The Experts below are selected from a list of 242868 Experts worldwide ranked by ideXlab platform
V M Alexeenko - One of the best experts on this subject based on the ideXlab platform.
-
factors affecting the output pulse flatness of the linear transformer driver cavity systems with 5th harmonics
Physical review accelerators and beams, 2016Co-Authors: M G Mazarakis, V M Alexeenko, S S Kondratiev, V A Sinebryukhov, S N Volkov, M E Cuneo, Mark L Kiefer, J J Leckby, B V OliverAbstract:Here, we describe the study we have undertaken to evaluate the effect of Component tolerances in obtaining a voltage output flat top for a linear transformer driver (LTD) cavity containing 3rd and 5th harmonic bricks [A. A. Kim et al., in Proc. IEEE Pulsed Power and Plasma Science PPPS2013 (San Francisco, California, USA, 2013), pp. 1354–1356.] and for 30 cavity voltage adder. Our goal was to define the necessary Component Value precision in order to obtain a voltage output flat top with no more than ±0.5% amplitude variation.
-
factors affecting the output pulse flatness of the linear transformer driver cavity systems with 5th harmonics
Physical review accelerators and beams, 2016Co-Authors: M G Mazarakis, V M Alexeenko, S S Kondratiev, V A Sinebryukhov, S N Volkov, M E Cuneo, A A Kim, Mark L KieferAbstract:We describe the study we have undertaken to evaluate the effect of Component tolerances in obtaining a voltage output flat top for a linear transformer driver (LTD) cavity containing 3rd and 5th harmonic bricks [A. A. Kim et al., in Proc. IEEE Pulsed Power and Plasma Science PPPS2013 (San Francisco, California, USA, 2013), pp. 1354--1356.] and for 30 cavity voltage adder. Our goal was to define the necessary Component Value precision in order to obtain a voltage output flat top with no more than $\ifmmode\pm\else\textpm\fi{}0.5%$ amplitude variation.
Gustavo A Aucar - One of the best experts on this subject based on the ideXlab platform.
-
relativistic and qed effects on nmr magnetic shielding constant of neutral and ionized atoms and diatomic molecules
Journal of Chemical Physics, 2019Co-Authors: Karol Koziol, Agustin I Aucar, Gustavo A AucarAbstract:We show here results of four-Component calculations of nuclear magnetic resonance σ for atoms with 10 ≤ Z ≤ 86 and their ions, within the polarization propagator formalism at its random phase level of approach, and the first estimation of quantum electrodynamic (QED) effects and Breit interactions of those atomic systems by using two theoretical effective models. We also show QED corrections to σ(X) in simple diatomic HX and X2 (X = Br, I, At) molecules. We found that the Z dependence of QED corrections in bound-state many-electron systems is proportional to Z5, which is higher than its dependence in H-like systems. The analysis of relativistic ee (or paramagneticlike) and pp (or diamagneticlike) terms of σ exposes two different patterns: the pp contribution arises from virtual electron-positron pair creation/annihilation and the ee contribution is mainly given by 1s → ns and 2s → ns excitations. The QED effects on shieldings have a negative sign, and their magnitude is larger than 1% of the relativistic effects for high-Z atoms such as Hg and Rn, and up to 0.6% of its total four-Component Value for neutral Rn. Furthermore, percentual contributions of QED effects to the total shielding are larger for ionized than for neutral atoms. In a molecule, the contribution of QED effects to σ(X) is determined by its highest-Z atoms, being up to −0.6% of its total σ Value for astatine compounds. It is found that QED effects grow faster than relativistic effects with Z.We show here results of four-Component calculations of nuclear magnetic resonance σ for atoms with 10 ≤ Z ≤ 86 and their ions, within the polarization propagator formalism at its random phase level of approach, and the first estimation of quantum electrodynamic (QED) effects and Breit interactions of those atomic systems by using two theoretical effective models. We also show QED corrections to σ(X) in simple diatomic HX and X2 (X = Br, I, At) molecules. We found that the Z dependence of QED corrections in bound-state many-electron systems is proportional to Z5, which is higher than its dependence in H-like systems. The analysis of relativistic ee (or paramagneticlike) and pp (or diamagneticlike) terms of σ exposes two different patterns: the pp contribution arises from virtual electron-positron pair creation/annihilation and the ee contribution is mainly given by 1s → ns and 2s → ns excitations. The QED effects on shieldings have a negative sign, and their magnitude is larger than 1% of the relativistic ...
Jordi Sunyer - One of the best experts on this subject based on the ideXlab platform.
