spread functions and deconvolution of ultrasonic images.

PubMed

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.

Nimbus 7 earth radiation budget wide field of view climate data set improvement. I - The earth albedo from deconvolution of shortwave measurements

NASA Technical Reports Server (NTRS)

Hucek, Richard R.; Ardanuy, Philip E.; Kyle, H. Lee

1987-01-01

A deconvolution method for extracting the top of the atmosphere (TOA) mean, daily albedo field from a set of wide-FOV (WFOV) shortwave radiometer measurements is proposed. The method is based on constructing a synthetic measurement for each satellite observation. The albedo field is represented as a truncated series of spherical harmonic functions, and these linear equations are presented. Simulation studies were conducted to determine the sensitivity of the method. It is observed that a maximum of about 289 pieces of data can be extracted from a set of Nimbus 7 WFOV satellite measurements. The albedos derived using the deconvolution method are compared with albedos derived using the WFOV archival method; the developed albedo field achieved a 20 percent reduction in the global rms regional reflected flux density errors. The deconvolution method is applied to estimate the mean, daily average TOA albedo field for January 1983. A strong and extensive albedo maximum (0.42), which corresponds to the El Nino/Southern Oscillation event of 1982-1983, is detected over the south central Pacific Ocean.

Hypocortisolemic clamp unmasks jointly feedforward- and feedback-dependent control of overnight ACTH secretion

PubMed Central

Iranmanesh, Ali; Veldhuis, Johannes D

2009-01-01

Background ACTH secretion is under hypothalamic stimulatory (feedforward) and adrenal inhibitory (feedback) control. Hypothesis Assessment of overnight ACTH secretion during a hypocortisolemic clamp will permit the estimation of changing feedforward and feedback. Subjects Seven healthy men. Interventions An oral dose of placebo (PLAC), metyrapone (METY, 3 g), or ketoconazole (KTCZ, 1.2 g) was given at midnight (MN) to block glucocorticoid synthesis. Plasma ACTH was sampled every 10 min (MN to 0800 h). Analysis Variable-waveform deconvolution analysis of ACTH secretion and approximate entropy (ApEn) analysis of pattern regularity. Results Compared with PLAC, administration of METY and KTCZ reduced morning cortisol concentrations by ≥77 and 54% respectively (P<0.001). Hypocortisolemia elevated pulsatile ACTH secretion by 8.2- (METY) and 5.3-fold (KTCZ; both P<0.001). Basal ACTH secretion rose by 3.4-fold under METY-induced cortisol depletion (P = 0.020). ACTH secretory-burst shape and half-life were stable. ApEn of ACTH release declined overnight (P = 0.021) and with the drug (P = 0.001), denoting enhanced feedforward coordination. Conclusion The combined data predict overnight amplification and coordination of hypothalamic feedforward drive onto ACTH release. Therefore, disruption of either mechanism might contribute to clinical pathophysiology, such as late-day elevations of cortisol output in fasting, alcoholism, depression, or aging. PMID:18713842

Cortisol production rate is similarly elevated in obese women with or without the polycystic ovary syndrome.

PubMed

Roelfsema, Ferdinand; Kok, Petra; Pereira, Alberto M; Pijl, Hanno

2010-07-01

The pituitary-adrenal axis in obesity and polycystic ovary syndrome (PCOS) is marked by increased urinary excretion of cortisol and its metabolites. It is not as yet clear whether the increased cortisol production in PCOS is related to obesity per se. We investigated 15 obese PCOS women with a body mass index of 30-54 kg/m(2) and 15 healthy obese controls (body mass index 31-60 kg/m(2)) with a regular menstrual cycle. Patients and control women underwent 24-h blood sampling at 20-min intervals. Cortisol concentrations were measured with a sensitive assay. Data were analyzed with a new deconvolution program, approximate entropy, and cosinor regression. Basal, pulsatile, and total cortisol production expressed per liter distribution volume, per square meter body surface, and as absolute amount per 24 h was similar in PCOS patients and matched healthy control women. In addition, the regularity of cortisol secretion and the diurnal properties were identical. Compared with 10 lean control women, mean cortisol production per liter distribution volume was similar in the three groups, but the total 24-h cortisol production was increased in obese control women and PCOS women. This study demonstrates equally increased cortisol production in PCOS women and obese healthy control women.

Investigation of the dynamic stereochemistry of dimesityl-2,4,6-trimethoxyphenylmethane by complete lineshape analysis and 2D EXSY NMR spectroscopy.

PubMed

Denkova, Pavletta; Vassilev, Nikolay; Van Lokeren, Luk; Willem, Rudolph

2008-04-01

The static and dynamic stereochemistry of dimesityl-2,4,6-trimethoxyphenylmethane in solution was investigated by lineshape analysis of 1D NMR spectra and cross-peak amplitude processing in 2D EXSY spectra, recorded at variable temperatures. Previous studies on this propeller-shaped chiral compound show that the stereomer threshold interconversion is associated with helicity reversal and occurs through [1,2]- and [1,3]-two ring flips of one mesityl and the 2,4,6-trimethoxyphenyl rings. In the present study, the experimental rate constants of the [1,2]- and [1,3]-two ring flips, which are identical, were determined at various temperatures by combining quantitative 2D EXSY spectra processing and complete lineshape analysis (CLSA) of 1D NMR spectra. The latter were subjected to reference deconvolution and linear prediction in order to eliminate the lineshape distortions due to magnetic field inhomogeneity. The activation parameters of these ring flips were determined by an Eyring equation analysis of the temperature dependence of the rate constant. The experimentally determined activation enthalpy and entropy for the two-ring flips, and those obtained from theoretical ab initio calculations at different levels of theory and basis sets, were found to be in good agreement. Copyright (c) 2008 John Wiley & Sons, Ltd.

Hypocortisolemic clamp unmasks jointly feedforward- and feedback-dependent control of overnight ACTH secretion.

PubMed

Iranmanesh, Ali; Veldhuis, Johannes D

2008-11-01

ACTH secretion is under hypothalamic stimulatory (feedforward) and adrenal inhibitory (feedback) control. Assessment of overnight ACTH secretion during a hypocortisolemic clamp will permit the estimation of changing feedforward and feedback. Seven healthy men. An oral dose of placebo (PLAC), metyrapone (METY, 3 g), or ketoconazole (KTCZ, 1.2 g) was given at midnight (MN) to block glucocorticoid synthesis. Plasma ACTH was sampled every 10 min (MN to 0800 h). Variable-waveform deconvolution analysis of ACTH secretion and approximate entropy (ApEn) analysis of pattern regularity. Compared with PLAC, administration of METY and KTCZ reduced morning cortisol concentrations by >or=77 and 54% respectively (P<0.001). Hypocortisolemia elevated pulsatile ACTH secretion by 8.2- (METY) and 5.3-fold (KTCZ; both P<0.001). Basal ACTH secretion rose by 3.4-fold under METY-induced cortisol depletion (P=0.020). ACTH secretory-burst shape and half-life were stable. ApEn of ACTH release declined overnight (P=0.021) and with the drug (P=0.001), denoting enhanced feedforward coordination. The combined data predict overnight amplification and coordination of hypothalamic feedforward drive onto ACTH release. Therefore, disruption of either mechanism might contribute to clinical pathophysiology, such as late-day elevations of cortisol output in fasting, alcoholism, depression, or aging.

Deconvolution of astronomical images using SOR with adaptive relaxation.

PubMed

Vorontsov, S V; Strakhov, V N; Jefferies, S M; Borelli, K J

2011-07-04

We address the potential performance of the successive overrelaxation technique (SOR) in image deconvolution, focusing our attention on the restoration of astronomical images distorted by atmospheric turbulence. SOR is the classical Gauss-Seidel iteration, supplemented with relaxation. As indicated by earlier work, the convergence properties of SOR, and its ultimate performance in the deconvolution of blurred and noisy images, can be made competitive to other iterative techniques, including conjugate gradients, by a proper choice of the relaxation parameter. The question of how to choose the relaxation parameter, however, remained open, and in the practical work one had to rely on experimentation. In this paper, using constructive (rather than exact) arguments, we suggest a simple strategy for choosing the relaxation parameter and for updating its value in consecutive iterations to optimize the performance of the SOR algorithm (and its positivity-constrained version, +SOR) at finite iteration counts. We suggest an extension of the algorithm to the notoriously difficult problem of "blind" deconvolution, where both the true object and the point-spread function have to be recovered from the blurred image. We report the results of numerical inversions with artificial and real data, where the algorithm is compared with techniques based on conjugate gradients. In all of our experiments +SOR provides the highest quality results. In addition +SOR is found to be able to detect moderately small changes in the true object between separate data frames: an important quality for multi-frame blind deconvolution where stationarity of the object is a necesessity.

Gaussian and linear deconvolution of LC-MS/MS chromatograms of the eight aminobutyric acid isomers

PubMed Central

Vemula, Harika; Kitase, Yukiko; Ayon, Navid J.; Bonewald, Lynda; Gutheil, William G.

2016-01-01

Isomeric molecules present a challenge for analytical resolution and quantification, even with MS-based detection. The eight-aminobutyric acid (ABA) isomers are of interest for their various biological activities, particularly γ-aminobutyric acid (GABA) and the d- and l-isomers of β-aminoisobutyric acid (β-AIBA; BAIBA). This study aimed to investigate LC-MS/MS-based resolution of these ABA isomers as their Marfey's (Mar) reagent derivatives. HPLC was able to separate three Mar-ABA isomers l-β-ABA (l-BABA), and l- and d-α-ABA (AABA) completely, with three isomers (GABA, and d/l-BAIBA) in one chromatographic cluster, and two isomers (α-AIBA (AAIBA) and d-BABA) in a second cluster. Partially separated cluster components were deconvoluted using Gaussian peak fitting except for GABA and d-BAIBA. MS/MS detection of Marfey's derivatized ABA isomers provided six MS/MS fragments, with substantially different intensity profiles between structural isomers. This allowed linear deconvolution of ABA isomer peaks. Combining HPLC separation with linear and Gaussian deconvolution allowed resolution of all eight ABA isomers. Application to human serum found a substantial level of l-AABA (13 μM), an intermediate level of l-BAIBA (0.8 μM), and low but detectable levels (<0.2 μM) of GABA, l-BABA, AAIBA, d-BAIBA, and d-AABA. This approach should be useful for LC-MS/MS deconvolution of other challenging groups of isomeric molecules. PMID:27771391

Deconvolution of ferredoxin, plastocyanin, and P700 transmittance changes in intact leaves with a new type of kinetic LED array spectrophotometer.

PubMed

Klughammer, Christof; Schreiber, Ulrich

2016-05-01

A newly developed compact measuring system for assessment of transmittance changes in the near-infrared spectral region is described; it allows deconvolution of redox changes due to ferredoxin (Fd), P700, and plastocyanin (PC) in intact leaves. In addition, it can also simultaneously measure chlorophyll fluorescence. The major opto-electronic components as well as the principles of data acquisition and signal deconvolution are outlined. Four original pulse-modulated dual-wavelength difference signals are measured (785-840 nm, 810-870 nm, 870-970 nm, and 795-970 nm). Deconvolution is based on specific spectral information presented graphically in the form of 'Differential Model Plots' (DMP) of Fd, P700, and PC that are derived empirically from selective changes of these three components under appropriately chosen physiological conditions. Whereas information on maximal changes of Fd is obtained upon illumination after dark-acclimation, maximal changes of P700 and PC can be readily induced by saturating light pulses in the presence of far-red light. Using the information of DMP and maximal changes, the new measuring system enables on-line deconvolution of Fd, P700, and PC. The performance of the new device is demonstrated by some examples of practical applications, including fast measurements of flash relaxation kinetics and of the Fd, P700, and PC changes paralleling the polyphasic fluorescence rise upon application of a 300-ms pulse of saturating light.

SU-E-I-08: Investigation of Deconvolution Methods for Blocker-Based CBCT Scatter Estimation

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

Zhao, C; Jin, M; Ouyang, L

2015-06-15

Purpose: To investigate whether deconvolution methods can improve the scatter estimation under different blurring and noise conditions for blocker-based scatter correction methods for cone-beam X-ray computed tomography (CBCT). Methods: An “ideal” projection image with scatter was first simulated for blocker-based CBCT data acquisition by assuming no blurring effect and no noise. The ideal image was then convolved with long-tail point spread functions (PSF) with different widths to mimic the blurring effect from the finite focal spot and detector response. Different levels of noise were also added. Three deconvolution Methods: 1) inverse filtering; 2) Wiener; and 3) Richardson-Lucy, were used tomore » recover the scatter signal in the blocked region. The root mean square error (RMSE) of estimated scatter serves as a quantitative measure for the performance of different methods under different blurring and noise conditions. Results: Due to the blurring effect, the scatter signal in the blocked region is contaminated by the primary signal in the unblocked region. The direct use of the signal in the blocked region to estimate scatter (“direct method”) leads to large RMSE values, which increase with the increased width of PSF and increased noise. The inverse filtering is very sensitive to noise and practically useless. The Wiener and Richardson-Lucy deconvolution methods significantly improve scatter estimation compared to the direct method. For a typical medium PSF and medium noise condition, both methods (∼20 RMSE) can achieve 4-fold improvement over the direct method (∼80 RMSE). The Wiener method deals better with large noise and Richardson-Lucy works better on wide PSF. Conclusion: We investigated several deconvolution methods to recover the scatter signal in the blocked region for blocker-based scatter correction for CBCT. Our simulation results demonstrate that Wiener and Richardson-Lucy deconvolution can significantly improve the scatter estimation compared to the direct method.« less

Gold - A novel deconvolution algorithm with optimization for waveform LiDAR processing

NASA Astrophysics Data System (ADS)

Zhou, Tan; Popescu, Sorin C.; Krause, Keith; Sheridan, Ryan D.; Putman, Eric

2017-07-01

Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: (1) direct decomposition, (2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms - the Richardson-Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from the corresponding reference data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference (<1.22 m for DTMs, <0.77 m for CHMs) and root mean square error (RMSE) (<1.26 m for DTMs, <1.93 m for CHMs). More specifically, the Gold algorithm is superior to others with smaller root mean square error (RMSE) (<1.01 m), while the direct decomposition approach works better in terms of the percentage of spatial difference within 0.5 and 1 m. The parameter uncertainty analysis demonstrates that the Gold algorithm outperforms other approaches in dense vegetation areas, with the smallest RMSE, and the RL algorithm performs better in sparse vegetation areas in terms of RMSE. Additionally, the high level of uncertainty occurs more on areas with high slope and high vegetation. This study provides an alternative and innovative approach for waveform processing that will benefit high fidelity processing of waveform LiDAR data to characterize vegetation structures.

Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL).

PubMed

Koestler, Devin C; Jones, Meaghan J; Usset, Joseph; Christensen, Brock C; Butler, Rondi A; Kobor, Michael S; Wiencke, John K; Kelsey, Karl T

2016-03-08

Confounding due to cellular heterogeneity represents one of the foremost challenges currently facing Epigenome-Wide Association Studies (EWAS). Statistical methods leveraging the tissue-specificity of DNA methylation for deconvoluting the cellular mixture of heterogenous biospecimens offer a promising solution, however the performance of such methods depends entirely on the library of methylation markers being used for deconvolution. Here, we introduce a novel algorithm for Identifying Optimal Libraries (IDOL) that dynamically scans a candidate set of cell-specific methylation markers to find libraries that optimize the accuracy of cell fraction estimates obtained from cell mixture deconvolution. Application of IDOL to training set consisting of samples with both whole-blood DNA methylation data (Illumina HumanMethylation450 BeadArray (HM450)) and flow cytometry measurements of cell composition revealed an optimized library comprised of 300 CpG sites. When compared existing libraries, the library identified by IDOL demonstrated significantly better overall discrimination of the entire immune cell landscape (p = 0.038), and resulted in improved discrimination of 14 out of the 15 pairs of leukocyte subtypes. Estimates of cell composition across the samples in the training set using the IDOL library were highly correlated with their respective flow cytometry measurements, with all cell-specific R (2)>0.99 and root mean square errors (RMSEs) ranging from [0.97 % to 1.33 %] across leukocyte subtypes. Independent validation of the optimized IDOL library using two additional HM450 data sets showed similarly strong prediction performance, with all cell-specific R (2)>0.90 and R M S E<4.00 %. In simulation studies, adjustments for cell composition using the IDOL library resulted in uniformly lower false positive rates compared to competing libraries, while also demonstrating an improved capacity to explain epigenome-wide variation in DNA methylation within two large publicly available HM450 data sets. Despite consisting of half as many CpGs compared to existing libraries for whole blood mixture deconvolution, the optimized IDOL library identified herein resulted in outstanding prediction performance across all considered data sets and demonstrated potential to improve the operating characteristics of EWAS involving adjustments for cell distribution. In addition to providing the EWAS community with an optimized library for whole blood mixture deconvolution, our work establishes a systematic and generalizable framework for the assembly of libraries that improve the accuracy of cell mixture deconvolution.

SU-C-9A-03: Simultaneous Deconvolution and Segmentation for PET Tumor Delineation Using a Variational Method

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

Li, L; Tan, S; Lu, W

2014-06-01

Purpose: To implement a new method that integrates deconvolution with segmentation under the variational framework for PET tumor delineation. Methods: Deconvolution and segmentation are both challenging problems in image processing. The partial volume effect (PVE) makes tumor boundaries in PET image blurred which affects the accuracy of tumor segmentation. Deconvolution aims to obtain a PVE-free image, which can help to improve the segmentation accuracy. Conversely, a correct localization of the object boundaries is helpful to estimate the blur kernel, and thus assist in the deconvolution. In this study, we proposed to solve the two problems simultaneously using a variational methodmore » so that they can benefit each other. The energy functional consists of a fidelity term and a regularization term, and the blur kernel was limited to be the isotropic Gaussian kernel. We minimized the energy functional by solving the associated Euler-Lagrange equations and taking the derivative with respect to the parameters of the kernel function. An alternate minimization method was used to iterate between segmentation, deconvolution and blur-kernel recovery. The performance of the proposed method was tested on clinic PET images of patients with non-Hodgkin's lymphoma, and compared with seven other segmentation methods using the dice similarity index (DSI) and volume error (VE). Results: Among all segmentation methods, the proposed one (DSI=0.81, VE=0.05) has the highest accuracy, followed by the active contours without edges (DSI=0.81, VE=0.25), while other methods including the Graph Cut and the Mumford-Shah (MS) method have lower accuracy. A visual inspection shows that the proposed method localizes the real tumor contour very well. Conclusion: The result showed that deconvolution and segmentation can contribute to each other. The proposed variational method solve the two problems simultaneously, and leads to a high performance for tumor segmentation in PET. This work was supported in part by National Natural Science Foundation of China (NNSFC), under Grant Nos. 60971112 and 61375018, and Fundamental Research Funds for the Central Universities, under Grant No. 2012QN086. Wei Lu was supported in part by the National Institutes of Health (NIH) Grant No. R01 CA172638.« less

Parabolic replicator dynamics and the principle of minimum Tsallis information gain

PubMed Central

2013-01-01

Background Non-linear, parabolic (sub-exponential) and hyperbolic (super-exponential) models of prebiological evolution of molecular replicators have been proposed and extensively studied. The parabolic models appear to be the most realistic approximations of real-life replicator systems due primarily to product inhibition. Unlike the more traditional exponential models, the distribution of individual frequencies in an evolving parabolic population is not described by the Maximum Entropy (MaxEnt) Principle in its traditional form, whereby the distribution with the maximum Shannon entropy is chosen among all the distributions that are possible under the given constraints. We sought to identify a more general form of the MaxEnt principle that would be applicable to parabolic growth. Results We consider a model of a population that reproduces according to the parabolic growth law and show that the frequencies of individuals in the population minimize the Tsallis relative entropy (non-additive information gain) at each time moment. Next, we consider a model of a parabolically growing population that maintains a constant total size and provide an “implicit” solution for this system. We show that in this case, the frequencies of the individuals in the population also minimize the Tsallis information gain at each moment of the ‘internal time” of the population. Conclusions The results of this analysis show that the general MaxEnt principle is the underlying law for the evolution of a broad class of replicator systems including not only exponential but also parabolic and hyperbolic systems. The choice of the appropriate entropy (information) function depends on the growth dynamics of a particular class of systems. The Tsallis entropy is non-additive for independent subsystems, i.e. the information on the subsystems is insufficient to describe the system as a whole. In the context of prebiotic evolution, this “non-reductionist” nature of parabolic replicator systems might reflect the importance of group selection and competition between ensembles of cooperating replicators. Reviewers This article was reviewed by Viswanadham Sridhara (nominated by Claus Wilke), Puushottam Dixit (nominated by Sergei Maslov), and Nick Grishin. For the complete reviews, see the Reviewers’ Reports section. PMID:23937956

Spectrophotometric Determination of the Dissociation Constant of an Acid-Base Indicator Using a Mathematical Deconvolution Technique

ERIC Educational Resources Information Center

Alter, Krystyn P.; Molloy, John L.; Niemeyer, Emily D.

2005-01-01

A laboratory experiment reinforces the concept of acid-base equilibria while introducing a common application of spectrophotometry and can easily be completed within a standard four-hour laboratory period. It provides students with an opportunity to use advanced data analysis techniques like data smoothing and spectral deconvolution to…

Deconvolution of Energy Spectra in the ATIC Experiment

NASA Technical Reports Server (NTRS)

Batkov, K. E.; Panov, A. D.; Adams, J. H.; Ahn, H. S.; Bashindzhagyan, G. L.; Chang, J.; Christl, M.; Fazley, A. R.; Ganel, O.; Gunasigha, R. M.;

Sequential deconvolution from wave-front sensing using bivariate simplex splines

NASA Astrophysics Data System (ADS)

Guo, Shiping; Zhang, Rongzhi; Li, Jisheng; Zou, Jianhua; Xu, Rong; Liu, Changhai

2015-05-01

Deconvolution from wave-front sensing (DWFS) is an imaging compensation technique for turbulence degraded images based on simultaneous recording of short exposure images and wave-front sensor data. This paper employs the multivariate splines method for the sequential DWFS: a bivariate simplex splines based average slopes measurement model is built firstly for Shack-Hartmann wave-front sensor; next, a well-conditioned least squares estimator for the spline coefficients is constructed using multiple Shack-Hartmann measurements; then, the distorted wave-front is uniquely determined by the estimated spline coefficients; the object image is finally obtained by non-blind deconvolution processing. Simulated experiments in different turbulence strength show that our method performs superior image restoration results and noise rejection capability especially when extracting the multidirectional phase derivatives.

SOURCE PULSE ENHANCEMENT BY DECONVOLUTION OF AN EMPIRICAL GREEN'S FUNCTION.

USGS Publications Warehouse

Mueller, Charles S.

1985-01-01

Observations of the earthquake source-time function are enhanced if path, recording-site, and instrument complexities can be removed from seismograms. Assuming that a small earthquake has a simple source, its seismogram can be treated as an empirical Green's function and deconvolved from the seismogram of a larger and/or more complex earthquake by spectral division. When the deconvolution is well posed, the quotient spectrum represents the apparent source-time function of the larger event. This study shows that with high-quality locally recorded earthquake data it is feasible to Fourier transform the quotient and obtain a useful result in the time domain. In practice, the deconvolution can be stabilized by one of several simple techniques. Application of the method is given. Refs.

Deconvolution of time series in the laboratory

NASA Astrophysics Data System (ADS)

John, Thomas; Pietschmann, Dirk; Becker, Volker; Wagner, Christian

2016-10-01

In this study, we present two practical applications of the deconvolution of time series in Fourier space. First, we reconstruct a filtered input signal of sound cards that has been heavily distorted by a built-in high-pass filter using a software approach. Using deconvolution, we can partially bypass the filter and extend the dynamic frequency range by two orders of magnitude. Second, we construct required input signals for a mechanical shaker in order to obtain arbitrary acceleration waveforms, referred to as feedforward control. For both situations, experimental and theoretical approaches are discussed to determine the system-dependent frequency response. Moreover, for the shaker, we propose a simple feedback loop as an extension to the feedforward control in order to handle nonlinearities of the system.

A Novel Method to Increase LinLog CMOS Sensors’ Performance in High Dynamic Range Scenarios

PubMed Central

Martínez-Sánchez, Antonio; Fernández, Carlos; Navarro, Pedro J.; Iborra, Andrés

2011-01-01

Images from high dynamic range (HDR) scenes must be obtained with minimum loss of information. For this purpose it is necessary to take full advantage of the quantification levels provided by the CCD/CMOS image sensor. LinLog CMOS sensors satisfy the above demand by offering an adjustable response curve that combines linear and logarithmic responses. This paper presents a novel method to quickly adjust the parameters that control the response curve of a LinLog CMOS image sensor. We propose to use an Adaptive Proportional-Integral-Derivative controller to adjust the exposure time of the sensor, together with control algorithms based on the saturation level and the entropy of the images. With this method the sensor’s maximum dynamic range (120 dB) can be used to acquire good quality images from HDR scenes with fast, automatic adaptation to scene conditions. Adaptation to a new scene is rapid, with a sensor response adjustment of less than eight frames when working in real time video mode. At least 67% of the scene entropy can be retained with this method. PMID:22164083

A novel method to increase LinLog CMOS sensors' performance in high dynamic range scenarios.

PubMed

Martínez-Sánchez, Antonio; Fernández, Carlos; Navarro, Pedro J; Iborra, Andrés

2011-01-01

Images from high dynamic range (HDR) scenes must be obtained with minimum loss of information. For this purpose it is necessary to take full advantage of the quantification levels provided by the CCD/CMOS image sensor. LinLog CMOS sensors satisfy the above demand by offering an adjustable response curve that combines linear and logarithmic responses. This paper presents a novel method to quickly adjust the parameters that control the response curve of a LinLog CMOS image sensor. We propose to use an Adaptive Proportional-Integral-Derivative controller to adjust the exposure time of the sensor, together with control algorithms based on the saturation level and the entropy of the images. With this method the sensor's maximum dynamic range (120 dB) can be used to acquire good quality images from HDR scenes with fast, automatic adaptation to scene conditions. Adaptation to a new scene is rapid, with a sensor response adjustment of less than eight frames when working in real time video mode. At least 67% of the scene entropy can be retained with this method.

Nature of phase transitions in crystalline and amorphous GeTe-Sb2Te3 phase change materials.

PubMed

Kalkan, B; Sen, S; Clark, S M

2011-09-28

The thermodynamic nature of phase stabilities and transformations are investigated in crystalline and amorphous Ge(1)Sb(2)Te(4) (GST124) phase change materials as a function of pressure and temperature using high-resolution synchrotron x-ray diffraction in a diamond anvil cell. The phase transformation sequences upon compression, for cubic and hexagonal GST124 phases are found to be: cubic → amorphous → orthorhombic → bcc and hexagonal → orthorhombic → bcc. The Clapeyron slopes for melting of the hexagonal and bcc phases are negative and positive, respectively, resulting in a pressure dependent minimum in the liquidus. When taken together, the phase equilibria relations are consistent with the presence of polyamorphism in this system with the as-deposited amorphous GST phase being the low entropy low-density amorphous phase and the laser melt-quenched and high-pressure amorphized GST being the high entropy high-density amorphous phase. The metastable phase boundary between these two polyamorphic phases is expected to have a negative Clapeyron slope. © 2011 American Institute of Physics

Unbiased All-Optical Random-Number Generator

NASA Astrophysics Data System (ADS)

Steinle, Tobias; Greiner, Johannes N.; Wrachtrup, Jörg; Giessen, Harald; Gerhardt, Ilja

2017-10-01

The generation of random bits is of enormous importance in modern information science. Cryptographic security is based on random numbers which require a physical process for their generation. This is commonly performed by hardware random-number generators. These often exhibit a number of problems, namely experimental bias, memory in the system, and other technical subtleties, which reduce the reliability in the entropy estimation. Further, the generated outcome has to be postprocessed to "iron out" such spurious effects. Here, we present a purely optical randomness generator, based on the bistable output of an optical parametric oscillator. Detector noise plays no role and postprocessing is reduced to a minimum. Upon entering the bistable regime, initially the resulting output phase depends on vacuum fluctuations. Later, the phase is rigidly locked and can be well determined versus a pulse train, which is derived from the pump laser. This delivers an ambiguity-free output, which is reliably detected and associated with a binary outcome. The resulting random bit stream resembles a perfect coin toss and passes all relevant randomness measures. The random nature of the generated binary outcome is furthermore confirmed by an analysis of resulting conditional entropies.

Simulations of dissociation constants in low pressure supercritical water

NASA Astrophysics Data System (ADS)

Halstead, S. J.; An, P.; Zhang, S.

2014-09-01

This article reports molecular dynamics simulations of the dissociation of hydrochloric acid and sodium hydroxide in water from ambient to supercritical temperatures at a fixed pressure of 250 atm. Corrosion of reaction vessels is known to be a serious problem of supercritical water, and acid/base dissociation can be a significant contributing factor to this. The SPC/e model was used in conjunction with solute models determined from density functional calculations and OPLSAA Lennard-Jones parameters. Radial distribution functions were calculated, and these show a significant increase in solute-solvent ordering upon forming the product ions at all temperatures. For both dissociations, rapidly decreasing entropy of reaction was found to be the controlling thermodynamic factor, and this is thought to arise due to the ions produced from dissociation maintaining a relatively high density and ordered solvation shell compared to the reactants. The change in entropy of reaction reaches a minimum at the critical temperature. The values of pKa and pKb were calculated and both increased with temperature, in qualitative agreement with other work, until a maximum value at 748 K, after which there was a slight decrease.

Offline modeling for product quality prediction of mineral processing using modeling error PDF shaping and entropy minimization.

