scholarly journals Cellular signaling beyond the Wiener-Kolmogorov limit

2021 ◽  
Author(s):  
Casey Weisenberger ◽  
David Hathcock ◽  
Michael Hinczewski
Keyword(s):  
Numerical Solutions ◽  
Metabolic Cost ◽  
Biochemical Networks ◽  
Signaling Cascades ◽  
Performance Limits ◽  
Signaling Systems ◽  
Noise Filter ◽  
Engineering Problems ◽  
Multi Level ◽  
Continuum Description

Accurate propagation of signals through stochastic biochemical networks involves significant expenditure of cellular resources. The same is true for regulatory mechanisms that suppress fluctuations in biomolecular populations. Wiener-Kolmogorov (WK) optimal noise filter theory, originally developed for engineering problems, has recently emerged as a valuable tool to estimate the maximum performance achievable in such biological systems for a given metabolic cost. However, WK theory has one assumption that potentially limits its applicability: it relies on a linear, continuum description of the reaction dynamics. Despite this, up to now no explicit test of the theory in nonlinear signaling systems with discrete molecular populations has ever seen performance beyond the WK bound. Here we report the first direct evidence the bound being broken. To accomplish this, we develop a theoretical framework for multi-level signaling cascades, including the possibility of feedback interactions between input and output. In the absence of feedback, we introduce an analytical approach that allows us to calculate exact moments of the stationary distribution for a nonlinear system. With feedback, we rely on numerical solutions of the system's master equation. The results show WK violations in two common network motifs: a two-level signaling cascade and a negative feedback loop. However the magnitude of the violation is biologically negligible, particularly in the parameter regime where signaling is most effective. The results demonstrate that while WK theory does not provide strict bounds, its predictions for performance limits are excellent approximations, even for nonlinear systems.

scholarly journals Data Driven Solutions and Discoveries in Mechanics Using Physics Informed Neural Network

2020 ◽  
Author(s):  
Qi Zhang ◽  
Yilin Chen ◽  
Ziyi Yang
Keyword(s):  
Neural Network ◽  
Differential Equations ◽  
Automatic Differentiation ◽  
Numerical Solutions ◽  
Data Driven ◽  
Attractive Alternative ◽  
The Finite Element Method ◽  
The Neural Network ◽  
Engineering Problems ◽  
Free Parameters

Deep learning has achieved remarkable success in diverse computer science applications, however, its use in other traditional engineering fields has emerged only recently. In this project, we solved several mechanics problems governed by differential equations, using physics informed neural networks (PINN). The PINN embeds the differential equations into the loss of the neural network using automatic differentiation. We present our developments in the context of solving two main classes of problems: data-driven solutions and data-driven discoveries, and we compare the results with either analytical solutions or numerical solutions using the finite element method. The remarkable achievements of the PINN model shown in this report suggest the bright prospect of the physics-informed surrogate models that are fully differentiable with respect to all input coordinates and free parameters. More broadly, this study shows that PINN provides an attractive alternative to solve traditional engineering problems.

Adaptive Numerical Modeling of Engineering Problems Using Hierarchical Fup Basis Functions and Control Volume IsoGeometric Analysis

2021 ◽  
Author(s):  
◽  
Grgo Kamber ◽  
Keyword(s):  
Isogeometric Analysis ◽  
Numerical Solutions ◽  
Control Volume ◽  
Spatial Scales ◽  
Basis Functions ◽  
Approximation Properties ◽  
Unified Framework ◽  
B Splines ◽  
Engineering Problems ◽  
Resolution Level

