Independent Realizations Research Articles

Accelerated acquisition of tagged MRI for cardiac motion correction in simultaneous PET-MR: phantom and patient studies.

Degradation of image quality caused by cardiac and respiratory motions hampers the diagnostic quality of cardiac PET. It has been shown that improved diagnostic accuracy of myocardial defect can be achieved by tagged MR (tMR) based PET motion correction using simultaneous PET-MR. However, one major hurdle for the adoption of tMR-based PET motion correction in the PET-MR routine is the long acquisition time needed for the collection of fully sampled tMR data. In this work, the authors propose an accelerated tMR acquisition strategy using parallel imaging and/or compressed sensing and assess the impact on the tMR-based motion corrected PET using phantom and patient data. Fully sampled tMR data were acquired simultaneously with PET list-mode data on two simultaneous PET-MR scanners for a cardiac phantom and a patient. Parallel imaging and compressed sensing were retrospectively performed by GRAPPA and kt-FOCUSS algorithms with various acceleration factors. Motion fields were estimated using nonrigid B-spline image registration from both the accelerated and fully sampled tMR images. The motion fields were incorporated into a motion corrected ordered subset expectation maximization reconstruction algorithm with motion-dependent attenuation correction. Although tMR acceleration introduced image artifacts into the tMR images for both phantom and patient data, motion corrected PET images yielded similar image quality as those obtained using the fully sampled tMR images for low to moderate acceleration factors (<4). Quantitative analysis of myocardial defect contrast over ten independent noise realizations showed similar results. It was further observed that although the image quality of the motion corrected PET images deteriorates for high acceleration factors, the images were still superior to the images reconstructed without motion correction. Accelerated tMR images obtained with more than 4 times acceleration can still provide relatively accurate motion fields and yield tMR-based motion corrected PET images with similar image quality as those reconstructed using fully sampled tMR data. The reduction of tMR acquisition time makes it more compatible with routine clinical cardiac PET-MR studies.

When is a parameterized controller suitable for adaptive control?

In this paper we investigate when a parameterized controller, designed for a plant depending on unknown parameters, admits a realization which is independent of these parameters. It is argued that adaptation is unnecessary for this class of parameterized controllers. We prove that standard model reference controllers (state and output-feedback) for linear time invariant systems with a suitably chosen filter at the plant input admit a parameter independent realization.

Evaluating panel data forecasts under independent realization

Independent realization is a commonly used shortcut for deriving forecast properties. It is also an unrealistic assumption in many empirical applications. In this paper we consider the effect of the assumption when deriving the properties of panel data forecasts. To do so, we derive and compare the asymptotic forecast loss of a set of vector autoregressions (VARs) under both independent and same-sample realization. We show that adopting the independent realization assumption can result in an overstatement of forecast loss when common forms of parameterized heterogeneity (such as fixed effects) are included in the VAR. Because these parameters are often used in dynamic panel forecasting applications, our results imply that the independent realization shortcut should only be used with caution when working with panel data.

Experimental evidence of replica symmetry breaking in random lasers.

Spin-glass theory is one of the leading paradigms of complex physics and describes condensed matter, neural networks and biological systems, ultracold atoms, random photonics and many other research fields. According to this theory, identical systems under identical conditions may reach different states. This effect is known as replica symmetry breaking and is revealed by the shape of the probability distribution function of an order parameter named the Parisi overlap. However, a direct experimental evidence in any field of research is still missing. Here we investigate pulse-to-pulse fluctuations in random lasers, we introduce and measure the analogue of the Parisi overlap in independent experimental realizations of the same disordered sample, and we find that the distribution function yields evidence of a transition to a glassy light phase compatible with a replica symmetry breaking.

Genetic enablers underlying the clustered evolutionary origins of C4 photosynthesis in angiosperms.