PubMed

Ding, Jinliang; Chai, Tianyou; Wang, Hong

2011-03-01

This paper presents a novel offline modeling for product quality prediction of mineral processing which consists of a number of unit processes in series. The prediction of the product quality of the whole mineral process (i.e., the mixed concentrate grade) plays an important role and the establishment of its predictive model is a key issue for the plantwide optimization. For this purpose, a hybrid modeling approach of the mixed concentrate grade prediction is proposed, which consists of a linear model and a nonlinear model. The least-squares support vector machine is adopted to establish the nonlinear model. The inputs of the predictive model are the performance indices of each unit process, while the output is the mixed concentrate grade. In this paper, the model parameter selection is transformed into the shape control of the probability density function (PDF) of the modeling error. In this context, both the PDF-control-based and minimum-entropy-based model parameter selection approaches are proposed. Indeed, this is the first time that the PDF shape control idea is used to deal with system modeling, where the key idea is to turn model parameters so that either the modeling error PDF is controlled to follow a target PDF or the modeling error entropy is minimized. The experimental results using the real plant data and the comparison of the two approaches are discussed. The results show the effectiveness of the proposed approaches.

Efficient volumetric estimation from plenoptic data

NASA Astrophysics Data System (ADS)

Anglin, Paul; Reeves, Stanley J.; Thurow, Brian S.

2013-03-01

The commercial release of the Lytro camera, and greater availability of plenoptic imaging systems in general, have given the image processing community cost-effective tools for light-field imaging. While this data is most commonly used to generate planar images at arbitrary focal depths, reconstruction of volumetric fields is also possible. Similarly, deconvolution is a technique that is conventionally used in planar image reconstruction, or deblurring, algorithms. However, when leveraged with the ability of a light-field camera to quickly reproduce multiple focal planes within an imaged volume, deconvolution offers a computationally efficient method of volumetric reconstruction. Related research has shown than light-field imaging systems in conjunction with tomographic reconstruction techniques are also capable of estimating the imaged volume and have been successfully applied to particle image velocimetry (PIV). However, while tomographic volumetric estimation through algorithms such as multiplicative algebraic reconstruction techniques (MART) have proven to be highly accurate, they are computationally intensive. In this paper, the reconstruction problem is shown to be solvable by deconvolution. Deconvolution offers significant improvement in computational efficiency through the use of fast Fourier transforms (FFTs) when compared to other tomographic methods. This work describes a deconvolution algorithm designed to reconstruct a 3-D particle field from simulated plenoptic data. A 3-D extension of existing 2-D FFT-based refocusing techniques is presented to further improve efficiency when computing object focal stacks and system point spread functions (PSF). Reconstruction artifacts are identified; their underlying source and methods of mitigation are explored where possible, and reconstructions of simulated particle fields are provided.

Fast Fourier-based deconvolution for three-dimensional acoustic source identification with solid spherical arrays

NASA Astrophysics Data System (ADS)

Yang, Yang; Chu, Zhigang; Shen, Linbang; Ping, Guoli; Xu, Zhongming

2018-07-01

Being capable of demystifying the acoustic source identification result fast, Fourier-based deconvolution has been studied and applied widely for the delay and sum (DAS) beamforming with two-dimensional (2D) planar arrays. It is, however so far, still blank in the context of spherical harmonics beamforming (SHB) with three-dimensional (3D) solid spherical arrays. This paper is motivated to settle this problem. Firstly, for the purpose of determining the effective identification region, the premise of deconvolution, a shift-invariant point spread function (PSF), is analyzed with simulations. To make the premise be satisfied approximately, the opening angle in elevation dimension of the surface of interest should be small, while no restriction is imposed to the azimuth dimension. Then, two kinds of deconvolution theories are built for SHB using the zero and the periodic boundary conditions respectively. Both simulations and experiments demonstrate that the periodic boundary condition is superior to the zero one, and fits the 3D acoustic source identification with solid spherical arrays better. Finally, four periodic boundary condition based deconvolution methods are formulated, and their performance is disclosed both with simulations and experimentally. All the four methods offer enhanced spatial resolution and reduced sidelobe contaminations over SHB. The recovered source strength approximates to the exact one multiplied with a coefficient that is the square of the focus distance divided by the distance from the source to the array center, while the recovered pressure contribution is scarcely affected by the focus distance, always approximating to the exact one.

Detection of increased vasa vasorum in artery walls: improving CT number accuracy using image deconvolution

NASA Astrophysics Data System (ADS)

Rajendran, Kishore; Leng, Shuai; Jorgensen, Steven M.; Abdurakhimova, Dilbar; Ritman, Erik L.; McCollough, Cynthia H.

2017-03-01

Changes in arterial wall perfusion are an indicator of early atherosclerosis. This is characterized by an increased spatial density of vasa vasorum (VV), the micro-vessels that supply oxygen and nutrients to the arterial wall. Detection of increased VV during contrast-enhanced computed tomography (CT) imaging is limited due to contamination from blooming effect from the contrast-enhanced lumen. We report the application of an image deconvolution technique using a measured system point-spread function, on CT data obtained from a photon-counting CT system to reduce blooming and to improve the CT number accuracy of arterial wall, which enhances detection of increased VV. A phantom study was performed to assess the accuracy of the deconvolution technique. A porcine model was created with enhanced VV in one carotid artery; the other carotid artery served as a control. CT images at an energy range of 25-120 keV were reconstructed. CT numbers were measured for multiple locations in the carotid walls and for multiple time points, pre and post contrast injection. The mean CT number in the carotid wall was compared between the left (increased VV) and right (control) carotid arteries. Prior to deconvolution, results showed similar mean CT numbers in the left and right carotid wall due to the contamination from blooming effect, limiting the detection of increased VV in the left carotid artery. After deconvolution, the mean CT number difference between the left and right carotid arteries was substantially increased at all the time points, enabling detection of the increased VV in the artery wall.

VizieR Online Data Catalog: Spatial deconvolution code (Quintero Noda+, 2015)

NASA Astrophysics Data System (ADS)

Quintero Noda, C.; Asensio Ramos, A.; Orozco Suarez, D.; Ruiz Cobo, B.

2015-05-01

This deconvolution method follows the scheme presented in Ruiz Cobo & Asensio Ramos (2013A&A...549L...4R) The Stokes parameters are projected onto a few spectral eigenvectors and the ensuing maps of coefficients are deconvolved using a standard Lucy-Richardson algorithm. This introduces a stabilization because the PCA filtering reduces the amount of noise. (1 data file).

A method to measure the presampling MTF in digital radiography using Wiener deconvolution

NASA Astrophysics Data System (ADS)

Zhou, Zhongxing; Zhu, Qingzhen; Gao, Feng; Zhao, Huijuan; Zhang, Lixin; Li, Guohui

2013-03-01

We developed a novel method for determining the presampling modulation transfer function (MTF) of digital radiography systems from slanted edge images based on Wiener deconvolution. The degraded supersampled edge spread function (ESF) was obtained from simulated slanted edge images with known MTF in the presence of poisson noise, and its corresponding ideal ESF without degration was constructed according to its central edge position. To meet the requirements of the absolute integrable condition of Fourier transformation, the origianl ESFs were mirrored to construct the symmetric pattern of ESFs. Then based on Wiener deconvolution technique, the supersampled line spread function (LSF) could be acquired from the symmetric pattern of degraded supersampled ESFs in the presence of ideal symmetric ESFs and system noise. The MTF is then the normalized magnitude of the Fourier transform of the LSF. The determined MTF showed a strong agreement with the theoritical true MTF when appropriated Wiener parameter was chosen. The effects of Wiener parameter value and the width of square-like wave peak in symmetric ESFs were illustrated and discussed. In conclusion, an accurate and simple method to measure the presampling MTF was established using Wiener deconvolution technique according to slanted edge images.

Deconvolution of interferometric data using interior point iterative algorithms

NASA Astrophysics Data System (ADS)

Theys, C.; Lantéri, H.; Aime, C.

2016-09-01

We address the problem of deconvolution of astronomical images that could be obtained with future large interferometers in space. The presentation is made in two complementary parts. The first part gives an introduction to the image deconvolution with linear and nonlinear algorithms. The emphasis is made on nonlinear iterative algorithms that verify the constraints of non-negativity and constant flux. The Richardson-Lucy algorithm appears there as a special case for photon counting conditions. More generally, the algorithm published recently by Lanteri et al. (2015) is based on scale invariant divergences without assumption on the statistic model of the data. The two proposed algorithms are interior-point algorithms, the latter being more efficient in terms of speed of calculation. These algorithms are applied to the deconvolution of simulated images corresponding to an interferometric system of 16 diluted telescopes in space. Two non-redundant configurations, one disposed around a circle and the other on an hexagonal lattice, are compared for their effectiveness on a simple astronomical object. The comparison is made in the direct and Fourier spaces. Raw "dirty" images have many artifacts due to replicas of the original object. Linear methods cannot remove these replicas while iterative methods clearly show their efficacy in these examples.

Single-Ion Deconvolution of Mass Peak Overlaps for Atom Probe Microscopy.

PubMed

London, Andrew J; Haley, Daniel; Moody, Michael P

2017-04-01

Due to the intrinsic evaporation properties of the material studied, insufficient mass-resolving power and lack of knowledge of the kinetic energy of incident ions, peaks in the atom probe mass-to-charge spectrum can overlap and result in incorrect composition measurements. Contributions to these peak overlaps can be deconvoluted globally, by simply examining adjacent peaks combined with knowledge of natural isotopic abundances. However, this strategy does not account for the fact that the relative contributions to this convoluted signal can often vary significantly in different regions of the analysis volume; e.g., across interfaces and within clusters. Some progress has been made with spatially localized deconvolution in cases where the discrete microstructural regions can be easily identified within the reconstruction, but this means no further point cloud analyses are possible. Hence, we present an ion-by-ion methodology where the identity of each ion, normally obscured by peak overlap, is resolved by examining the isotopic abundance of their immediate surroundings. The resulting peak-deconvoluted data are a point cloud and can be analyzed with any existing tools. We present two detailed case studies and discussion of the limitations of this new technique.

Image deblurring by motion estimation for remote sensing

NASA Astrophysics Data System (ADS)

Chen, Yueting; Wu, Jiagu; Xu, Zhihai; Li, Qi; Feng, Huajun

2010-08-01

The imagery resolution of imaging systems for remote sensing is often limited by image degradation resulting from unwanted motion disturbances of the platform during image exposures. Since the form of the platform vibration can be arbitrary, the lack of priori knowledge about the motion function (the PSF) suggests blind restoration approaches. A deblurring method which combines motion estimation and image deconvolution both for area-array and TDI remote sensing has been proposed in this paper. The image motion estimation is accomplished by an auxiliary high-speed detector and a sub-pixel correlation algorithm. The PSF is then reconstructed from estimated image motion vectors. Eventually, the clear image can be recovered by the Richardson-Lucy (RL) iterative deconvolution algorithm from the blurred image of the prime camera with the constructed PSF. The image deconvolution for the area-array detector is direct. While for the TDICCD detector, an integral distortion compensation step and a row-by-row deconvolution scheme are applied. Theoretical analyses and experimental results show that, the performance of the proposed concept is convincing. Blurred and distorted images can be properly recovered not only for visual observation, but also with significant objective evaluation increment.

Comparison of active-set method deconvolution and matched-filtering for derivation of an ultrasound transit time spectrum.

PubMed

Wille, M-L; Zapf, M; Ruiter, N V; Gemmeke, H; Langton, C M

2015-06-21

The quality of ultrasound computed tomography imaging is primarily determined by the accuracy of ultrasound transit time measurement. A major problem in analysis is the overlap of signals making it difficult to detect the correct transit time. The current standard is to apply a matched-filtering approach to the input and output signals. This study compares the matched-filtering technique with active set deconvolution to derive a transit time spectrum from a coded excitation chirp signal and the measured output signal. The ultrasound wave travels in a direct and a reflected path to the receiver, resulting in an overlap in the recorded output signal. The matched-filtering and deconvolution techniques were applied to determine the transit times associated with the two signal paths. Both techniques were able to detect the two different transit times; while matched-filtering has a better accuracy (0.13 μs versus 0.18 μs standard deviations), deconvolution has a 3.5 times improved side-lobe to main-lobe ratio. A higher side-lobe suppression is important to further improve image fidelity. These results suggest that a future combination of both techniques would provide improved signal detection and hence improved image fidelity.

Chemometric Data Analysis for Deconvolution of Overlapped Ion Mobility Profiles

NASA Astrophysics Data System (ADS)

Zekavat, Behrooz; Solouki, Touradj

2012-11-01

We present the details of a data analysis approach for deconvolution of the ion mobility (IM) overlapped or unresolved species. This approach takes advantage of the ion fragmentation variations as a function of the IM arrival time. The data analysis involves the use of an in-house developed data preprocessing platform for the conversion of the original post-IM/collision-induced dissociation mass spectrometry (post-IM/CID MS) data to a Matlab compatible format for chemometric analysis. We show that principle component analysis (PCA) can be used to examine the post-IM/CID MS profiles for the presence of mobility-overlapped species. Subsequently, using an interactive self-modeling mixture analysis technique, we show how to calculate the total IM spectrum (TIMS) and CID mass spectrum for each component of the IM overlapped mixtures. Moreover, we show that PCA and IM deconvolution techniques provide complementary results to evaluate the validity of the calculated TIMS profiles. We use two binary mixtures with overlapping IM profiles, including (1) a mixture of two non-isobaric peptides (neurotensin (RRPYIL) and a hexapeptide (WHWLQL)), and (2) an isobaric sugar isomer mixture of raffinose and maltotriose, to demonstrate the applicability of the IM deconvolution.

Evaluation of uncertainty for regularized deconvolution: A case study in hydrophone measurements.

PubMed

Eichstädt, S; Wilkens, V

2017-06-01

An estimation of the measurand in dynamic metrology usually requires a deconvolution based on a dynamic calibration of the measuring system. Since deconvolution is, mathematically speaking, an ill-posed inverse problem, some kind of regularization is required to render the problem stable and obtain usable results. Many approaches to regularized deconvolution exist in the literature, but the corresponding evaluation of measurement uncertainties is, in general, an unsolved issue. In particular, the uncertainty contribution of the regularization itself is a topic of great importance, because it has a significant impact on the estimation result. Here, a versatile approach is proposed to express prior knowledge about the measurand based on a flexible, low-dimensional modeling of an upper bound on the magnitude spectrum of the measurand. This upper bound allows the derivation of an uncertainty associated with the regularization method in line with the guidelines in metrology. As a case study for the proposed method, hydrophone measurements in medical ultrasound with an acoustic working frequency of up to 7.5 MHz are considered, but the approach is applicable for all kinds of estimation methods in dynamic metrology, where regularization is required and which can be expressed as a multiplication in the frequency domain.

Designing a stable feedback control system for blind image deconvolution.

PubMed

Cheng, Shichao; Liu, Risheng; Fan, Xin; Luo, Zhongxuan

2018-05-01

Blind image deconvolution is one of the main low-level vision problems with wide applications. Many previous works manually design regularization to simultaneously estimate the latent sharp image and the blur kernel under maximum a posterior framework. However, it has been demonstrated that such joint estimation strategies may lead to the undesired trivial solution. In this paper, we present a novel perspective, using a stable feedback control system, to simulate the latent sharp image propagation. The controller of our system consists of regularization and guidance, which decide the sparsity and sharp features of latent image, respectively. Furthermore, the formational model of blind image is introduced into the feedback process to avoid the image restoration deviating from the stable point. The stability analysis of the system indicates the latent image propagation in blind deconvolution task can be efficiently estimated and controlled by cues and priors. Thus the kernel estimation used for image restoration becomes more precision. Experimental results show that our system is effective on image propagation, and can perform favorably against the state-of-the-art blind image deconvolution methods on different benchmark image sets and special blurred images. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multi-limit unsymmetrical MLIBD image restoration algorithm

NASA Astrophysics Data System (ADS)

Yang, Yang; Cheng, Yiping; Chen, Zai-wang; Bo, Chen

2012-11-01

A novel multi-limit unsymmetrical iterative blind deconvolution(MLIBD) algorithm was presented to enhance the performance of adaptive optics image restoration.The algorithm enhances the reliability of iterative blind deconvolution by introducing the bandwidth limit into the frequency domain of point spread(PSF),and adopts the PSF dynamic support region estimation to improve the convergence speed.The unsymmetrical factor is automatically computed to advance its adaptivity.Image deconvolution comparing experiments between Richardson-Lucy IBD and MLIBD were done,and the result indicates that the iteration number is reduced by 22.4% and the peak signal-to-noise ratio is improved by 10.18dB with MLIBD method. The performance of MLIBD algorithm is outstanding in the images restoration the FK5-857 adaptive optics and the double-star adaptive optics.

A feasibility and optimization study to determine cooling time and burnup of advanced test reactor fuels using a nondestructive technique

NASA Astrophysics Data System (ADS)

Navarro, Jorge

The goal of this study presented is to determine the best available nondestructive technique necessary to collect validation data as well as to determine burnup and cooling time of the fuel elements on-site at the Advanced Test Reactor (ATR) canal. This study makes a recommendation of the viability of implementing a permanent fuel scanning system at the ATR canal and leads to the full design of a permanent fuel scan system. The study consisted at first in determining if it was possible and which equipment was necessary to collect useful spectra from ATR fuel elements at the canal adjacent to the reactor. Once it was establish that useful spectra can be obtained at the ATR canal, the next step was to determine which detector and which configuration was better suited to predict burnup and cooling time of fuel elements nondestructively. Three different detectors of High Purity Germanium (HPGe), Lanthanum Bromide (LaBr3), and High Pressure Xenon (HPXe) in two system configurations of above and below the water pool were used during the study. The data collected and analyzed were used to create burnup and cooling time calibration prediction curves for ATR fuel. The next stage of the study was to determine which of the three detectors tested was better suited for the permanent system. From spectra taken and the calibration curves obtained, it was determined that although the HPGe detector yielded better results, a detector that could better withstand the harsh environment of the ATR canal was needed. The in-situ nature of the measurements required a rugged fuel scanning system, low in maintenance and easy to control system. Based on the ATR canal feasibility measurements and calibration results, it was determined that the LaBr3 detector was the best alternative for canal in-situ measurements; however, in order to enhance the quality of the spectra collected using this scintillator, a deconvolution method was developed. Following the development of the deconvolution method for ATR applications, the technique was tested using one-isotope, multi-isotope, and fuel simulated sources. Burnup calibrations were perfomed using convoluted and deconvoluted data. The calibrations results showed burnup prediction by this method improves using deconvolution. The final stage of the deconvolution method development was to perform an irradiation experiment in order to create a surrogate fuel source to test the deconvolution method using experimental data. A conceptual design of the fuel scan system is path forward using the rugged LaBr 3 detector in an above the water configuration and deconvolution algorithms.

Why Does the Human Body Maintain a Constant 37-Degree Temperature?: Thermodynamic Switch Controls Chemical Equilibrium in Biological Systems

NASA Astrophysics Data System (ADS)

Chun, Paul W.

2005-01-01

Applying the Planck-Benzinger methodology to biological systems, we have established that the negative Gibbs free energy minimum at a well-defined stable temperature, langTSrang, where the bound unavailable energy TΔS° = 0, has its origin in the sequence-specific hydrophobic interactions. Each such system we have examined confirms the existence of a thermodynamic molecular switch wherein a change of sign in [ΔCp°]reaction leads to a true negative minimum in the Gibbs free energy change of reaction, and hence a maximum in the related equilibrium constant, Keq. At this temperature, langTSrang, where ΔH°(TS)(-) = ΔG°(TS)(-)min, the maximum work can be accomplished in transpiration, digestion, reproduction or locomotion. In the human body, this temperature is 37°C. The langTSrang values may vary from one living organism to another, but the fact that the value of TΔS°(T) = 0 will not. There is a lower cutoff point, langThrang, where enthalpy is unfavorable but entropy is favorable, i.e. ΔH°(Th)(+) = TΔS°(Th)(+), and an upper limit, langTmrang, above which enthalpy is favorable but entropy is unfavorable, i.e. ΔH°(Tm)(-) = TΔS°(Tm)(-). Only between these two temperature limits, where ΔG°(T) = 0, is the net chemical driving force favorable for such biological processes as protein folding, protein-protein, protein-nucleic acid or protein-membrane interactions, and protein self-assembly. All interacting biological systems examined using the Planck-Benzinger methodology have shown such a thermodynamic switch at the molecular level, suggesting that its existence may be universal.

Measurement Uncertainty Relations for Discrete Observables: Relative Entropy Formulation

NASA Astrophysics Data System (ADS)

Barchielli, Alberto; Gregoratti, Matteo; Toigo, Alessandro

2018-02-01

We introduce a new information-theoretic formulation of quantum measurement uncertainty relations, based on the notion of relative entropy between measurement probabilities. In the case of a finite-dimensional system and for any approximate joint measurement of two target discrete observables, we define the entropic divergence as the maximal total loss of information occurring in the approximation at hand. For fixed target observables, we study the joint measurements minimizing the entropic divergence, and we prove the general properties of its minimum value. Such a minimum is our uncertainty lower bound: the total information lost by replacing the target observables with their optimal approximations, evaluated at the worst possible state. The bound turns out to be also an entropic incompatibility degree, that is, a good information-theoretic measure of incompatibility: indeed, it vanishes if and only if the target observables are compatible, it is state-independent, and it enjoys all the invariance properties which are desirable for such a measure. In this context, we point out the difference between general approximate joint measurements and sequential approximate joint measurements; to do this, we introduce a separate index for the tradeoff between the error of the first measurement and the disturbance of the second one. By exploiting the symmetry properties of the target observables, exact values, lower bounds and optimal approximations are evaluated in two different concrete examples: (1) a couple of spin-1/2 components (not necessarily orthogonal); (2) two Fourier conjugate mutually unbiased bases in prime power dimension. Finally, the entropic incompatibility degree straightforwardly generalizes to the case of many observables, still maintaining all its relevant properties; we explicitly compute it for three orthogonal spin-1/2 components.

A MAP blind image deconvolution algorithm with bandwidth over-constrained

NASA Astrophysics Data System (ADS)

Ren, Zhilei; Liu, Jin; Liang, Yonghui; He, Yulong

2018-03-01

We demonstrate a maximum a posteriori (MAP) blind image deconvolution algorithm with bandwidth over-constrained and total variation (TV) regularization to recover a clear image from the AO corrected images. The point spread functions (PSFs) are estimated by bandwidth limited less than the cutoff frequency of the optical system. Our algorithm performs well in avoiding noise magnification. The performance is demonstrated on simulated data.

Successive Over-Relaxation Technique for High-Performance Blind Image Deconvolution

DTIC Science & Technology

2015-06-08

deconvolution, space surveillance, Gauss - Seidel iteration 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18, NUMBER OF PAGES 5...sensible approximate solutions to the ill-posed nonlinear inverse problem. These solutions are addresses as fixed points of the iteration which consists in...alternating approximations (AA) for the object and for the PSF performed with a prescribed number of inner iterative descents from trivial (zero

Deconvolution for three-dimensional acoustic source identification based on spherical harmonics beamforming

NASA Astrophysics Data System (ADS)

Chu, Zhigang; Yang, Yang; He, Yansong

2015-05-01

Spherical Harmonics Beamforming (SHB) with solid spherical arrays has become a particularly attractive tool for doing acoustic sources identification in cabin environments. However, it presents some intrinsic limitations, specifically poor spatial resolution and severe sidelobe contaminations. This paper focuses on overcoming these limitations effectively by deconvolution. First and foremost, a new formulation is proposed, which expresses SHB's output as a convolution of the true source strength distribution and the point spread function (PSF) defined as SHB's response to a unit-strength point source. Additionally, the typical deconvolution methods initially suggested for planar arrays, deconvolution approach for the mapping of acoustic sources (DAMAS), nonnegative least-squares (NNLS), Richardson-Lucy (RL) and CLEAN, are adapted to SHB successfully, which are capable of giving rise to highly resolved and deblurred maps. Finally, the merits of the deconvolution methods are validated and the relationships of source strength and pressure contribution reconstructed by the deconvolution methods vs. focus distance are explored both with computer simulations and experimentally. Several interesting results have emerged from this study: (1) compared with SHB, DAMAS, NNLS, RL and CLEAN all can not only improve the spatial resolution dramatically but also reduce or even eliminate the sidelobes effectively, allowing clear and unambiguous identification of single source or incoherent sources. (2) The availability of RL for coherent sources is highest, then DAMAS and NNLS, and that of CLEAN is lowest due to its failure in suppressing sidelobes. (3) Whether or not the real distance from the source to the array center equals the assumed one that is referred to as focus distance, the previous two results hold. (4) The true source strength can be recovered by dividing the reconstructed one by a coefficient that is the square of the focus distance divided by the real distance from the source to the array center. (5) The reconstructed pressure contribution is almost not affected by the focus distance, always approximating to the true one. This study will be of great significance to the accurate localization and quantification of acoustic sources in cabin environments.

Quantitative phase imaging and complex field reconstruction by pupil modulation differential phase contrast

PubMed Central

Lu, Hangwen; Chung, Jaebum; Ou, Xiaoze; Yang, Changhuei

2016-01-01

Differential phase contrast (DPC) is a non-interferometric quantitative phase imaging method achieved by using an asymmetric imaging procedure. We report a pupil modulation differential phase contrast (PMDPC) imaging method by filtering a sample’s Fourier domain with half-circle pupils. A phase gradient image is captured with each half-circle pupil, and a quantitative high resolution phase image is obtained after a deconvolution process with a minimum of two phase gradient images. Here, we introduce PMDPC quantitative phase image reconstruction algorithm and realize it experimentally in a 4f system with an SLM placed at the pupil plane. In our current experimental setup with the numerical aperture of 0.36, we obtain a quantitative phase image with a resolution of 1.73μm after computationally removing system aberrations and refocusing. We also extend the depth of field digitally by 20 times to ±50μm with a resolution of 1.76μm. PMID:27828473

Biophysical characterization of soluble Pseudomonas syringae ice nucleation protein InaZ fragments.

PubMed

Han, Yu Jin; Song, HyoJin; Lee, Chang Woo; Ly, Nguyễn Hoàng; Joo, Sang-Woo; Lee, Jun Hyuck; Kim, Soon-Jong; Park, SangYoun

2017-01-01

Ice nucleation protein (INP) with its functional domain consisting of multiple 48-residue repeat units effectively induces super-cooled water into ice. Circular dichroism and infrared deconvolution analyses on a soluble 240-residue fragment of Pseudomonas syringae InaZ (InaZ240) containing five 48-residue repeat units indicated that it is mostly composed of β-sheet and random coil. Analytical ultracentrifugation suggested that InaZ240 behaves as a monomer of an elongated ellipsoid. However, InaZ240 showed only minimum ice binding compared to anti-freeze proteins. Other P. syringae InaZ proteins with more 48-residue repeat units were made, in which the largest soluble fragment obtainable was an InaZ with twelve 48-residue repeat units. Size-exclusion chromatography analyses further suggested that the overall shape of the expressed InaZ fragments is pH-dependent, which becomes compact as the numbers of 48-residue repeat unit increase. Copyright © 2016 Elsevier B.V. All rights reserved.

Cosmic Microwave Background Mapmaking with a Messenger Field

NASA Astrophysics Data System (ADS)

Huffenberger, Kevin M.; Næss, Sigurd K.

2018-01-01

We apply a messenger field method to solve the linear minimum-variance mapmaking equation in the context of Cosmic Microwave Background (CMB) observations. In simulations, the method produces sky maps that converge significantly faster than those from a conjugate gradient descent algorithm with a diagonal preconditioner, even though the computational cost per iteration is similar. The messenger method recovers large scales in the map better than conjugate gradient descent, and yields a lower overall χ2. In the single, pencil beam approximation, each iteration of the messenger mapmaking procedure produces an unbiased map, and the iterations become more optimal as they proceed. A variant of the method can handle differential data or perform deconvolution mapmaking. The messenger method requires no preconditioner, but a high-quality solution needs a cooling parameter to control the convergence. We study the convergence properties of this new method and discuss how the algorithm is feasible for the large data sets of current and future CMB experiments.

A Quantitative Microscopy Technique for Determining the Number of Specific Proteins in Cellular Compartments

PubMed Central

Mutch, Sarah A.; Gadd, Jennifer C.; Fujimoto, Bryant S.; Kensel-Hammes, Patricia; Schiro, Perry G.; Bajjalieh, Sandra M.; Chiu, Daniel T.

2013-01-01

This protocol describes a method to determine both the average number and variance of proteins in the few to tens of copies in isolated cellular compartments, such as organelles and protein complexes. Other currently available protein quantification techniques either provide an average number but lack information on the variance or are not suitable for reliably counting proteins present in the few to tens of copies. This protocol entails labeling the cellular compartment with fluorescent primary-secondary antibody complexes, TIRF (total internal reflection fluorescence) microscopy imaging of the cellular compartment, digital image analysis, and deconvolution of the fluorescence intensity data. A minimum of 2.5 days is required to complete the labeling, imaging, and analysis of a set of samples. As an illustrative example, we describe in detail the procedure used to determine the copy number of proteins in synaptic vesicles. The same procedure can be applied to other organelles or signaling complexes. PMID:22094731

Determination of ion mobility collision cross sections for unresolved isomeric mixtures using tandem mass spectrometry and chemometric deconvolution.

PubMed

Harper, Brett; Neumann, Elizabeth K; Stow, Sarah M; May, Jody C; McLean, John A; Solouki, Touradj

2016-10-05

Ion mobility (IM) is an important analytical technique for determining ion collision cross section (CCS) values in the gas-phase and gaining insight into molecular structures and conformations. However, limited instrument resolving powers for IM may restrict adequate characterization of conformationally similar ions, such as structural isomers, and reduce the accuracy of IM-based CCS calculations. Recently, we introduced an automated technique for extracting "pure" IM and collision-induced dissociation (CID) mass spectra of IM overlapping species using chemometric deconvolution of post-IM/CID mass spectrometry (MS) data [J. Am. Soc. Mass Spectrom., 2014, 25, 1810-1819]. Here we extend those capabilities to demonstrate how extracted IM profiles can be used to calculate accurate CCS values of peptide isomer ions which are not fully resolved by IM. We show that CCS values obtained from deconvoluted IM spectra match with CCS values measured from the individually analyzed corresponding peptides on uniform field IM instrumentation. We introduce an approach that utilizes experimentally determined IM arrival time (AT) "shift factors" to compensate for ion acceleration variations during post-IM/CID and significantly improve the accuracy of the calculated CCS values. Also, we discuss details of this IM deconvolution approach and compare empirical CCS values from traveling wave (TW)IM-MS and drift tube (DT)IM-MS with theoretically calculated CCS values using the projected superposition approximation (PSA). For example, experimentally measured deconvoluted TWIM-MS mean CCS values for doubly-protonated RYGGFM, RMFGYG, MFRYGG, and FRMYGG peptide isomers were 288.8 Å(2), 295.1 Å(2), 296.8 Å(2), and 300.1 Å(2); all four of these CCS values were within 1.5% of independently measured DTIM-MS values. Copyright © 2016 Elsevier B.V. All rights reserved.

