scholarly journals A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments

2016 ◽  
Vol 3 (1) ◽  
pp. 150473 ◽  
Author(s):  
Bertrand Collignon ◽  
Axel Séguret ◽  
José Halloy
Keyword(s):  
Experimental Data ◽  
Stochastic Process ◽  
Distribution Function ◽  
Probability Distribution Function ◽  
Collective Motion ◽  
Three Dimensional ◽  
Sensory System ◽  
Heterogeneous Environments ◽  
Parameter Values ◽  
Made In

Collective motion is one of the most ubiquitous behaviours displayed by social organisms and has led to the development of numerous models. Recent advances in the understanding of sensory system and information processing by animals impels one to revise classical assumptions made in decisional algorithms. In this context, we present a model describing the three-dimensional visual sensory system of fish that adjust their trajectory according to their perception field. Furthermore, we introduce a stochastic process based on a probability distribution function to move in targeted directions rather than on a summation of influential vectors as is classically assumed by most models. In parallel, we present experimental results of zebrafish (alone or in group of 10) swimming in both homogeneous and heterogeneous environments. We use these experimental data to set the parameter values of our model and show that this perception-based approach can simulate the collective motion of species showing cohesive behaviour in heterogeneous environments. Finally, we discuss the advances of this multilayer model and its possible outcomes in biological, physical and robotic sciences.

Interpretation of the photon: wave–particle duality

2012 ◽  
Vol 90 (9) ◽  
pp. 855-863
Author(s):  
Gilbert R. Hoy ◽  
Jos Odeurs
Keyword(s):  
Distribution Function ◽  
Probability Distribution ◽  
Probability Density ◽  
Coherence Length ◽  
Probability Distribution Function ◽  
Three Dimensional ◽  
Space Time ◽  
Maximum Probability ◽  
Excited System ◽  
Wave Particle Duality

A simple model is provided to obtain the space–time probability-distribution function of a photon emitted without recoil by an excited system (atom, nucleus, …) in one dimension. A three-dimensional formulation is not needed for our discussion. A quantum mechanical calculation, using the Heitler method, is employed to obtain the solution. The space–time probability-distribution function is not the photon wavefunction. In fact, the area under the space–time probability-distribution function is time dependent. It obtains its final value only as t → ∞. The frequency composition of the photon is found and its time dependence determined to be in accord with the time–energy uncertainty principle. In the wave picture, the coherence length of a photon is found to be equal to the distance from the maximum probability-density position in the photon back toward the source to a position where the probability density has decreased to e–1 of its maximum value. The concept of the coherence length is applied to understand the exponential lifetime curve in the wave picture. This latter measurement is usually explained by saying, in the particle picture, that the photon can appear immediately after formation of the excited state or at a variety of later times according to an exponential probability distribution.

scholarly journals The chaos in calibrating crop models

2020 ◽  
Author(s):  
Daniel Wallach ◽  
Taru Palosuo ◽  
Peter Thorburn ◽  
Zvi Hochman ◽  
Emmanuelle Gourdain ◽  
...  
Keyword(s):  
Experimental Data ◽  
Model Calibration ◽  
Crop Model ◽  
Process Models ◽  
Model Parameters ◽  
Model Structure ◽  
Crop Models ◽  
Estimation Of Model Parameters ◽  
Parameter Values ◽  
Made In

Calibration, that is the estimation of model parameters based on fitting the model to experimental data, is among the first steps in essentially every application of crop models and process models in other fields and has an important impact on simulated values. The goal of this study is to develop a comprehensive list of the decisions involved in calibration and to identify the range of choices made in practice, as groundwork for developing guidelines for crop model calibration starting with phenology. Three groups of decisions are identified; the criterion for choosing the parameter values, the choice of parameters to estimate and numerical aspects of parameter estimation. It is found that in practice there is a large diversity of choices for every decision, even among modeling groups using the same model structure. These findings are relevant to process models in other fields.

The Experimental Study and Numerical Simulation of Turbulent Flow in Pumping Forebay

2009 ◽  
Author(s):  
Chao Liu ◽  
Jiren Zhou ◽  
Li Cheng
Keyword(s):  
Experimental Data ◽  
Numerical Simulation ◽  
Turbulent Flow ◽  
Three Dimensional ◽  
Computational Results ◽  
Experiment Study ◽  
Study Results ◽  
Measurement Results ◽  
Good Agreement ◽  
Made In

The experiment study was made to optimize the design of a pumping forebay. The Combined-sills were made in the forebay to eliminate the circulation and vortices of the diffusing flow successfully. The Numerical simulation of three-dimensional turbulent flow is applied on the complicate fore-and-aft flow of sills. The computational results are compared with the measurement results of physical model. The calculated results are in good agreement with the experimental data. The flow pattern is obviously improved. The study results have been applied in the project which gives a uniform approach flow to the pumping sump.

The joint probability distribution function of structure factors with rational indices. VI. Cases with reduced dimensionality

1999 ◽  
Vol 55 (6) ◽  
pp. 984-990
Author(s):  
Carmelo Giacovazzo ◽  
Dritan Siliqi ◽  
Cristina Fernández-Castaño ◽  
Giovanni Luca Cascarano ◽  
Benedetta Carrozzini
Keyword(s):  
Distribution Function ◽  
Probability Distribution ◽  
Probability Distribution Function ◽  
Mixed Type ◽  
Three Dimensional ◽  
Joint Probability ◽  
Joint Probability Distribution ◽  
Reduced Dimensionality ◽  
Structure Factors ◽  
Joint Probability Distribution Function

The probabilistic formulas relating standard and mixed type reflections (these last show integral and half-integral indices) are derived. It is shown that probabilistic estimates can be obtained by using particular sections of the three-dimensional reciprocal space. The concept of structure invariant is extended to define the wider class of structure quasi-invariant. Their statistical behaviour is briefly discussed with the help of some practical tests.

Predicting spatial activity patterns in a neural map from a probabilistic atlas of 3-D reconstructed neurons

1995 ◽  
Vol 53 ◽  
pp. 812-813
Author(s):  
G. Jacobs ◽  
F. Theunissen
Keyword(s):  
Activity Patterns ◽  
Three Dimensional ◽  
Sensory System ◽  
Neural System ◽  
Probabilistic Atlas ◽  
Uniform Sample ◽  
Dimensional Reconstruction ◽  
The Time Domain ◽  
And Function ◽  
Visualization Techniques

In order to understand how the algorithms underlying neural computation are implemented within any neural system, it is necessary to understand details of the anatomy, physiology and global organization of the neurons from which the system is constructed. Information is represented in neural systems by patterns of activity that vary in both their spatial extent and in the time domain. One of the great challenges to microscopists is to devise methods for imaging these patterns of activity and to correlate them with the underlying neuroanatomy and physiology. We have addressed this problem by using a combination of three dimensional reconstruction techniques, quantitative analysis and computer visualization techniques to build a probabilistic atlas of a neural map in an insect sensory system. The principal goal of this study was to derive a quantitative representation of the map, based on a uniform sample of afferents that was of sufficient size to allow statistically meaningful analyses of the relationships between structure and function.

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