Belgacem Ben Youssef

Regular Paper: Parallel Implementation of a Cellular Automaton Modeling the Growth of Three-Dimensional Tissues

A promising approach for treating tissue or organ failure involves the use of bioartificial tissue substitutes grown in scaffolds with appropriate structure and shape. Currently, however, the engineering of tissue substitutes is a long and costly process based exclusively on experimentation. Predictive computer models can greatly reduce the development costs of tissue-engineered therapies by enabling scientists to rapidly evaluate the effect of system parameters on the growth rates and quality of regenerated tissues. We report here the parallel implementation of a three-dimensional model that employs cellular automata to describe the dynamic behavior of a population of mammalian cells that migrate, interact and proliferate to generate new tissues. The simulator uses MPI for interprocessor communication and is suitable for distributed memory multi-computers. Three parallel algorithms are developed to approximate the sequential algorithm describing this dynamic process of tissue growth. The parallel algorithms progressively relax the correctness requirements using different approaches to handle the cells that either move/ divide in the boundary layers of processors or cross sub-domain boundaries. Finally, a systematic study is carried out to evaluate the accuracy and performance of these algorithms.

P-RnaPredict-a parallel evolutionary algorithm for RNA folding: effects of pseudorandom number quality

This paper presents a fully parallel version of RnaPredict, a genetic algorithm (GA) for RNA secondary structure prediction. The research presented here builds on previous work and examines the impact of three different pseudorandom number generators (PRNGs) on the GAs performance. The three generators tested are the C standard library PRNG RAND, a parallelized multiplicative congruential generator (MCG), and a parallelized Mersenne Twister (MT). A fully parallel version of RnaPredict using the Message Passing Interface (MPI) was implemented on a 128-node Beowulf cluster. The PRNG comparison tests were performed with known structures whose sequences are 118, 122, 468, 543, and 556 nucleotides in length. The effects of the PRNGs are investigated and the predicted structures are compared to known structures. Results indicate that P-RnaPredict demonstrated good prediction accuracy, particularly so for shorter sequences.

Simulation of Multiple Cell Population Dynamics Using a 3-D Cellular Automata Model for Tissue Growth

In this paper, the authors describe a computational model for the growth of multicellular tissues using a discrete approach based on cellular automata to simulate the tissue growth rates and population dynamics of multiple populations of proliferating and migrating cells. Each population of cells has its own division, motion, collision, and aggregation characteristics. These random dynamic processes can be modeled by appropriately choosing the governing rules of the state transitions of each computational site. This extended model contains a number of system parameters that allow their effects on the volume coverage, the overall tissue growth rate, and some other aspects of cell behavior like the average speed of locomotion to be explored. These discrete systems provide an alternative approach to continuous models for the purpose of describing the temporal dynamics of complex systems.

Simulation of Cell Population Dynamics Using 3-D Cellular Automata

We present the simulation results of a comprehensive model based on cellular automata that describes the dynamic behavior of a population of mammalian cells that migrate and proliferate to fill a three-dimensional scaffold. The model is applied to study how cell migration and the density or spatial distribution of seed cells affect the cell proliferation rates. A large number of system parameters allow for a detailed simulation of the population dynamics of migrating and proliferating cells. This permits the exploration of the relative influence of these parameters on the proliferation rate and some other aspects of cell behavior such as the average speed of locomotion and the collision rate.

A 3-d computational model for multicellular tissue growth

We report the development of a computational model for the growth of multicellular tissues using a discrete approach based on cellular automata to study the tissue growth rates and population dynamics of two different populations of migrating and proliferating mammalian cells. Cell migration is modeled using a discrete-time Markov chain approach and each population of cells has its own division and motion characteristics that are based on experimental data. A large number of parameters allow for a detailed study of the population dynamics. This permits the exploration of the relative influence of various system parameters on the proliferation rate and some other aspects of cell behavior such as average speed of locomotion