The main objective of this thesis is to utilize the powerful approximation properties of Fup basis functions for numerical solutions of engineering problems with highly localized steep gradients while controlling spurious numerical oscillations and describing different spatial scales. The concept of isogeometric analysis (IGA) is presented as a unified framework for multiscale representation of the geometry and solution. This fundamentally high-order approach enables the description of all fields as continuous and smooth functions by using a linear combination of spline basis functions. Classical IGA usually employs Galerkin or collocation approach using B-splines or NURBS as basis functions. However, in this thesis, a third concept in the form of control volume isogeometric analysis (CV-IGA) is used with Fup basis functions which represent infinitely smooth splines. Novel hierarchical Fup (HF) basis functions is constructed, enabling a local hp-refinement such that they can replace certain basis functions at one resolution level with new basis functions at the next resolution level that have a smaller length of the compact support (h-refinement), but also higher order (p-refinement). This hp-refinement property enables spectral convergence which is significant improvement in comparison to the hierarchical truncated B-splines which enable h-refinement and polynomial convergence. Thus, in domain zones with larger gradients, the algorithm uses smaller local spatial scales, while in other region, larger spatial scales are used, controlling the numerical error by the prescribed accuracy. The efficiency and accuracy of the adaptive algorithm is verified with some classic 1D and 2D benchmark test cases with application to the engineering problems with highly localized steep gradients and advection-dominated problems.

Cellular oxygen sensing by mitochondria: old questions, new insight

2000 ◽  
Vol 88 (5) ◽  
pp. 1880-1889 ◽  
Author(s):  
Navdeep S. Chandel ◽  
Paul T. Schumacker
Keyword(s):  
Second Messengers ◽  
Cell Types ◽  
Tissue Level ◽  
Cellular Level ◽  
Signaling Cascades ◽  
Adaptive Responses ◽  
Signaling Systems ◽  
Multiple Sensors ◽  
Cell Death Pathways ◽  
Cellular Oxygen

Hypoxia elicits a variety of adaptive responses at the tissue level, at the cellular level, and at the molecular level. A physiological response to hypoxia requires the existence of an O2sensor coupled to a signal transduction system, which in turn activates the functional response. Although much has been learned about the signaling systems activated by hypoxia, no consensus exists regarding the nature of the underlying O2sensor or whether multiple sensors exist. Among previously considered mechanisms, heme proteins have been suggested to undergo allosteric modification in response to O2binding or release at different [Formula: see text] levels. Other studies suggest that ion channels may change conductance as a function of[Formula: see text], allowing them to signal the onset of hypoxia. Still other studies suggest that NADPH oxidase may decrease its generation of reactive O2species (ROS) during hypoxia. Recent data suggest that mitochondria may function as O2sensors by increasing their generation of ROS during hypoxia. These oxidant signals appear to act as second messengers in the adaptive responses to hypoxia in a variety of cell types. Such observations contribute to a growing awareness that mitochondria do more than just generate ATP, in that they initiate signaling cascades involved in adaptive responses to hypoxia and that they participate in the control of cell death pathways.

Transient thermal elastohydrodynamic lubrication of point contacts subjected to normal vibration

2016 ◽  
Vol 68 (5) ◽  
pp. 536-547
Author(s):  
Jianjun Zhang ◽  
Qibo Ni ◽  
Jing Wang ◽  
Feng Guo
Keyword(s):  
Film Thickness ◽  
Newtonian Fluid ◽  
Normal Vibration ◽  
Numerical Solutions ◽  
Elastohydrodynamic Lubrication ◽  
Vibration Period ◽  
Content Type ◽  
Multi Level ◽  
Vertical Vibrations ◽  
Thermal Ehl

