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My Computational Science Research 18 July 2014 Nol Chindapol, PhD Candidate Section Computational Science University of Amsterdam Science Park 904, C3156 1098 XH Amsterdam

A brief summary of my scientific contribution

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computational science, multidisciplinary research projects; modelling and simulations; morphogenesis;

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Page 1: A brief summary of my scientific contribution

My Computational Science Research

18 July 2014Nol Chindapol, PhD Candidate

Section Computational ScienceUniversity of AmsterdamScience Park 904, C31561098 XH Amsterdam

Page 2: A brief summary of my scientific contribution

About MeMathematics

& Computer Engineering backgrounds

Passion in Computational science

Page 3: A brief summary of my scientific contribution

Research Projects

Flow & Morphological Plasticity of Coral Growth

Re-Modelling of Purkinje Cells Forest

Page 4: A brief summary of my scientific contribution

Research questions Is morphological plasticity the emergent property of

the external stressors induced by flow constraint to the sessile organisms?

What is the interaction between those constraints and intrinsic property of the organism that leads to self-generation property of the growth forms?

How to quantify plastic response relevant to such constraints?

Page 5: A brief summary of my scientific contribution

Accretive growth model is coupled with FEM modelling software (COMSOL) in order to investigate the plasticity of the resulting growth forms under uni-directional & bi-directional flow

(Tali et al. 2011)

Data Acquisition

Page 6: A brief summary of my scientific contribution

Unidirectional Flow & Accretive Growth Model

Inflo

w

OutFlow

Nutrient Injection C = 1 mol/m3

Object and Ground = Sink; C = 0

Schematic diagram of the simulation (A) A spherical objected represents a simulated object in a first growth step. (B) A simulation phase involves solving the Navier-Stokes equations and the Advection-Diffusion equation. (C) Simulated growth form: the accretive growth process generates new growth layers on top of the previous one.

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Bidirectional Flow & Symmetry perseverance Hypotheses

Schematic diagram of the bi-directional flow simulation coupled with the accretive growth model: (a) initialization phase, (b) the simulation phase consists of two subsequence flow simulation steps. . (c) The solutions of the nutrient transport are acquired and translocated on the surface of the simulated corals. The next growth layer is built on top of the previous one by the local growth function

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Advance Morphometric

Morphometric traits used in our quantitative analysis; (a) local morphometric traits (LMT) are defined as local traits that are not associated with directional bias e.g. branch spacing (br_spacing), branch angle (br_angle), ground angle (g_angle), and diameter of branches (da, db and dc) whereas (b) symmetric-oriented traits (SOT) are those associated with directional bias (h_angle, v_angle, and spd_angle) i.e. requiring the reference axis.

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Bifurcations in nature are locally flat – using data from Neurons & Corals

We do not touch upon this.

Yihawa et al. 2012

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Morphospace of the flow-induced forms

An overview of the morphospace showing the transition from compact colony to thin branching form by means of intrinsic model parameter n, while exposed to the flow condition with increasing Pe number (i.e. decreasing diffusivity D). Red arrows indicate directional variation of flow. . (a) In silico corals group 1 (b) In silico corals group 2(c) In silico corals group 3

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Unpublished Work in Turbulent Flow Simulation

Solved high Reynolds number flow by using the one equation Spalart-Allmaras turbulent model, and coupled with growth model.

Page 12: A brief summary of my scientific contribution

Flow & Morphological Plasticity of Coral Growth

Re-Modelling of Purkinje Cells Forest

Page 13: A brief summary of my scientific contribution

Research Questions

How neuron’s complex morphology is created during nervous development, and eventually leads to the development of neuron forest.

How the interaction of genes mediates dendrite self-avoidance by means of repulsive signal – discriminates self/non self.

The role of traveling waves in Purkinje cells during early developmental stage and their significance in cortical microcircuit wiring.

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Dendritic infrastructureWe simulate the

growing micro tubes i.e. the mechanic property (e.g. contact-mediated) is reduced to a non-volumetric abstraction.

With VTKLines and Tube Filter

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Start

Fint

Contact-mediated

Spatial Gradient

Branch

Re-mode

l

Global Maturation check

For each neuron

Fext

L

stochastic

End

Update Geometry

Li = A set of growth event

Li = Gi (N)

Gi = FIntrinsic + Fextrinsic

Growth Mechanisms at each time step

Page 16: A brief summary of my scientific contribution

Branching and remodeling definition

Let dendritic tree composes of a n number of cell (n=0,…k), in which each cell constitutes of a finite set Li (i=0,..m)of non-bifurcated line; branching mechanism is the addition of cellk+1 to a non-terminated cell k.

Branch?

Re-model

?

; re-modeling, on the other hand denotes an action of trimming terminal cell, by which the line Lm is eliminated, or redefined.

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N=0

N=7

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Simulation of Neuronal Forest Initialization (spherical

objects N=100 at rand(position)

Neurite elongation

Neurite branching (1,2,3 chem) and dendritic shape formation prob(gradients)

Stopping criteria (rule based)

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Thank You!

Please Check coral growth movie 1

Movie 2