The precision with which single cells of Dictyostelium discoideum can locate a source of cyclic AMP

When stimulated by a point source of cyclic AMP, a starved amoeba of Dictyostelium discoideum responds by putting out a hollow balloon-like membrane extension followed by a pseudopod. The effect of the stimulus is to influence the position where either of these protrusions is made on the cell rather than to cause them to be made. Because the pseudopod forms perpendicular to the cell surface, its location is a measure of the precision with which the cell can locate the cAMP source. Cells beyond 1 h of starvation respond non-randomly with a precision that improves steadily thereafter. A cell that is starved for 1-2 h can locate the source accurately 43% of the time; and if starved for 6-7 h, 87% of the time. The response always has a high scatter; population-level heterogeneity reflects stochasticity in single cell behaviour. From the angular distribution of the response its maximum information content is estimated to be 2-3 bits. In summary, we quantitatively demonstrate the stochastic nature of the directional response and the increase in its accuracy over time.

A study on the usefulness of Support Vector Machines for the realtime computational simulation of soft biological organs

Realistic and realtime computational simulation of soft biological organs (e.g., liver, kidney) is necessary when one tries to build a quality surgical simulator that can simulate surgical procedures involving these organs. Since the realistic simulation of these soft biological organs should account for both nonlinear material behavior and large deformation, achieving realistic simulations in realtime using continuum mechanics based numerical techniques necessitates the use of a supercomputer or a high end computer cluster which are costly. Hence there is a need to employ soft computing techniques like Support Vector Machines (SVMs) which can do function approximation, and hence could achieve physically realistic simulations in realtime by making use of just a desktop computer. Present work tries to simulate a pig liver in realtime. Liver is assumed to be homogeneous, isotropic, and hyperelastic. Hyperelastic material constants are taken from the literature. An SVM is employed to achieve realistic simulations in realtime, using just a desktop computer. The code for the SVM is obtained from [1]. The SVM is trained using the dataset generated by performing hyperelastic analyses on the liver geometry, using the commercial finite element software package ANSYS. The methodology followed in the present work closely follows the one followed in [2] except that [2] uses Artificial Neural Networks (ANNs) while the present work uses SVMs to achieve realistic simulations in realtime. Results indicate the speed and accuracy that is obtained by employing the SVM for the targeted realistic and realtime simulation of the liver.

An enthalpy-based model of dendritic growth in a convecting binary alloy melt

Purpose-In the present work, a numerical method, based on the well established enthalpy technique, is developed to simulate the growth of binary alloy equiaxed dendrites in presence of melt convection. The paper aims to discuss these issues. Design/methodology/approach-The principle of volume-averaging is used to formulate the governing equations (mass, momentum, energy and species conservation) which are solved using a coupled explicit-implicit method. The velocity and pressure fields are obtained using a fully implicit finite volume approach whereas the energy and species conservation equations are solved explicitly to obtain the enthalpy and solute concentration fields. As a model problem, simulation of the growth of a single crystal in a two-dimensional cavity filled with an undercooled melt is performed. Findings-Comparison of the simulation results with available solutions obtained using level set method and the phase field method shows good agreement. The effects of melt flow on dendrite growth rate and solute distribution along the solid-liquid interface are studied. A faster growth rate of the upstream dendrite arm in case of binary alloys is observed, which can be attributed to the enhanced heat transfer due to convection as well as lower solute pile-up at the solid-liquid interface. Subsequently, the influence of thermal and solutal Peclet number and undercooling on the dendrite tip velocity is investigated. Originality/value-As the present enthalpy based microscopic solidification model with melt convection is based on a framework similar to popularly used enthalpy models at the macroscopic scale, it lays the foundation to develop effective multiscale solidification.

Insight into instabilities in burning droplets

The complex multiscale physics of nano-particle laden functional droplets in a reacting environment is of fundamental and applied significance for a wide variety of applications ranging from thermal sprays to pharmaceutics to modern day combustors using new brands of bio-fuels. Formation of homogenous nucleated bubbles at the superheat limit inside vaporizing droplets (with or without nanoparticles) represents an unstable system. Here we show that self-induced boiling in burning functional pendant droplets can produce severe volumetric shape oscillations. Internal pressure build-up due to ebullition activity ejects bubbles from the droplet domain causing undulations on the droplet surface and oscillations in bulk. Through experiments, we establish that the degree of droplet deformation depends on the frequency and intensity of these bubble expulsion events. In a distinct regime of single isolated bubble residing in the droplet, however, pre-ejection transient time is identified by Darrieus-Landau evaporative instability, where bubble-droplet system behaves as a synchronized driver-driven system with bulk bubble-shape oscillations being imposed on the droplet. The agglomeration of nanophase additives modulates the flow structures within the droplet and also influences the bubble inception and growth leading to different levels of instabilities. (C) 2014 AIP Publishing LLC.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 `high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