Geometric characterization of separability and entanglement in pure Gaussian states by single-mode unitary operations

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

Adesso, Gerardo; CNR-INFM Coherentia, Naples; CNISM, Unita di Salerno, Salerno

2007-10-15

We present a geometric approach to the characterization of separability and entanglement in pure Gaussian states of an arbitrary number of modes. The analysis is performed adapting to continuous variables a formalism based on single subsystem unitary transformations that has been recently introduced to characterize separability and entanglement in pure states of qubits and qutrits [S. M. Giampaolo and F. Illuminati, Phys. Rev. A 76, 042301 (2007)]. In analogy with the finite-dimensional case, we demonstrate that the 1xM bipartite entanglement of a multimode pure Gaussian state can be quantified by the minimum squared Euclidean distance between the state itself andmore » the set of states obtained by transforming it via suitable local symplectic (unitary) operations. This minimum distance, corresponding to a, uniquely determined, extremal local operation, defines an entanglement monotone equivalent to the entropy of entanglement, and amenable to direct experimental measurement with linear optical schemes.« less

Automated mango fruit assessment using fuzzy logic approach

NASA Astrophysics Data System (ADS)

Hasan, Suzanawati Abu; Kin, Teoh Yeong; Sauddin@Sa'duddin, Suraiya; Aziz, Azlan Abdul; Othman, Mahmod; Mansor, Ab Razak; Parnabas, Vincent

2014-06-01

In term of value and volume of production, mango is the third most important fruit product next to pineapple and banana. Accurate size assessment of mango fruits during harvesting is vital to ensure that they are classified to the grade accordingly. However, the current practice in mango industry is grading the mango fruit manually using human graders. This method is inconsistent, inefficient and labor intensive. In this project, a new method of automated mango size and grade assessment is developed using RGB fiber optic sensor and fuzzy logic approach. The calculation of maximum, minimum and mean values based on RGB fiber optic sensor and the decision making development using minimum entropy formulation to analyse the data and make the classification for the mango fruit. This proposed method is capable to differentiate three different grades of mango fruit automatically with 77.78% of overall accuracy compared to human graders sorting. This method was found to be helpful for the application in the current agricultural industry.

Restoring defect structures in 3C-SiC/Si (001) from spherical aberration-corrected high-resolution transmission electron microscope images by means of deconvolution processing.

PubMed

Wen, C; Wan, W; Li, F H; Tang, D

2015-04-01

The [110] cross-sectional samples of 3C-SiC/Si (001) were observed with a spherical aberration-corrected 300 kV high-resolution transmission electron microscope. Two images taken not close to the Scherzer focus condition and not representing the projected structures intuitively were utilized for performing the deconvolution. The principle and procedure of image deconvolution and atomic sort recognition are summarized. The defect structure restoration together with the recognition of Si and C atoms from the experimental images has been illustrated. The structure maps of an intrinsic stacking fault in the area of SiC, and of Lomer and 60° shuffle dislocations at the interface have been obtained at atomic level. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sheet-scanned dual-axis confocal microscopy using Richardson-Lucy deconvolution.

PubMed

Wang, D; Meza, D; Wang, Y; Gao, L; Liu, J T C

2014-09-15

We have previously developed a line-scanned dual-axis confocal (LS-DAC) microscope with subcellular resolution suitable for high-frame-rate diagnostic imaging at shallow depths. Due to the loss of confocality along one dimension, the contrast (signal-to-background ratio) of a LS-DAC microscope is deteriorated compared to a point-scanned DAC microscope. However, by using a sCMOS camera for detection, a short oblique light-sheet is imaged at each scanned position. Therefore, by scanning the light sheet in only one dimension, a thin 3D volume is imaged. Both sequential two-dimensional deconvolution and three-dimensional deconvolution are performed on the thin image volume to improve the resolution and contrast of one en face confocal image section at the center of the volume, a technique we call sheet-scanned dual-axis confocal (SS-DAC) microscopy.

Computerized glow curve deconvolution of thermoluminescent emission from polyminerals of Jamaica Mexican flower

NASA Astrophysics Data System (ADS)

Favalli, A.; Furetta, C.; Zaragoza, E. Cruz; Reyes, A.

The aim of this work is to study the main thermoluminescence (TL) characteristics of the inorganic polyminerals extracted from dehydrated Jamaica flower or roselle (Hibiscus sabdariffa L.) belonging to Malvaceae family of Mexican origin. TL emission properties of the polymineral fraction in powder were studied using the initial rise (IR) method. The complex structure and kinetic parameters of the glow curves have been analysed accurately using the computerized glow curve deconvolution (CGCD) assuming an exponential distribution of trapping levels. The extension of the IR method to the case of a continuous and exponential distribution of traps is reported, such as the derivation of the TL glow curve deconvolution functions for continuous trap distribution. CGCD is performed both in the case of frequency factor, s, temperature independent, and in the case with the s function of temperature.

Punch stretching process monitoring using acoustic emission signal analysis. II - Application of frequency domain deconvolution

NASA Technical Reports Server (NTRS)

Liang, Steven Y.; Dornfeld, David A.; Nickerson, Jackson A.

1987-01-01

The coloring effect on the acoustic emission signal due to the frequency response of the data acquisition/processing instrumentation may bias the interpretation of AE signal characteristics. In this paper, a frequency domain deconvolution technique, which involves the identification of the instrumentation transfer functions and multiplication of the AE signal spectrum by the inverse of these system functions, has been carried out. In this way, the change in AE signal characteristics can be better interpreted as the result of the change in only the states of the process. Punch stretching process was used as an example to demonstrate the application of the technique. Results showed that, through the deconvolution, the frequency characteristics of AE signals generated during the stretching became more distinctive and can be more effectively used as tools for process monitoring.

Improving the Ability of Image Sensors to Detect Faint Stars and Moving Objects Using Image Deconvolution Techniques

PubMed Central

Fors, Octavi; Núñez, Jorge; Otazu, Xavier; Prades, Albert; Cardinal, Robert D.

2010-01-01

In this paper we show how the techniques of image deconvolution can increase the ability of image sensors as, for example, CCD imagers, to detect faint stars or faint orbital objects (small satellites and space debris). In the case of faint stars, we show that this benefit is equivalent to double the quantum efficiency of the used image sensor or to increase the effective telescope aperture by more than 30% without decreasing the astrometric precision or introducing artificial bias. In the case of orbital objects, the deconvolution technique can double the signal-to-noise ratio of the image, which helps to discover and control dangerous objects as space debris or lost satellites. The benefits obtained using CCD detectors can be extrapolated to any kind of image sensors. PMID:22294896

Improving the ability of image sensors to detect faint stars and moving objects using image deconvolution techniques.

PubMed

Fors, Octavi; Núñez, Jorge; Otazu, Xavier; Prades, Albert; Cardinal, Robert D

2010-01-01

In this paper we show how the techniques of image deconvolution can increase the ability of image sensors as, for example, CCD imagers, to detect faint stars or faint orbital objects (small satellites and space debris). In the case of faint stars, we show that this benefit is equivalent to double the quantum efficiency of the used image sensor or to increase the effective telescope aperture by more than 30% without decreasing the astrometric precision or introducing artificial bias. In the case of orbital objects, the deconvolution technique can double the signal-to-noise ratio of the image, which helps to discover and control dangerous objects as space debris or lost satellites. The benefits obtained using CCD detectors can be extrapolated to any kind of image sensors.

Regression-assisted deconvolution.

PubMed

McIntyre, Julie; Stefanski, Leonard A

2011-06-30

We present a semi-parametric deconvolution estimator for the density function of a random variable biX that is measured with error, a common challenge in many epidemiological studies. Traditional deconvolution estimators rely only on assumptions about the distribution of X and the error in its measurement, and ignore information available in auxiliary variables. Our method assumes the availability of a covariate vector statistically related to X by a mean-variance function regression model, where regression errors are normally distributed and independent of the measurement errors. Simulations suggest that the estimator achieves a much lower integrated squared error than the observed-data kernel density estimator when models are correctly specified and the assumption of normal regression errors is met. We illustrate the method using anthropometric measurements of newborns to estimate the density function of newborn length. Copyright © 2011 John Wiley & Sons, Ltd.

XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling

NASA Astrophysics Data System (ADS)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-08-01

XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.

Two-Dimensional Signal Processing and Storage and Theory and Applications of Electromagnetic Measurements.

DTIC Science & Technology

1983-06-01

system, provides a convenient, low- noise , fully parallel method of improving contrast and enhancing structural detail in an image prior to input to a...directed towards problems in deconvolution, reconstruction from projections, bandlimited extrapolation, and shift varying deblurring of images...deconvolution algorithm has been studied with promising 5 results [I] for simulated motion blurs. Future work will focus on noise effects and the extension

Chemometric Deconvolution of Continuous Electrokinetic Injection Micellar Electrokinetic Chromatography Data for the Quantitation of Trinitrotoluene in Mixtures of Other Nitroaromatic Compounds

DTIC Science & Technology

2014-02-24

Suite 600 Washington, DC 20036 NRL/MR/ 6110 --14-9521 Approved for public release; distribution is unlimited. 1Science & Engineering Apprenticeship...Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/ 6110 --14-9521 Chemometric Deconvolution of Continuous Electrokinetic Injection Micellar... Engineering Apprenticeship Program American Society for Engineering Education Washington, DC Kevin Johnson Navy Technology Center for Safety and

Enhanced Seismic Imaging of Turbidite Deposits in Chicontepec Basin, Mexico

NASA Astrophysics Data System (ADS)

Chavez-Perez, S.; Vargas-Meleza, L.

2007-05-01

We test, as postprocessing tools, a combination of migration deconvolution and geometric attributes to attack the complex problems of reflector resolution and detection in migrated seismic volumes. Migration deconvolution has been empirically shown to be an effective approach for enhancing the illumination of migrated images, which are blurred versions of the subsurface reflectivity distribution, by decreasing imaging artifacts, improving spatial resolution, and alleviating acquisition footprint problems. We utilize migration deconvolution as a means to improve the quality and resolution of 3D prestack time migrated results from Chicontepec basin, Mexico, a very relevant portion of the producing onshore sector of Pemex, the Mexican petroleum company. Seismic data covers the Agua Fria, Coapechaca, and Tajin fields. It exhibits acquisition footprint problems, migration artifacts and a severe lack of resolution in the target area, where turbidite deposits need to be characterized between major erosional surfaces. Vertical resolution is about 35 m and the main hydrocarbon plays are turbidite beds no more than 60 m thick. We also employ geometric attributes (e.g., coherent energy and curvature), computed after migration deconvolution, to detect and map out depositional features, and help design development wells in the area. Results of this workflow show imaging enhancement and allow us to identify meandering channels and individual sand bodies, previously undistinguishable in the original seismic migrated images.

Dependence of quantitative accuracy of CT perfusion imaging on system parameters

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Guang-Hong

2017-03-01

Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

Data Dependent Peak Model Based Spectrum Deconvolution for Analysis of High Resolution LC-MS Data

PubMed Central

2015-01-01

A data dependent peak model (DDPM) based spectrum deconvolution method was developed for analysis of high resolution LC-MS data. To construct the selected ion chromatogram (XIC), a clustering method, the density based spatial clustering of applications with noise (DBSCAN), is applied to all m/z values of an LC-MS data set to group the m/z values into each XIC. The DBSCAN constructs XICs without the need for a user defined m/z variation window. After the XIC construction, the peaks of molecular ions in each XIC are detected using both the first and the second derivative tests, followed by an optimized chromatographic peak model selection method for peak deconvolution. A total of six chromatographic peak models are considered, including Gaussian, log-normal, Poisson, gamma, exponentially modified Gaussian, and hybrid of exponential and Gaussian models. The abundant nonoverlapping peaks are chosen to find the optimal peak models that are both data- and retention-time-dependent. Analysis of 18 spiked-in LC-MS data demonstrates that the proposed DDPM spectrum deconvolution method outperforms the traditional method. On average, the DDPM approach not only detected 58 more chromatographic peaks from each of the testing LC-MS data but also improved the retention time and peak area 3% and 6%, respectively. PMID:24533635

Motion correction of PET brain images through deconvolution: I. Theoretical development and analysis in software simulations

NASA Astrophysics Data System (ADS)

Faber, T. L.; Raghunath, N.; Tudorascu, D.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. Existing correction methods that use known patient motion obtained from tracking devices either require multi-frame acquisitions, detailed knowledge of the scanner, or specialized reconstruction algorithms. A deconvolution algorithm has been developed that alleviates these drawbacks by using the reconstructed image to estimate the original non-blurred image using maximum likelihood estimation maximization (MLEM) techniques. A high-resolution digital phantom was created by shape-based interpolation of the digital Hoffman brain phantom. Three different sets of 20 movements were applied to the phantom. For each frame of the motion, sinograms with attenuation and three levels of noise were simulated and then reconstructed using filtered backprojection. The average of the 20 frames was considered the motion blurred image, which was restored with the deconvolution algorithm. After correction, contrast increased from a mean of 2.0, 1.8 and 1.4 in the motion blurred images, for the three increasing amounts of movement, to a mean of 2.5, 2.4 and 2.2. Mean error was reduced by an average of 55% with motion correction. In conclusion, deconvolution can be used for correction of motion blur when subject motion is known.

Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction

NASA Astrophysics Data System (ADS)

Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng

2017-01-01

Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.

Partitioning of nitroxides in dispersed systems investigated by ultrafiltration, EPR and NMR spectroscopy.

PubMed

Krudopp, Heimke; Sönnichsen, Frank D; Steffen-Heins, Anja

2015-08-15

The partitioning behavior of paramagnetic nitroxides in dispersed systems can be determined by deconvolution of electron paramagnetic resonance (EPR) spectra giving equivalent results with the validated methods of ultrafiltration techniques (UF) and pulsed-field gradient nuclear magnetic resonance spectroscopy (PFG-NMR). The partitioning behavior of nitroxides with increasing lipophilicity was investigated in anionic, cationic and nonionic micellar systems and 10 wt% o/w emulsions. Apart from EPR spectra deconvolution, the PFG-NMR was used in micellar solutions as a non-destructive approach, while UF based on separation of very small volume of the aqueous phase. As a function of their substituent and lipophilicity, the proportions of nitroxides that were solubilized in the micellar or emulsion interface increased with increasing nitroxide lipophilicity for all emulsifier used. Comparing the different approaches, EPR deconvolution and UF revealed comparable nitroxide proportions that were solubilized in the interfaces. Those proportions were higher than found with PFG-NMR. For PFG-NMR self-diffusion experiments the reduced nitroxides were used revealing a high dynamic of hydroxylamines and emulsifiers. Deconvolution of EPR spectra turned out to be the preferred method for measuring the partitioning behavior of paramagnetic molecules as it enables distinguishing between several populations at their individual solubilization sites. Copyright © 2015 Elsevier Inc. All rights reserved.

Extraction of near-surface properties for a lossy layered medium using the propagator matrix

USGS Publications Warehouse

Mehta, K.; Snieder, R.; Graizer, V.

2007-01-01

Near-surface properties play an important role in advancing earthquake hazard assessment. Other areas where near-surface properties are crucial include civil engineering and detection and delineation of potable groundwater. From an exploration point of view, near-surface properties are needed for wavefield separation and correcting for the local near-receiver structure. It has been shown that these properties can be estimated for a lossless homogeneous medium using the propagator matrix. To estimate the near-surface properties, we apply deconvolution to passive borehole recordings of waves excited by an earthquake. Deconvolution of these incoherent waveforms recorded by the sensors at different depths in the borehole with the recording at the surface results in waves that propagate upwards and downwards along the array. These waves, obtained by deconvolution, can be used to estimate the P- and S-wave velocities near the surface. As opposed to waves obtained by cross-correlation that represent filtered version of the sum of causal and acausal Green's function between the two receivers, the waves obtained by deconvolution represent the elements of the propagator matrix. Finally, we show analytically the extension of the propagator matrix analysis to a lossy layered medium for a special case of normal incidence. ?? 2007 The Authors Journal compilation ?? 2007 RAS.

Resolving complex fibre architecture by means of sparse spherical deconvolution in the presence of isotropic diffusion

NASA Astrophysics Data System (ADS)

Zhou, Q.; Michailovich, O.; Rathi, Y.

2014-03-01

High angular resolution diffusion imaging (HARDI) improves upon more traditional diffusion tensor imaging (DTI) in its ability to resolve the orientations of crossing and branching neural fibre tracts. The HARDI signals are measured over a spherical shell in q-space, and are usually used as an input to q-ball imaging (QBI) which allows estimation of the diffusion orientation distribution functions (ODFs) associated with a given region-of interest. Unfortunately, the partial nature of single-shell sampling imposes limits on the estimation accuracy. As a result, the recovered ODFs may not possess sufficient resolution to reveal the orientations of fibre tracts which cross each other at acute angles. A possible solution to the problem of limited resolution of QBI is provided by means of spherical deconvolution, a particular instance of which is sparse deconvolution. However, while capable of yielding high-resolution reconstructions over spacial locations corresponding to white matter, such methods tend to become unstable when applied to anatomical regions with a substantial content of isotropic diffusion. To resolve this problem, a new deconvolution approach is proposed in this paper. Apart from being uniformly stable across the whole brain, the proposed method allows one to quantify the isotropic component of cerebral diffusion, which is known to be a useful diagnostic measure by itself.

Convex blind image deconvolution with inverse filtering

NASA Astrophysics Data System (ADS)

Lv, Xiao-Guang; Li, Fang; Zeng, Tieyong

2018-03-01

Blind image deconvolution is the process of estimating both the original image and the blur kernel from the degraded image with only partial or no information about degradation and the imaging system. It is a bilinear ill-posed inverse problem corresponding to the direct problem of convolution. Regularization methods are used to handle the ill-posedness of blind deconvolution and get meaningful solutions. In this paper, we investigate a convex regularized inverse filtering method for blind deconvolution of images. We assume that the support region of the blur object is known, as has been done in a few existing works. By studying the inverse filters of signal and image restoration problems, we observe the oscillation structure of the inverse filters. Inspired by the oscillation structure of the inverse filters, we propose to use the star norm to regularize the inverse filter. Meanwhile, we use the total variation to regularize the resulting image obtained by convolving the inverse filter with the degraded image. The proposed minimization model is shown to be convex. We employ the first-order primal-dual method for the solution of the proposed minimization model. Numerical examples for blind image restoration are given to show that the proposed method outperforms some existing methods in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), visual quality and time consumption.

Model-free quantification of dynamic PET data using nonparametric deconvolution

PubMed Central

Zanderigo, Francesca; Parsey, Ramin V; Todd Ogden, R

2015-01-01

Dynamic positron emission tomography (PET) data are usually quantified using compartment models (CMs) or derived graphical approaches. Often, however, CMs either do not properly describe the tracer kinetics, or are not identifiable, leading to nonphysiologic estimates of the tracer binding. The PET data are modeled as the convolution of the metabolite-corrected input function and the tracer impulse response function (IRF) in the tissue. Using nonparametric deconvolution methods, it is possible to obtain model-free estimates of the IRF, from which functionals related to tracer volume of distribution and binding may be computed, but this approach has rarely been applied in PET. Here, we apply nonparametric deconvolution using singular value decomposition to simulated and test–retest clinical PET data with four reversible tracers well characterized by CMs ([11C]CUMI-101, [11C]DASB, [11C]PE2I, and [11C]WAY-100635), and systematically compare reproducibility, reliability, and identifiability of various IRF-derived functionals with that of traditional CMs outcomes. Results show that nonparametric deconvolution, completely free of any model assumptions, allows for estimates of tracer volume of distribution and binding that are very close to the estimates obtained with CMs and, in some cases, show better test–retest performance than CMs outcomes. PMID:25873427

Investigation of the hydrogen fluxes in the plasma edge of W7-AS during H-mode discharges

NASA Astrophysics Data System (ADS)

Langer, U.; Taglauer, E.; Fischer, R.; W7-AS Team

2001-03-01

In the stellarator W7-AS the H-mode is characterized by an edge transport barrier which is localized within a few centimeters inside the separatrix. The corresponding L-H transition shows well-known features such as the steepening of the temperature and density profiles in the region of the separatrix. With a so-called sniffer probe the temporal development of the hydrogen and deuterium fluxes has been studied in the plasma edge during different H-mode discharges with deuterium gas puffing. Prior to the transition a significant reduction of the deuterium and also the hydrogen fluxes can be observed. This fact confirms the assumption that the steepening of the density profiles starts at the outermost edge of the plasma. Moreover, sniffer probe measurements in the plasma edge could therefore identify a precursor for the L-H transition. The analysis of the hydrogen neutral gases shows a distinct change of the hydrogen isotope ratio during the transition. This observation is in agreement with the change in the particle fluxes onto the targets and can also be seen in the reduced H α signals from the limiters. It is further demonstrated that significant improvement in the time resolution of the measured data can be obtained by deconvolution of the data with the apparatus function using Bayesian probability theory and the Maximum Entropy method with adaptive kernels.

Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma.

PubMed

Schob, Stefan; Beeskow, Anne; Dieckow, Julia; Meyer, Hans-Jonas; Krause, Matthias; Frydrychowicz, Clara; Hirsch, Franz-Wolfgang; Surov, Alexey

2018-05-31

Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features. Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed. ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.

Free Volume, Energy, and Entropy at the Polymer Glass Transition: New Results and Connections with Widely Used Treatments

NASA Astrophysics Data System (ADS)

White, Ronald; Lipson, Jane

Free volume has a storied history in polymer physics. To introduce our own results, we consider how free volume has been defined in the past, e.g. in the works of Fox and Flory, Doolittle, and the equation of Williams, Landel, and Ferry. We contrast these perspectives with our own analysis using our Locally Correlated Lattice (LCL) model where we have found a striking connection between polymer free volume (analyzed using PVT data) and the polymer's corresponding glass transition temperature, Tg. The pattern, covering over 50 different polymers, is robust enough to be reasonably predictive based on melt properties alone; when a melt hits this T-dependent boundary of critical minimum free volume it becomes glassy. We will present a broad selection of results from our thermodynamic analysis, and make connections with historical treatments. We will discuss patterns that have emerged across the polymers in the energy and entropy when quantified as ''per LCL theoretical segment''. Finally we will relate the latter trend to the point of view popularized in the theory of Adam and Gibbs. The authors gratefully acknowledge support from NSF DMR-1403757.

Quantization Of Temperature

NASA Astrophysics Data System (ADS)

O'Brien, Paul

2017-01-01

Max Plank did not quantize temperature. I will show that the Plank temperature violates the Plank scale. Plank stated that the Plank scale was Natures scale and independent of human construct. Also stating that even aliens would derive the same values. He made a huge mistake, because temperature is based on the Kelvin scale, which is man-made just like the meter and kilogram. He did not discover natures scale for the quantization of temperature. His formula is flawed, and his value is incorrect. Plank's calculation is Tp = c2Mp/Kb. The general form of this equation is T = E/Kb Why is this wrong? The temperature for a fixed amount of energy is dependent upon the volume it occupies. Using the correct formula involves specifying the radius of the volume in the form of (RE). This leads to an inequality and a limit that is equivalent to the Bekenstein Bound, but using temperature instead of entropy. Rewriting this equation as a limit defines both the maximum temperature and Boltzmann's constant. This will saturate any space-time boundary with maximum temperature and information density, also the minimum radius and entropy. The general form of the equation then becomes a limit in BH thermodynamics T <= (RE)/(λKb) .

Hot-start Giant Planets Form with Radiative Interiors

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

Berardo, David; Cumming, Andrew, E-mail: david.berardo@mcgill.ca, E-mail: andrew.cumming@mcgill.ca

In the hot-start core accretion formation model for gas giants, the interior of a planet is usually assumed to be fully convective. By calculating the detailed internal evolution of a planet assuming hot-start outer boundary conditions, we show that such a planet will in fact form with a radially increasing internal entropy profile, so that its interior will be radiative instead of convective. For a hot outer boundary, there is a minimum value for the entropy of the internal adiabat S {sub min} below which the accreting envelope does not match smoothly onto the interior, but instead deposits high entropymore » material onto the growing interior. One implication of this would be to at least temporarily halt the mixing of heavy elements within the planet, which are deposited by planetesimals accreted during formation. The compositional gradient this would impose could subsequently disrupt convection during post-accretion cooling, which would alter the observed cooling curve of the planet. However, even with a homogeneous composition, for which convection develops as the planet cools, the difference in cooling timescale will change the inferred mass of directly imaged gas giants.« less

Multicellular regulation of entropy, spatial order, and information

NASA Astrophysics Data System (ADS)

Youk, Hyun

Many multicellular systems such as tissues and microbial biofilms consist of cells that secrete and sense signalling molecules. Understanding how collective behaviours of secrete-and-sense cells is an important challenge. We combined experimental and theoretical approaches to understand multicellular coordination of gene expression and spatial pattern formation among secrete-and-sense cells. We engineered secrete-and-sense yeast cells to show that cells can collectively and permanently remember a past event by reminding each other with their secreted signalling molecule. If one cell ``forgets'' then another cell can remind it. Cell-cell communication ensures a long-term (permanent) memory by overcoming common limitations of intracellular memory. We also established a new theoretical framework inspired by statistical mechanics to understand how fields of secrete-and-sense cells form spatial patterns. We introduce new metrics - cellular entropy, cellular Hamiltonian, and spatial order index - for dynamics of cellular automata that form spatial patterns. Our theory predicts how fast any spatial patterns form, how ordered they are, and establishes cellular Hamiltonian that, like energy for non-living systems, monotonically decreases towards a minimum over time. ERC Starting Grant (MultiCellSysBio), NWO VIDI, NWO NanoFront.

Image restoration using aberration taken by a Hartmann wavefront sensor on extended object, towards real-time deconvolution

NASA Astrophysics Data System (ADS)

Darudi, Ahmad; Bakhshi, Hadi; Asgari, Reza

2015-05-01

In this paper we present the results of image restoration using the data taken by a Hartmann sensor. The aberration is measure by a Hartmann sensor in which the object itself is used as reference. Then the Point Spread Function (PSF) is simulated and used for image reconstruction using the Lucy-Richardson technique. A technique is presented for quantitative evaluation the Lucy-Richardson technique for deconvolution.

Novel Image Quality Control Systems(Add-On). Innovative Computational Methods for Inverse Problems in Optical and SAR Imaging

DTIC Science & Technology

2007-02-28

Iterative Ultrasonic Signal and Image Deconvolution for Estimation of the Complex Medium Response, International Journal of Imaging Systems and...1767-1782, 2006. 31. Z. Mu, R. Plemmons, and P. Santago. Iterative Ultrasonic Signal and Image Deconvolution for Estimation of the Complex...rigorous mathematical and computational research on inverse problems in optical imaging of direct interest to the Army and also the intelligence agencies

Adaptive Optics Image Restoration Based on Frame Selection and Multi-frame Blind Deconvolution

NASA Astrophysics Data System (ADS)

Tian, Yu; Rao, Chang-hui; Wei, Kai

Restricted by the observational condition and the hardware, adaptive optics can only make a partial correction of the optical images blurred by atmospheric turbulence. A postprocessing method based on frame selection and multi-frame blind deconvolution is proposed for the restoration of high-resolution adaptive optics images. By frame selection we mean we first make a selection of the degraded (blurred) images for participation in the iterative blind deconvolution calculation, with no need of any a priori knowledge, and with only a positivity constraint. This method has been applied to the restoration of some stellar images observed by the 61-element adaptive optics system installed on the Yunnan Observatory 1.2m telescope. The experimental results indicate that this method can effectively compensate for the residual errors of the adaptive optics system on the image, and the restored image can reach the diffraction-limited quality.

Forward Looking Radar Imaging by Truncated Singular Value Decomposition and Its Application for Adverse Weather Aircraft Landing.

PubMed

Huang, Yulin; Zha, Yuebo; Wang, Yue; Yang, Jianyu

2015-06-18

The forward looking radar imaging task is a practical and challenging problem for adverse weather aircraft landing industry. Deconvolution method can realize the forward looking imaging but it often leads to the noise amplification in the radar image. In this paper, a forward looking radar imaging based on deconvolution method is presented for adverse weather aircraft landing. We first present the theoretical background of forward looking radar imaging task and its application for aircraft landing. Then, we convert the forward looking radar imaging task into a corresponding deconvolution problem, which is solved in the framework of algebraic theory using truncated singular decomposition method. The key issue regarding the selecting of the truncated parameter is addressed using generalized cross validation approach. Simulation and experimental results demonstrate that the proposed method is effective in achieving angular resolution enhancement with suppressing the noise amplification in forward looking radar imaging.

Towards real-time image deconvolution: application to confocal and STED microscopy

PubMed Central

Zanella, R.; Zanghirati, G.; Cavicchioli, R.; Zanni, L.; Boccacci, P.; Bertero, M.; Vicidomini, G.

