Search

We describe an investigation into spatial modelling by means of an ongoing case study, namely phase variation patterning in bacterial colony growth, forming circular colonies on a flat medium. We explore the application of two different geometries, rectangular and circular, for modelling and analysing the colony growth in 2.5 dimensions. Our modelling paradigm is that of coloured stochastic Petri nets and we employ stochastic simulation in order to generate output which is then analysed for sector patterning. The analysis results are used to compare the two geometries, and our multidimensional approach is a precursor to more work on detailed multiscale modelling.

Although communication mechanism between individuals was adopted in the existing bacterial colony chemotaxis algorithm, there still are some defects such as premature, lacking diversity and falling into local optima etc. In this paper, from a new angle of view, we intensively investigate self-adaptive searching behaviors of bacteria, and design a new optimization algorithm which is called as self-adaptive bacterial colony chemotaxis algorithm (SBCC). In this algorithm, in order to improve the adaptability and searching ability of artificial bacteria, a self-adaptive mechanism is designed. As a result, bacteria can automatically select different behavior modes in different searching periods so that to keep fit with complex environments. In the experiments, the SBCC is tested by 4 multimodal functions, and the results are compared with PSO and BCC algorithm. The test results show that the algorithm can get better results with high speed.

An increased area of focus in Microbiology is the automation of counting methods. These obstacles include: How to handle confluent growth or growth of colonies that touch or overlap other colonies, How to identify each colony as a unit in spite of differing shapes, sizes, textures, colors, light intensities, etc. Counting of bacterial colonies is complex task for microbiologist. Further in an Industry thousands of such samples are formed per day and colonies on each sample are counted manually, then this becomes a time consuming hectic and error prone job. We proposed a method to count these colonies to save time with accurate results and fast delivery to customers. This proposed research work will count the colonies after 6 to 8 hours priori, saving a lot more time and this work will more efficient because market range for this is about 10,000 only as compare to prior systems.

In this paper we proposes a new optimization algorithm—Bacterial Colony Optimization (BCO) which formulates the bacterial behavior model in a new way. The model is based on the principle of artificial bacterial behavior, including Chemotaxis, Communication, Elimination, Reproduction and Migration. The Chemotaxis and Communication are spread over the whole optimization process while other behaviors are implemented only when their relevant conditions are reached. Experiment results have proved a high efficiency searching capability of the new proposed artificial bacterial colony.

This research aimed to study on microbe change and fresh-keeping of wet-fresh noodles under refrigerated condition. On the basis of studying on the microbe change of wet-fresh noodles, we studied antimicrobial effect of several food preservatives on wet-fresh noodles under refrigerated condition. The optimize formulation was accquired by single-factor tests and orthogonal tests. Results indicated that the acidity and number of bacterial colony in wet-fresh noodles both showed an incresing trend under refrigerated condition. The optimal antistaling agents were ethylparabe, SDA(Sodium Diacetate) and Rpolysaccharide. When 0.04% of ethylparaben, 0.05% of SDA, 0.04% of Rpolysaccharide were added to wet-fresh noodles. which can be preserved for at least 14 days under refrigerated condition.

This paper proposes a novel bacterial colony foraging (BCF) algorithm for complex optimization problems. The proposed BCF extend original bacterial foraging algorithm to adaptive and cooperative mode by combining bacterial chemotaxis, cell-to-cell communication, and a self-adaptive foraging strategy. The cell-to-cell communication enables the historical search experience sharing among the bacterial colony that can significantly improve convergence. With the self-adaptive strategy, each bacterium can be characterized by focused and deeper exploitation of the promising regions and wider exploration of other regions of the search space. In the experiments, the proposed algorithm is benchmarked against four state-of-the-art reference algorithms using a set of classical test functions.

This paper will attempt to formally analyze the problem of individual existence of a being versus its existence in a social structure, through evaluation of Collective Intelligence efficiency. On the basis of two simulation models of two very distant cases of Collective Intelligence, some results to this problem will be given and discussed. Cases are: survival abilities of a bacterial colony, and hunter and dog versus rabbit. This paper also presents the methodology of identification and translation of the mentioned cases of Collective Intelligence phenomena into simulation models. The results show a strong increase of the social structure ability when the Collective Intelligence is functioning. The problem of the Collective Intelligence is so complex, that the results presented here should be considered as a case study. In general, on the basis of presented results, the paper advertises and advocates the theory of Collective Intelligence based on molecular model of computations.

1 What is diffusion? 1.1 Discrete diffusion models 1.2 Continuous models 2 Paradox of diffusion 3 Diffusive patterns and waves - bistable RD equations 3.1 Scalar bistable RD equation 3.2 Two component systems of bistable RD equations 4 Resource-consumer RD systems 4.1 Bacterial colony model 4.2 Grey-Scott model 5 Competition-diffusion systems and singular limit procedures 5.1 Spatial segregating limits of two competing species model 5.2 Dynamics of triple junctions arising in three competing species model 6 Chemotactic patterns - aggregation and colonies 6.1 Aggregation of Dictyostelium discoideum 6.2 New pattern arising in a chemotaxis-diffusion-growth system References