NUMERICAL SIMULATIONS OF LIQUID JET BREAK UP IN A CROSSFLOW

Atomization is the process of disintegration of a liquid jet into ligaments and subsequently into smaller droplets. A liquid jet injected from a circular orifice into cross flow of air undergoes atomization primarily due to the interaction of the two phases rather than an intrinsic break up. Direct numerical simulation of this process resolving the finest droplets is computationally very expensive and impractical. In the present study, we resort to multiscale modelling to reduce the computational cost. The primary break up of the liquid jet is simulated using Gerris, an open source code, which employs Volume-of-Fluid (VOF) algorithm. The smallest droplets formed during primary atomization are modeled as Lagrangian particles. This one-way coupling approach is validated with the help of the simple test case of tracking a particle in a Taylor-Green vortex. The temporal evolution of the liquid jet forming the spray is captured and the flattening of the cylindrical liquid column prior to breakup is observed. The size distribution of the resultant droplets is presented at different distances downstream from the location of injection and their spatial evolution is analyzed.

Soft-spring wall based non-periodic boundary conditions for non-equilibrium molecular dynamics of dense fluids

Non-equilibrium molecular dynamics (MD) simulations require imposition of non-periodic boundary conditions (NPBCs) that seamlessly account for the effect of the truncated bulk region on the simulated MD region. Standard implementation of specular boundary conditions in such simulations results in spurious density and force fluctuations near the domain boundary and is therefore inappropriate for coupled atomistic-continuum calculations. In this work, we present a novel NPBC model that relies on boundary atoms attached to a simple cubic lattice with soft springs to account for interactions from particles which would have been present in an untruncated full domain treatment. We show that the proposed model suppresses the unphysical fluctuations in the density to less than 1% of the mean while simultaneously eliminating spurious oscillations in both mean and boundary forces. The model allows for an effective coupling of atomistic and continuum solvers as demonstrated through multiscale simulation of boundary driven singular flow in a cavity. The geometric flexibility of the model enables straightforward extension to nonplanar complex domains without any adverse effects on dynamic properties such as the diffusion coefficient. (c) 2015 AIP Publishing LLC.

Smaller is Plastic: Polymorphic Structures and Mechanism of Deformation in Nanoscale hcp Metals

Using first-principles calculations, we establish the existence of highly-stable polymorphs of hcp metals (Ti, Mg, Be, La and Y) with nanoscale structural periodicity. They arise from heterogeneous deformation of the hcp structure occurring in response to large shear stresses localized at the basal planes separated by a few nanometers. Through Landau theoretical analysis, we show that their stability derives from nonlinear coupling between strains at different length scales. Such multiscale hyperelasticity and long-period structures constitute a new mechanism of size-dependent plasticity and its enhancement in nanoscale hcp metals.

An Optimizing Code Generator for a Class of Lattice-Boltzmann Computations

The Lattice-Boltzmann method (LBM), a promising new particle-based simulation technique for complex and multiscale fluid flows, has seen tremendous adoption in recent years in computational fluid dynamics. Even with a state-of-the-art LBM solver such as Palabos, a user has to still manually write the program using library-supplied primitives. We propose an automated code generator for a class of LBM computations with the objective to achieve high performance on modern architectures. Few studies have looked at time tiling for LBM codes. We exploit a key similarity between stencils and LBM to enable polyhedral optimizations and in turn time tiling for LBM. We also characterize the performance of LBM with the Roofline performance model. Experimental results for standard LBM simulations like Lid Driven Cavity, Flow Past Cylinder, and Poiseuille Flow show that our scheme consistently outperforms Palabos-on average by up to 3x while running on 16 cores of an Intel Xeon (Sandybridge). We also obtain an improvement of 2.47x on the SPEC LBM benchmark.

Spectral solutions to the Korteweg-de-Vries and nonlinear Schrodinger equations

In this paper, we present the solutions of 1-D and 2-D non-linear partial differential equations with initial conditions. We approach the solutions in time domain using two methods. We first solve the equations using Fourier spectral approximation in the spatial domain and secondly we compare the results with the approximation in the spatial domain using orthogonal functions such as Legendre or Chebyshev polynomials as their basis functions. The advantages and the applicability of the two different methods for different types of problems are brought out by considering 1-D and 2-D nonlinear partial differential equations namely the Korteweg-de-Vries and nonlinear Schrodinger equation with different potential function. (C) 2015 Elsevier Ltd. All rights reserved.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.