2013-01-01

Although deconvolution can improve the quality of any type of microscope, the high computational time required has so far limited its massive spreading. Here we demonstrate the ability of the scaled-gradient-projection (SGP) method to provide accelerated versions of the most used algorithms in microscopy. To achieve further increases in efficiency, we also consider implementations on graphic processing units (GPUs). We test the proposed algorithms both on synthetic and real data of confocal and STED microscopy. Combining the SGP method with the GPU implementation we achieve a speed-up factor from about a factor 25 to 690 (with respect the conventional algorithm). The excellent results obtained on STED microscopy images demonstrate the synergy between super-resolution techniques and image-deconvolution. Further, the real-time processing allows conserving one of the most important property of STED microscopy, i.e the ability to provide fast sub-diffraction resolution recordings. PMID:23982127

Removing the echoes from terahertz pulse reflection system and sample

NASA Astrophysics Data System (ADS)

Liu, Haishun; Zhang, Zhenwei; Zhang, Cunlin

2018-01-01

Due to the echoes both from terahertz (THz) pulse reflection system and sample, the THz primary pulse will be distorted. The system echoes include two types. One preceding the main peak probably is caused by ultrafast laser pulse and the other at the back of the primary pulse is caused by the Fabry-Perot (F-P) etalon effect of detector. We attempt to remove the corresponding echoes by using two kinds of deconvolution. A Si wafer of 400μm was selected as the tested sample. Firstly, the method of double Gaussian filter (DGF) decnvolution was used to remove the systematic echoes, and then another deconvolution technique was employed to eliminate the two obvious echoes of the sample. The ultimate results indicated: although the combination of two deconvolution techniques could not entirely remove the echoes of sample and system, the echoes were largely reduced.

Determination of uronic acids in isolated hemicelluloses from kenaf using diffuse reflectance infrared fourier transform spectroscopy (DRIFTS) and the curve-fitting deconvolution method.

PubMed

Batsoulis, A N; Nacos, M K; Pappas, C S; Tarantilis, P A; Mavromoustakos, T; Polissiou, M G

2004-02-01

Hemicellulose samples were isolated from kenaf (Hibiscus cannabinus L.). Hemicellulosic fractions usually contain a variable percentage of uronic acids. The uronic acid content (expressed in polygalacturonic acid) of the isolated hemicelluloses was determined by diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and the curve-fitting deconvolution method. A linear relationship between uronic acids content and the sum of the peak areas at 1745, 1715, and 1600 cm(-1) was established with a high correlation coefficient (0.98). The deconvolution analysis using the curve-fitting method allowed the elimination of spectral interferences from other cell wall components. The above method was compared with an established spectrophotometric method and was found equivalent for accuracy and repeatability (t-test, F-test). This method is applicable in analysis of natural or synthetic mixtures and/or crude substances. The proposed method is simple, rapid, and nondestructive for the samples.

A feasibility and optimization study to determine cooling time and burnup of advanced test reactor fuels using a nondestructive technique

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

Navarro, Jorge

2013-12-01

The goal of this study presented is to determine the best available non-destructive technique necessary to collect validation data as well as to determine burn-up and cooling time of the fuel elements onsite at the Advanced Test Reactor (ATR) canal. This study makes a recommendation of the viability of implementing a permanent fuel scanning system at the ATR canal and leads3 to the full design of a permanent fuel scan system. The study consisted at first in determining if it was possible and which equipment was necessary to collect useful spectra from ATR fuel elements at the canal adjacent tomore » the reactor. Once it was establish that useful spectra can be obtained at the ATR canal the next step was to determine which detector and which configuration was better suited to predict burnup and cooling time of fuel elements non-destructively. Three different detectors of High Purity Germanium (HPGe), Lanthanum Bromide (LaBr3), and High Pressure Xenon (HPXe) in two system configurations of above and below the water pool were used during the study. The data collected and analyzed was used to create burnup and cooling time calibration prediction curves for ATR fuel. The next stage of the study was to determine which of the three detectors tested was better suited for the permanent system. From spectra taken and the calibration curves obtained, it was determined that although the HPGe detector yielded better results, a detector that could better withstand the harsh environment of the ATR canal was needed. The in-situ nature of the measurements required a rugged fuel scanning system, low in maintenance and easy to control system. Based on the ATR canal feasibility measurements and calibration results it was determined that the LaBr3 detector was the best alternative for canal in-situ measurements; however in order to enhance the quality of the spectra collected using this scintillator a deconvolution method was developed. Following the development of the deconvolution method for ATR applications the technique was tested using one-isotope, multi-isotope and fuel simulated sources. Burnup calibrations were perfomed using convoluted and deconvoluted data. The calibrations results showed burnup prediction by this method improves using deconvolution. The final stage of the deconvolution method development was to perform an irradiation experiment in order to create a surrogate fuel source to test the deconvolution method using experimental data. A conceptual design of the fuel scan system is path forward using the rugged LaBr3 detector in an above the water configuration and deconvolution algorithms.« less

Quantitative fluorescence microscopy and image deconvolution.

PubMed

Swedlow, Jason R

2013-01-01

Quantitative imaging and image deconvolution have become standard techniques for the modern cell biologist because they can form the basis of an increasing number of assays for molecular function in a cellular context. There are two major types of deconvolution approaches--deblurring and restoration algorithms. Deblurring algorithms remove blur but treat a series of optical sections as individual two-dimensional entities and therefore sometimes mishandle blurred light. Restoration algorithms determine an object that, when convolved with the point-spread function of the microscope, could produce the image data. The advantages and disadvantages of these methods are discussed in this chapter. Image deconvolution in fluorescence microscopy has usually been applied to high-resolution imaging to improve contrast and thus detect small, dim objects that might otherwise be obscured. Their proper use demands some consideration of the imaging hardware, the acquisition process, fundamental aspects of photon detection, and image processing. This can prove daunting for some cell biologists, but the power of these techniques has been proven many times in the works cited in the chapter and elsewhere. Their usage is now well defined, so they can be incorporated into the capabilities of most laboratories. A major application of fluorescence microscopy is the quantitative measurement of the localization, dynamics, and interactions of cellular factors. The introduction of green fluorescent protein and its spectral variants has led to a significant increase in the use of fluorescence microscopy as a quantitative assay system. For quantitative imaging assays, it is critical to consider the nature of the image-acquisition system and to validate its response to known standards. Any image-processing algorithms used before quantitative analysis should preserve the relative signal levels in different parts of the image. A very common image-processing algorithm, image deconvolution, is used to remove blurred signal from an image. There are two major types of deconvolution approaches, deblurring and restoration algorithms. Deblurring algorithms remove blur, but treat a series of optical sections as individual two-dimensional entities, and therefore sometimes mishandle blurred light. Restoration algorithms determine an object that, when convolved with the point-spread function of the microscope, could produce the image data. The advantages and disadvantages of these methods are discussed. Copyright © 1998 Elsevier Inc. All rights reserved.

A Robust Deconvolution Method based on Transdimensional Hierarchical Bayesian Inference

NASA Astrophysics Data System (ADS)

Kolb, J.; Lekic, V.

2012-12-01

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

A mathematical deconvolution formulation for superficial dose distribution measurement by Cerenkov light dosimetry.

PubMed

Brost, Eric Edward; Watanabe, Yoichi

2018-06-01

Cerenkov photons are created by high-energy radiation beams used for radiation therapy. In this study, we developed a Cerenkov light dosimetry technique to obtain a two-dimensional dose distribution in a superficial region of medium from the images of Cerenkov photons by using a deconvolution method. An integral equation was derived to represent the Cerenkov photon image acquired by a camera for a given incident high-energy photon beam by using convolution kernels. Subsequently, an equation relating the planar dose at a depth to a Cerenkov photon image using the well-known relationship between the incident beam fluence and the dose distribution in a medium was obtained. The final equation contained a convolution kernel called the Cerenkov dose scatter function (CDSF). The CDSF function was obtained by deconvolving the Cerenkov scatter function (CSF) with the dose scatter function (DSF). The GAMOS (Geant4-based Architecture for Medicine-Oriented Simulations) Monte Carlo particle simulation software was used to obtain the CSF and DSF. The dose distribution was calculated from the Cerenkov photon intensity data using an iterative deconvolution method with the CDSF. The theoretical formulation was experimentally evaluated by using an optical phantom irradiated by high-energy photon beams. The intensity of the deconvolved Cerenkov photon image showed linear dependence on the dose rate and the photon beam energy. The relative intensity showed a field size dependence similar to the beam output factor. Deconvolved Cerenkov images showed improvement in dose profiles compared with the raw image data. In particular, the deconvolution significantly improved the agreement in the high dose gradient region, such as in the penumbra. Deconvolution with a single iteration was found to provide the most accurate solution of the dose. Two-dimensional dose distributions of the deconvolved Cerenkov images agreed well with the reference distributions for both square fields and a multileaf collimator (MLC) defined, irregularly shaped field. The proposed technique improved the accuracy of the Cerenkov photon dosimetry in the penumbra region. The results of this study showed initial validation of the deconvolution method for beam profile measurements in a homogeneous media. The new formulation accounted for the physical processes of Cerenkov photon transport in the medium more accurately than previously published methods. © 2018 American Association of Physicists in Medicine.

Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study.

PubMed

Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

2016-11-21

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed 'MPD-AwTTV'. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study

NASA Astrophysics Data System (ADS)

Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

2016-11-01

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed ‘MPD-AwTTV’. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

A deconvolution extraction method for 2D multi-object fibre spectroscopy based on the regularized least-squares QR-factorization algorithm

NASA Astrophysics Data System (ADS)

Yu, Jian; Yin, Qian; Guo, Ping; Luo, A.-li

2014-09-01

This paper presents an efficient method for the extraction of astronomical spectra from two-dimensional (2D) multifibre spectrographs based on the regularized least-squares QR-factorization (LSQR) algorithm. We address two issues: we propose a modified Gaussian point spread function (PSF) for modelling the 2D PSF from multi-emission-line gas-discharge lamp images (arc images), and we develop an efficient deconvolution method to extract spectra in real circumstances. The proposed modified 2D Gaussian PSF model can fit various types of 2D PSFs, including different radial distortion angles and ellipticities. We adopt the regularized LSQR algorithm to solve the sparse linear equations constructed from the sparse convolution matrix, which we designate the deconvolution spectrum extraction method. Furthermore, we implement a parallelized LSQR algorithm based on graphics processing unit programming in the Compute Unified Device Architecture to accelerate the computational processing. Experimental results illustrate that the proposed extraction method can greatly reduce the computational cost and memory use of the deconvolution method and, consequently, increase its efficiency and practicability. In addition, the proposed extraction method has a stronger noise tolerance than other methods, such as the boxcar (aperture) extraction and profile extraction methods. Finally, we present an analysis of the sensitivity of the extraction results to the radius and full width at half-maximum of the 2D PSF.

Unsupervised Learning for Monaural Source Separation Using Maximization–Minimization Algorithm with Time–Frequency Deconvolution †

PubMed Central

Bouridane, Ahmed; Ling, Bingo Wing-Kuen

2018-01-01

This paper presents an unsupervised learning algorithm for sparse nonnegative matrix factor time–frequency deconvolution with optimized fractional β-divergence. The β-divergence is a group of cost functions parametrized by a single parameter β. The Itakura–Saito divergence, Kullback–Leibler divergence and Least Square distance are special cases that correspond to β=0, 1, 2, respectively. This paper presents a generalized algorithm that uses a flexible range of β that includes fractional values. It describes a maximization–minimization (MM) algorithm leading to the development of a fast convergence multiplicative update algorithm with guaranteed convergence. The proposed model operates in the time–frequency domain and decomposes an information-bearing matrix into two-dimensional deconvolution of factor matrices that represent the spectral dictionary and temporal codes. The deconvolution process has been optimized to yield sparse temporal codes through maximizing the likelihood of the observations. The paper also presents a method to estimate the fractional β value. The method is demonstrated on separating audio mixtures recorded from a single channel. The paper shows that the extraction of the spectral dictionary and temporal codes is significantly more efficient by using the proposed algorithm and subsequently leads to better source separation performance. Experimental tests and comparisons with other factorization methods have been conducted to verify its efficacy. PMID:29702629

MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra

NASA Astrophysics Data System (ADS)

Reid, Deseree J.; Diesing, Jessica M.; Miller, Matthew A.; Perry, Scott M.; Wales, Jessica A.; Montfort, William R.; Marty, Michael T.

2018-04-01

The expansion of native mass spectrometry (MS) methods for both academic and industrial applications has created a substantial need for analysis of large native MS datasets. Existing software tools are poorly suited for high-throughput deconvolution of native electrospray mass spectra from intact proteins and protein complexes. The UniDec Bayesian deconvolution algorithm is uniquely well suited for high-throughput analysis due to its speed and robustness but was previously tailored towards individual spectra. Here, we optimized UniDec for deconvolution, analysis, and visualization of large data sets. This new module, MetaUniDec, centers around a hierarchical data format 5 (HDF5) format for storing datasets that significantly improves speed, portability, and file size. It also includes code optimizations to improve speed and a new graphical user interface for visualization, interaction, and analysis of data. To demonstrate the utility of MetaUniDec, we applied the software to analyze automated collision voltage ramps with a small bacterial heme protein and large lipoprotein nanodiscs. Upon increasing collisional activation, bacterial heme-nitric oxide/oxygen binding (H-NOX) protein shows a discrete loss of bound heme, and nanodiscs show a continuous loss of lipids and charge. By using MetaUniDec to track changes in peak area or mass as a function of collision voltage, we explore the energetic profile of collisional activation in an ultra-high mass range Orbitrap mass spectrometer. [Figure not available: see fulltext.

Whole-Lesion Apparent Diffusion Coefficient-Based Entropy-Related Parameters for Characterizing Cervical Cancers: Initial Findings.

PubMed

Guan, Yue; Li, Weifeng; Jiang, Zhuoran; Chen, Ying; Liu, Song; He, Jian; Zhou, Zhengyang; Ge, Yun

2016-12-01

This study aimed to develop whole-lesion apparent diffusion coefficient (ADC)-based entropy-related parameters of cervical cancer to preliminarily assess intratumoral heterogeneity of this lesion in comparison to adjacent normal cervical tissues. A total of 51 women (mean age, 49 years) with cervical cancers confirmed by biopsy underwent 3-T pelvic diffusion-weighted magnetic resonance imaging with b values of 0 and 800 s/mm 2 prospectively. ADC-based entropy-related parameters including first-order entropy and second-order entropies were derived from the whole tumor volume as well as adjacent normal cervical tissues. Intraclass correlation coefficient, Wilcoxon test with Bonferroni correction, Kruskal-Wallis test, and receiver operating characteristic curve were used for statistical analysis. All the parameters showed excellent interobserver agreement (all intraclass correlation coefficients  > 0.900). Entropy, entropy(H) 0 , entropy(H) 45 , entropy(H) 90 , entropy(H) 135 , and entropy(H) mean were significantly higher, whereas entropy(H) range and entropy(H) std were significantly lower in cervical cancers compared to adjacent normal cervical tissues (all P <.0001). Kruskal-Wallis test showed that there were no significant differences among the values of various second-order entropies including entropy(H) 0, entropy(H) 45 , entropy(H) 90 , entropy(H) 135 , and entropy(H) mean. All second-order entropies had larger area under the receiver operating characteristic curve than first-order entropy in differentiating cervical cancers from adjacent normal cervical tissues. Further, entropy(H) 45 , entropy(H) 90 , entropy(H) 135 , and entropy(H) mean had the same largest area under the receiver operating characteristic curve of 0.867. Whole-lesion ADC-based entropy-related parameters of cervical cancers were developed successfully, which showed initial potential in characterizing intratumoral heterogeneity in comparison to adjacent normal cervical tissues. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

A Model Based Deconvolution Approach for Creating Surface Composition Maps of Irregularly Shaped Bodies from Limited Orbiting Nuclear Spectrometer Measurements

NASA Astrophysics Data System (ADS)

Dallmann, N. A.; Carlsten, B. E.; Stonehill, L. C.

2017-12-01

Orbiting nuclear spectrometers have contributed significantly to our understanding of the composition of solar system bodies. Gamma rays and neutrons are produced within the surfaces of bodies by impacting galactic cosmic rays (GCR) and by intrinsic radionuclide decay. Measuring the flux and energy spectrum of these products at one point in an orbit elucidates the elemental content of the area in view. Deconvolution of measurements from many spatially registered orbit points can produce detailed maps of elemental abundances. In applying these well-established techniques to small and irregularly shaped bodies like Phobos, one encounters unique challenges beyond those of a large spheroid. Polar mapping orbits are not possible for Phobos and quasistatic orbits will realize only modest inclinations unavoidably limiting surface coverage and creating North-South ambiguities in deconvolution. The irregular shape causes self-shadowing both of the body to the spectrometer but also of the body to the incoming GCR. The view angle to the surface normal as well as the distance between the surface and the spectrometer is highly irregular. These characteristics can be synthesized into a complicated and continuously changing measurement system point spread function. We have begun to explore different model-based, statistically rigorous, iterative deconvolution methods to produce elemental abundance maps for a proposed future investigation of Phobos. By incorporating the satellite orbit, the existing high accuracy shape-models of Phobos, and the spectrometer response function, a detailed and accurate system model can be constructed. Many aspects of this model formation are particularly well suited to modern graphics processing techniques and parallel processing. We will present the current status and preliminary visualizations of the Phobos measurement system model. We will also discuss different deconvolution strategies and their relative merit in statistical rigor, stability, achievable resolution, and exploitation of the irregular shape to partially resolve ambiguities. The general applicability of these new approaches to existing data sets from Mars, Mercury, and Lunar investigations will be noted.

A comparison of deconvolution and the Rutland-Patlak plot in parenchymal renal uptake rate.

PubMed

Al-Shakhrah, Issa A

2012-07-01

Deconvolution and the Rutland-Patlak (R-P) plot are two of the most commonly used methods for analyzing dynamic radionuclide renography. Both methods allow estimation of absolute and relative renal uptake of radiopharmaceutical and of its rate of transit through the kidney. Seventeen patients (32 kidneys) were referred for further evaluation by renal scanning. All patients were positioned supine with their backs to the scintillation gamma camera, so that the kidneys and the heart are both in the field of view. Approximately 5-7 mCi of (99m)Tc-DTPA (diethylinetriamine penta-acetic acid) in about 0.5 ml of saline is injected intravenously and sequential 20 s frames were acquired, the study on each patient lasts for approximately 20 min. The time-activity curves of the parenchymal region of interest of each kidney, as well as the heart were obtained for analysis. The data were then analyzed with deconvolution and the R-P plot. A strong positive association (n = 32; r = 0.83; R (2) = 0.68) was found between the values that obtained by applying the two methods. Bland-Altman statistical analysis demonstrated that ninety seven percent of the values in the study (31 cases from 32 cases, 97% of the cases) were within limits of agreement (mean ± 1.96 standard deviation). We believe that R-P analysis method is expected to be more reproducible than iterative deconvolution method, because the deconvolution technique (the iterative method) relies heavily on the accuracy of the first point analyzed, as any errors are carried forward into the calculations of all the subsequent points, whereas R-P technique is based on an initial analysis of the data by means of the R-P plot, and it can be considered as an alternative technique to find and calculate the renal uptake rate.

Interpretation of high resolution airborne magnetic data (HRAMD) of Ilesha and its environs, Southwest Nigeria, using Euler deconvolution method

NASA Astrophysics Data System (ADS)

Olurin, Oluwaseun Tolutope

2017-12-01

Interpretation of high resolution aeromagnetic data of Ilesha and its environs within the basement complex of the geological setting of Southwestern Nigeria was carried out in the study. The study area is delimited by geographic latitudes 7°30'-8°00'N and longitudes 4°30'-5°00'E. This investigation was carried out using Euler deconvolution on filtered digitised total magnetic data (Sheet Number 243) to delineate geological structures within the area under consideration. The digitised airborne magnetic data acquired in 2009 were obtained from the archives of the Nigeria Geological Survey Agency (NGSA). The airborne magnetic data were filtered, processed and enhanced; the resultant data were subjected to qualitative and quantitative magnetic interpretation, geometry and depth weighting analyses across the study area using Euler deconvolution filter control file in Oasis Montag software. Total magnetic intensity distribution in the field ranged from -77.7 to 139.7 nT. Total magnetic field intensities reveal high-magnitude magnetic intensity values (high-amplitude anomaly) and magnetic low intensities (low-amplitude magnetic anomaly) in the area under consideration. The study area is characterised with high intensity correlated with lithological variation in the basement. The sharp contrast is enhanced due to the sharp contrast in magnetic intensity between the magnetic susceptibilities of the crystalline and sedimentary rocks. The reduced-to-equator (RTE) map is characterised by high frequencies, short wavelengths, small size, weak intensity, sharp low amplitude and nearly irregular shaped anomalies, which may due to near-surface sources, such as shallow geologic units and cultural features. Euler deconvolution solution indicates a generally undulating basement, with a depth ranging from -500 to 1000 m. The Euler deconvolution results show that the basement relief is generally gentle and flat, lying within the basement terrain.

On quantum Rényi entropies: A new generalization and some properties

NASA Astrophysics Data System (ADS)

Müller-Lennert, Martin; Dupuis, Frédéric; Szehr, Oleg; Fehr, Serge; Tomamichel, Marco

2013-12-01

The Rényi entropies constitute a family of information measures that generalizes the well-known Shannon entropy, inheriting many of its properties. They appear in the form of unconditional and conditional entropies, relative entropies, or mutual information, and have found many applications in information theory and beyond. Various generalizations of Rényi entropies to the quantum setting have been proposed, most prominently Petz's quasi-entropies and Renner's conditional min-, max-, and collision entropy. However, these quantum extensions are incompatible and thus unsatisfactory. We propose a new quantum generalization of the family of Rényi entropies that contains the von Neumann entropy, min-entropy, collision entropy, and the max-entropy as special cases, thus encompassing most quantum entropies in use today. We show several natural properties for this definition, including data-processing inequalities, a duality relation, and an entropic uncertainty relation.

Upper entropy axioms and lower entropy axioms

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

Guo, Jin-Li, E-mail: phd5816@163.com; Suo, Qi

2015-04-15

The paper suggests the concepts of an upper entropy and a lower entropy. We propose a new axiomatic definition, namely, upper entropy axioms, inspired by axioms of metric spaces, and also formulate lower entropy axioms. We also develop weak upper entropy axioms and weak lower entropy axioms. Their conditions are weaker than those of Shannon–Khinchin axioms and Tsallis axioms, while these conditions are stronger than those of the axiomatics based on the first three Shannon–Khinchin axioms. The subadditivity and strong subadditivity of entropy are obtained in the new axiomatics. Tsallis statistics is a special case of satisfying our axioms. Moreover,more » different forms of information measures, such as Shannon entropy, Daroczy entropy, Tsallis entropy and other entropies, can be unified under the same axiomatics.« less

A Division-Dependent Compartmental Model for Computing Cell Numbers in CFSE-based Lymphocyte Proliferation Assays

DTIC Science & Technology

2012-02-12

is the total number of data points, is an approximately unbiased estimate of the “expected relative Kullback - Leibler distance” ( information loss...possible models). Thus, after each model from Table 2 is fit to a data set, we can compute the Akaike weights for the set of candidate models and use ...computed from the OLS best- fit model solution (top), from a deconvolution of the data using normal curves (middle) and from a deconvolution of the data

Fourier Deconvolution Methods for Resolution Enhancement in Continuous-Wave EPR Spectroscopy.

PubMed

Reed, George H; Poyner, Russell R

2015-01-01

An overview of resolution enhancement of conventional, field-swept, continuous-wave electron paramagnetic resonance spectra using Fourier transform-based deconvolution methods is presented. Basic steps that are involved in resolution enhancement of calculated spectra using an implementation based on complex discrete Fourier transform algorithms are illustrated. Advantages and limitations of the method are discussed. An application to an experimentally obtained spectrum is provided to illustrate the power of the method for resolving overlapped transitions. © 2015 Elsevier Inc. All rights reserved.

Least-Squares Deconvolution of Compton Telescope Data with the Positivity Constraint

NASA Technical Reports Server (NTRS)

Wheaton, William A.; Dixon, David D.; Tumer, O. Tumay; Zych, Allen D.

1993-01-01

We describe a Direct Linear Algebraic Deconvolution (DLAD) approach to imaging of data from Compton gamma-ray telescopes. Imposition of the additional physical constraint, that all components of the model be non-negative, has been found to have a powerful effect in stabilizing the results, giving spatial resolution at or near the instrumental limit. A companion paper (Dixon et al. 1993) presents preliminary images of the Crab Nebula region using data from COMPTEL on the Compton Gamma-Ray Observatory.

An l1-TV Algorithm for Deconvolution with Salt and Pepper Noise

DTIC Science & Technology

2009-04-01

deblurring in the presence of impulsive noise ,” Int. J. Comput. Vision, vol. 70, no. 3, pp. 279–298, Dec. 2006. [13] A. E. Beaton and J. W. Tukey, “The...AN 1-TV ALGORITHM FOR DECONVOLUTIONWITH SALT AND PEPPER NOISE Brendt Wohlberg∗ T-7 Mathematical Modeling and Analysis Los Alamos National Laboratory...and pepper noise , but the extension of this formulation to more general prob- lems, such as deconvolution, has received little attention. We consider

EEG entropy measures in anesthesia

PubMed Central

Liang, Zhenhu; Wang, Yinghua; Sun, Xue; Li, Duan; Voss, Logan J.; Sleigh, Jamie W.; Hagihira, Satoshi; Li, Xiaoli

2015-01-01

Highlights: ► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.► Approximate Entropy and Sample Entropy performed best in detecting burst suppression. Objective: Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents. Methods: Twelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy entropy, and three permutation entropy (PE) measures [Shannon PE (SPE), Tsallis PE (TPE) and Renyi PE (RPE)]. Two EEG data sets from sevoflurane-induced and isoflurane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability (Pk) analysis were applied. The multifractal detrended fluctuation analysis (MDFA) as a non-entropy measure was compared. Results: All the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline variability, higher coefficient of determination (R2) and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an advantage in computation efficiency compared with MDFA. Conclusion: Each entropy index has its advantages and disadvantages in estimating DoA. Overall, it is suggested that the RPE index was a superior measure. Investigating the advantages and disadvantages of these entropy indices could help improve current clinical indices for monitoring DoA. PMID:25741277

On Use of Multi-Chambered Fission Detectors for In-Core, Neutron Spectroscopy

NASA Astrophysics Data System (ADS)

Roberts, Jeremy A.

2018-01-01

Presented is a short, computational study on the potential use of multichambered fission detectors for in-core, neutron spectroscopy. Motivated by the development of very small fission chambers at CEA in France and at Kansas State University in the U.S., it was assumed in this preliminary analysis that devices can be made small enough to avoid flux perturbations and that uncertainties related to measurements can be ignored. It was hypothesized that a sufficient number of chambers with unique reactants can act as a real-time, foilactivation experiment. An unfolding scheme based on maximizing (Shannon) entropy was used to produce a flux spectrum from detector signals that requires no prior information. To test the method, integral, detector responses were generated for singleisotope detectors of various Th, U, Np, Pu, Am, and Cs isotopes using a simplified, pressurized-water reactor spectrum and fluxweighted, microscopic, fission cross sections, in the WIMS-69 multigroup format. An unfolded spectrum was found from subsets of these responses that had a maximum entropy while reproducing the responses considered and summing to one (that is, they were normalized). Several nuclide subsets were studied, and, as expected, the results indicate inclusion of more nuclides leads to better spectra but with diminishing improvements, with the best-case spectrum having an average, relative, group-wise error of approximately 51%. Furthermore, spectra found from minimum-norm and Tihkonov-regularization inversion were of lower quality than the maximum entropy solutions. Finally, the addition of thermal-neutron filters (here, Cd and Gd) provided substantial improvement over unshielded responses alone. The results, as a whole, suggest that in-core, neutron spectroscopy is at least marginally feasible.

Communication: Introducing prescribed biases in out-of-equilibrium Markov models

NASA Astrophysics Data System (ADS)

Dixit, Purushottam D.

2018-03-01

Markov models are often used in modeling complex out-of-equilibrium chemical and biochemical systems. However, many times their predictions do not agree with experiments. We need a systematic framework to update existing Markov models to make them consistent with constraints that are derived from experiments. Here, we present a framework based on the principle of maximum relative path entropy (minimum Kullback-Leibler divergence) to update Markov models using stationary state and dynamical trajectory-based constraints. We illustrate the framework using a biochemical model network of growth factor-based signaling. We also show how to find the closest detailed balanced Markov model to a given Markov model. Further applications and generalizations are discussed.

SU-E-QI-17: Dependence of 3D/4D PET Quantitative Image Features On Noise

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

Oliver, J; Budzevich, M; Zhang, G

2014-06-15

Purpose: Quantitative imaging is a fast evolving discipline where a large number of features are extracted from images; i.e., radiomics. Some features have been shown to have diagnostic, prognostic and predictive value. However, they are sensitive to acquisition and processing factors; e.g., noise. In this study noise was added to positron emission tomography (PET) images to determine how features were affected by noise. Methods: Three levels of Gaussian noise were added to 8 lung cancer patients PET images acquired in 3D mode (static) and using respiratory tracking (4D); for the latter images from one of 10 phases were used. Amore » total of 62 features: 14 shape, 19 intensity (1stO), 18 GLCM textures (2ndO; from grey level co-occurrence matrices) and 11 RLM textures (2ndO; from run-length matrices) features were extracted from segmented tumors. Dimensions of GLCM were 256×256, calculated using 3D images with a step size of 1 voxel in 13 directions. Grey levels were binned into 256 levels for RLM and features were calculated in all 13 directions. Results: Feature variation generally increased with noise. Shape features were the most stable while RLM were the most unstable. Intensity and GLCM features performed well; the latter being more robust. The most stable 1stO features were compactness, maximum and minimum length, standard deviation, root-mean-squared, I30, V10-V90, and entropy. The most stable 2ndO features were entropy, sum-average, sum-entropy, difference-average, difference-variance, difference-entropy, information-correlation-2, short-run-emphasis, long-run-emphasis, and run-percentage. In general, features computed from images from one of the phases of 4D scans were more stable than from 3D scans. Conclusion: This study shows the need to characterize image features carefully before they are used in research and medical applications. It also shows that the performance of features, and thereby feature selection, may be assessed in part by noise analysis.« less

Texas two-step: a framework for optimal multi-input single-output deconvolution.