The evolutionary accessibility of novel adaptations varies among lineages, depending in part on the genetic elements present in each group. However, the factors determining the evolutionary potential of closely related genes remain largely unknown. In plants, CO2-concentrating mechanisms such as C4 and crassulacean acid metabolism (CAM) photosynthesis have evolved numerous times in distantly related groups of species, and constitute excellent systems to study constraints and enablers of evolution. It has been previously shown for multiple proteins that grasses preferentially co-opted the same gene lineage for C4 photosynthesis, when multiple copies were present. In this work, we use comparative transcriptomics to show that this bias also exists within Caryophyllales, a distantly related group with multiple C4 origins. However, the bias is not the same as in grasses and, when all angiosperms are considered jointly, the number of distinct gene lineages co-opted is not smaller than that expected by chance. These results show that most gene lineages present in the common ancestor of monocots and eudicots produced gene descendants that were recruited into C4 photosynthesis, but that C4-suitability changed during the diversification of angiosperms. When selective pressures drove C4 evolution, some copies were preferentially co-opted, probably because they already possessed C4-like expression patterns. However, the identity of these C4-suitable genes varies among clades of angiosperms, and C4 phenotypes in distant angiosperm groups thus represent genuinely independent realizations, based on different genetic precursors.

Accounting for shared and unshared dosimetric uncertainties in the dose response for ultrasound-detected thyroid nodules after exposure to radioactive fallout.

Dosimetic uncertainties, particularly those that are shared among subgroups of a study population, can bias, distort or reduce the slope or significance of a dose response. Exposure estimates in studies of health risks from environmental radiation exposures are generally highly uncertain and thus, susceptible to these methodological limitations. An analysis was published in 2008 concerning radiation-related thyroid nodule prevalence in a study population of 2,994 villagers under the age of 21 years old between August 1949 and September 1962 and who lived downwind from the Semipalatinsk Nuclear Test Site in Kazakhstan. This dose-response analysis identified a statistically significant association between thyroid nodule prevalence and reconstructed doses of fallout-related internal and external radiation to the thyroid gland; however, the effects of dosimetric uncertainty were not evaluated since the doses were simple point "best estimates". In this work, we revised the 2008 study by a comprehensive treatment of dosimetric uncertainties. Our present analysis improves upon the previous study, specifically by accounting for shared and unshared uncertainties in dose estimation and risk analysis, and differs from the 2008 analysis in the following ways: 1. The study population size was reduced from 2,994 to 2,376 subjects, removing 618 persons with uncertain residence histories; 2. Simulation of multiple population dose sets (vectors) was performed using a two-dimensional Monte Carlo dose estimation method; and 3. A Bayesian model averaging approach was employed for evaluating the dose response, explicitly accounting for large and complex uncertainty in dose estimation. The results were compared against conventional regression techniques. The Bayesian approach utilizes 5,000 independent realizations of population dose vectors, each of which corresponds to a set of conditional individual median internal and external doses for the 2,376 subjects. These 5,000 population dose vectors reflect uncertainties in dosimetric parameters, partly shared and partly independent, among individual members of the study population. Risk estimates for thyroid nodules from internal irradiation were higher than those published in 2008, which results, to the best of our knowledge, from explicitly accounting for dose uncertainty. In contrast to earlier findings, the use of Bayesian methods led to the conclusion that the biological effectiveness for internal and external dose was similar. Estimates of excess relative risk per unit dose (ERR/Gy) for males (177 thyroid nodule cases) were almost 30 times those for females (571 cases) and were similar to those reported for thyroid cancers related to childhood exposures to external and internal sources in other studies. For confirmed cases of papillary thyroid cancers (3 in males, 18 in females), the ERR/Gy was also comparable to risk estimates from other studies, but not significantly different from zero. These findings represent the first reported dose response for a radiation epidemiologic study considering all known sources of shared and unshared errors in dose estimation and using a Bayesian model averaging (BMA) method for analysis of the dose response.