Purpose Vibration exists widely in all machineries working under high speed. The unpredictability of vibration and the change of the relative surface speed may result in difficulties in the elastohydrodynamic lubrication (EHL) analysis. By far, few studies on EHL relating to vibration have been published. The purpose of the present study is to investigate the effect of the vertical vibrations and the influence of temperature on the thermal EHL contacts. Design/methodology/approach The lubricant was assumed to be Newtonian fluid. The time-dependent numerical solutions were achieved instant after instant in each period of the vibration. At each instant, the pressure field was solved with a multi-level technique, the surface deformation was solved with a multi-level multi-integration method and the temperature filed was solved with a finite different scheme through a sweeping progress. The periodic error was checked at each end of the vibration period until the responses of pressure, film thickness and temperature were all periodic functions with the frequency of the roller’s vibrations. Findings The results reveal that normal vibration produces little drastic change of pressure, film thickness and temperature in EHL. Under some conditions, the vibrations of the roller can produce transient dimples within the contact conjunction. It is also showed that the lubrication in the same sliding is better than the opposite sliding. Research limitations/implications For the unpredictability of vibration, it is not easy to do the experiment to realize a real comparison with numerical results. The reach does not show any verification and consider the effect of non-Newtonian fluid. Originality/value The effect of the vertical vibrations on the thermal EHL point contact hast been studied. The effects of both the amplitude and the frequency on the predicted load-carrying capacity, minimum film thickness, center pressure and center temperature and the coefficient of friction were investigated. The role of the thermal effect was given.

scholarly journals Eigenvalues and Eigenvectors for 3×3 Symmetric Matrices: An Analytical Approach

2020 ◽  
pp. 106-118
Author(s):  
Abu Bakar Siddique ◽  
Tariq A. Khraishi
Keyword(s):  
Analytical Solutions ◽  
Analytical Approach ◽  
Numerical Solutions ◽  
Linear Equations ◽  
Symmetric Matrices ◽  
Matrix Equations ◽  
Eigenvalues And Eigenvectors ◽  
Engineering Problems ◽  
The Matrix ◽  
Research Problems

Research problems are often modeled using sets of linear equations and presented as matrix equations. Eigenvalues and eigenvectors of those coupling matrices provide vital information about the dynamics/flow of the problems and so needs to be calculated accurately. Analytical solutions are advantageous over numerical solutions because numerical solutions are approximate in nature, whereas analytical solutions are exact. In many engineering problems, the dimension of the problem matrix is 3 and the matrix is symmetric. In this paper, the theory behind finding eigenvalues and eigenvectors for order 3×3 symmetric matrices is presented. This is followed by the development of analytical solutions for the eigenvalues and eigenvectors, depending on patterns of the sparsity of the matrix. The developed solutions are tested against some examples with numerical solutions.

Application of Opposition Based Improved Firefly Algorithm in Multi-Level Image Thresholding of Color Images using Between Class Variance

2019 ◽  
Vol 12 ◽  
Author(s):  
Abhay Sharma ◽  
Rekha Chaturvedi ◽  
Umesh Dwivedi ◽  
Sandeep Kumar
Keyword(s):  
Image Segmentation ◽  
Firefly Algorithm ◽  
Color Image ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Image Thresholding ◽  
Opposition Based Learning ◽  
Improved Firefly Algorithm ◽  
Engineering Problems ◽  
Multi Level

Background: Image segmentation is the fundamental step in image processing. Multi-level image segmentation for color image is a very complex and time-consuming process which can be defined as non-deterministic optimization problem. Nature inspired meta-heuristics are best suited to solve such problems. Though several algorithms exist; a modification to suit certain class of engineering problems is always welcome. Objective: This paper provides a modified firefly algorithm and its uses for multilevel thresholding in colored images. Opposition based learning is incorporated in the firefly algorithm to improve convergence rate and robustness. Between class variance method of thresholding is used to formulate the objective function. Method: Numerous benchmark images are tested for evaluating the performance of proposed method. Results: The Experimental results validate the performance of Opposition based improved firefly algorithm (OBIFA) for multi-level image segmentation using peak signal to noise ratio (PSNR) and structured similarity index metric (SSIM)parameter. Conclusion: The OBIFA algorithm is best suited for multilevel image thresholding. It provides best results compared to Darwinian Particle Swarm Optimization (DPSO) and Electro magnetism optimization (EMO) for the parameter: convergence speed, PSNR and SSIM values.

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