PubMed

Neelamani, Ramesh; Deffenbaugh, Max; Baraniuk, Richard G

2007-11-01

Multi-input single-output deconvolution (MISO-D) aims to extract a deblurred estimate of a target signal from several blurred and noisy observations. This paper develops a new two step framework--Texas Two-Step--to solve MISO-D problems with known blurs. Texas Two-Step first reduces the MISO-D problem to a related single-input single-output deconvolution (SISO-D) problem by invoking the concept of sufficient statistics (SSs) and then solves the simpler SISO-D problem using an appropriate technique. The two-step framework enables new MISO-D techniques (both optimal and suboptimal) based on the rich suite of existing SISO-D techniques. In fact, the properties of SSs imply that a MISO-D algorithm is mean-squared-error optimal if and only if it can be rearranged to conform to the Texas Two-Step framework. Using this insight, we construct new wavelet- and curvelet-based MISO-D algorithms with asymptotically optimal performance. Simulated and real data experiments verify that the framework is indeed effective.

Voigt deconvolution method and its applications to pure oxygen absorption spectrum at 1270 nm band.

PubMed

Al-Jalali, Muhammad A; Aljghami, Issam F; Mahzia, Yahia M

2016-03-15

Experimental spectral lines of pure oxygen at 1270 nm band were analyzed by Voigt deconvolution method. The method gave a total Voigt profile, which arises from two overlapping bands. Deconvolution of total Voigt profile leads to two Voigt profiles, the first as a result of O2 dimol at 1264 nm band envelope, and the second from O2 monomer at 1268 nm band envelope. In addition, Voigt profile itself is the convolution of Lorentzian and Gaussian distributions. Competition between thermal and collisional effects was clearly observed through competition between Gaussian and Lorentzian width for each band envelope. Voigt full width at half-maximum height (Voigt FWHM) for each line, and the width ratio between Lorentzian and Gaussian width (ΓLΓG(-1)) have been investigated. The following applied pressures were at 1, 2, 3, 4, 5, and 8 bar, while the temperatures were at 298 K, 323 K, 348 K, and 373 K range. Copyright © 2015 Elsevier B.V. All rights reserved.

AIDA: an adaptive image deconvolution algorithm with application to multi-frame and three-dimensional data

PubMed Central

Hom, Erik F. Y.; Marchis, Franck; Lee, Timothy K.; Haase, Sebastian; Agard, David A.; Sedat, John W.

2011-01-01

We describe an adaptive image deconvolution algorithm (AIDA) for myopic deconvolution of multi-frame and three-dimensional data acquired through astronomical and microscopic imaging. AIDA is a reimplementation and extension of the MISTRAL method developed by Mugnier and co-workers and shown to yield object reconstructions with excellent edge preservation and photometric precision [J. Opt. Soc. Am. A 21, 1841 (2004)]. Written in Numerical Python with calls to a robust constrained conjugate gradient method, AIDA has significantly improved run times over the original MISTRAL implementation. Included in AIDA is a scheme to automatically balance maximum-likelihood estimation and object regularization, which significantly decreases the amount of time and effort needed to generate satisfactory reconstructions. We validated AIDA using synthetic data spanning a broad range of signal-to-noise ratios and image types and demonstrated the algorithm to be effective for experimental data from adaptive optics–equipped telescope systems and wide-field microscopy. PMID:17491626

A novel SURE-based criterion for parametric PSF estimation.

PubMed

Xue, Feng; Blu, Thierry

2015-02-01

We propose an unbiased estimate of a filtered version of the mean squared error--the blur-SURE (Stein's unbiased risk estimate)--as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.

Palladium-based Mass-Tag Cell Barcoding with a Doublet-Filtering Scheme and Single Cell Deconvolution Algorithm

PubMed Central

Zunder, Eli R.; Finck, Rachel; Behbehani, Gregory K.; Amir, El-ad D.; Krishnaswamy, Smita; Gonzalez, Veronica D.; Lorang, Cynthia G.; Bjornson, Zach; Spitzer, Matthew H.; Bodenmiller, Bernd; Fantl, Wendy J.; Pe’er, Dana; Nolan, Garry P.

2015-01-01

SUMMARY Mass-tag cell barcoding (MCB) labels individual cell samples with unique combinatorial barcodes, after which they are pooled for processing and measurement as a single multiplexed sample. The MCB method eliminates variability between samples in antibody staining and instrument sensitivity, reduces antibody consumption, and shortens instrument measurement time. Here, we present an optimized MCB protocol with several improvements over previously described methods. The use of palladium-based labeling reagents expands the number of measurement channels available for mass cytometry and reduces interference with lanthanide-based antibody measurement. An error-detecting combinatorial barcoding scheme allows cell doublets to be identified and removed from the analysis. A debarcoding algorithm that is single cell-based rather than population-based improves the accuracy and efficiency of sample deconvolution. This debarcoding algorithm has been packaged into software that allows rapid and unbiased sample deconvolution. The MCB procedure takes 3–4 h, not including sample acquisition time of ~1 h per million cells. PMID:25612231

Automated processing for proton spectroscopic imaging using water reference deconvolution.

PubMed

Maudsley, A A; Wu, Z; Meyerhoff, D J; Weiner, M W

1994-06-01

Automated formation of MR spectroscopic images (MRSI) is necessary before routine application of these methods is possible for in vivo studies; however, this task is complicated by the presence of spatially dependent instrumental distortions and the complex nature of the MR spectrum. A data processing method is presented for completely automated formation of in vivo proton spectroscopic images, and applied for analysis of human brain metabolites. This procedure uses the water reference deconvolution method (G. A. Morris, J. Magn. Reson. 80, 547(1988)) to correct for line shape distortions caused by instrumental and sample characteristics, followed by parametric spectral analysis. Results for automated image formation were found to compare favorably with operator dependent spectral integration methods. While the water reference deconvolution processing was found to provide good correction of spatially dependent resonance frequency shifts, it was found to be susceptible to errors for correction of line shape distortions. These occur due to differences between the water reference and the metabolite distributions.

Deconvolutions based on singular value decomposition and the pseudoinverse: a guide for beginners.

PubMed

Hendler, R W; Shrager, R I

1994-01-01

Singular value decomposition (SVD) is deeply rooted in the theory of linear algebra, and because of this is not readily understood by a large group of researchers who could profit from its application. In this paper, we discuss the subject on a level that should be understandable to scientists who are not well versed in linear algebra. However, because it is necessary that certain key concepts in linear algebra be appreciated in order to comprehend what is accomplished by SVD, we present the section, 'Bare basics of linear algebra'. This is followed by a discussion of the theory of SVD. Next we present step-by-step examples to illustrate how SVD is applied to deconvolute a titration involving a mixture of three pH indicators. One noiseless case is presented as well as two cases where either a fixed or varying noise level is present. Finally, we discuss additional deconvolutions of mixed spectra based on the use of the pseudoinverse.

Robust dynamic myocardial perfusion CT deconvolution using adaptive-weighted tensor total variation regularization

NASA Astrophysics Data System (ADS)

Gong, Changfei; Zeng, Dong; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Feng, Qianjin; Liang, Zhengrong; Ma, Jianhua

2016-03-01

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for diagnosis and risk stratification of coronary artery disease by assessing the myocardial perfusion hemodynamic maps (MPHM). Meanwhile, the repeated scanning of the same region results in a relatively large radiation dose to patients potentially. In this work, we present a robust MPCT deconvolution algorithm with adaptive-weighted tensor total variation regularization to estimate residue function accurately under the low-dose context, which is termed `MPD-AwTTV'. More specifically, the AwTTV regularization takes into account the anisotropic edge property of the MPCT images compared with the conventional total variation (TV) regularization, which can mitigate the drawbacks of TV regularization. Subsequently, an effective iterative algorithm was adopted to minimize the associative objective function. Experimental results on a modified XCAT phantom demonstrated that the present MPD-AwTTV algorithm outperforms and is superior to other existing deconvolution algorithms in terms of noise-induced artifacts suppression, edge details preservation and accurate MPHM estimation.

Deconvoluting complex structural histories archived in brittle fault zones

NASA Astrophysics Data System (ADS)

Viola, G.; Scheiber, T.; Fredin, O.; Zwingmann, H.; Margreth, A.; Knies, J.

2016-11-01

Brittle deformation can saturate the Earth's crust with faults and fractures in an apparently chaotic fashion. The details of brittle deformational histories and implications on, for example, seismotectonics and landscape, can thus be difficult to untangle. Fortunately, brittle faults archive subtle details of the stress and physical/chemical conditions at the time of initial strain localization and eventual subsequent slip(s). Hence, reading those archives offers the possibility to deconvolute protracted brittle deformation. Here we report K-Ar isotopic dating of synkinematic/authigenic illite coupled with structural analysis to illustrate an innovative approach to the high-resolution deconvolution of brittle faulting and fluid-driven alteration of a reactivated fault in western Norway. Permian extension preceded coaxial reactivation in the Jurassic and Early Cretaceous fluid-related alteration with pervasive clay authigenesis. This approach represents important progress towards time-constrained structural models, where illite characterization and K-Ar analysis are a fundamental tool to date faulting and alteration in crystalline rocks.

Refined two-index entropy and multiscale analysis for complex system

NASA Astrophysics Data System (ADS)

Bian, Songhan; Shang, Pengjian

2016-10-01

As a fundamental concept in describing complex system, entropy measure has been proposed to various forms, like Boltzmann-Gibbs (BG) entropy, one-index entropy, two-index entropy, sample entropy, permutation entropy etc. This paper proposes a new two-index entropy Sq,δ and we find the new two-index entropy is applicable to measure the complexity of wide range of systems in the terms of randomness and fluctuation range. For more complex system, the value of two-index entropy is smaller and the correlation between parameter δ and entropy Sq,δ is weaker. By combining the refined two-index entropy Sq,δ with scaling exponent h(δ), this paper analyzes the complexities of simulation series and classifies several financial markets in various regions of the world effectively.

Entropy criteria applied to pattern selection in systems with free boundaries

NASA Astrophysics Data System (ADS)

Kirkaldy, J. S.

1985-10-01

The steady state differential or integral equations which describe patterned dissipative structures, typically to be identified with first order phase transformation morphologies like isothermal pearlites, are invariably degenerate in one or more order parameters (the lamellar spacing in the pearlite case). It is often observed that a different pattern is attained at the steady state for each initial condition (the hysteresis or metastable case). Alternatively, boundary perturbations and internal fluctuations during transition up to, or at the steady state, destroy the path coherence. In this case a statistical ensemble of imperfect patterns often emerges which represents a fluctuating but recognizably patterned and unique average steady state. It is cases like cellular, lamellar pearlite, involving an assembly of individual cell patterns which are regularly perturbed by local fluctuation and growth processes, which concern us here. Such weakly fluctuating nonlinear steady state ensembles can be arranged in a thought experiment so as to evolve as subsystems linking two very large mass-energy reservoirs in isolation. Operating on this discontinuous thermodynamic ideal, Onsager’s principle of maximum path probability for isolated systems, which we interpret as a minimal time correlation function connecting subsystem and baths, identifies the stable steady state at a parametric minimum or maximum (or both) in the dissipation rate. This nonlinear principle is independent of the Principle of Minimum Dissipation which is applicable in the linear regime of irreversible thermodynamics. The statistical argument is equivalent to the weak requirement that the isolated system entropy as a function of time be differentiable to the second order despite the macroscopic pattern fluctuations which occur in the subsystem. This differentiability condition is taken for granted in classical stability theory based on the 2nd Law. The optimal principle as applied to isothermal and forced velocity pearlites (in this case maximal) possesses a Le Chatelier (perturbation) Principle which can be formulated exactly via Langer’s conjecture that “each lamella must grow in a direction which is perpendicular to the solidification front”. This is the first example of such an equivalence to be experimentally and theoretically recognized in nonlinear irreversible thermodynamics. A further application to binary solidification cells is reviewed. In this case the optimum in the dissipation is a minimum and the closure between theory and experiment is excellent. Other applications in thermal-hydraulics, biology, and solid state physics are briefy described.

Aging and cardiovascular complexity: effect of the length of RR tachograms

PubMed Central

Nagaraj, Nithin

2016-01-01

As we age, our hearts undergo changes that result in a reduction in complexity of physiological interactions between different control mechanisms. This results in a potential risk of cardiovascular diseases which are the number one cause of death globally. Since cardiac signals are nonstationary and nonlinear in nature, complexity measures are better suited to handle such data. In this study, three complexity measures are used, namely Lempel–Ziv complexity (LZ), Sample Entropy (SampEn) and Effort-To-Compress (ETC). We determined the minimum length of RR tachogram required for characterizing complexity of healthy young and healthy old hearts. All the three measures indicated significantly lower complexity values for older subjects than younger ones. However, the minimum length of heart-beat interval data needed differs for the three measures, with LZ and ETC needing as low as 10 samples, whereas SampEn requires at least 80 samples. Our study indicates that complexity measures such as LZ and ETC are good candidates for the analysis of cardiovascular dynamics since they are able to work with very short RR tachograms. PMID:27957395

Comment on "Inference with minimal Gibbs free energy in information field theory".

PubMed

Iatsenko, D; Stefanovska, A; McClintock, P V E

2012-03-01

Enßlin and Weig [Phys. Rev. E 82, 051112 (2010)] have introduced a "minimum Gibbs free energy" (MGFE) approach for estimation of the mean signal and signal uncertainty in Bayesian inference problems: it aims to combine the maximum a posteriori (MAP) and maximum entropy (ME) principles. We point out, however, that there are some important questions to be clarified before the new approach can be considered fully justified, and therefore able to be used with confidence. In particular, after obtaining a Gaussian approximation to the posterior in terms of the MGFE at some temperature T, this approximation should always be raised to the power of T to yield a reliable estimate. In addition, we show explicitly that MGFE indeed incorporates the MAP principle, as well as the MDI (minimum discrimination information) approach, but not the well-known ME principle of Jaynes [E.T. Jaynes, Phys. Rev. 106, 620 (1957)]. We also illuminate some related issues and resolve apparent discrepancies. Finally, we investigate the performance of MGFE estimation for different values of T, and we discuss the advantages and shortcomings of the approach.

A globally convergent Lagrange and barrier function iterative algorithm for the traveling salesman problem.

PubMed

Dang, C; Xu, L

2001-03-01

In this paper a globally convergent Lagrange and barrier function iterative algorithm is proposed for approximating a solution of the traveling salesman problem. The algorithm employs an entropy-type barrier function to deal with nonnegativity constraints and Lagrange multipliers to handle linear equality constraints, and attempts to produce a solution of high quality by generating a minimum point of a barrier problem for a sequence of descending values of the barrier parameter. For any given value of the barrier parameter, the algorithm searches for a minimum point of the barrier problem in a feasible descent direction, which has a desired property that the nonnegativity constraints are always satisfied automatically if the step length is a number between zero and one. At each iteration the feasible descent direction is found by updating Lagrange multipliers with a globally convergent iterative procedure. For any given value of the barrier parameter, the algorithm converges to a stationary point of the barrier problem without any condition on the objective function. Theoretical and numerical results show that the algorithm seems more effective and efficient than the softassign algorithm.

Optimal application of Morrison's iterative noise removal for deconvolution. Appendices

NASA Technical Reports Server (NTRS)

Ioup, George E.; Ioup, Juliette W.

1987-01-01

Morrison's iterative method of noise removal, or Morrison's smoothing, is applied in a simulation to noise-added data sets of various noise levels to determine its optimum use. Morrison's smoothing is applied for noise removal alone, and for noise removal prior to deconvolution. For the latter, an accurate method is analyzed to provide confidence in the optimization. The method consists of convolving the data with an inverse filter calculated by taking the inverse discrete Fourier transform of the reciprocal of the transform of the response of the system. Various length filters are calculated for the narrow and wide Gaussian response functions used. Deconvolution of non-noisy data is performed, and the error in each deconvolution calculated. Plots are produced of error versus filter length; and from these plots the most accurate length filters determined. The statistical methodologies employed in the optimizations of Morrison's method are similar. A typical peak-type input is selected and convolved with the two response functions to produce the data sets to be analyzed. Both constant and ordinate-dependent Gaussian distributed noise is added to the data, where the noise levels of the data are characterized by their signal-to-noise ratios. The error measures employed in the optimizations are the L1 and L2 norms. Results of the optimizations for both Gaussians, both noise types, and both norms include figures of optimum iteration number and error improvement versus signal-to-noise ratio, and tables of results. The statistical variation of all quantities considered is also given.

Total variation based image deconvolution for extended depth-of-field microscopy images

NASA Astrophysics Data System (ADS)

Hausser, F.; Beckers, I.; Gierlak, M.; Kahraman, O.

2015-03-01

One approach for a detailed understanding of dynamical cellular processes during drug delivery is the use of functionalized biocompatible nanoparticles and fluorescent markers. An appropriate imaging system has to detect these moving particles so as whole cell volumes in real time with high lateral resolution in a range of a few 100 nm. In a previous study Extended depth-of-field microscopy (EDF-microscopy) has been applied to fluorescent beads and tradiscantia stamen hair cells and the concept of real-time imaging has been proved in different microscopic modes. In principle a phase retardation system like a programmable space light modulator or a static waveplate is incorporated in the light path and modulates the wavefront of light. Hence the focal ellipsoid is smeared out and images seem to be blurred in a first step. An image restoration by deconvolution using the known point-spread-function (PSF) of the optical system is necessary to achieve sharp microscopic images of an extended depth-of-field. This work is focused on the investigation and optimization of deconvolution algorithms to solve this restoration problem satisfactorily. This inverse problem is challenging due to presence of Poisson distributed noise and Gaussian noise, and since the PSF used for deconvolution exactly fits in just one plane within the object. We use non-linear Total Variation based image restoration techniques, where different types of noise can be treated properly. Various algorithms are evaluated for artificially generated 3D images as well as for fluorescence measurements of BPAE cells.

Deconvolution of the vestibular evoked myogenic potential.

PubMed

Lütkenhöner, Bernd; Basel, Türker

2012-02-07

The vestibular evoked myogenic potential (VEMP) and the associated variance modulation can be understood by a convolution model. Two functions of time are incorporated into the model: the motor unit action potential (MUAP) of an average motor unit, and the temporal modulation of the MUAP rate of all contributing motor units, briefly called rate modulation. The latter is the function of interest, whereas the MUAP acts as a filter that distorts the information contained in the measured data. Here, it is shown how to recover the rate modulation by undoing the filtering using a deconvolution approach. The key aspects of our deconvolution algorithm are as follows: (1) the rate modulation is described in terms of just a few parameters; (2) the MUAP is calculated by Wiener deconvolution of the VEMP with the rate modulation; (3) the model parameters are optimized using a figure-of-merit function where the most important term quantifies the difference between measured and model-predicted variance modulation. The effectiveness of the algorithm is demonstrated with simulated data. An analysis of real data confirms the view that there are basically two components, which roughly correspond to the waves p13-n23 and n34-p44 of the VEMP. The rate modulation corresponding to the first, inhibitory component is much stronger than that corresponding to the second, excitatory component. But the latter is more extended so that the two modulations have almost the same equivalent rectangular duration. Copyright © 2011 Elsevier Ltd. All rights reserved.

Isotope pattern deconvolution as a tool to study iron metabolism in plants.

PubMed

Rodríguez-Castrillón, José Angel; Moldovan, Mariella; García Alonso, J Ignacio; Lucena, Juan José; García-Tomé, Maria Luisa; Hernández-Apaolaza, Lourdes

2008-01-01

Isotope pattern deconvolution is a mathematical technique for isolating distinct isotope signatures from mixtures of natural abundance and enriched tracers. In iron metabolism studies measurement of all four isotopes of the element by high-resolution multicollector or collision cell ICP-MS allows the determination of the tracer/tracee ratio with simultaneous internal mass bias correction and lower uncertainties. This technique was applied here for the first time to study iron uptake by cucumber plants using 57Fe-enriched iron chelates of the o,o and o,p isomers of ethylenediaminedi(o-hydroxyphenylacetic) acid (EDDHA) and ethylenediamine tetraacetic acid (EDTA). Samples of root, stem, leaves, and xylem sap, after exposure of the cucumber plants to the mentioned 57Fe chelates, were collected, dried, and digested using nitric acid. The isotopic composition of iron in the samples was measured by ICP-MS using a high-resolution multicollector instrument. Mass bias correction was computed using both a natural abundance iron standard and by internal correction using isotope pattern deconvolution. It was observed that, for plants with low 57Fe enrichment, isotope pattern deconvolution provided lower tracer/tracee ratio uncertainties than the traditional method applying external mass bias correction. The total amount of the element in the plants was determined by isotope dilution analysis, using a collision cell quadrupole ICP-MS instrument, after addition of 57Fe or natural abundance Fe in a known amount which depended on the isotopic composition of the sample.

Ground-penetrating radar: use and misuse

NASA Astrophysics Data System (ADS)

Olhoeft, Gary R.

1999-10-01

Ground penetrating radar (GPR) has been used to explore the subsurface of the earth since 1929. Over the past 70 years, it has been widely used, misused and abused. Use includes agriculture, archaeology, environmental and geotechnical site characterization, minerals, groundwater and permafrost exploration, tunnel, utility, and unexploded ordnance location, dam inspection, and much more. Misuse includes mistaking above ground reflections for subsurface events or mapping things from off to the side as if they were directly below, synthetic aperture processing of dispersive data, minimum phase deconvolution, locating objects smaller than resolution limits of the wavelength in the ground, ignoring Fresnel zone limitations in mapping subsurface structure, processing radar data through seismic software packages without allowing for the differences, mapping the bottom of metal pipes from the top, claiming to see through thousands of feet of sediments, and more. GPR is also being abused as the regulatory environment changes and the radiofrequency spectrum is becoming more crowded by cellular phones, pagers, garage door openers, wireless computer networks, and the like. It is often thought to be a source of interference (though it never is) and it is increasingly interfered with by other radiofrequency transmitters.

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

Douglas, Matthew; Bernacki, Bruce E.; Erchinger, Jennifer L.

Liquid scintillation counting (LSC) is a versatile and commonplace method for radiometric measurement of charged particle emitting radionuclides. The LSC method provides utility in a range of environmental science applications including hydrological studies of water transport, anthropogenic releases of radionuclides into the environment, and vertical mixing rates within oceans. Instrumental measurement background is one limiting factor of radiometric measurement sensitivity. As part of the development of a custom low background LSC system located in a shallow underground laboratory at Pacific Northwest National Laboratory, a number of measurement applications of LSC have been considered and are summarized here. The focus ismore » on determining which aspects of such measurements would gain the greatest benefit from the reduction of LSC backgrounds by a factor of 10-100 relative to values reported in the literature. Examples of benefits include lowering the minimum detectable activity, reducing the sample size required, and shortening the elapsed timeline of the processing and analysis sequence. In particular tritium, strontium, and actinium isotopes are examined as these isotopes cover a range of requirements related to the LSC measurement method (e.g., 3H: low energy; Sr: spectral deconvolution; Ac: alpha/beta discrimination).« less

Nucleus segmentation in histology images with hierarchical multilevel thresholding

NASA Astrophysics Data System (ADS)

Ahmady Phoulady, Hady; Goldgof, Dmitry B.; Hall, Lawrence O.; Mouton, Peter R.

2016-03-01

Automatic segmentation of histological images is an important step for increasing throughput while maintaining high accuracy, avoiding variation from subjective bias, and reducing the costs for diagnosing human illnesses such as cancer and Alzheimer's disease. In this paper, we present a novel method for unsupervised segmentation of cell nuclei in stained histology tissue. Following an initial preprocessing step involving color deconvolution and image reconstruction, the segmentation step consists of multilevel thresholding and a series of morphological operations. The only parameter required for the method is the minimum region size, which is set according to the resolution of the image. Hence, the proposed method requires no training sets or parameter learning. Because the algorithm requires no assumptions or a priori information with regard to cell morphology, the automatic approach is generalizable across a wide range of tissues. Evaluation across a dataset consisting of diverse tissues, including breast, liver, gastric mucosa and bone marrow, shows superior performance over four other recent methods on the same dataset in terms of F-measure with precision and recall of 0.929 and 0.886, respectively.

Microcanonical entropy for classical systems

NASA Astrophysics Data System (ADS)

Franzosi, Roberto

2018-03-01

The entropy definition in the microcanonical ensemble is revisited. We propose a novel definition for the microcanonical entropy that resolve the debate on the correct definition of the microcanonical entropy. In particular we show that this entropy definition fixes the problem inherent the exact extensivity of the caloric equation. Furthermore, this entropy reproduces results which are in agreement with the ones predicted with standard Boltzmann entropy when applied to macroscopic systems. On the contrary, the predictions obtained with the standard Boltzmann entropy and with the entropy we propose, are different for small system sizes. Thus, we conclude that the Boltzmann entropy provides a correct description for macroscopic systems whereas extremely small systems should be better described with the entropy that we propose here.

On S-mixing entropy of quantum channels

NASA Astrophysics Data System (ADS)

Mukhamedov, Farrukh; Watanabe, Noboru

2018-06-01

In this paper, an S-mixing entropy of quantum channels is introduced as a generalization of Ohya's S-mixing entropy. We investigate several properties of the introduced entropy. Moreover, certain relations between the S-mixing entropy and the existing map and output entropies of quantum channels are investigated as well. These relations allowed us to find certain connections between separable states and the introduced entropy. Hence, there is a sufficient condition to detect entangled states. Moreover, several properties of the introduced entropy are investigated. Besides, entropies of qubit and phase-damping channels are calculated.

Fermionic entanglement in superconducting systems

NASA Astrophysics Data System (ADS)

Di Tullio, M.; Gigena, N.; Rossignoli, R.

2018-06-01

We examine distinct measures of fermionic entanglement in the exact ground state of a finite superconducting system. It is first shown that global measures such as the one-body entanglement entropy, which represents the minimum relative entropy between the exact ground state and the set of fermionic Gaussian states, exhibit a close correlation with the BCS gap, saturating in the strong superconducting regime. The same behavior is displayed by the bipartite entanglement between the set of all single-particle states k of positive quasimomenta and their time-reversed partners k ¯. In contrast, the entanglement associated with the reduced density matrix of four single-particle modes k ,k ¯ , k',k¯' , which can be measured through a properly defined fermionic concurrence, exhibits a different behavior, showing a peak in the vicinity of the superconducting transition for states k ,k' close to the Fermi level and becoming small in the strong coupling regime. In the latter, such reduced state exhibits, instead, a finite mutual information and quantum discord. While the first measures can be correctly estimated with the BCS approximation, the previous four-level concurrence lies strictly beyond the latter, requiring at least a particle-number projected BCS treatment for its description. Formal properties of all previous entanglement measures are as well discussed.

Application of maximum entropy to statistical inference for inversion of data from a single track segment.

PubMed

Stotts, Steven A; Koch, Robert A

2017-08-01

In this paper an approach is presented to estimate the constraint required to apply maximum entropy (ME) for statistical inference with underwater acoustic data from a single track segment. Previous algorithms for estimating the ME constraint require multiple source track segments to determine the constraint. The approach is relevant for addressing model mismatch effects, i.e., inaccuracies in parameter values determined from inversions because the propagation model does not account for all acoustic processes that contribute to the measured data. One effect of model mismatch is that the lowest cost inversion solution may be well outside a relatively well-known parameter value's uncertainty interval (prior), e.g., source speed from track reconstruction or towed source levels. The approach requires, for some particular parameter value, the ME constraint to produce an inferred uncertainty interval that encompasses the prior. Motivating this approach is the hypothesis that the proposed constraint determination procedure would produce a posterior probability density that accounts for the effect of model mismatch on inferred values of other inversion parameters for which the priors might be quite broad. Applications to both measured and simulated data are presented for model mismatch that produces minimum cost solutions either inside or outside some priors.

Analytical design of intelligent machines

NASA Technical Reports Server (NTRS)

Saridis, George N.; Valavanis, Kimon P.

1987-01-01

The problem of designing 'intelligent machines' to operate in uncertain environments with minimum supervision or interaction with a human operator is examined. The structure of an 'intelligent machine' is defined to be the structure of a Hierarchically Intelligent Control System, composed of three levels hierarchically ordered according to the principle of 'increasing precision with decreasing intelligence', namely: the organizational level, performing general information processing tasks in association with a long-term memory; the coordination level, dealing with specific information processing tasks with a short-term memory; and the control level, which performs the execution of various tasks through hardware using feedback control methods. The behavior of such a machine may be managed by controls with special considerations and its 'intelligence' is directly related to the derivation of a compatible measure that associates the intelligence of the higher levels with the concept of entropy, which is a sufficient analytic measure that unifies the treatment of all the levels of an 'intelligent machine' as the mathematical problem of finding the right sequence of internal decisions and controls for a system structured in the order of intelligence and inverse order of precision such that it minimizes its total entropy. A case study on the automatic maintenance of a nuclear plant illustrates the proposed approach.

Einstein-Podolsky-Rosen paradox implies a minimum achievable temperature

NASA Astrophysics Data System (ADS)

Rogers, David M.

2017-01-01

This work examines the thermodynamic consequences of the repeated partial projection model for coupling a quantum system to an arbitrary series of environments under feedback control. This paper provides observational definitions of heat and work that can be realized in current laboratory setups. In contrast to other definitions, it uses only properties of the environment and the measurement outcomes, avoiding references to the "measurement" of the central system's state in any basis. These definitions are consistent with the usual laws of thermodynamics at all temperatures, while never requiring complete projective measurement of the entire system. It is shown that the back action of measurement must be counted as work rather than heat to satisfy the second law. Comparisons are made to quantum jump (unravelling) and transition-probability based definitions, many of which appear as particular limits of the present model. These limits show that our total entropy production is a lower bound on traditional definitions of heat that trace out the measurement device. Examining the master equation approximation to the process at finite measurement rates, we show that most interactions with the environment make the system unable to reach absolute zero. We give an explicit formula for the minimum temperature achievable in repeatedly measured quantum systems. The phenomenon of minimum temperature offers an explanation of recent experiments aimed at testing fluctuation theorems in the quantum realm and places a fundamental purity limit on quantum computers.