Establishment of Detection and Correction Parameters for a Geostatistical Homogenisation Approach

Non-natural irregularities are an inevitable part of long-time climate records. They are originated during the process of measuring and collecting data from weather stations. In order to use those records as an input for environmental projects or climate studies, it is essential to detect and correct the irregularities through the process of homogenisation. The use of geostatistical approaches as homogenisation techniques has already been proven to be successful. The gsimcli homogenisation process is based on a geostatistical simulation method, the direct sequential simulation. This method generates a set of equally probable and independent realisations, and calculates a probability distribution function at the candidate station's location. This probability distribution function is then used in the identification and correction of irregularities. Currently, gsimcli is being developed into an open source software package. During the homogenisation process, gsimcli requires the selection of several parameters in the detection and correction of irregularities. The candidate stations’ order to be homogenised, the value of the probability used in the detection of irregularities, and the statistic value to be used in the correction of the irregularity or in the replacement of missing data, are examples of parameters to be chosen for the homogenisation with gsimcli. This work presents a sensitivity analysis of those parameters, in order to find the most suitable set of values for the homogenisation of monthly precipitation data. A benchmark data set, comprising climate records from an Austrian precipitation network, will be used in this analysis. Performance metrics are calculated to evaluate the efficiency of the homogenisation process. The set of parameters providing the best values of performance metrics will be defined as the default set of homogenisation parameters for precipitation data.

Polynomial Chaos Expansion of a Multimodal Random Vector

A methodology and algorithms are proposed for constructing the polynomial chaos expansion (PCE) of multimodal random vectors. An algorithm is developed for generating independent realizations of any multimodal multivariate probability measure that is constructed from a set of independent realizations using the Gaussian kernel-density estimation method. The PCE is then performed with respect to this multimodal probability measure, for which the realizations of the polynomial chaos are computed with an adapted algorithm. Finally, a numerical application is presented for analyzing the convergence properties.

Polarimetric Simulations of SAR at L-Band Over Bare Soil Using Scattering Matrices of Random Rough Surfaces From Numerical Three-Dimensional Solutions of Maxwell Equations

We have performed simulations of random rough surface scattering using 3-D numerical solution of Maxwell equations (NMM3D) using surface size up to 32 $\times$ 32 squared wavelengths. The rough surfaces are characterized by exponential correlation functions. The simulation results of cross- and copolarization backscattering coefficients were in good agreement with experimental measurements of bare soils at L-band. Because in numerical solutions of Maxwell equations the electric fields of the scattered wave are calculated for each realization, scattering matrices can be simulated by NMM3D, and such simulations are performed in this paper. For a given RMS height, correlation length, soil permittivity, and incident angle, we calculated the radar scattering matrix up to 958 independent realizations. For each realization, the components of the scattering matrix, namely, $S_{\rm HH}$ , $S_{\rm VV}$ , $S_{\rm HV}$ , and $S_{\rm VH}$ , are calculated. Using the simulated scattering matrices, we calculate the polarimetric speckle statistics (amplitude and phase difference), followed by a comparison with theoretical distributions. For fully developed speckle from the homogeneous rough surface, the results are examined and validated to ensure the simulated data quality as far as polarimetric properties are concerned. By taking ensemble averages, we calculate the coherency matrix from which the eigenvalues, entropy, anisotropy, and alpha angle in coherent target decomposition are then calculated. In particular, characterization of polarimetric descriptors for rough surface is presented. Issues of scattering symmetry characteristics are also discussed.

A disagreement-percolation type uniqueness condition for Gibbs states in models with long-range interactions

We extend a condition for the uniqueness of Gibbs states in terms of percolation in the coupling of two independent realizations to lattice spin models with long-range interactions and a not necessarily unique ground state.

Simulation of Intrinsic Random Fields of Order $$k$$ k with Gaussian Generalized Increments by Gibbs Sampling

This work pertains to the simulation of an intrinsic random field of order $$k$$ with a given generalized covariance function and multivariate Gaussian generalized increments. An iterative algorithm based on the Gibbs sampler is proposed to simulate such a random field at a finite set of locations, resulting in a sequence of random vectors that converges in distribution to a random vector with the desired distribution. The algorithm is tested on synthetic case studies to experimentally assess its rate of convergence, showing that few iterations are sufficient for convergence to take place. The sequence of random vectors also proves to be strongly mixing, allowing the generation of as many independent realizations as desired with a single run of the algorithm. Another interesting property of this algorithm is its versatility, insofar as it can be adapted to construct realizations conditioned to pre-existing data and can be used for any number and configuration of the target locations and any generalized covariance model.

