Volumetric and multispectral DWI near metallic implants using a non‐linear phase Carr‐Purcell‐Meiboom‐Gill diffusion preparation

2022 ◽  
Author(s):  
Philip K. Lee ◽  
Daehyun Yoon ◽  
Jesse K. Sandberg ◽  
Shreyas S. Vasanawala ◽  
Brian A. Hargreaves
Keyword(s):  
Linear Phase ◽  
Metallic Implants ◽  
Non Linear

scholarly journals Cosmic flows and the expansion of the local Universe from non-linear phase–space reconstructions

2016 ◽  
Vol 456 (4) ◽  
pp. 4247-4255 ◽  
Author(s):  
Steffen Heß ◽  
Francisco-Shu Kitaura
Keyword(s):  
Phase Space ◽  
Cold Dark Matter ◽  
Initial Conditions ◽  
Hubble Constant ◽  
Linear Phase ◽  
Local Universe ◽  
Non Linear ◽  
Galaxy Sample ◽  
Fisher Relation ◽  
The Impact

Abstract In this work, we investigate the impact of cosmic flows and density perturbations on Hubble constant H0 measurements using non-linear phase–space reconstructions of the Local Universe (LU). In particular, we rely on a set of 25 precise constrained N-body simulations based on Bayesian initial conditions reconstructions of the LU using the Two-Micron Redshift Survey galaxy sample within distances of about 90  h−1 Mpc. These have been randomly extended up to volumes enclosing distances of 360  h−1 Mpc with augmented Lagrangian perturbation theory (750 simulations in total), accounting in this way for gravitational mode coupling from larger scales, correcting for periodic boundary effects, and estimating systematics of missing attractors (σlarge = 134  s−1 km). We report on Local Group (LG) speed reconstructions, which for the first time are compatible with those derived from cosmic microwave background-dipole measurements: |vLG| = 685 ± 137  s−1 km. The direction (l, b) = (260$_{.}^{\circ}$5 ± 13$_{.}^{\circ}$3, 39$_{.}^{\circ}$1 ± 10$_{.}^{\circ}$4) is found to be compatible with the observations after considering the variance of large scales. Considering this effect of large scales, our local bulk flow estimations assuming a Λ cold dark matter model are compatible with the most recent estimates based on velocity data derived from the Tully–Fisher relation. We focus on low-redshift supernova measurements out to 0.01 < z < 0.025, which have been found to disagree with probes at larger distances. Our analysis indicates that there are two effects related to cosmic variance contributing to this tension. The first one is caused by the anisotropic distribution of supernovae, which aligns with the velocity dipole and hence induces a systematic boost in H0. The second one is due to the inhomogeneous matter fluctuations in the LU. In particular, a divergent region surrounding the Virgo Supercluster is responsible for an additional positive bias in H0. Taking these effects into account yields a correction of ΔH0 = -1.76 ± 0.21  s− 1 km Mpc− 1, thereby reducing the tension between local probes and more distant probes. Effectively H0 is lower by about 2 per cent.

scholarly journals Non-linear forecasting of the state of a socio-eco-oriented innovative economy in the conditions of systemic crises

2019 ◽  
Vol 65 ◽  
pp. 06007
Author(s):  
Sultan Ramazanov ◽  
Oleksandr Chernyak ◽  
Bogdan Tishkov ◽  
Renat Ahmedov ◽  
Oleksandr Honcharenko
Keyword(s):  
Complex Systems ◽  
Growth Dynamics ◽  
The State ◽  
Linear Phase ◽  
Dynamics Model ◽  
Modeling And Forecasting ◽  
Non Linear ◽  
Innovative Economy ◽  
Synergetic Model ◽  
Systemic Crises

The paper deals with the problem of sustainable development and innovative integral modeling and forecasting approach in the management of technogenic objects and processes (TOP) as a system of socio-eco-economic and humanitarian type (SEEH). Based on the use of information and innovation technologies in order to forecast the non-linear dynamics of eco-economic and socio-humanitarian systems, integrated stochastic models of objects and processes were developed and studied, suitable for the conditions of systemic crises. The paper handles the aspect of integration of 4 business and functioning areas of the modern complex systems. It proposes a general conceptual integrated model, generalized synergetic model of dynamics, considering different uncertainty (stochastic and chaotic components). The paper examines the aspects of integration of multiple business areas and sectors of the modern complex systems functioning and developing under the present conditions of non-linearity, instability and crises. An integrated stochastic non-linear phase-space growth dynamics model was developed and studied to forecast the development of the state of an innovative economy. The paper looks into the aspects of activity management of the modern complex systems functioning and developing under the present conditions of instability.