Comment on the paper "Thermoluminescence glow-curve deconvolution functions for mixed order of kinetics and continuous trap distribution by G. Kitis, J.M. Gomez-Ros, Nuclear Instruments and Methods in Physics Research A 440, 2000, pp 224-231"

NASA Astrophysics Data System (ADS)

Kazakis, Nikolaos A.

2018-01-01

The present comment concerns the correct presentation of an algorithm proposed in the above paper for the glow-curve deconvolution in the case of continuous distribution of trapping states. Since most researchers would use directly the proposed algorithm as published, they should be notified of its correct formulation during the fitting of TL glow curves of materials with continuous trap distribution using this Equation.

An l1-TV algorithm for deconvolution with salt and pepper noise

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

Wohlberg, Brendt; Rodriguez, Paul

2008-01-01

There has recently been considerable interest in applying Total Variation with an {ell}{sup 1} data fidelity term to the denoising of images subject to salt and pepper noise, but the extension of this formulation to more general problems, such as deconvolution, has received little attention, most probably because most efficient algorithms for {ell}{sup 1}-TV denoising can not handle more general inverse problems. We apply the Iteratively Reweighted Norm algorithm to this problem, and compare performance with an alternative algorithm based on the Mumford-Shah functional.

Entropy and equilibrium via games of complexity

NASA Astrophysics Data System (ADS)

Topsøe, Flemming

2004-09-01

It is suggested that thermodynamical equilibrium equals game theoretical equilibrium. Aspects of this thesis are discussed. The philosophy is consistent with maximum entropy thinking of Jaynes, but goes one step deeper by deriving the maximum entropy principle from an underlying game theoretical principle. The games introduced are based on measures of complexity. Entropy is viewed as minimal complexity. It is demonstrated that Tsallis entropy ( q-entropy) and Kaniadakis entropy ( κ-entropy) can be obtained in this way, based on suitable complexity measures. A certain unifying effect is obtained by embedding these measures in a two-parameter family of entropy functions.

Quantile based Tsallis entropy in residual lifetime

NASA Astrophysics Data System (ADS)

Khammar, A. H.; Jahanshahi, S. M. A.

2018-02-01

Tsallis entropy is a generalization of type α of the Shannon entropy, that is a nonadditive entropy unlike the Shannon entropy. Shannon entropy may be negative for some distributions, but Tsallis entropy can always be made nonnegative by choosing appropriate value of α. In this paper, we derive the quantile form of this nonadditive's entropy function in the residual lifetime, namely the residual quantile Tsallis entropy (RQTE) and get the bounds for it, depending on the Renyi's residual quantile entropy. Also, we obtain relationship between RQTE and concept of proportional hazards model in the quantile setup. Based on the new measure, we propose a stochastic order and aging classes, and study its properties. Finally, we prove characterizations theorems for some well known lifetime distributions. It is shown that RQTE uniquely determines the parent distribution unlike the residual Tsallis entropy.

Time-dependent entropy evolution in microscopic and macroscopic electromagnetic relaxation

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

Baker-Jarvis, James

This paper is a study of entropy and its evolution in the time and frequency domains upon application of electromagnetic fields to materials. An understanding of entropy and its evolution in electromagnetic interactions bridges the boundaries between electromagnetism and thermodynamics. The approach used here is a Liouville-based statistical-mechanical theory. I show that the microscopic entropy is reversible and the macroscopic entropy satisfies an H theorem. The spectral entropy development can be very useful for studying the frequency response of materials. Using a projection-operator based nonequilibrium entropy, different equations are derived for the entropy and entropy production and are applied tomore » the polarization, magnetization, and macroscopic fields. I begin by proving an exact H theorem for the entropy, progress to application of time-dependent entropy in electromagnetics, and then apply the theory to relevant applications in electromagnetics. The paper concludes with a discussion of the relationship of the frequency-domain form of the entropy to the permittivity, permeability, and impedance.« less

Entropy flow and entropy production in the human body in basal conditions.

PubMed

Aoki, I

1989-11-08

Entropy inflow and outflow for the naked human body in basal conditions in the respiration calorimeter due to infrared radiation, convection, evaporation of water and mass-flow are calculated by use of the energetic data obtained by Hardy & Du Bois. Also, the change of entropy content in the body is estimated. The entropy production in the human body is obtained as the change of entropy content minus the net entropy flow into the body. The entropy production thus calculated becomes positive. The magnitude of entropy production per effective radiating surface area does not show any significant variation with subjects. The entropy production is nearly constant at the calorimeter temperatures of 26-32 degrees C; the average in this temperature range is 0.172 J m-2 sec-1 K-1. The forced air currents around the human body and also clothing have almost no effect in changing the entropy production. Thus, the entropy production of the naked human body in basal conditions does not depend on its environmental factors.

Gabor Deconvolution as Preliminary Method to Reduce Pitfall in Deeper Target Seismic Data

NASA Astrophysics Data System (ADS)

Oktariena, M.; Triyoso, W.

2018-03-01

Anelastic attenuation process during seismic wave propagation is the trigger of seismic non-stationary characteristic. An absorption and a scattering of energy are causing the seismic energy loss as the depth increasing. A series of thin reservoir layers found in the study area is located within Talang Akar Fm. Level, showing an indication of interpretation pitfall due to attenuation effect commonly occurred in deeper level seismic data. Attenuation effect greatly influences the seismic images of deeper target level, creating pitfalls in several aspect. Seismic amplitude in deeper target level often could not represent its real subsurface character due to a low amplitude value or a chaotic event nearing the Basement. Frequency wise, the decaying could be seen as the frequency content diminishing in deeper target. Meanwhile, seismic amplitude is the simple tool to point out Direct Hydrocarbon Indicator (DHI) in preliminary Geophysical study before a further advanced interpretation method applied. A quick-look of Post-Stack Seismic Data shows the reservoir associated with a bright spot DHI while another bigger bright spot body detected in the North East area near the field edge. A horizon slice confirms a possibility that the other bright spot zone has smaller delineation; an interpretation pitfall commonly occurs in deeper level of seismic. We evaluates this pitfall by applying Gabor Deconvolution to address the attenuation problem. Gabor Deconvolution forms a Partition of Unity to factorize the trace into smaller convolution window that could be processed as stationary packets. Gabor Deconvolution estimates both the magnitudes of source signature alongside its attenuation function. The enhanced seismic shows a better imaging in the pitfall area that previously detected as a vast bright spot zone. When the enhanced seismic is used for further advanced reprocessing process, the Seismic Impedance and Vp/Vs Ratio slices show a better reservoir delineation, in which the pitfall area is reduced and some morphed as background lithology. Gabor Deconvolution removes the attenuation by performing Gabor Domain spectral division, which in extension also reduces interpretation pitfall in deeper target seismic.

DECONVOLUTION OF IMAGES FROM BLAST 2005: INSIGHT INTO THE K3-50 AND IC 5146 STAR-FORMING REGIONS

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

Roy, Arabindo; Netterfield, Calvin B.; Ade, Peter A. R.

2011-04-01

We present an implementation of the iterative flux-conserving Lucy-Richardson (L-R) deconvolution method of image restoration for maps produced by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Compared to the direct Fourier transform method of deconvolution, the L-R operation restores images with better-controlled background noise and increases source detectability. Intermediate iterated images are useful for studying extended diffuse structures, while the later iterations truly enhance point sources to near the designed diffraction limit of the telescope. The L-R method of deconvolution is efficient in resolving compact sources in crowded regions while simultaneously conserving their respective flux densities. We have analyzed itsmore » performance and convergence extensively through simulations and cross-correlations of the deconvolved images with available high-resolution maps. We present new science results from two BLAST surveys, in the Galactic regions K3-50 and IC 5146, further demonstrating the benefits of performing this deconvolution. We have resolved three clumps within a radius of 4.'5 inside the star-forming molecular cloud containing K3-50. Combining the well-resolved dust emission map with available multi-wavelength data, we have constrained the spectral energy distributions (SEDs) of five clumps to obtain masses (M), bolometric luminosities (L), and dust temperatures (T). The L-M diagram has been used as a diagnostic tool to estimate the evolutionary stages of the clumps. There are close relationships between dust continuum emission and both 21 cm radio continuum and {sup 12}CO molecular line emission. The restored extended large-scale structures in the Northern Streamer of IC 5146 have a strong spatial correlation with both SCUBA and high-resolution extinction images. A dust temperature of 12 K has been obtained for the central filament. We report physical properties of ten compact sources, including six associated protostars, by fitting SEDs to multi-wavelength data. All of these compact sources are still quite cold (typical temperature below {approx} 16 K) and are above the critical Bonner-Ebert mass. They have associated low-power young stellar objects. Further evidence for starless clumps has also been found in the IC 5146 region.« less

Deconvolution of Images from BLAST 2005: Insight into the K3-50 and IC 5146 Star-forming Regions

NASA Astrophysics Data System (ADS)

Roy, Arabindo; Ade, Peter A. R.; Bock, James J.; Brunt, Christopher M.; Chapin, Edward L.; Devlin, Mark J.; Dicker, Simon R.; France, Kevin; Gibb, Andrew G.; Griffin, Matthew; Gundersen, Joshua O.; Halpern, Mark; Hargrave, Peter C.; Hughes, David H.; Klein, Jeff; Marsden, Gaelen; Martin, Peter G.; Mauskopf, Philip; Netterfield, Calvin B.; Olmi, Luca; Patanchon, Guillaume; Rex, Marie; Scott, Douglas; Semisch, Christopher; Truch, Matthew D. P.; Tucker, Carole; Tucker, Gregory S.; Viero, Marco P.; Wiebe, Donald V.

2011-04-01

We present an implementation of the iterative flux-conserving Lucy-Richardson (L-R) deconvolution method of image restoration for maps produced by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Compared to the direct Fourier transform method of deconvolution, the L-R operation restores images with better-controlled background noise and increases source detectability. Intermediate iterated images are useful for studying extended diffuse structures, while the later iterations truly enhance point sources to near the designed diffraction limit of the telescope. The L-R method of deconvolution is efficient in resolving compact sources in crowded regions while simultaneously conserving their respective flux densities. We have analyzed its performance and convergence extensively through simulations and cross-correlations of the deconvolved images with available high-resolution maps. We present new science results from two BLAST surveys, in the Galactic regions K3-50 and IC 5146, further demonstrating the benefits of performing this deconvolution. We have resolved three clumps within a radius of 4farcm5 inside the star-forming molecular cloud containing K3-50. Combining the well-resolved dust emission map with available multi-wavelength data, we have constrained the spectral energy distributions (SEDs) of five clumps to obtain masses (M), bolometric luminosities (L), and dust temperatures (T). The L-M diagram has been used as a diagnostic tool to estimate the evolutionary stages of the clumps. There are close relationships between dust continuum emission and both 21 cm radio continuum and 12CO molecular line emission. The restored extended large-scale structures in the Northern Streamer of IC 5146 have a strong spatial correlation with both SCUBA and high-resolution extinction images. A dust temperature of 12 K has been obtained for the central filament. We report physical properties of ten compact sources, including six associated protostars, by fitting SEDs to multi-wavelength data. All of these compact sources are still quite cold (typical temperature below ~ 16 K) and are above the critical Bonner-Ebert mass. They have associated low-power young stellar objects. Further evidence for starless clumps has also been found in the IC 5146 region.

Image processing tools dedicated to quantification in 3D fluorescence microscopy

NASA Astrophysics Data System (ADS)

Dieterlen, A.; De Meyer, A.; Colicchio, B.; Le Calvez, S.; Haeberlé, O.; Jacquey, S.

2006-05-01

3-D optical fluorescent microscopy now becomes an efficient tool for the volume investigation of living biological samples. Developments in instrumentation have permitted to beat off the conventional Abbe limit. In any case the recorded image can be described by the convolution equation between the original object and the Point Spread Function (PSF) of the acquisition system. Due to the finite resolution of the instrument, the original object is recorded with distortions and blurring, and contaminated by noise. This induces that relevant biological information cannot be extracted directly from raw data stacks. If the goal is 3-D quantitative analysis, then to assess optimal performance of the instrument and to ensure the data acquisition reproducibility, the system characterization is mandatory. The PSF represents the properties of the image acquisition system; we have proposed the use of statistical tools and Zernike moments to describe a 3-D PSF system and to quantify the variation of the PSF. This first step toward standardization is helpful to define an acquisition protocol optimizing exploitation of the microscope depending on the studied biological sample. Before the extraction of geometrical information and/or intensities quantification, the data restoration is mandatory. Reduction of out-of-focus light is carried out computationally by deconvolution process. But other phenomena occur during acquisition, like fluorescence photo degradation named "bleaching", inducing an alteration of information needed for restoration. Therefore, we have developed a protocol to pre-process data before the application of deconvolution algorithms. A large number of deconvolution methods have been described and are now available in commercial package. One major difficulty to use this software is the introduction by the user of the "best" regularization parameters. We have pointed out that automating the choice of the regularization level; also greatly improves the reliability of the measurements although it facilitates the use. Furthermore, to increase the quality and the repeatability of quantitative measurements a pre-filtering of images improves the stability of deconvolution process. In the same way, the PSF prefiltering stabilizes the deconvolution process. We have shown that Zemike polynomials can be used to reconstruct experimental PSF, preserving system characteristics and removing the noise contained in the PSF.

Three faces of entropy for complex systems: Information, thermodynamics, and the maximum entropy principle

NASA Astrophysics Data System (ADS)

Thurner, Stefan; Corominas-Murtra, Bernat; Hanel, Rudolf

2017-09-01

There are at least three distinct ways to conceptualize entropy: entropy as an extensive thermodynamic quantity of physical systems (Clausius, Boltzmann, Gibbs), entropy as a measure for information production of ergodic sources (Shannon), and entropy as a means for statistical inference on multinomial processes (Jaynes maximum entropy principle). Even though these notions represent fundamentally different concepts, the functional form of the entropy for thermodynamic systems in equilibrium, for ergodic sources in information theory, and for independent sampling processes in statistical systems, is degenerate, H (p ) =-∑ipilogpi . For many complex systems, which are typically history-dependent, nonergodic, and nonmultinomial, this is no longer the case. Here we show that for such processes, the three entropy concepts lead to different functional forms of entropy, which we will refer to as SEXT for extensive entropy, SIT for the source information rate in information theory, and SMEP for the entropy functional that appears in the so-called maximum entropy principle, which characterizes the most likely observable distribution functions of a system. We explicitly compute these three entropy functionals for three concrete examples: for Pólya urn processes, which are simple self-reinforcing processes, for sample-space-reducing (SSR) processes, which are simple history dependent processes that are associated with power-law statistics, and finally for multinomial mixture processes.

Objective evaluation of linear and nonlinear tomosynthetic reconstruction algorithms

NASA Astrophysics Data System (ADS)

Webber, Richard L.; Hemler, Paul F.; Lavery, John E.

2000-04-01

This investigation objectively tests five different tomosynthetic reconstruction methods involving three different digital sensors, each used in a different radiologic application: chest, breast, and pelvis, respectively. The common task was to simulate a specific representative projection for each application by summation of appropriately shifted tomosynthetically generated slices produced by using the five algorithms. These algorithms were, respectively, (1) conventional back projection, (2) iteratively deconvoluted back projection, (3) a nonlinear algorithm similar to back projection, except that the minimum value from all of the component projections for each pixel is computed instead of the average value, (4) a similar algorithm wherein the maximum value was computed instead of the minimum value, and (5) the same type of algorithm except that the median value was computed. Using these five algorithms, we obtained data from each sensor-tissue combination, yielding three factorially distributed series of contiguous tomosynthetic slices. The respective slice stacks then were aligned orthogonally and averaged to yield an approximation of a single orthogonal projection radiograph of the complete (unsliced) tissue thickness. Resulting images were histogram equalized, and actual projection control images were subtracted from their tomosynthetically synthesized counterparts. Standard deviations of the resulting histograms were recorded as inverse figures of merit (FOMs). Visual rankings of image differences by five human observers of a subset (breast data only) also were performed to determine whether their subjective observations correlated with homologous FOMs. Nonparametric statistical analysis of these data demonstrated significant differences (P > 0.05) between reconstruction algorithms. The nonlinear minimization reconstruction method nearly always outperformed the other methods tested. Observer rankings were similar to those measured objectively.

An improved method for polarimetric image restoration in interferometry

NASA Astrophysics Data System (ADS)

Pratley, Luke; Johnston-Hollitt, Melanie

2016-11-01

Interferometric radio astronomy data require the effects of limited coverage in the Fourier plane to be accounted for via a deconvolution process. For the last 40 years this process, known as `cleaning', has been performed almost exclusively on all Stokes parameters individually as if they were independent scalar images. However, here we demonstrate for the case of the linear polarization P, this approach fails to properly account for the complex vector nature resulting in a process which is dependent on the axes under which the deconvolution is performed. We present here an improved method, `Generalized Complex CLEAN', which properly accounts for the complex vector nature of polarized emission and is invariant under rotations of the deconvolution axes. We use two Australia Telescope Compact Array data sets to test standard and complex CLEAN versions of the Högbom and SDI (Steer-Dwedney-Ito) CLEAN algorithms. We show that in general the complex CLEAN version of each algorithm produces more accurate clean components with fewer spurious detections and lower computation cost due to reduced iterations than the current methods. In particular, we find that the complex SDI CLEAN produces the best results for diffuse polarized sources as compared with standard CLEAN algorithms and other complex CLEAN algorithms. Given the move to wide-field, high-resolution polarimetric imaging with future telescopes such as the Square Kilometre Array, we suggest that Generalized Complex CLEAN should be adopted as the deconvolution method for all future polarimetric surveys and in particular that the complex version of an SDI CLEAN should be used.

A Robust Gold Deconvolution Approach for LiDAR Waveform Data Processing to Characterize Vegetation Structure

NASA Astrophysics Data System (ADS)

Zhou, T.; Popescu, S. C.; Krause, K.; Sheridan, R.; Ku, N. W.

2014-12-01

Increasing attention has been paid in the remote sensing community to the next generation Light Detection and Ranging (lidar) waveform data systems for extracting information on topography and the vertical structure of vegetation. However, processing waveform lidar data raises some challenges compared to analyzing discrete return data. The overall goal of this study was to present a robust de-convolution algorithm- Gold algorithm used to de-convolve waveforms in a lidar dataset acquired within a 60 x 60m study area located in the Harvard Forest in Massachusetts. The waveform lidar data was collected by the National Ecological Observatory Network (NEON). Specific objectives were to: (1) explore advantages and limitations of various waveform processing techniques to derive topography and canopy height information; (2) develop and implement a novel de-convolution algorithm, the Gold algorithm, to extract elevation and canopy metrics; and (3) compare results and assess accuracy. We modeled lidar waveforms with a mixture of Gaussian functions using the Non-least squares (NLS) algorithm implemented in R and derived a Digital Terrain Model (DTM) and canopy height. We compared our waveform-derived topography and canopy height measurements using the Gold de-convolution algorithm to results using the Richardson-Lucy algorithm. Our findings show that the Gold algorithm performed better than the Richardson-Lucy algorithm in terms of recovering the hidden echoes and detecting false echoes for generating a DTM, which indicates that the Gold algorithm could potentially be applied to processing of waveform lidar data to derive information on terrain elevation and canopy characteristics.

Water Residence Time estimation by 1D deconvolution in the form of a l2 -regularized inverse problem with smoothness, positivity and causality constraints

NASA Astrophysics Data System (ADS)

Meresescu, Alina G.; Kowalski, Matthieu; Schmidt, Frédéric; Landais, François

2018-06-01

The Water Residence Time distribution is the equivalent of the impulse response of a linear system allowing the propagation of water through a medium, e.g. the propagation of rain water from the top of the mountain towards the aquifers. We consider the output aquifer levels as the convolution between the input rain levels and the Water Residence Time, starting with an initial aquifer base level. The estimation of Water Residence Time is important for a better understanding of hydro-bio-geochemical processes and mixing properties of wetlands used as filters in ecological applications, as well as protecting fresh water sources for wells from pollutants. Common methods of estimating the Water Residence Time focus on cross-correlation, parameter fitting and non-parametric deconvolution methods. Here we propose a 1D full-deconvolution, regularized, non-parametric inverse problem algorithm that enforces smoothness and uses constraints of causality and positivity to estimate the Water Residence Time curve. Compared to Bayesian non-parametric deconvolution approaches, it has a fast runtime per test case; compared to the popular and fast cross-correlation method, it produces a more precise Water Residence Time curve even in the case of noisy measurements. The algorithm needs only one regularization parameter to balance between smoothness of the Water Residence Time and accuracy of the reconstruction. We propose an approach on how to automatically find a suitable value of the regularization parameter from the input data only. Tests on real data illustrate the potential of this method to analyze hydrological datasets.

Pulse-Inversion Subharmonic Ultrafast Active Cavitation Imaging in Tissue Using Fast Eigenspace-Based Adaptive Beamforming and Cavitation Deconvolution.

PubMed

Bai, Chen; Xu, Shanshan; Duan, Junbo; Jing, Bowen; Yang, Miao; Wan, Mingxi

2017-08-01

Pulse-inversion subharmonic (PISH) imaging can display information relating to pure cavitation bubbles while excluding that of tissue. Although plane-wave-based ultrafast active cavitation imaging (UACI) can monitor the transient activities of cavitation bubbles, its resolution and cavitation-to-tissue ratio (CTR) are barely satisfactory but can be significantly improved by introducing eigenspace-based (ESB) adaptive beamforming. PISH and UACI are a natural combination for imaging of pure cavitation activity in tissue; however, it raises two problems: 1) the ESB beamforming is hard to implement in real time due to the enormous amount of computation associated with the covariance matrix inversion and eigendecomposition and 2) the narrowband characteristic of the subharmonic filter will incur a drastic degradation in resolution. Thus, in order to jointly address these two problems, we propose a new PISH-UACI method using novel fast ESB (F-ESB) beamforming and cavitation deconvolution for nonlinear signals. This method greatly reduces the computational complexity by using F-ESB beamforming through dimensionality reduction based on principal component analysis, while maintaining the high quality of ESB beamforming. The degraded resolution is recovered using cavitation deconvolution through a modified convolution model and compressive deconvolution. Both simulations and in vitro experiments were performed to verify the effectiveness of the proposed method. Compared with the ESB-based PISH-UACI, the entire computation of our proposed approach was reduced by 99%, while the axial resolution gain and CTR were increased by 3 times and 2 dB, respectively, confirming that satisfactory performance can be obtained for monitoring pure cavitation bubbles in tissue erosion.

Wavespace-Based Coherent Deconvolution

NASA Technical Reports Server (NTRS)

Bahr, Christopher J.; Cattafesta, Louis N., III

2012-01-01

Array deconvolution is commonly used in aeroacoustic analysis to remove the influence of a microphone array's point spread function from a conventional beamforming map. Unfortunately, the majority of deconvolution algorithms assume that the acoustic sources in a measurement are incoherent, which can be problematic for some aeroacoustic phenomena with coherent, spatially-distributed characteristics. While several algorithms have been proposed to handle coherent sources, some are computationally intractable for many problems while others require restrictive assumptions about the source field. Newer generalized inverse techniques hold promise, but are still under investigation for general use. An alternate coherent deconvolution method is proposed based on a wavespace transformation of the array data. Wavespace analysis offers advantages over curved-wave array processing, such as providing an explicit shift-invariance in the convolution of the array sampling function with the acoustic wave field. However, usage of the wavespace transformation assumes the acoustic wave field is accurately approximated as a superposition of plane wave fields, regardless of true wavefront curvature. The wavespace technique leverages Fourier transforms to quickly evaluate a shift-invariant convolution. The method is derived for and applied to ideal incoherent and coherent plane wave fields to demonstrate its ability to determine magnitude and relative phase of multiple coherent sources. Multi-scale processing is explored as a means of accelerating solution convergence. A case with a spherical wave front is evaluated. Finally, a trailing edge noise experiment case is considered. Results show the method successfully deconvolves incoherent, partially-coherent, and coherent plane wave fields to a degree necessary for quantitative evaluation. Curved wave front cases warrant further investigation. A potential extension to nearfield beamforming is proposed.

Sparse Solution of Fiber Orientation Distribution Function by Diffusion Decomposition

PubMed Central

Yeh, Fang-Cheng; Tseng, Wen-Yih Isaac

2013-01-01

Fiber orientation is the key information in diffusion tractography. Several deconvolution methods have been proposed to obtain fiber orientations by estimating a fiber orientation distribution function (ODF). However, the L 2 regularization used in deconvolution often leads to false fibers that compromise the specificity of the results. To address this problem, we propose a method called diffusion decomposition, which obtains a sparse solution of fiber ODF by decomposing the diffusion ODF obtained from q-ball imaging (QBI), diffusion spectrum imaging (DSI), or generalized q-sampling imaging (GQI). A simulation study, a phantom study, and an in-vivo study were conducted to examine the performance of diffusion decomposition. The simulation study showed that diffusion decomposition was more accurate than both constrained spherical deconvolution and ball-and-sticks model. The phantom study showed that the angular error of diffusion decomposition was significantly lower than those of constrained spherical deconvolution at 30° crossing and ball-and-sticks model at 60° crossing. The in-vivo study showed that diffusion decomposition can be applied to QBI, DSI, or GQI, and the resolved fiber orientations were consistent regardless of the diffusion sampling schemes and diffusion reconstruction methods. The performance of diffusion decomposition was further demonstrated by resolving crossing fibers on a 30-direction QBI dataset and a 40-direction DSI dataset. In conclusion, diffusion decomposition can improve angular resolution and resolve crossing fibers in datasets with low SNR and substantially reduced number of diffusion encoding directions. These advantages may be valuable for human connectome studies and clinical research. PMID:24146772

Multiwavelet packet entropy and its application in transmission line fault recognition and classification.

PubMed

Liu, Zhigang; Han, Zhiwei; Zhang, Yang; Zhang, Qiaoge

2014-11-01

Multiwavelets possess better properties than traditional wavelets. Multiwavelet packet transformation has more high-frequency information. Spectral entropy can be applied as an analysis index to the complexity or uncertainty of a signal. This paper tries to define four multiwavelet packet entropies to extract the features of different transmission line faults, and uses a radial basis function (RBF) neural network to recognize and classify 10 fault types of power transmission lines. First, the preprocessing and postprocessing problems of multiwavelets are presented. Shannon entropy and Tsallis entropy are introduced, and their difference is discussed. Second, multiwavelet packet energy entropy, time entropy, Shannon singular entropy, and Tsallis singular entropy are defined as the feature extraction methods of transmission line fault signals. Third, the plan of transmission line fault recognition using multiwavelet packet entropies and an RBF neural network is proposed. Finally, the experimental results show that the plan with the four multiwavelet packet energy entropies defined in this paper achieves better performance in fault recognition. The performance with SA4 (symmetric antisymmetric) multiwavelet packet Tsallis singular entropy is the best among the combinations of different multiwavelet packets and the four multiwavelet packet entropies.

Uniqueness and characterization theorems for generalized entropies

NASA Astrophysics Data System (ADS)

Enciso, Alberto; Tempesta, Piergiulio

2017-12-01

The requirement that an entropy function be composable is key: it means that the entropy of a compound system can be calculated in terms of the entropy of its independent components. We prove that, under mild regularity assumptions, the only composable generalized entropy in trace form is the Tsallis one-parameter family (which contains Boltzmann-Gibbs as a particular case). This result leads to the use of generalized entropies that are not of trace form, such as Rényi’s entropy, in the study of complex systems. In this direction, we also present a characterization theorem for a large class of composable non-trace-form entropy functions with features akin to those of Rényi’s entropy.

Experimental heat capacities, excess entropies, and magnetic properties of bulk and nano Fe3O4-Co3O4 and Fe3O4-Mn3O4 spinel solid solutions

NASA Astrophysics Data System (ADS)

Schliesser, Jacob M.; Huang, Baiyu; Sahu, Sulata K.; Asplund, Megan; Navrotsky, Alexandra; Woodfield, Brian F.

2018-03-01

We have measured the heat capacities of several well-characterized bulk and nanophase Fe3O4-Co3O4 and Fe3O4-Mn3O4 spinel solid solution samples from which magnetic properties of transitions and third-law entropies have been determined. The magnetic transitions show several features common to effects of particle and magnetic domain sizes. From the standard molar entropies, excess entropies of mixing have been generated for these solid solutions and compared with configurational entropies determined previously by assuming appropriate cation and valence distributions. The vibrational and magnetic excess entropies for bulk materials are comparable in magnitude to the respective configurational entropies indicating that excess entropies of mixing must be included when analyzing entropies of mixing. The excess entropies for nanophase materials are even larger than the configurational entropies. Changes in valence, cation distribution, bonding and microstructure between the mixing ions are the likely sources of the positive excess entropies of mixing.

Extracting the building response using seismic interferometry: Theory and application to the Millikan Library in Pasadena, California

USGS Publications Warehouse

Snieder, R.; Safak, E.

2006-01-01

The motion of a building depends on the excitation, the coupling of the building to the ground, and the mechanical properties of the building. We separate the building response from the excitation and the ground coupling by deconvolving the motion recorded at different levels in the building and apply this to recordings of the motion in the Robert A. Millikan Library in Pasadena, California. This deconvolution allows for the separation of instrinsic attenuation and radiation damping. The waveforms obtained from deconvolution with the motion in the top floor show a superposition of one upgoing and one downgoing wave. The waveforms obtained by deconvolution with the motion in the basement can be formulated either as a sum of upgoing and downgoing waves, or as a sum over normal modes. Because these deconvolved waves for late time have a monochromatic character, they are most easily analyzed with normal-mode theory. For this building we estimate a shear velocity c = 322 m/sec and a quality factor Q = 20. These values explain both the propagating waves and the normal modes.