How to reliably determine the complex refractive index (RI) of graphene by using two independent measurement constraints.

Reliable determination of the complex refractive index (RI) of graphene inherently requires two independent measurement realizations for two independent unknowns of the real (nG) and imaginary (kG) components, i.e., RI = nG + i kG. Thus, any single set of measurement realization provides only one constraint that is insufficient to uniquely determine the complex RI of graphene. Tandem uses of two independent measurement techniques, namely the surface plasmon resonance (SPR) angle detection and the attenuated total reflection (ATR) intensity measurement, allow for the unique determination of the complex RI of CVD-synthesized graphene. The presently measured graphene RI is determined to be 2.65 + 1.27i for the E-field oscillating parallel to graphene at 634 nm wavelength, with variations for different numbers of L (1, 3 and 5) remaining within ±3%. Thus, our demonstration results for the specified wavelength serve as an impetus to suggest the need for two independent measurement techniques in determining both the real and imaginary RI values for graphene. Additional efforts have been made to characterize graphene layers using the density function theory (DFT): this calculation provides RIG = 2.71 + 1.41i.

Fast simulations for intensity mapping experiments

We present a code to generate mock observations of 21 cm intensity mapping experiments. The emphasis of the code is on reducing the computational cost of running a full-blown simulation, trading computational time for accuracy. The code can be used to generate independent realizations of the cosmological signal and foregrounds, which are necessary, for instance, in order to obtain realistic forecasts for future intensity mapping experiments. The code is able to reproduce the correct angular and radial clustering pattern for the cosmological signal, including redshift-space distortions, lightcone evolution and bias. Furthermore, it is possible to simulate a variety of foregrounds, including the potentially problematic polarized synchrotron emission.

COSMIC REIONIZATION ON COMPUTERS. II. REIONIZATION HISTORY AND ITS BACK-REACTION ON EARLY GALAXIES

We compare the results from several sets of cosmological simulations of cosmic reionization, produced under Cosmic Reionization On Computers (CROC) project, with existing observational data on the high-redshift Ly-alpha forest and the abundance of Ly-alpha emitters. We find good consistency with the observational measurements and the previous simulation work. By virtue of having several independent realizations for each set of numerical parameters, we are able to explore the effect of cosmic variance on observable quantities. One unexpected conclusion we are forced into is that cosmic variance is unusually large at z>6, with both our simulations and, most likely, observational measurements are still not fully converged for even such basic quantities as the average Gunn-Peterson optical depth or the volume-weighted neutral fraction. We also find that reionization has little effect on the early galaxies or on global cosmic star formation history, because galaxies whose gas content is affected by photoionization contain no molecular (i.e. star-forming) gas in the first place. In particular, measurements of the faint end of the galaxy luminosity function by JWST are unlikely to provide a useful constraint on reionization.

Estimating cosmological parameter covariance

We investigate the bias and error in estimates of the cosmological parameter covariance matrix, due to sampling or modelling the data covariance matrix, for likelihood width and peak scatter estimators. We show that these estimators do not coincide unless the data covariance is exactly known. For sampled data covariances, with Gaussian distributed data and parameters, the parameter covariance matrix estimated from the width of the likelihood has a Wishart distribution, from which we derive the mean and covariance. This mean is biased and we propose an unbiased estimator of the parameter covariance matrix. Comparing our analytic results to a numerical Wishart sampler of the data covariance matrix we find excellent agreement. An accurate ansatz for the mean parameter covariance for the peak scatter estimator is found, and we fit its covariance to our numerical analysis. The mean is again biased and we propose an unbiased estimator for the peak parameter covariance. For sampled data covariances the width estimator is more accurate than the peak scatter estimator. We investigate modelling the data covariance, or equivalently data compression, and shown that the peak scatter estimator is less sensitive to biases in the model data covariance matrix than the width estimator, but requires independent realisations of the data to reduce the statistical error. If the model bias on the peak estimator is sufficiently low this is promising, otherwise the sampled width estimator is preferable.

