Exodus Method Research Articles

Lipidomic identification of urinary extracellular vesicles for non-alcoholic steatohepatitis diagnosis

Background and AimsNon-alcoholic fatty liver disease (NAFLD) is a usual chronic liver disease and lacks non-invasive biomarkers for the clinical diagnosis and prognosis. Extracellular vesicles (EVs), a group of heterogeneous small membrane-bound vesicles, carry proteins and nucleic acids as promising biomarkers for clinical applications, but it has not been well explored on their lipid compositions related to NAFLD studies. Here, we investigate the lipid molecular function of urinary EVs and their potential as biomarkers for non-alcoholic steatohepatitis (NASH) detection.MethodsThis work includes 43 patients with non-alcoholic fatty liver (NAFL) and 40 patients with NASH. The EVs of urine were isolated and purified using the EXODUS method. The EV lipidomics was performed by LC-MS/MS. We then systematically compare the EV lipidomic profiles of NAFL and NASH patients and reveal the lipid signatures of NASH with the assistance of machine learning.ResultsBy lipidomic profiling of urinary EVs, we identify 422 lipids mainly including sterol lipids, fatty acyl lipids, glycerides, glycerophospholipids, and sphingolipids. Via the machine learning and random forest modeling, we obtain a biomarker panel composed of 4 lipid molecules including FFA (18:0), LPC (22:6/0:0), FFA (18:1), and PI (16:0/18:1), that can distinguish NASH with an AUC of 92.3%. These lipid molecules are closely associated with the occurrence and development of NASH.ConclusionThe lack of non-invasive means for diagnosing NASH causes increasing morbidity. We investigate the NAFLD biomarkers from the insights of urinary EVs, and systematically compare the EV lipidomic profiles of NAFL and NASH, which holds the promise to expand the current knowledge of disease pathogenesis and evaluate their role as non-invasive biomarkers for NASH diagnosis and progression.

Solution of Axisymmetric Potential Problem in Oblate Spheroid Using the Exodus Method

This paper presents the use of Exodus method for computing potential distribution within a conducting oblate spheroidal system. An explicit finite difference method for solving Laplace’s equation in oblate spheroidal coordinate systems for an axially symmetric geometry was developed. This was used to determine the transition probabilities for the Exodus method. A strategy was developed to overcome the singularity problems encountered in the oblate spheroid pole regions. The potential computation results obtained correlate with those obtained by exact solution and explicit finite difference methods.

Applying the Exodus method to calculate the set of impulse response functions of a wall

The article presents how the Exodus method can be used to simulate heat transfer through opaque building components. The components are modelled as Linear Time Invariant systems described by their thermal impulse response functions. This method can be used to determine the temperature at any point inside the wall. Although the point can be selected arbitrarily, the research was focused on the inner surface of the wall. This temperature is particularly helpful in determining heat fluxes transferring external walls of the building in transient conditions. It can be also used to obtain the average radiation temperature in the heated rooms in order to estimate the variable thermal comfort conditions. The results of the Exodus method were verified by a comparison with the ones obtained from a more advanced simulation software Ansys CFX. The proposed method allowed for much faster calculations while preserving the results quality.

Potential Distribution Computation in Conducting Prolate Spheroidal Shells Using the Exodus Method

This paper presents the use of the Exodus method to compute the potential distribution in a conducting prolate spheroidal shell. The transition probabilities for the Exodus method simulation were obtained from the finite-difference scheme transformation of the prolate spheroid Laplace equation. This method is independent of the random number generation from the computing facility and gives more accurate results than the fixed random walk Monte Carlo method. The results obtained matched perfectly with those obtained by using an exact solution and explicit finite-difference solution method.

Modeling of Thermal Spraying Heat Transfer Processes by Exodus Stochastic Method

This article deals with the application of the stochastic Exodus method for modelling of thermal spraying heat transfer processes and for solving direct and indirect problems. The Exodus stochastic method has an advantage in straightforward solving of the transient inverse heat transfer multi-dimensional problems over other methods based on iterative fittings procedures used for example by finite element methods (FEM). Theoretical background of the method is introduced. Application capabilities of the method are shown on the example of high velocity oxygen fuel thermal spraying heat transfer process analysis. Comparisons with results of FEM computational method application are presented.

Exodus stochastic method application in the continuous reheating furnace control system

A computer simulation model of billet heating process in continuous pusher‐type furnace is presented. The Exodus stochastic simulation method is used to solve the heat conduction partial differential equation. This paper deals with the application of the Exodus method in the furnace optimal heating‐control system. A comparison of the computed results with results of the measurement is presented to show the capabilities of the simulation model.

Applying the Exodus method to solve Poisson's equation

In this paper, the Exodus method is applied in solving Poisson's equation for problems involving rectangular and axisymmetric solution regions. The Exodus method is a numerical technique which is capable of providing an "exact" solution. Although the method is probabilistic in its approach, it is not subject to randomness like other Monte Carlo techniques because it does not involve the use of a pseudo-random generation subroutine.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A BOUNDARY-DISPATCH MONTE CARLO (EXODUS) METHOD FOR ANALYSIS OF CONDUCTIVE HEAT TRANSFER PROBLEMS

A boundary-dispatch Monte Carlo (Exodus) method, in which the particles are dispatched from the boundaries of a conductive medium or source of heat, is developed. A fixed number of particles are dispatched from a boundary node to the nearest internal node. These particles make random walks within the medium similar to that of the conventional Monte Carlo method. Once a particle visits an internal node, a number equal to the temperature of the boundary node from which particles are dispatched is added to a counter. Performing this procedure for all boundary nodes, the temperature of a node can be determined by dividing the flag, or the counter, of this node by the total number of particle visits to this node. Two versions of the boundary-dispatch method (BDM) are presented, multispecies and bispecies BDM. The results of bispecies BDM based on the Exodus dispatching method compare well with the Gauss-Seidel method in both accuracy and computational time. Its computational time is much less than the shrinkin...

Solution of Dirichlet problems by the Exodus method

Applying the Exodus method to Dirichlet problems in rectangular and axisymmetric solution regions is proposed. The stochastic technique is illustrated with specific practical applications to the solution of Laplace's equation. Although the method is probabilistic in its approach, it is not subject to randomness as are the other Monte Carlo techniques because it does not involve the use of a pseudo-random generation subroutine. The method provides a more accurate solution in less amount of time compared with the fixed random walk. It is also found that the accuracy of the Exodus method is comparable to that of the finite difference method.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Heat conduction with internal sources by modified Monte Carlo methods

To estimate local steady state temperatures in heat generating reactor components, several efficient modified Monte Carlo methods have been developed. One of these is shown to be the theoretical optimum (zero variance) method for internal source problems. Numerical studies of a simple two-dimensional problem confirm the expected improvements in efficiency over classical Monte Carlo, and permit a comparison with the Exodus method.