this paper, which presents randomized, algorithmic techniques for path planning that are particular suited for problems that involve dierential constraints.

Various bacterial strains exhibit colonial branching patterns during growth on poor substrates. These patterns reflect bacterial cooperative self-organization and cybernetic processes of communication, regulation and control employed during colonial development. One method of modeling is the continuous, or coupled reaction-diffusion approach, in which continuous time evolution equations describe the bacterial density and the concentration of the relevant chemical fields. In the context of branching growth, this idea has been pursued by a number of groups. We present an additional model which includes a lubrication fluid excreted by the bacteria. We also add fields of chemotactic agents to the other models. We then present a critique of this whole enterprise with focus on the models ’ potential for revealing new biological features. I.

Various bacterial strains (e.g. strains belonging to the genera Bacillus, Paenibacillus, Serratia and Salmonella) exhibit colonial branching patterns during growth on poor semi-solid substrates. These patterns reflect the bacterial cooperative self-organization. Central part of the cooperation is the collective formation of lubricant on top of the agar which enables the bacteria to swim. Hence it provides the colony means to advance towards the food. One method of modeling the colonial development is via coupled reaction-diffusion equations which describe the time evolution of the bacterial density and the concentrations of the relevant chemical fields. This idea has been pursued by a number of groups. Here we present an additional model which specifically includes an evolution equation for the lubricant excreted by the bacteria. We show that when the diffusion of the fluid is governed by nonlinear diffusion coefficient branching patterns evolves. We study the effect of the rates of emission and decomposition of the lubricant fluid on the observed patterns. The results are compared with experimental observations. We also include fields of chemotactic agents and food chemotaxis and conclude that these features are needed in order to explain the observations. 1 I.

In nature, microorganisms must often cope with hostile environmental conditions. To do so they have developed sophisticated cooperative behavior and intricate communication capabilities, such as: direct cellcell physical interactions via extra-membrane polymers, collective production of extracellular "wetting" fluid for movement on hard surfaces, long range chemical signaling such as quorum sensing and chemotactic (bias of movement according to gradient of chemical agent) signaling, collective activation and deactivation of genes and even exchange of genetic material. Utilizing these capabilities, the colonies develop complex spatio-temporal patterns in response to adverse growth conditions. We present a wealth of branching and chiral patterns formed during colonial development of lubricating bacteria (bacteria which produce a wetting layer of fluid for their movement). Invoking ideas from pattern formation in non-living systems and using "generic" modeling we are able to reveal nov...

In this paper a new method for modeling the growth of neural structures is proposed. The motive of this research is to explore the possibilities for biologically plausible neural growth, and to study how neural based systems could be closely embodied into the environment where they exist. As a result of this research we have found a simple method based on diffusion field modeling to be able to control neural growth together with genetic factors. The simulation results show how neural structures are capable of creating a meaningful network to control the simple behaviors of an artificial creature in a simulated world. The environment control reduces the need for genetic control factors thereby providing faster evolution with a simple genetic coding. 1 Introduction The modeling of growing neural structures has long been a subject of interest for biologists [3, 2]. However, the growth models of neural structures could also make interesting contributions to the engineering field. In this...

Segregation of populations is a key question in evolution theory. One important aspect is the relation between spatial organization and the population 's composition. Here we study a specific example -- sectors in expanding bacterial colonies. Such sectors are spatially segregated sub-populations of mutants. The sectors can be seen both in disk-shaped colonies and in branching colonies. We study the sectors using two models we have used in the past to study bacterial colonies -- a continuous reaction-diffusion model with non-linear diffusion and a discrete "Communicating Walkers" model. We find that in expanding colonies, and especially in branching colonies, segregation processes are more likely than in a spatially static population. One such process is the establishment of stable sub- population having neutral mutation. Another example is the maintenance of wild-type population along side with sub-population of advantageous mutants. Understanding such processes in bacterial colonies ...

ion Validation Implemen tation Verification Validation Computation Specific Model Validation Transformation <-Figure 3: Summary of the various conceptual stages in the development of a computer experiment Where the computation specific model consists of representing the derived conceptual model into a language that can be implemented. One of the things that often goes wrong in these stages is that the scientist tends to confuse his code with a conceptual model or-even worse- with the natural system itself, the researcher has falling in love with his model! This is a situation we should be prepared for and try to avoid at all cost. One way to maintain a critical attitude is to carefully design and test sub stages in the modelling and simulation cycle and to add primitives to the simulation that constantly monitor for 'unrealistic' results 6 I.2 A closer look at system models In the next paragraphs we will use some concepts from the fields of (discrete event) computer simulations, the ...

this paper we use three groups of bacterial strains, all of which we initially isolated from plates containing Bacillus subtilis [11, 14, 38, 39]. The strains were subsequently identified as belonging to the BRANCHING OF BACTERIA 5 genera Paenibacillus. The strains display characteristic and distinct colonial morphologies and thus are characterized as three different morphotypes. We define morphotype as a group of bacteria exhibiting typical colonial patterns. Two strains belong to the same morphotype if under similar growth conditions they develop colonies of the same morphology for a range of growth conditions. Colonial growth patterns of a morphotype are inheritable and can be generated following inoculation with a single cell [2, 40] (note that this definition does not exclude the possibility that bacteria from different species will belong to the same morphotype, or that a specific species can belong to two different morphotypes depending on conditions).

Various bacterial strains exhibit colonial branching patterns during growth on thin poor substrates. The growth can be either diffusion-limited or kinetic-limited, according to the imposed growth conditions. We present experimental observations of patterns exhibited by the bacterial strains Paenibacillus dendritiformis and Paenibacillus vortex. All manners of branching patterns are observed, the three main being: 1) basic branching; 2)chiral branching; 3) vortex branching. We show that the following biological features can explain the spectrum of observed patterns: 1. Formation of a lubricating fluid. 2. Food chemotaxis. 3. Attractive and repulsive chemotaxis signaling. 4. Flagella handedness. 5. Transition into pre-spore state. In the theoretical studies we employ knowledge drawn from branching patterning in non-living systems and the mathematical properties of reaction-diffusion models and atomistic models. The above can be used not just to describe existing biological und...

In this working document, we report on a new approach to high performance simulation. The main inspiration to this approach is the concept of complex systems: disparate elements with well defined interactions rules and non nonlinear emergent macroscopic behavior. We provide arguments and mechanisms to abstract temporal and spatial locality from the application and to incorporate this locality into the complete design cycle of modeling and simulation on parallel architectures. Although the main application area discussed here is physics, the presented Virtual Particle (VIP) paradigm in the context of Dynamic Complex Systems (DCS), is applicable to other areas of compute intensive applications. Part I deals with the concepts behind the VIP and DCS models. A formal approach to the mapping of application task-graphs to machine task-graphs is presented. The major part of section 3 has recently (July 1997) been accepted for publication in Complexity. In Part II we will elaborate on the execution behavior of