MODEL OF THE INTERNAL CONFLICT IN HUMANISTIC PSYCHOLOGY OF THE PERSON

In the article sights of founders of humanistic psychology at phenomenology and psychological mechanisms of intrapersonal conflicts are considered. It is underlined, that the basic internal conflict is connected with comprehension negative I-image. Experiences by the person of the I-image are substantially defined by opportunities of the person to self-realization. Psychological pressure from the social world on the person of the individual generates a deep emotional dissatisfaction with self. The solution of the internal conflict is accompanied by experiences of deep confidence I, feeling of finding of internal and external freedom. It is emphasized, that realization of freedom and relative independence is the main quality of social human life. Overcoming of intrapersonal conflicts is realized comprehension of necessity to enter the open, sincere dialogue with significant others, to show spontaneity, creation. Integrity of the person, image-I is reached through a support on cultural moral values. Spontaneous contact to the deep unconscious feeling I is necessary for the person. The self-realization, harmonious persons have the developed individuality, they are opened to own experiences, are not afraid of negative assessment from others, do not follow stereotypes, are less planned, they can be given to authority to emotions and are capable to self-acceptance. Purpose. To study determinants of internal conflicts in humanistic psychology of the person. Methodology. The qualitative theoretical analysis and synthesis of literary data. Results. In the article general concepts leading foreign humanistic psychologists on phenomenology and mechanisms of the solution of intrapersonal conflicts are presented also. The significant attention is given sights A. Maslou and K. Rogers as main representatives of psychology of this direction. Practical implications. Preparation of psychologists in the field of humanistic psychotherapeutic consultation. DOI: http://dx.doi.org/10.12731/2218-7405-2013-12-8

Frequentist confidence intervals for orbits

The problem of efficiently computing the orbital elements of a visual binary while still deriving confidence intervals with frequentist properties is treated. When formulated in terms of the Thiele-Innes elements, the known distribution of probability in Thiele-Innes space allows efficient grid-search plus Monte-Carlo-sampling schemes to be constructed for both the minimum-$\!\chi^{2}$ and Bayesian approaches to parameter estimation. Numerical experiments with $10^{4}$ independent realizations of an observed orbit confirm that the $1-$ and $2\sigma$ confidence and credibility intervals have coverage fractions close to their frequentist values. \keywords{binaries: visual - stars: fundamental parameters - methods:statistical}

MR‐based motion correction for PET imaging using wired active MR microcoils in simultaneous PET‐MR: Phantom study

Artifacts caused by head motion present a major challenge in brain positron emission tomography (PET) imaging. The authors investigated the feasibility of using wired active MR microcoils to track head motion and incorporate the measured rigid motion fields into iterative PET reconstruction. Several wired active MR microcoils and a dedicated MR coil-tracking sequence were developed. The microcoils were attached to the outer surface of an anthropomorphic(18)F-filled Hoffman phantom to mimic a brain PET scan. Complex rotation/translation motion of the phantom was induced by a balloon, which was connected to a ventilator. PET list-mode and MR tracking data were acquired simultaneously on a PET-MR scanner. The acquired dynamic PET data were reconstructed iteratively with and without motion correction. Additionally, static phantom data were acquired and used as the gold standard. Motion artifacts in PET images were effectively removed by wired active MR microcoil based motion correction. Motion correction yielded an activity concentration bias ranging from -0.6% to 3.4% as compared to a bias ranging from -25.0% to 16.6% if no motion correction was applied. The contrast recovery values were improved by 37%-156% with motion correction as compared to no motion correction. The image correlation (mean ± standard deviation) between the motion corrected (uncorrected) images of 20 independent noise realizations and static reference was R(2) = 0.978 ± 0.007 (0.588 ± 0.010, respectively). Wired active MR microcoil based motion correction significantly improves brain PET quantitative accuracy and image contrast.