-
independent multiple factor association analysis for multiblock data in imaging genetics
Neuroinformatics, 2019Co-Authors: Natalia Vilortejedor, Mohammad Arfan Ikram, Gennady V Roshchupkin, Alejandro Caceres, Silvia Alemany, Meike W Vernooij, Wiro J Niessen, Cornelia M Van Duijn, Jordi SunyerAbstract:Multivariate methods have the potential to better capture complex relationships that may exist between different biological levels. Multiple Factor Analysis (MFA) is one of the most popular methods to obtain factor scores and measures of discrepancy between data sets. However, singular Value decomposition in MFA is based on PCA, which is adequate only if the data is normally distributed, linear or stationary. In addition, including strongly correlated variables can overemphasize the contribution of the estimated Components. In this work, we introduced a novel method referred as Independent Multifactorial Analysis (ICA-MFA) to derive relevant features from multiscale data. This method is an extended implementation of MFA, where the Component Value decomposition is based on Independent Component Analysis. In addition, ICA-MFA incorporates a predictive step based on an Independent Component Regression. We evaluated and compared the performance of ICA-MFA with both, the MFA method and traditional univariate analyses, in a simulation study. We showed how ICA-MFA explained up to 10-fold more variance than MFA and univariate methods. We applied the proposed algorithm in a study of 4057 individuals belonging to the population-based Rotterdam Study with available genetic and neuroimaging data, as well as information about executive cognitive functioning. Specifically, we used ICA-MFA to detect relevant genetic features related to structural brain regions, which in turn were involved, in the mechanisms of executive cognitive function. The proposed strategy makes it possible to determine the degree to which the whole set of genetic and/or neuroimaging markers contribute to the variability of the symptomatology jointly, rather than individually. While univariate results and MFA combinations only explained a limited proportion of variance (less than 2%), our method increased the explained variance (10%) and allowed the identification of significant Components that maximize the variance explained in the model. The potential application of the ICA-MFA algorithm constitutes an important aspect of integrating multivariate multiscale data, specifically in the field of Neurogenetics.
Wiro J Niessen - One of the best experts on this subject based on the ideXlab platform.
-
independent multiple factor association analysis for multiblock data in imaging genetics
Neuroinformatics, 2019Co-Authors: Natalia Vilortejedor, Mohammad Arfan Ikram, Gennady V Roshchupkin, Alejandro Caceres, Silvia Alemany, Meike W Vernooij, Wiro J Niessen, Cornelia M Van Duijn, Jordi SunyerAbstract:Multivariate methods have the potential to better capture complex relationships that may exist between different biological levels. Multiple Factor Analysis (MFA) is one of the most popular methods to obtain factor scores and measures of discrepancy between data sets. However, singular Value decomposition in MFA is based on PCA, which is adequate only if the data is normally distributed, linear or stationary. In addition, including strongly correlated variables can overemphasize the contribution of the estimated Components. In this work, we introduced a novel method referred as Independent Multifactorial Analysis (ICA-MFA) to derive relevant features from multiscale data. This method is an extended implementation of MFA, where the Component Value decomposition is based on Independent Component Analysis. In addition, ICA-MFA incorporates a predictive step based on an Independent Component Regression. We evaluated and compared the performance of ICA-MFA with both, the MFA method and traditional univariate analyses, in a simulation study. We showed how ICA-MFA explained up to 10-fold more variance than MFA and univariate methods. We applied the proposed algorithm in a study of 4057 individuals belonging to the population-based Rotterdam Study with available genetic and neuroimaging data, as well as information about executive cognitive functioning. Specifically, we used ICA-MFA to detect relevant genetic features related to structural brain regions, which in turn were involved, in the mechanisms of executive cognitive function. The proposed strategy makes it possible to determine the degree to which the whole set of genetic and/or neuroimaging markers contribute to the variability of the symptomatology jointly, rather than individually. While univariate results and MFA combinations only explained a limited proportion of variance (less than 2%), our method increased the explained variance (10%) and allowed the identification of significant Components that maximize the variance explained in the model. The potential application of the ICA-MFA algorithm constitutes an important aspect of integrating multivariate multiscale data, specifically in the field of Neurogenetics.
Mark L Kiefer - One of the best experts on this subject based on the ideXlab platform.
-
factors affecting the output pulse flatness of the linear transformer driver cavity systems with 5th harmonics
Physical review accelerators and beams, 2016Co-Authors: M G Mazarakis, V M Alexeenko, S S Kondratiev, V A Sinebryukhov, S N Volkov, M E Cuneo, Mark L Kiefer, J J Leckby, B V OliverAbstract:Here, we describe the study we have undertaken to evaluate the effect of Component tolerances in obtaining a voltage output flat top for a linear transformer driver (LTD) cavity containing 3rd and 5th harmonic bricks [A. A. Kim et al., in Proc. IEEE Pulsed Power and Plasma Science PPPS2013 (San Francisco, California, USA, 2013), pp. 1354–1356.] and for 30 cavity voltage adder. Our goal was to define the necessary Component Value precision in order to obtain a voltage output flat top with no more than ±0.5% amplitude variation.
-
factors affecting the output pulse flatness of the linear transformer driver cavity systems with 5th harmonics
Physical review accelerators and beams, 2016Co-Authors: M G Mazarakis, V M Alexeenko, S S Kondratiev, V A Sinebryukhov, S N Volkov, M E Cuneo, A A Kim, Mark L KieferAbstract:We describe the study we have undertaken to evaluate the effect of Component tolerances in obtaining a voltage output flat top for a linear transformer driver (LTD) cavity containing 3rd and 5th harmonic bricks [A. A. Kim et al., in Proc. IEEE Pulsed Power and Plasma Science PPPS2013 (San Francisco, California, USA, 2013), pp. 1354--1356.] and for 30 cavity voltage adder. Our goal was to define the necessary Component Value precision in order to obtain a voltage output flat top with no more than $\ifmmode\pm\else\textpm\fi{}0.5%$ amplitude variation.