Real-time blind deconvolution of retinal images in adaptive optics scanning laser ophthalmoscopy

NASA Astrophysics Data System (ADS)

Li, Hao; Lu, Jing; Shi, Guohua; Zhang, Yudong

2011-06-01

With the use of adaptive optics (AO), the ocular aberrations can be compensated to get high-resolution image of living human retina. However, the wavefront correction is not perfect due to the wavefront measure error and hardware restrictions. Thus, it is necessary to use a deconvolution algorithm to recover the retinal images. In this paper, a blind deconvolution technique called Incremental Wiener filter is used to restore the adaptive optics confocal scanning laser ophthalmoscope (AOSLO) images. The point-spread function (PSF) measured by wavefront sensor is only used as an initial value of our algorithm. We also realize the Incremental Wiener filter on graphics processing unit (GPU) in real-time. When the image size is 512 × 480 pixels, six iterations of our algorithm only spend about 10 ms. Retinal blood vessels as well as cells in retinal images are restored by our algorithm, and the PSFs are also revised. Retinal images with and without adaptive optics are both restored. The results show that Incremental Wiener filter reduces the noises and improve the image quality.

Supersampling multiframe blind deconvolution resolution enhancement of adaptive-optics-compensated imagery of LEO satellites

NASA Astrophysics Data System (ADS)

Gerwe, David R.; Lee, David J.; Barchers, Jeffrey D.

2000-10-01

A post-processing methodology for reconstructing undersampled image sequences with randomly varying blur is described which can provide image enhancement beyond the sampling resolution of the sensor. This method is demonstrated on simulated imagery and on adaptive optics compensated imagery taken by the Starfire Optical Range 3.5 meter telescope that has been artificially undersampled. Also shown are the results of multiframe blind deconvolution of some of the highest quality optical imagery of low earth orbit satellites collected with a ground based telescope to date. The algorithm used is a generalization of multiframe blind deconvolution techniques which includes a representation of spatial sampling by the focal plane array elements in the forward stochastic model of the imaging system. This generalization enables the random shifts and shape of the adaptive compensated PSF to be used to partially eliminate the aliasing effects associated with sub- Nyquist sampling of the image by the focal plane array. The method could be used to reduce resolution loss which occurs when imaging in wide FOV modes.

Supersampling multiframe blind deconvolution resolution enhancement of adaptive optics compensated imagery of low earth orbit satellites

NASA Astrophysics Data System (ADS)

Gerwe, David R.; Lee, David J.; Barchers, Jeffrey D.

2002-09-01

We describe a postprocessing methodology for reconstructing undersampled image sequences with randomly varying blur that can provide image enhancement beyond the sampling resolution of the sensor. This method is demonstrated on simulated imagery and on adaptive-optics-(AO)-compensated imagery taken by the Starfire Optical Range 3.5-m telescope that has been artificially undersampled. Also shown are the results of multiframe blind deconvolution of some of the highest quality optical imagery of low earth orbit satellites collected with a ground-based telescope to date. The algorithm used is a generalization of multiframe blind deconvolution techniques that include a representation of spatial sampling by the focal plane array elements based on a forward stochastic model. This generalization enables the random shifts and shape of the AO- compensated point spread function (PSF) to be used to partially eliminate the aliasing effects associated with sub-Nyquist sampling of the image by the focal plane array. The method could be used to reduce resolution loss that occurs when imaging in wide- field-of-view (FOV) modes.

Pulse analysis of acoustic emission signals

NASA Technical Reports Server (NTRS)

Houghton, J. R.; Packman, P. F.

1977-01-01

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio were examined in the frequency domain analysis and pulse shape deconvolution was developed for use in the time domain analysis. Comparisons of the relative performance of each analysis technique are made for the characterization of acoustic emission pulses recorded by a measuring system. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameter values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emission associated with (a) crack propagation, (b) ball dropping on a plate, (c) spark discharge, and (d) defective and good ball bearings. Deconvolution of the first few micro-seconds of the pulse train is shown to be the region in which the significant signatures of the acoustic emission event are to be found.

Scanning two-photon microscopy with upconverting lanthanide nanoparticles via Richardson-Lucy deconvolution.

PubMed

Gainer, Christian F; Utzinger, Urs; Romanowski, Marek

2012-07-01

The use of upconverting lanthanide nanoparticles in fast-scanning microscopy is hindered by a long luminescence decay time, which greatly blurs images acquired in a nondescanned mode. We demonstrate herein an image processing method based on Richardson-Lucy deconvolution that mitigates the detrimental effects of their luminescence lifetime. This technique generates images with lateral resolution on par with the system's performance, ∼1.2  μm, while maintaining an axial resolution of 5 μm or better at a scan rate comparable with traditional two-photon microscopy. Remarkably, this can be accomplished with near infrared excitation power densities of 850 W/cm(2), several orders of magnitude below those used in two-photon imaging with molecular fluorophores. By way of illustration, we introduce the use of lipids to coat and functionalize these nanoparticles, rendering them water dispersible and readily conjugated to biologically relevant ligands, in this case epidermal growth factor receptor antibody. This deconvolution technique combined with the functionalized nanoparticles will enable three-dimensional functional tissue imaging at exceptionally low excitation power densities.

Spatial studies of planetary nebulae with IRAS

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

Hawkins, G.W.; Zuckerman, B.

1991-06-01

The infrared sizes at the four IRAS wavelengths of 57 planetaries, most with 20-60 arcsec optical size, are derived from spatial deconvolution of one-dimensional survey mode scans. Survey observations from multiple detectors and hours confirmed (HCON) observations are combined to increase the sampling to a rate that is sufficient for successful deconvolution. The Richardson-Lucy deconvolution algorithm is used to obtain an increase in resolution of a factor of about 2 or 3 from the normal IRAS detector sizes of 45, 45, 90, and 180 arcsec at wavelengths 12, 25, 60, and 100 microns. Most of the planetaries deconvolve at 12more » and 25 microns to sizes equal to or smaller than the optical size. Some of the planetaries with optical rings 60 arcsec or more in diameter show double-peaked IRAS profiles. Many, such as NGC 6720 and NGC 6543 show all infrared sizes equal to the optical size, while others indicate increasing infrared size with wavelength. Deconvolved IRAS profiles are presented for the 57 planetaries at nearly all wavelengths where IRAS flux densities are 1-2 Jy or higher. 60 refs.« less

A spatially-variant deconvolution method based on total variation for optical coherence tomography images

NASA Astrophysics Data System (ADS)

Almasganj, Mohammad; Adabi, Saba; Fatemizadeh, Emad; Xu, Qiuyun; Sadeghi, Hamid; Daveluy, Steven; Nasiriavanaki, Mohammadreza

2017-03-01

Optical Coherence Tomography (OCT) has a great potential to elicit clinically useful information from tissues due to its high axial and transversal resolution. In practice, an OCT setup cannot reach to its theoretical resolution due to imperfections of its components, which make its images blurry. The blurriness is different alongside regions of image; thus, they cannot be modeled by a unique point spread function (PSF). In this paper, we investigate the use of solid phantoms to estimate the PSF of each sub-region of imaging system. We then utilize Lucy-Richardson, Hybr and total variation (TV) based iterative deconvolution methods for mitigating occurred spatially variant blurriness. It is shown that the TV based method will suppress the so-called speckle noise in OCT images better than the two other approaches. The performance of proposed algorithm is tested on various samples, including several skin tissues besides the test image blurred with synthetic PSF-map, demonstrating qualitatively and quantitatively the advantage of TV based deconvolution method using spatially-variant PSF for enhancing image quality.

A stopping criterion to halt iterations at the Richardson-Lucy deconvolution of radiographic images

NASA Astrophysics Data System (ADS)

Almeida, G. L.; Silvani, M. I.; Souza, E. S.; Lopes, R. T.

2015-07-01

Radiographic images, as any experimentally acquired ones, are affected by spoiling agents which degrade their final quality. The degradation caused by agents of systematic character, can be reduced by some kind of treatment such as an iterative deconvolution. This approach requires two parameters, namely the system resolution and the best number of iterations in order to achieve the best final image. This work proposes a novel procedure to estimate the best number of iterations, which replaces the cumbersome visual inspection by a comparison of numbers. These numbers are deduced from the image histograms, taking into account the global difference G between them for two subsequent iterations. The developed algorithm, including a Richardson-Lucy deconvolution procedure has been embodied into a Fortran program capable to plot the 1st derivative of G as the processing progresses and to stop it automatically when this derivative - within the data dispersion - reaches zero. The radiograph of a specially chosen object acquired with thermal neutrons from the Argonauta research reactor at Institutode Engenharia Nuclear - CNEN, Rio de Janeiro, Brazil, have undergone this treatment with fair results.

[Deconvolution of overlapped peaks in total ion chromatogram of essential oil from citri reticulatae pericarpium viride by automated mass spectral deconvolution & identification system].

PubMed

Wang, Jian; Chen, Hong-Ping; Liu, You-Ping; Wei, Zheng; Liu, Rong; Fan, Dan-Qing

2013-05-01

This experiment shows how to use the automated mass spectral deconvolution & identification system (AMDIS) to deconvolve the overlapped peaks in the total ion chromatogram (TIC) of volatile oil from Chineses materia medica (CMM). The essential oil was obtained by steam distillation. Its TIC was gotten by GC-MS, and the superimposed peaks in TIC were deconvolved by AMDIS. First, AMDIS can detect the number of components in TIC through the run function. Then, by analyzing the extracted spectrum of corresponding scan point of detected component and the original spectrum of this scan point, and their counterparts' spectra in the referred MS Library, researchers can ascertain the component's structure accurately or deny some compounds, which don't exist in nature. Furthermore, through examining the changeability of characteristic fragment ion peaks of identified compounds, the previous outcome can be affirmed again. The result demonstrated that AMDIS could efficiently deconvolve the overlapped peaks in TIC by taking out the spectrum of matching scan point of discerned component, which led to exact identification of the component's structure.

Thorium concentrations in the lunar surface. V - Deconvolution of the central highlands region

NASA Technical Reports Server (NTRS)

Metzger, A. E.; Etchegaray-Ramirez, M. I.; Haines, E. L.

1982-01-01

The distribution of thorium in the lunar central highlands measured from orbit by the Apollo 16 gamma-ray spectrometer is subjected to a deconvolution analysis to yield improved spatial resolution and contrast. Use of two overlapping data fields for complete coverage also provides a demonstration of the technique's ability to model concentrations several degrees beyond the data track. Deconvolution reveals an association between Th concentration and the Kant Plateau, Descartes Mountain and Cayley plains surface formations. The Kant Plateau and Descartes Mountains model with Th less than 1 part per million, which is typical of farside highlands but is infrequently seen over any other nearside highland portions of the Apollo 15 and 16 ground tracks. It is noted that, if the Cayley plains are the result of basin-forming impact ejecta, the distribution of Th concentration with longitude supports an origin from the Imbrium basin rather than the Nectaris or Orientale basins. Nectaris basin materials are found to have a Th concentration similar to that of the Descartes Mountains, evidence that the latter may have been emplaced as Nectaris basin impact deposits.

An Optimal Deconvolution Method for Reconstructing Pneumatically Distorted Near-Field Sonic Boom Pressure Measurements

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Haering, Edward A., Jr.; Ehernberger, L. J.

1996-01-01

In-flight measurements of the SR-71 near-field sonic boom were obtained by an F-16XL airplane at flightpath separation distances from 40 to 740 ft. Twenty-two signatures were obtained from Mach 1.60 to Mach 1.84 and altitudes from 47,600 to 49,150 ft. The shock wave signatures were measured by the total and static sensors on the F-16XL noseboo. These near-field signature measurements were distorted by pneumatic attenuation in the pitot-static sensors and accounting for their effects using optimal deconvolution. Measurement system magnitude and phase characteristics were determined from ground-based step-response tests and extrapolated to flight conditions using analytical models. Deconvolution was implemented using Fourier transform methods. Comparisons of the shock wave signatures reconstructed from the total and static pressure data are presented. The good agreement achieved gives confidence of the quality of the reconstruction analysis. although originally developed to reconstruct the sonic boom signatures from SR-71 sonic boom flight tests, the methods presented here generally apply to other types of highly attenuated or distorted pneumatic measurements.

Two-dimensional imaging of two types of radicals by the CW-EPR method

NASA Astrophysics Data System (ADS)

Czechowski, Tomasz; Krzyminiewski, Ryszard; Jurga, Jan; Chlewicki, Wojciech

2008-01-01

The CW-EPR method of image reconstruction is based on sample rotation in a magnetic field with a constant gradient (50 G/cm). In order to obtain a projection (radical density distribution) along a given direction, the EPR spectra are recorded with and without the gradient. Deconvolution, then gives the distribution of the spin density. Projection at 36 different angles gives the information that is necessary for reconstruction of the radical distribution. The problem becomes more complex when there are at least two types of radicals in the sample, because the deconvolution procedure does not give satisfactory results. We propose a method to calculate the projections for each radical, based on iterative procedures. The images of density distribution for each radical obtained by our procedure have proved that the method of deconvolution, in combination with iterative fitting, provides correct results. The test was performed on a sample of polymer PPS Br 111 ( p-phenylene sulphide) with glass fibres and minerals. The results indicated a heterogeneous distribution of radicals in the sample volume. The images obtained were in agreement with the known shape of the sample.

Variation of High-Intensity Therapeutic Ultrasound (HITU) Pressure Field Characterization: Effects of Hydrophone Choice, Nonlinearity, Spatial Averaging and Complex Deconvolution.

PubMed

Liu, Yunbo; Wear, Keith A; Harris, Gerald R

2017-10-01

Reliable acoustic characterization is fundamental for patient safety and clinical efficacy during high-intensity therapeutic ultrasound (HITU) treatment. Technical challenges, such as measurement variation and signal analysis, still exist for HITU exposimetry using ultrasound hydrophones. In this work, four hydrophones were compared for pressure measurement: a robust needle hydrophone, a small polyvinylidene fluoride capsule hydrophone and two fiberoptic hydrophones. The focal waveform and beam distribution of a single-element HITU transducer (1.05 MHz and 3.3 MHz) were evaluated. Complex deconvolution between the hydrophone voltage signal and frequency-dependent complex sensitivity was performed to obtain pressure waveforms. Compressional pressure (p + ), rarefactional pressure (p - ) and focal beam distribution were compared up to 10.6/-6.0 MPa (p + /p - ) (1.05 MHz) and 20.65/-7.20 MPa (3.3 MHz). The effects of spatial averaging, local non-linear distortion, complex deconvolution and hydrophone damage thresholds were investigated. This study showed a variation of no better than 10%-15% among hydrophones during HITU pressure characterization. Published by Elsevier Inc.

Pulse analysis of acoustic emission signals

NASA Technical Reports Server (NTRS)

Houghton, J. R.; Packman, P. F.

1977-01-01

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio were examined in the frequency domain analysis, and pulse shape deconvolution was developed for use in the time domain analysis. Comparisons of the relative performance of each analysis technique are made for the characterization of acoustic emission pulses recorded by a measuring system. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameters values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emissions associated with: (1) crack propagation, (2) ball dropping on a plate, (3) spark discharge and (4) defective and good ball bearings. Deconvolution of the first few micro-seconds of the pulse train are shown to be the region in which the significant signatures of the acoustic emission event are to be found.

Stability of Tsallis entropy and instabilities of Rényi and normalized Tsallis entropies: a basis for q-exponential distributions.

PubMed

Abe, Sumiyoshi

2002-10-01

The q-exponential distributions, which are generalizations of the Zipf-Mandelbrot power-law distribution, are frequently encountered in complex systems at their stationary states. From the viewpoint of the principle of maximum entropy, they can apparently be derived from three different generalized entropies: the Rényi entropy, the Tsallis entropy, and the normalized Tsallis entropy. Accordingly, mere fittings of observed data by the q-exponential distributions do not lead to identification of the correct physical entropy. Here, stabilities of these entropies, i.e., their behaviors under arbitrary small deformation of a distribution, are examined. It is shown that, among the three, the Tsallis entropy is stable and can provide an entropic basis for the q-exponential distributions, whereas the others are unstable and cannot represent any experimentally observable quantities.

On the entropy variation in the scenario of entropic gravity

NASA Astrophysics Data System (ADS)

Xiao, Yong; Bai, Shi-Yang

2018-05-01

In the scenario of entropic gravity, entropy varies as a function of the location of the matter, while the tendency to increase entropy appears as gravity. We concentrate on studying the entropy variation of a typical gravitational system with different relative positions between the mass and the gravitational source. The result is that the entropy of the system doesn't increase when the mass is displaced closer to the gravitational source. In this way it disproves the proposal of entropic gravity from thermodynamic entropy. It doesn't exclude the possibility that gravity originates from non-thermodynamic entropy like entanglement entropy.

Entropy and climate. I - ERBE observations of the entropy production of the earth

NASA Technical Reports Server (NTRS)

Stephens, G. L.; O'Brien, D. M.

1993-01-01

An approximate method for estimating the global distributions of the entropy fluxes flowing through the upper boundary of the climate system is introduced, and an estimate of the entropy exchange between the earth and space and the entropy production of the planet is provided. Entropy fluxes calculated from the Earth Radiation Budget Experiment measurements show how the long-wave entropy flux densities dominate the total entropy fluxes at all latitudes compared with the entropy flux densities associated with reflected sunlight, although the short-wave flux densities are important in the context of clear sky-cloudy sky net entropy flux differences. It is suggested that the entropy production of the planet is both constant for the 36 months of data considered and very near its maximum possible value. The mean value of this production is 0.68 x 10 exp 15 W/K, and the amplitude of the annual cycle is approximately 1 to 2 percent of this value.

Logarithmic black hole entropy corrections and holographic Rényi entropy

NASA Astrophysics Data System (ADS)

Mahapatra, Subhash

2018-01-01

The entanglement and Rényi entropies for spherical entangling surfaces in CFTs with gravity duals can be explicitly calculated by mapping these entropies first to the thermal entropy on hyperbolic space and then, using the AdS/CFT correspondence, to the Wald entropy of topological black holes. Here we extend this idea by taking into account corrections to the Wald entropy. Using the method based on horizon symmetries and the asymptotic Cardy formula, we calculate corrections to the Wald entropy and find that these corrections are proportional to the logarithm of the area of the horizon. With the corrected expression for the entropy of the black hole, we then find corrections to the Rényi entropies. We calculate these corrections for both Einstein and Gauss-Bonnet gravity duals. Corrections with logarithmic dependence on the area of the entangling surface naturally occur at the order GD^0. The entropic c-function and the inequalities of the Rényi entropy are also satisfied even with the correction terms.

The Dynameomics Entropy Dictionary: A Large-Scale Assessment of Conformational Entropy across Protein Fold Space.

PubMed

Towse, Clare-Louise; Akke, Mikael; Daggett, Valerie

2017-04-27

Molecular dynamics (MD) simulations contain considerable information with regard to the motions and fluctuations of a protein, the magnitude of which can be used to estimate conformational entropy. Here we survey conformational entropy across protein fold space using the Dynameomics database, which represents the largest existing data set of protein MD simulations for representatives of essentially all known protein folds. We provide an overview of MD-derived entropies accounting for all possible degrees of dihedral freedom on an unprecedented scale. Although different side chains might be expected to impose varying restrictions on the conformational space that the backbone can sample, we found that the backbone entropy and side chain size are not strictly coupled. An outcome of these analyses is the Dynameomics Entropy Dictionary, the contents of which have been compared with entropies derived by other theoretical approaches and experiment. As might be expected, the conformational entropies scale linearly with the number of residues, demonstrating that conformational entropy is an extensive property of proteins. The calculated conformational entropies of folding agree well with previous estimates. Detailed analysis of specific cases identifies deviations in conformational entropy from the average values that highlight how conformational entropy varies with sequence, secondary structure, and tertiary fold. Notably, α-helices have lower entropy on average than do β-sheets, and both are lower than coil regions.

Double symbolic joint entropy in nonlinear dynamic complexity analysis

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-07-01

Symbolizations, the base of symbolic dynamic analysis, are classified as global static and local dynamic approaches which are combined by joint entropy in our works for nonlinear dynamic complexity analysis. Two global static methods, symbolic transformations of Wessel N. symbolic entropy and base-scale entropy, and two local ones, namely symbolizations of permutation and differential entropy, constitute four double symbolic joint entropies that have accurate complexity detections in chaotic models, logistic and Henon map series. In nonlinear dynamical analysis of different kinds of heart rate variability, heartbeats of healthy young have higher complexity than those of the healthy elderly, and congestive heart failure (CHF) patients are lowest in heartbeats' joint entropy values. Each individual symbolic entropy is improved by double symbolic joint entropy among which the combination of base-scale and differential symbolizations have best complexity analysis. Test results prove that double symbolic joint entropy is feasible in nonlinear dynamic complexity analysis.

Effect of entropy on anomalous transport in ITG-modes of magneto-plasma

NASA Astrophysics Data System (ADS)

Yaqub Khan, M.; Qaiser Manzoor, M.; Haq, A. ul; Iqbal, J.

2017-04-01

The ideal gas equation and S={{c}v}log ≤ft(P/ρ \\right) (where S is entropy, P is pressure and ρ is the mass density) define the interconnection of entropy with the temperature and density of plasma. Therefore, different phenomena relating to plasma and entropy need to be investigated. By employing the Braginskii transport equations for a nonuniform electron-ion magnetoplasma, two new parameters—the entropy distribution function and the entropy gradient drift—are defined, a new dispersion relation is obtained, and the dependence of anomalous transport on entropy is also proved. Some results, like monotonicity, the entropy principle and the second law of thermodynamics, are proved with a new definition of entropy. This work will open new horizons in fusion processes, not only by controlling entropy in tokamak plasmas—particularly in the pedestal regions of the H-mode and space plasmas—but also in engineering sciences.

Quantifying and minimizing entropy generation in AMTEC cells

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

Hendricks, T.J.; Huang, C.

1997-12-31

Entropy generation in an AMTEC cell represents inherent power loss to the AMTEC cell. Minimizing cell entropy generation directly maximizes cell power generation and efficiency. An internal project is on-going at AMPS to identify, quantify and minimize entropy generation mechanisms within an AMTEC cell, with the goal of determining cost-effective design approaches for maximizing AMTEC cell power generation. Various entropy generation mechanisms have been identified and quantified. The project has investigated several cell design techniques in a solar-driven AMTEC system to minimize cell entropy generation and produce maximum power cell designs. In many cases, various sources of entropy generation aremore » interrelated such that minimizing entropy generation requires cell and system design optimization. Some of the tradeoffs between various entropy generation mechanisms are quantified and explained and their implications on cell design are discussed. The relationship between AMTEC cell power and efficiency and entropy generation is presented and discussed.« less

Blind image deconvolution using the Fields of Experts prior

NASA Astrophysics Data System (ADS)

Dong, Wende; Feng, Huajun; Xu, Zhihai; Li, Qi

2012-11-01

In this paper, we present a method for single image blind deconvolution. To improve its ill-posedness, we formulate the problem under Bayesian probabilistic framework and use a prior named Fields of Experts (FoE) which is learnt from natural images to regularize the latent image. Furthermore, due to the sparse distribution of the point spread function (PSF), we adopt a Student-t prior to regularize it. An improved alternating minimization (AM) approach is proposed to solve the resulted optimization problem. Experiments on both synthetic and real world blurred images show that the proposed method can achieve results of high quality.

Application of the Lucy–Richardson Deconvolution Procedure to High Resolution Photoemission Spectra

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

Rameau, J.; Yang, H.-B.; Johnson, P.D.

2010-07-01

Angle-resolved photoemission has developed into one of the leading probes of the electronic structure and associated dynamics of condensed matter systems. As with any experimental technique the ability to resolve features in the spectra is ultimately limited by the resolution of the instrumentation used in the measurement. Previously developed for sharpening astronomical images, the Lucy-Richardson deconvolution technique proves to be a useful tool for improving the photoemission spectra obtained in modern hemispherical electron spectrometers where the photoelectron spectrum is displayed as a 2D image in energy and momentum space.

Comment on ‘A novel method for fast and robust estimation of fluorescence decay dynamics using constrained least-square deconvolution with Laguerre expansion’

NASA Astrophysics Data System (ADS)

Zhang, Yongliang; Day-Uei Li, David

2017-02-01

This comment is to clarify that Poisson noise instead of Gaussian noise shall be included to assess the performances of least-squares deconvolution with Laguerre expansion (LSD-LE) for analysing fluorescence lifetime imaging data obtained from time-resolved systems. Moreover, we also corrected an equation in the paper. As the LSD-LE method is rapid and has the potential to be widely applied not only for diagnostic but for wider bioimaging applications, it is desirable to have precise noise models and equations.

Thermodynamic and Differential Entropy under a Change of Variables

PubMed Central

Hnizdo, Vladimir; Gilson, Michael K.

2013-01-01

The differential Shannon entropy of information theory can change under a change of variables (coordinates), but the thermodynamic entropy of a physical system must be invariant under such a change. This difference is puzzling, because the Shannon and Gibbs entropies have the same functional form. We show that a canonical change of variables can, indeed, alter the spatial component of the thermodynamic entropy just as it alters the differential Shannon entropy. However, there is also a momentum part of the entropy, which turns out to undergo an equal and opposite change when the coordinates are transformed, so that the total thermodynamic entropy remains invariant. We furthermore show how one may correctly write the change in total entropy for an isothermal physical process in any set of spatial coordinates. PMID:24436633

Entropy for Mechanically Vibrating Systems

NASA Astrophysics Data System (ADS)

Tufano, Dante

The research contained within this thesis deals with the subject of entropy as defined for and applied to mechanically vibrating systems. This work begins with an overview of entropy as it is understood in the fields of classical thermodynamics, information theory, statistical mechanics, and statistical vibroacoustics. Khinchin's definition of entropy, which is the primary definition used for the work contained in this thesis, is introduced in the context of vibroacoustic systems. The main goal of this research is to to establish a mathematical framework for the application of Khinchin's entropy in the field of statistical vibroacoustics by examining the entropy context of mechanically vibrating systems. The introduction of this thesis provides an overview of statistical energy analysis (SEA), a modeling approach to vibroacoustics that motivates this work on entropy. The objective of this thesis is given, and followed by a discussion of the intellectual merit of this work as well as a literature review of relevant material. Following the introduction, an entropy analysis of systems of coupled oscillators is performed utilizing Khinchin's definition of entropy. This analysis develops upon the mathematical theory relating to mixing entropy, which is generated by the coupling of vibroacoustic systems. The mixing entropy is shown to provide insight into the qualitative behavior of such systems. Additionally, it is shown that the entropy inequality property of Khinchin's entropy can be reduced to an equality using the mixing entropy concept. This equality can be interpreted as a facet of the second law of thermodynamics for vibroacoustic systems. Following this analysis, an investigation of continuous systems is performed using Khinchin's entropy. It is shown that entropy analyses using Khinchin's entropy are valid for continuous systems that can be decomposed into a finite number of modes. The results are shown to be analogous to those obtained for simple oscillators, which demonstrates the applicability of entropy-based approaches to real-world systems. Three systems are considered to demonstrate these findings: 1) a rod end-coupled to a simple oscillator, 2) two end-coupled rods, and 3) two end-coupled beams. The aforementioned work utilizes the weak coupling assumption to determine the entropy of composite systems. Following this discussion, a direct method of finding entropy is developed which does not rely on this limiting assumption. The resulting entropy provides a useful benchmark for evaluating the accuracy of the weak coupling approach, and is validated using systems of coupled oscillators. The later chapters of this work discuss Khinchin's entropy as applied to nonlinear and nonconservative systems, respectively. The discussion of entropy for nonlinear systems is motivated by the desire to expand the applicability of SEA techniques beyond the linear regime. The discussion of nonconservative systems is also crucial, since real-world systems interact with their environment, and it is necessary to confirm the validity of an entropy approach for systems that are relevant in the context of SEA. Having developed a mathematical framework for determining entropy under a number of previously unexplored cases, the relationship between thermodynamics and statistical vibroacoustics can be better understood. Specifically, vibroacoustic temperatures can be obtained for systems that are not necessarily linear or weakly coupled. In this way, entropy provides insight into how the power flow proportionality of statistical energy analysis (SEA) can be applied to a broader class of vibroacoustic systems. As such, entropy is a useful tool for both justifying and expanding the foundational results of SEA.

Entropy is more resistant to artifacts than bispectral index in brain-dead organ donors.

PubMed

Wennervirta, Johanna; Salmi, Tapani; Hynynen, Markku; Yli-Hankala, Arvi; Koivusalo, Anna-Maria; Van Gils, Mark; Pöyhiä, Reino; Vakkuri, Anne

2007-01-01

To evaluate the usefulness of entropy and the bispectral index (BIS) in brain-dead subjects. A prospective, open, nonselective, observational study in the university hospital. 16 brain-dead organ donors. Time-domain electroencephalography (EEG), spectral entropy of the EEG, and BIS were recorded during solid organ harvest. State entropy differed significantly from 0 (isoelectric EEG) 28%, response entropy 29%, and BIS 68% of the total recorded time. The median values during the operation were state entropy 0.0, response entropy 0.0, and BIS 3.0. In four of 16 organ donors studied the EEG was not isoelectric, and nonreactive rhythmic activity was noted in time-domain EEG. After excluding the results from subjects with persistent residual EEG activity state entropy, response entropy, and BIS values differed from zero 17%, 18%, and 62% of the recorded time, respectively. Median values were 0.0, 0.0, and 2.0 for state entropy, response entropy, and BIS, respectively. The highest index values in entropy and BIS monitoring were recorded without neuromuscular blockade. The main sources of artifacts were electrocauterization, 50-Hz artifact, handling of the donor, ballistocardiography, electromyography, and electrocardiography. Both entropy and BIS showed nonzero values due to artifacts after brain death diagnosis. BIS was more liable to artifacts than entropy. Neither of these indices are diagnostic tools, and care should be taken when interpreting EEG and EEG-derived indices in the evaluation of brain death.

Mathematical investigations of branch length similarity entropy profiles of shapes for various resolutions

NASA Astrophysics Data System (ADS)

Jeon, Wonju; Lee, Sang-Hee

2012-12-01

In our previous study, we defined the branch length similarity (BLS) entropy for a simple network consisting of a single node and numerous branches. As the first application of this entropy to characterize shapes, the BLS entropy profiles of 20 battle tank shapes were calculated from simple networks created by connecting pixels in the boundary of the shape. The profiles successfully characterized the tank shapes through a comparison of their BLS entropy profiles. Following the application, this entropy was used to characterize human's emotional faces, such as happiness and sad, and to measure the degree of complexity for termite tunnel networks. These applications indirectly indicate that the BLS entropy profile can be a useful tool to characterize networks and shapes. However, the ability of the BLS entropy in the characterization depends on the image resolution because the entropy is determined by the number of nodes for the boundary of a shape. Higher resolution means more nodes. If the entropy is to be widely used in the scientific community, the effect of the resolution on the entropy profile should be understood. In the present study, we mathematically investigated the BLS entropy profile of a shape with infinite resolution and numerically investigated the variation in the pattern of the entropy profile caused by changes in the resolution change in the case of finite resolution.