Simulation Evaluation of Quantitative Myocardial Perfusion Assessment from Cardiac CT.

Contrast enhancement on cardiac CT provides valuable information about myocardial perfusion and methods have been proposed to assess perfusion with static and dynamic acquisitions. There is a lack of knowledge and consensus on the appropriate approach to ensure 1) sufficient diagnostic accuracy for clinical decisions and 2) low radiation doses for patient safety. This work developed a thorough dynamic CT simulation and several accepted blood flow estimation techniques to evaluate the performance of perfusion assessment across a range of acquisition and estimation scenarios. Cardiac CT acquisitions were simulated for a range of flow states (Flow = 0.5, 1, 2, 3 ml/g/min, cardiac output = 3,5,8 L/min). CT acquisitions were simulated with a validated CT simulator incorporating polyenergetic data acquisition and realistic x-ray flux levels for dynamic acquisitions with a range of scenarios including 1, 2, 3 sec sampling for 30 sec with 25, 70, 140 mAs. Images were generated using conventional image reconstruction with additional image-based beam hardening correction to account for iodine content. Time attenuation curves were extracted for multiple regions around the myocardium and used to estimate flow. In total, 2,700 independent realizations of dynamic sequences were generated and multiple MBF estimation methods were applied to each of these. Evaluation of quantitative kinetic modeling yielded blood flow estimates with an root mean square error (RMSE) of ∼0.6 ml/g/min averaged across multiple scenarios. Semi-quantitative modeling and qualitative static imaging resulted in significantly more error (RMSE = ∼1.2 and ∼1.2 ml/min/g respectively). For quantitative methods, dose reduction through reduced temporal sampling or reduced tube current had comparable impact on the MBF estimate fidelity. On average, half dose acquisitions increased the RMSE of estimates by only 18% suggesting that substantial dose reductions can be employed in the context of quantitative myocardial blood flow estimation. In conclusion, quantitative model-based dynamic cardiac CT perfusion assessment is capable of accurately estimating MBF across a range of cardiac outputs and tissue perfusion states, outperforms comparable static perfusion estimates, and is relatively robust to noise and temporal subsampling.

Motion compensation for brain PET imaging using wireless MR active markers in simultaneous PET–MR: Phantom and non-human primate studies

Brain PET scanning plays an important role in the diagnosis, prognostication and monitoring of many brain diseases. Motion artifacts from head motion are one of the major hurdles in brain PET. In this work, we propose to use wireless MR active markers to track head motion in real time during a simultaneous PET–MR brain scan and incorporate the motion measured by the markers in the listmode PET reconstruction.Several wireless MR active markers and a dedicated fast MR tracking pulse sequence module were built. Data were acquired on an ACR Flangeless PET phantom with multiple spheres and a non-human primate with and without motion. Motions of the phantom and monkey's head were measured with the wireless markers using a dedicated MR tracking sequence module. The motion PET data were reconstructed using list-mode reconstruction with and without motion correction. Static reference was used as gold standard for quantitative analysis.The motion artifacts, which were prominent on the images without motion correction, were eliminated by the wireless marker based motion correction in both the phantom and monkey experiments. Quantitative analysis was performed on the phantom motion data from 24 independent noise realizations. The reduction of bias of sphere-to-background PET contrast by active marker based motion correction ranges from 26% to 64% and 17% to 25% for hot (i.e., radioactive) and cold (i.e., non-radioactive) spheres, respectively. The motion correction improved the channelized Hotelling observer signal-to-noise ratio of the spheres by 1.2 to 6.9 depending on their locations and sizes.The proposed wireless MR active marker based motion correction technique removes the motion artifacts in the reconstructed PET images and yields accurate quantitative values.