A new energy dissipative cable bracing system

2019 ◽  
Vol 22 (14) ◽  
pp. 3134-3146
Author(s):  
Saman Bagheri ◽  
Siamak S Shishvan ◽  
Majid Barghian ◽  
Behzad Baniahmad
Keyword(s):  
Analytical Solution ◽  
Frictional Contact ◽  
Element Model ◽  
Linear Phase ◽  
Non Linear ◽  
New Energy ◽  
The Coefficient Of Friction ◽  
Geometrical Effects ◽  
Two Phases ◽  
Bracing System

A special type of cable bracing system comprising a pre-stressed cable and a drum interacting via frictional contact is proposed for lateral resistance of structures, and an analytical solution for the response of this system is developed. The response of the system is highly non-linear due to the existence of frictional contact as well as geometrical effects and it consists of two phases: a linear phase before gross slipping with a relatively high stiffness followed by a non-linear phase with gradually increasing stiffness (i.e. hardening). However, the analytical solution is capable of capturing the whole response with a remarkable accuracy when compared to the finite element model of the system constructed for cross-validation. This analytical solution facilitates studying the effects of various parameters on the behaviour of the system, namely, the coefficient of friction, pre-strain and geometrical aspect ratio. These parameters can be arbitrarily set to achieve a desirable behaviour of the system. The proposed system is capable of undergoing large deformations with symmetrical and stable hysteretic behaviour. The effectiveness of the proposed device in reducing the seismic responses of a building frame is examined using a simplified numerical model.

scholarly journals Non-linear complex principal component analysis of nearshore bathymetry

2005 ◽  
Vol 12 (5) ◽  
pp. 661-670 ◽  
Author(s):  
S. S. P. Rattan ◽  
B. G. Ruessink ◽  
W. W. Hsieh
Keyword(s):  
Principal Component Analysis ◽  
Data Structure ◽  
Linear Method ◽  
Principal Component ◽  
Component Analysis ◽  
Dimensional Structure ◽  
Linear Phase ◽  
Linear Complex ◽  
Amplitude Variability ◽  
Non Linear

Abstract. Complex principal component analysis (CPCA) is a useful linear method for dimensionality reduction of data sets characterized by propagating patterns, where the CPCA modes are linear functions of the complex principal component (CPC), consisting of an amplitude and a phase. The use of non-linear methods, such as the neural-network based circular non-linear principal component analysis (NLPCA.cir) and the recently developed non-linear complex principal component analysis (NLCPCA), may provide a more accurate description of data in case the lower-dimensional structure is non-linear. NLPCA.cir extracts non-linear phase information without amplitude variability, while NLCPCA is capable of extracting both. NLCPCA can thus be viewed as a non-linear generalization of CPCA. In this article, NLCPCA is applied to bathymetry data from the sandy barred beaches at Egmond aan Zee (Netherlands), the Hasaki coast (Japan) and Duck (North Carolina, USA) to examine how effective this new method is in comparison to CPCA and NLPCA.cir in representing propagating phenomena. At Duck, the underlying low-dimensional data structure is found to have linear phase and amplitude variability only and, accordingly, CPCA performs as well as NLCPCA. At Egmond, the reduced data structure contains non-linear spatial patterns (asymmetric bar/trough shapes) without much temporal amplitude variability and, consequently, is about equally well modelled by NLCPCA and NLPCA.cir. Finally, at Hasaki, the data structure displays not only non-linear spatial variability but also considerably temporal amplitude variability, and NLCPCA outperforms both CPCA and NLPCA.cir. Because it is difficult to know the structure of data in advance as to which one of the three models should be used, the generalized NLCPCA model can be used in each situation.

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