A diameter-sensitive flow entropy method for reliability consideration in water distribution system design

NASA Astrophysics Data System (ADS)

Liu, Haixing; Savić, Dragan; Kapelan, Zoran; Zhao, Ming; Yuan, Yixing; Zhao, Hongbin

2014-07-01

Flow entropy is a measure of uniformity of pipe flows in water distribution systems. By maximizing flow entropy one can identify reliable layouts or connectivity in networks. In order to overcome the disadvantage of the common definition of flow entropy that does not consider the impact of pipe diameter on reliability, an extended definition of flow entropy, termed as diameter-sensitive flow entropy, is proposed. This new methodology is then assessed by using other reliability methods, including Monte Carlo Simulation, a pipe failure probability model, and a surrogate measure (resilience index) integrated with water demand and pipe failure uncertainty. The reliability assessment is based on a sample of WDS designs derived from an optimization process for each of the two benchmark networks. Correlation analysis is used to evaluate quantitatively the relationship between entropy and reliability. To ensure reliability, a comparative analysis between the flow entropy and the new method is conducted. The results demonstrate that the diameter-sensitive flow entropy shows consistently much stronger correlation with the three reliability measures than simple flow entropy. Therefore, the new flow entropy method can be taken as a better surrogate measure for reliability and could be potentially integrated into the optimal design problem of WDSs. Sensitivity analysis results show that the velocity parameters used in the new flow entropy has no significant impact on the relationship between diameter-sensitive flow entropy and reliability.

Entropy generation of nanofluid flow in a microchannel heat sink

NASA Astrophysics Data System (ADS)

Manay, Eyuphan; Akyürek, Eda Feyza; Sahin, Bayram

2018-06-01

Present study aims to investigate the effects of the presence of nano sized TiO2 particles in the base fluid on entropy generation rate in a microchannel heat sink. Pure water was chosen as base fluid, and TiO2 particles were suspended into the pure water in five different particle volume fractions of 0.25%, 0.5%, 1.0%, 1.5% and 2.0%. Under laminar, steady state flow and constant heat flux boundary conditions, thermal, frictional, total entropy generation rates and entropy generation number ratios of nanofluids were experimentally analyzed in microchannel flow for different channel heights of 200 μm, 300 μm, 400 μm and 500 μm. It was observed that frictional and total entropy generation rates increased as thermal entropy generation rate were decreasing with an increase in particle volume fraction. In microchannel flows, thermal entropy generation could be neglected due to its too low rate smaller than 1.10e-07 in total entropy generation. Higher channel heights caused higher thermal entropy generation rates, and increasing channel height yielded an increase from 30% to 52% in thermal entropy generation. When channel height decreased, an increase of 66%-98% in frictional entropy generation was obtained. Adding TiO2 nanoparticles into the base fluid caused thermal entropy generation to decrease about 1.8%-32.4%, frictional entropy generation to increase about 3.3%-21.6%.

Entropy and entropy production in Fokker–Plank equation under the generalized fluctuation–dissipation relation

NASA Astrophysics Data System (ADS)

Guo, Ran

2018-04-01

In this paper, we investigate the definition of the entropy in the Fokker–Planck equation under the generalized fluctuation–dissipation relation (FDR), which describes a Brownian particle moving in a complex medium with friction and multiplicative noise. The friction and the noise are related by the generalized FDR. The entropy for such a system is defined first. According to the definition of the entropy, we calculate the entropy production and the entropy flux. Lastly, we make a numerical calculation to display the results in figures.

Single water entropy: hydrophobic crossover and application to drug binding.

PubMed

Sasikala, Wilbee D; Mukherjee, Arnab

2014-09-11

Entropy of water plays an important role in both chemical and biological processes e.g. hydrophobic effect, molecular recognition etc. Here we use a new approach to calculate translational and rotational entropy of the individual water molecules around different hydrophobic and charged solutes. We show that for small hydrophobic solutes, the translational and rotational entropies of each water molecule increase as a function of its distance from the solute reaching finally to a constant bulk value. As the size of the solute increases (0.746 nm), the behavior of the translational entropy is opposite; water molecules closest to the solute have higher entropy that reduces with distance from the solute. This indicates that there is a crossover in translational entropy of water molecules around hydrophobic solutes from negative to positive values as the size of the solute is increased. Rotational entropy of water molecules around hydrophobic solutes for all sizes increases with distance from the solute, indicating the absence of crossover in rotational entropy. This makes the crossover in total entropy (translation + rotation) of water molecule happen at much larger size (>1.5 nm) for hydrophobic solutes. Translational entropy of single water molecule scales logarithmically (Str(QH) = C + kB ln V), with the volume V obtained from the ellipsoid of inertia. We further discuss the origin of higher entropy of water around water and show the possibility of recovering the entropy loss of some hypothetical solutes. The results obtained are helpful to understand water entropy behavior around various hydrophobic and charged environments within biomolecules. Finally, we show how our approach can be used to calculate the entropy of the individual water molecules in a protein cavity that may be replaced during ligand binding.

RNA Thermodynamic Structural Entropy

PubMed Central

Garcia-Martin, Juan Antonio; Clote, Peter

2015-01-01

Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner’99 and Turner’04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http://bioinformatics.bc.edu/clotelab/RNAentropy, including source code and ancillary programs. PMID:26555444

RNA Thermodynamic Structural Entropy.

PubMed

Garcia-Martin, Juan Antonio; Clote, Peter

2015-01-01

Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http://bioinformatics.bc.edu/clotelab/RNAentropy, including source code and ancillary programs.

Relating different quantum generalizations of the conditional Rényi entropy

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

Tomamichel, Marco; School of Physics, The University of Sydney, Sydney 2006; Berta, Mario

2014-08-15

Recently a new quantum generalization of the Rényi divergence and the corresponding conditional Rényi entropies was proposed. Here, we report on a surprising relation between conditional Rényi entropies based on this new generalization and conditional Rényi entropies based on the quantum relative Rényi entropy that was used in previous literature. Our result generalizes the well-known duality relation H(A|B) + H(A|C) = 0 of the conditional von Neumann entropy for tripartite pure states to Rényi entropies of two different kinds. As a direct application, we prove a collection of inequalities that relate different conditional Rényi entropies and derive a new entropicmore » uncertainty relation.« less

Exact analytical thermodynamic expressions for a Brownian heat engine

NASA Astrophysics Data System (ADS)

Taye, Mesfin Asfaw

2015-09-01

The nonequilibrium thermodynamics feature of a Brownian motor operating between two different heat baths is explored as a function of time t . Using the Gibbs entropy and Schnakenberg microscopic stochastic approach, we find exact closed form expressions for the free energy, the rate of entropy production, and the rate of entropy flow from the system to the outside. We show that when the system is out of equilibrium, it constantly produces entropy and at the same time extracts entropy out of the system. Its entropy production and extraction rates decrease in time and saturate to a constant value. In the long time limit, the rate of entropy production balances the rate of entropy extraction, and at equilibrium both entropy production and extraction rates become zero. Furthermore, via the present model, many thermodynamic theories can be checked.

Exact analytical thermodynamic expressions for a Brownian heat engine.

PubMed

Taye, Mesfin Asfaw

2015-09-01

The nonequilibrium thermodynamics feature of a Brownian motor operating between two different heat baths is explored as a function of time t. Using the Gibbs entropy and Schnakenberg microscopic stochastic approach, we find exact closed form expressions for the free energy, the rate of entropy production, and the rate of entropy flow from the system to the outside. We show that when the system is out of equilibrium, it constantly produces entropy and at the same time extracts entropy out of the system. Its entropy production and extraction rates decrease in time and saturate to a constant value. In the long time limit, the rate of entropy production balances the rate of entropy extraction, and at equilibrium both entropy production and extraction rates become zero. Furthermore, via the present model, many thermodynamic theories can be checked.

Modeling the Overalternating Bias with an Asymmetric Entropy Measure

PubMed Central

Gronchi, Giorgio; Raglianti, Marco; Noventa, Stefano; Lazzeri, Alessandro; Guazzini, Andrea

2016-01-01

Psychological research has found that human perception of randomness is biased. In particular, people consistently show the overalternating bias: they rate binary sequences of symbols (such as Heads and Tails in coin flipping) with an excess of alternation as more random than prescribed by the normative criteria of Shannon's entropy. Within data mining for medical applications, Marcellin proposed an asymmetric measure of entropy that can be ideal to account for such bias and to quantify subjective randomness. We fitted Marcellin's entropy and Renyi's entropy (a generalized form of uncertainty measure comprising many different kinds of entropies) to experimental data found in the literature with the Differential Evolution algorithm. We observed a better fit for Marcellin's entropy compared to Renyi's entropy. The fitted asymmetric entropy measure also showed good predictive properties when applied to different datasets of randomness-related tasks. We concluded that Marcellin's entropy can be a parsimonious and effective measure of subjective randomness that can be useful in psychological research about randomness perception. PMID:27458418

Entropy for the Complexity of Physiological Signal Dynamics.

PubMed

Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

Information Entropy Analysis of the H1N1 Genetic Code

NASA Astrophysics Data System (ADS)

Martwick, Andy

2010-03-01

During the current H1N1 pandemic, viral samples are being obtained from large numbers of infected people world-wide and are being sequenced on the NCBI Influenza Virus Resource Database. The information entropy of the sequences was computed from the probability of occurrence of each nucleotide base at every position of each set of sequences using Shannon's definition of information entropy, [ H=∑bpb,2( 1pb ) ] where H is the observed information entropy at each nucleotide position and pb is the probability of the base pair of the nucleotides A, C, G, U. Information entropy of the current H1N1 pandemic is compared to reference human and swine H1N1 entropy. As expected, the current H1N1 entropy is in a low entropy state and has a very large mutation potential. Using the entropy method in mature genes we can identify low entropy regions of nucleotides that generally correlate to critical protein function.

Generalized Entanglement Entropy and Holography

NASA Astrophysics Data System (ADS)

Obregón, O.

2018-04-01

A nonextensive statistical mechanics entropy that depends only on the probability distribution is proposed in the framework of superstatistics. It is based on a Γ(χ 2) distribution that depends on β and also on pl . The corresponding modified von Neumann entropy is constructed; it is shown that it can also be obtained from a generalized Replica trick. We address the question whether the generalized entanglement entropy can play a role in the gauge/gravity duality. We pay attention to 2dCFT and their gravity duals. The correction terms to the von Neumann entropy result more relevant than the usual UV (for c = 1) ones and also than those due to the area dependent AdS 3 entropy which result comparable to the UV ones. Then the correction terms due to the new entropy would modify the Ryu-Takayanagi identification between the CFT entanglement entropy and the AdS entropy in a different manner than the UV ones or than the corrections to the AdS 3 area dependent entropy.

Quench action and Rényi entropies in integrable systems

NASA Astrophysics Data System (ADS)

Alba, Vincenzo; Calabrese, Pasquale

2017-09-01

Entropy is a fundamental concept in equilibrium statistical mechanics, yet its origin in the nonequilibrium dynamics of isolated quantum systems is not fully understood. A strong consensus is emerging around the idea that the stationary thermodynamic entropy is the von Neumann entanglement entropy of a large subsystem embedded in an infinite system. Also motivated by cold-atom experiments, here we consider the generalization to Rényi entropies. We develop a new technique to calculate the diagonal Rényi entropy in the quench action formalism. In the spirit of the replica treatment for the entanglement entropy, the diagonal Rényi entropies are generalized free energies evaluated over a thermodynamic macrostate which depends on the Rényi index and, in particular, is not the same state describing von Neumann entropy. The technical reason for this perhaps surprising result is that the evaluation of the moments of the diagonal density matrix shifts the saddle point of the quench action. An interesting consequence is that different Rényi entropies encode information about different regions of the spectrum of the postquench Hamiltonian. Our approach provides a very simple proof of the long-standing issue that, for integrable systems, the diagonal entropy is half of the thermodynamic one and it allows us to generalize this result to the case of arbitrary Rényi entropy.

Impact of sensor's point spread function on land cover characterization: Assessment and deconvolution

USGS Publications Warehouse

Huang, C.; Townshend, J.R.G.; Liang, S.; Kalluri, S.N.V.; DeFries, R.S.

2002-01-01

Measured and modeled point spread functions (PSF) of sensor systems indicate that a significant portion of the recorded signal of each pixel of a satellite image originates from outside the area represented by that pixel. This hinders the ability to derive surface information from satellite images on a per-pixel basis. In this study, the impact of the PSF of the Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m bands was assessed using four images representing different landscapes. Experimental results showed that though differences between pixels derived with and without PSF effects were small on the average, the PSF generally brightened dark objects and darkened bright objects. This impact of the PSF lowered the performance of a support vector machine (SVM) classifier by 5.4% in overall accuracy and increased the overall root mean square error (RMSE) by 2.4% in estimating subpixel percent land cover. An inversion method based on the known PSF model reduced the signals originating from surrounding areas by as much as 53%. This method differs from traditional PSF inversion deconvolution methods in that the PSF was adjusted with lower weighting factors for signals originating from neighboring pixels than those specified by the PSF model. By using this deconvolution method, the lost classification accuracy due to residual impact of PSF effects was reduced to only 1.66% in overall accuracy. The increase in the RMSE of estimated subpixel land cover proportions due to the residual impact of PSF effects was reduced to 0.64%. Spatial aggregation also effectively reduced the errors in estimated land cover proportion images. About 50% of the estimation errors were removed after applying the deconvolution method and aggregating derived proportion images to twice their dimensional pixel size. ?? 2002 Elsevier Science Inc. All rights reserved.

A gene profiling deconvolution approach to estimating immune cell composition from complex tissues.

PubMed

Chen, Shu-Hwa; Kuo, Wen-Yu; Su, Sheng-Yao; Chung, Wei-Chun; Ho, Jen-Ming; Lu, Henry Horng-Shing; Lin, Chung-Yen

2018-05-08

A new emerged cancer treatment utilizes intrinsic immune surveillance mechanism that is silenced by those malicious cells. Hence, studies of tumor infiltrating lymphocyte populations (TILs) are key to the success of advanced treatments. In addition to laboratory methods such as immunohistochemistry and flow cytometry, in silico gene expression deconvolution methods are available for analyses of relative proportions of immune cell types. Herein, we used microarray data from the public domain to profile gene expression pattern of twenty-two immune cell types. Initially, outliers were detected based on the consistency of gene profiling clustering results and the original cell phenotype notation. Subsequently, we filtered out genes that are expressed in non-hematopoietic normal tissues and cancer cells. For every pair of immune cell types, we ran t-tests for each gene, and defined differentially expressed genes (DEGs) from this comparison. Equal numbers of DEGs were then collected as candidate lists and numbers of conditions and minimal values for building signature matrixes were calculated. Finally, we used v -Support Vector Regression to construct a deconvolution model. The performance of our system was finally evaluated using blood biopsies from 20 adults, in which 9 immune cell types were identified using flow cytometry. The present computations performed better than current state-of-the-art deconvolution methods. Finally, we implemented the proposed method into R and tested extensibility and usability on Windows, MacOS, and Linux operating systems. The method, MySort, is wrapped as the Galaxy platform pluggable tool and usage details are available at https://testtoolshed.g2.bx.psu.edu/view/moneycat/mysort/e3afe097e80a .

Combining a Deconvolution and a Universal Library Search Algorithm for the Nontarget Analysis of Data-Independent Acquisition Mode Liquid Chromatography-High-Resolution Mass Spectrometry Results.

PubMed

Samanipour, Saer; Reid, Malcolm J; Bæk, Kine; Thomas, Kevin V

2018-04-17

Nontarget analysis is considered one of the most comprehensive tools for the identification of unknown compounds in a complex sample analyzed via liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Due to the complexity of the data generated via LC-HRMS, the data-dependent acquisition mode, which produces the MS 2 spectra of a limited number of the precursor ions, has been one of the most common approaches used during nontarget screening. However, data-independent acquisition mode produces highly complex spectra that require proper deconvolution and library search algorithms. We have developed a deconvolution algorithm and a universal library search algorithm (ULSA) for the analysis of complex spectra generated via data-independent acquisition. These algorithms were validated and tested using both semisynthetic and real environmental data. A total of 6000 randomly selected spectra from MassBank were introduced across the total ion chromatograms of 15 sludge extracts at three levels of background complexity for the validation of the algorithms via semisynthetic data. The deconvolution algorithm successfully extracted more than 60% of the added ions in the analytical signal for 95% of processed spectra (i.e., 3 complexity levels multiplied by 6000 spectra). The ULSA ranked the correct spectra among the top three for more than 95% of cases. We further tested the algorithms with 5 wastewater effluent extracts for 59 artificial unknown analytes (i.e., their presence or absence was confirmed via target analysis). These algorithms did not produce any cases of false identifications while correctly identifying ∼70% of the total inquiries. The implications, capabilities, and the limitations of both algorithms are further discussed.

Transformation of chlorinated paraffins to olefins during metal work and thermal exposure - Deconvolution of mass spectra and kinetics.

PubMed

Schinkel, Lena; Lehner, Sandro; Knobloch, Marco; Lienemann, Peter; Bogdal, Christian; McNeill, Kristopher; Heeb, Norbert V

2018-03-01

Chlorinated paraffins (CPs) are high production volume chemicals widely used as additives in metal working fluids. Thereby, CPs are exposed to hot metal surfaces which may induce degradation processes. We hypothesized that the elimination of hydrochloric acid would transform CPs into chlorinated olefins (COs). Mass spectrometry is widely used to detect CPs, mostly in the selected ion monitoring mode (SIM) evaluating 2-3 ions at mass resolutions R < 20'000. This approach is not suited to detected COs, because their mass spectra strongly overlap with CPs. We applied a mathematical deconvolution method based on full-scan MS data to separate interfered CP/CO spectra. Metal drilling indeed induced HCl-losses. CO proportions in exposed mixtures of chlorotridecanes increased. Thermal exposure of chlorotridecanes at 160, 180, 200 and 220 °C also induced dehydrohalogenation reactions and CO proportions also increased. Deconvolution of respective mass spectra is needed to study the CP transformation kinetics without bias from CO interferences. Apparent first-order rate constants (k app ) increased up to 0.17, 0.29 and 0.46 h -1 for penta-, hexa- and heptachloro-tridecanes exposed at 220 °C. Respective half-life times (τ 1/2 ) decreased from 4.0 to 2.4 and 1.5 h. Thus, higher chlorinated paraffins degrade faster than lower chlorinated ones. In conclusion, exposure of CPs during metal drilling and thermal treatment induced HCl losses and CO formation. It is expected that CPs and COs are co-released from such processes. Full-scan mass spectra and subsequent deconvolution of interfered signals is a promising approach to tackle the CP/CO problem, in case of insufficient mass resolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Raman Spectra of Crystalline Double Calcium Orthovanadates Ca10M(VO4)7 (M = Li, K, Na) and Their Interpretation Based on Deconvolution Into Voigt Profiles

NASA Astrophysics Data System (ADS)

Khodasevich, I. A.; Voitikov, S. V.; Orlovich, V. A.; Kosmyna, M. B.; Shekhovtsov, A. N.

2016-09-01

Unpolarized spontaneous Raman spectra of crystalline double calcium orthovanadates Ca10M(VO4)7 (M = Li, K, Na) in the range 150-1600 cm-1 were measured. Two vibrational bands with full-width at half-maximum (FWHM) of 37-50 cm-1 were found in the regions 150-500 and 700-1000 cm-1. The band shapes were approximated well by deconvolution into Voigt profiles. The band at 700-1000 cm-1 was stronger and deconvoluted into eight Voigt profiles. The frequencies of two strong lines were ~848 and ~862 cm-1 for Ca10Li(VO4)7; ~850 and ~866 cm-1 for Ca10Na(VO4)7; and ~844 and ~866 cm-1 for Ca10K(VO4)7. The Lorentzian width parameters of these lines in the Voigt profiles were ~5 times greater than those of the Gaussian width parameters. The FWHM of the Voigt profiles were ~18-42 cm-1. The two strongest lines had widths of 21-25 cm-1. The vibrational band at 300-500 cm-1 was ~5-6 times weaker than that at 700-1000 cm-1 and was deconvoluted into four lines with widths of 25-40 cm-1. The large FWHM of the Raman lines indicated that the crystal structures were disordered. These crystals could be of interest for Raman conversion of pico- and femtosecond laser pulses because of the intense vibrations with large FWHM in the Raman spectra.

Acceleration of image-based resolution modelling reconstruction using an expectation maximization nested algorithm.

PubMed

Angelis, G I; Reader, A J; Markiewicz, P J; Kotasidis, F A; Lionheart, W R; Matthews, J C

2013-08-07

Recent studies have demonstrated the benefits of a resolution model within iterative reconstruction algorithms in an attempt to account for effects that degrade the spatial resolution of the reconstructed images. However, these algorithms suffer from slower convergence rates, compared to algorithms where no resolution model is used, due to the additional need to solve an image deconvolution problem. In this paper, a recently proposed algorithm, which decouples the tomographic and image deconvolution problems within an image-based expectation maximization (EM) framework, was evaluated. This separation is convenient, because more computational effort can be placed on the image deconvolution problem and therefore accelerate convergence. Since the computational cost of solving the image deconvolution problem is relatively small, multiple image-based EM iterations do not significantly increase the overall reconstruction time. The proposed algorithm was evaluated using 2D simulations, as well as measured 3D data acquired on the high-resolution research tomograph. Results showed that bias reduction can be accelerated by interleaving multiple iterations of the image-based EM algorithm solving the resolution model problem, with a single EM iteration solving the tomographic problem. Significant improvements were observed particularly for voxels that were located on the boundaries between regions of high contrast within the object being imaged and for small regions of interest, where resolution recovery is usually more challenging. Minor differences were observed using the proposed nested algorithm, compared to the single iteration normally performed, when an optimal number of iterations are performed for each algorithm. However, using the proposed nested approach convergence is significantly accelerated enabling reconstruction using far fewer tomographic iterations (up to 70% fewer iterations for small regions). Nevertheless, the optimal number of nested image-based EM iterations is hard to be defined and it should be selected according to the given application.

Continuous monitoring of high-rise buildings using seismic interferometry

NASA Astrophysics Data System (ADS)

Mordret, A.; Sun, H.; Prieto, G. A.; Toksoz, M. N.; Buyukozturk, O.

2016-12-01

The linear seismic response of a building is commonly extracted from ambient vibration measurements. Seismic deconvolution interferometry performed on ambient vibration measurements can also be used to estimate the dynamic characteristics of a building, such as the velocity of shear-waves travelling inside the building as well as a damping parameter depending on the intrinsic attenuation of the building and the soil-structure coupling. The continuous nature of the ambient vibrations allows us to measure these parameters repeatedly and to observe their temporal variations. We used 2 weeks of ambient vibration recorded by 36 accelerometers installed in the Green Building on the Massachusetts Institute of Technology campus (Cambridge, MA) to continuously monitor the shear-wave speed and the attenuation factor of the building. Due to the low strain of the ambient vibrations, the observed changes are totally reversible. The relative velocity changes between a reference deconvolution function and the current deconvolution functions are measured with two different methods: 1) the Moving Window Cross-Spectral technique and 2) the stretching technique. Both methods show similar results. We show that measuring the stretching coefficient for the deconvolution functions filtered around the fundamental mode frequency is equivalent to measuring the wandering of the fundamental frequency in the raw ambient vibration data. By comparing these results with local weather parameters, we show that the relative air humidity is the factor dominating the relative seismic velocity variations in the Green Building, as well as the wandering of the fundamental mode. The one-day periodic variations are affected by both the temperature and the humidity. The attenuation factor, measured as the exponential decay of the fundamental mode waveforms, shows a more complex behaviour with respect to the weather measurements.

Radiative entropy generation in a gray absorbing, emitting, and scattering planar medium at radiative equilibrium

NASA Astrophysics Data System (ADS)

Sadeghi, Pegah; Safavinejad, Ali

2017-11-01

Radiative entropy generation through a gray absorbing, emitting, and scattering planar medium at radiative equilibrium with diffuse-gray walls is investigated. The radiative transfer equation and radiative entropy generation equations are solved using discrete ordinates method. Components of the radiative entropy generation are considered for two different boundary conditions: two walls are at a prescribed temperature and mixed boundary conditions, which one wall is at a prescribed temperature and the other is at a prescribed heat flux. The effect of wall emissivities, optical thickness, single scattering albedo, and anisotropic-scattering factor on the entropy generation is attentively investigated. The results reveal that entropy generation in the system mainly arises from irreversible radiative transfer at wall with lower temperature. Total entropy generation rate for the system with prescribed temperature at walls remarkably increases as wall emissivity increases; conversely, for system with mixed boundary conditions, total entropy generation rate slightly decreases. Furthermore, as the optical thickness increases, total entropy generation rate remarkably decreases for the system with prescribed temperature at walls; nevertheless, for the system with mixed boundary conditions, total entropy generation rate increases. The variation of single scattering albedo does not considerably affect total entropy generation rate. This parametric analysis demonstrates that the optical thickness and wall emissivities have a significant effect on the entropy generation in the system at radiative equilibrium. Considering the parameters affecting radiative entropy generation significantly, provides an opportunity to optimally design or increase overall performance and efficiency by applying entropy minimization techniques for the systems at radiative equilibrium.

Magnetization dynamics of single-domain nanodots and minimum energy dissipation during either irreversible or reversible switching

NASA Astrophysics Data System (ADS)

Madami, Marco; Gubbiotti, Gianluca; Tacchi, Silvia; Carlotti, Giovanni

2017-11-01

Single- or multi-layered planar magnetic dots, with lateral dimensions ranging from tens to hundreds of nanometers, are used as elemental switches in current and forthcoming devices for information and communication technology (ICT), including magnetic memories, spin-torque oscillators and nano-magnetic logic gates. In this review article, we will first discuss energy dissipation during irreversible switching protocols of dots of different dimensions, ranging from a few tens of nanometers to the micrometric range. Then we will focus on the fundamental energy limits of adiabatic (slow) erasure and reversal of a magnetic nanodot, showing that dissipationless operation is achievable, provided that both dynamic reversibility (arbitrarily slow application of external fields) and entropic reversibility (no free entropy increase) are insured. However, recent theoretical and experimental tests of magnetic-dot erasure reveal that intrinsic defects related to materials imperfections such as roughness or polycrystallinity, may cause an excess of dissipation if compared to the minimum theoretical limit. We will conclude providing an outlook on the most promising strategies to achieve a new generation of power-saving nanomagnetic logic devices based on clusters of interacting dots and on straintronics.

Quantum tomography for collider physics: illustrations with lepton-pair production

NASA Astrophysics Data System (ADS)

Martens, John C.; Ralston, John P.; Takaki, J. D. Tapia

2018-01-01

Quantum tomography is a method to experimentally extract all that is observable about a quantum mechanical system. We introduce quantum tomography to collider physics with the illustration of the angular distribution of lepton pairs. The tomographic method bypasses much of the field-theoretic formalism to concentrate on what can be observed with experimental data. We provide a practical, experimentally driven guide to model-independent analysis using density matrices at every step. Comparison with traditional methods of analyzing angular correlations of inclusive reactions finds many advantages in the tomographic method, which include manifest Lorentz covariance, direct incorporation of positivity constraints, exhaustively complete polarization information, and new invariants free from frame conventions. For example, experimental data can determine the entanglement entropy of the production process. We give reproducible numerical examples and provide a supplemental standalone computer code that implements the procedure. We also highlight a property of complex positivity that guarantees in a least-squares type fit that a local minimum of a χ 2 statistic will be a global minimum: There are no isolated local minima. This property with an automated implementation of positivity promises to mitigate issues relating to multiple minima and convention dependence that have been problematic in previous work on angular distributions.

The Nature of Grand Minima and Maxima from Fully Nonlinear Flux Transport Dynamos

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

Inceoglu, Fadil; Arlt, Rainer; Rempel, Matthias, E-mail: finceoglu@aip.de

We aim to investigate the nature and occurrence characteristics of grand solar minimum and maximum periods, which are observed in the solar proxy records such as {sup 10}Be and {sup 14}C, using a fully nonlinear Babcock–Leighton type flux transport dynamo including momentum and entropy equations. The differential rotation and meridional circulation are generated from the effect of turbulent Reynolds stress and are subjected to back-reaction from the magnetic field. To generate grand minimum- and maximum-like periods in our simulations, we used random fluctuations in the angular momentum transport process, namely the Λ-mechanism, and in the Babcock–Leighton mechanism. To characterize themore » nature and occurrences of the identified grand minima and maxima in our simulations, we used the waiting time distribution analyses, which reflect whether the underlying distribution arises from a random or a memory-bearing process. The results show that, in the majority of the cases, the distributions of grand minima and maxima reveal that the nature of these events originates from memoryless processes. We also found that in our simulations the meridional circulation speed tends to be smaller during grand maximum, while it is faster during grand minimum periods. The radial differential rotation tends to be larger during grand maxima, while it is smaller during grand minima. The latitudinal differential rotation, on the other hand, is found to be larger during grand minima.« less

High Order Entropy-Constrained Residual VQ for Lossless Compression of Images

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Scales, Allen

1995-01-01

High order entropy coding is a powerful technique for exploiting high order statistical dependencies. However, the exponentially high complexity associated with such a method often discourages its use. In this paper, an entropy-constrained residual vector quantization method is proposed for lossless compression of images. The method consists of first quantizing the input image using a high order entropy-constrained residual vector quantizer and then coding the residual image using a first order entropy coder. The distortion measure used in the entropy-constrained optimization is essentially the first order entropy of the residual image. Experimental results show very competitive performance.