Enhanced Pixel-Based Video Frame Interpolation Algorithms

In this paper, we compare three motion compensated interpolation (MCI) algorithms: adjacent-frame motion compensated interpolation (AFI), wide-span motion compensated interpolation (WS-TH), and wide-span motion compensated interpolation with spatial hinting (WS-TH+SH). The latter represents an extension to WS-TH by adding spatial hinting to the generation of motion vectors. The methods are quantitatively compared with the objective of optimizing interpolated frame quality relative to control interpolated frames. This is important because for high-resolution large flat-panel displays, frame transition coherence becomes a critical factor in assessing the quality of the users viewing experience. To enhance MCI, the encoder should attempt to exploit long-term statistical dependencies, precisely estimate motion by modeling the motion vector field, and superimpose efficient prediction/interpolation algorithms. Computer simulations using artificially generated video sequences demonstrate the consistent advantage of both WS- TH and WS-TH+SH over AFI under increasingly complex source scenes and chaotic occlusion conditions.

Interpolation techniques for the artificial construction of video slow motion in the postproduction process

Motion compensated interpolation (MCI) refers to the process of taking a video sequence, finding motion information, and then using that information to produce interpolated video frames between source frames. In this study, we compare two MCI techniques: adjacent-frame motion compensated interpolation (AF-MCI) and wide-span motion compensated interpolation (WS-MCI). Using reproducible artificially generated video sequences, the methods are quantitatively compared with the objective of optimizing interpolated frame quality relative to control interpolated frames. This is useful because on a large flat-panel display with high resolution (such as HDTV), frame transition coherence becomes a crucial factor in assessing the quality of the users viewing experience. To enhance MCI, the encoder should attempt to exploit long-term statistical dependencies, precisely estimate motion by modeling the motion vector field, and superimpose efficient prediction/interpolation algorithms. WS-MCI achieves this. Computer simulations using artificially generated video sequences demonstrate the consistent advantage of WS-MCI over adjacent-frame MCI under increasingly complex source scenes and chaotic occlusion conditions.

An early look at the visualization of three-dimensional tissue growth

The ability to visualize time-varying phenomena is paramount to ensure correct interpretation and analysis, provoke insights, and communicate those insights to others. In particular, interactive visualization allows us the freedom to explore the spatial and temporal domains of such phenomena. The task of visualizing tissue growth is challenging because of two factors: The amount of data that needs to be visualized and the large simulation parameter space. In this paper, we present our application of visualization to a three-dimensional simulation model for tissue growth. Cellular automata is used to model populations of cells that execute persistent random walks on the computational grid, collide, and proliferate until they reach confluence. Our research objective is the progress toward the development of a problem-solving environment that can guide the design of experiments for tissue engineers.

The impact of pseudorandom number quality on P-RnaPredict , a parallel genetic algorithm for RNA secondary structure prediction

This paper presents a parallel version of RnaPredict, a genetic algorithm (GA) for RNA secondary structure prediction. The research presented here builds on previous work and examines the impact of three different pseudorandom number generators (PRNGs) on the GAs performance. The three generators tested are the C standard library PRNG RAND, a parallelized multiplicative congruential generator (MCG), and a parallelized Mersenne Twister (MT). A fully parallel version of RnaPredict using the Message Passing Interface (MPI) was implemented. The PRNG comparison tests were performed with known structures that are 118, 122, 543, and 556 nucleotides in length. The effects of the PRNGs are investigated and the predicted structures are compared to known structures.

Significance of randomness in P-RnaPredict - a parallel evolutionary algorithm for RNA folding

This paper presents an extension to P-RnaPredict, a parallel evolutionary algorithm (EA) for RNA folding. The impact of three pseudorandom number generators (PRNGs) on the EAs performance is evaluated. The generators tested included the C standard library PRNG RAND, a parallelized multiplicative congruential generator (MCG), and a parallelized Mersenne Twister (MT). P-RnaPredict was implemented using the message passing interface (MPI) and tested on a 128 node Beowulf cluster. The PRNG comparison testing was performed with four known structures that are 118, 122, 543, and 556 nucleotides in length. PRNGs effects were investigated and predicted structures compared to known structures