Generalized run-and-tumble model in 1D geometry for an arbitrary distribution of drift velocities

2021 ◽  
Vol 2021 (8) ◽  
pp. 083220
Author(s):  
Derek Frydel
2020 ◽  
Vol 2020 (17) ◽  
pp. 34-1-34-7
Author(s):  
Matthew G. Finley ◽  
Tyler Bell

This paper presents a novel method for accurately encoding 3D range geometry within the color channels of a 2D RGB image that allows the encoding frequency—and therefore the encoding precision—to be uniquely determined for each coordinate. The proposed method can thus be used to balance between encoding precision and file size by encoding geometry along a normal distribution; encoding more precisely where the density of data is high and less precisely where the density is low. Alternative distributions may be followed to produce encodings optimized for specific applications. In general, the nature of the proposed encoding method is such that the precision of each point can be freely controlled or derived from an arbitrary distribution, ideally enabling this method for use within a wide range of applications.


Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3801 ◽  
Author(s):  
Ahmed Raza ◽  
Vladimir Ulansky

Among the different maintenance techniques applied to wind turbine (WT) components, online condition monitoring is probably the most promising technique. The maintenance models based on online condition monitoring have been examined in many studies. However, no study has considered preventive maintenance models with incorporated probabilities of correct and incorrect decisions made during continuous condition monitoring. This article presents a mathematical model of preventive maintenance, with imperfect continuous condition monitoring of the WT components. For the first time, the article introduces generalized expressions for calculating the interval probabilities of false positive, true positive, false negative, and true negative when continuously monitoring the condition of a WT component. Mathematical equations that allow for calculating the expected cost of maintenance per unit of time and the average lifetime maintenance cost are derived for an arbitrary distribution of time to degradation failure. A numerical example of WT blades maintenance illustrates that preventive maintenance with online condition monitoring reduces the average lifetime maintenance cost by 11.8 times, as compared to corrective maintenance, and by at least 4.2 and 2.6 times, compared with predetermined preventive maintenance for low and high crack initiation rates, respectively.


2014 ◽  
Vol 11 (97) ◽  
pp. 20140320 ◽  
Author(s):  
Gabriel Rosser ◽  
Ruth E. Baker ◽  
Judith P. Armitage ◽  
Alexander G. Fletcher

Most free-swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. A key open question concerns varying mechanisms by which reorientation occurs. We combine mathematical modelling with analysis of a large tracking dataset to study the poorly understood reorientation mechanism in the monoflagellate species Rhodobacter sphaeroides . The flagellum on this species rotates counterclockwise to propel the bacterium, periodically ceasing rotation to enable reorientation. When rotation restarts the cell body usually points in a new direction. It has been assumed that the new direction is simply the result of Brownian rotation. We consider three variants of a self-propelled particle model of bacterial motility. The first considers rotational diffusion only, corresponding to a non-chemotactic mutant strain. Two further models incorporate stochastic reorientations, describing ‘run-and-tumble’ motility. We derive expressions for key summary statistics and simulate each model using a stochastic computational algorithm. We also discuss the effect of cell geometry on rotational diffusion. Working with a previously published tracking dataset, we compare predictions of the models with data on individual stopping events in R. sphaeroides . This provides strong evidence that this species undergoes some form of active reorientation rather than simple reorientation by Brownian rotation.


2020 ◽  
Vol 101 (6) ◽  
Author(s):  
Andrea Villa-Torrealba ◽  
Cristóbal Chávez-Raby ◽  
Pablo de Castro ◽  
Rodrigo Soto

2019 ◽  
Vol 150 (17) ◽  
pp. 174111 ◽  
Author(s):  
Miru Lee ◽  
Kai Szuttor ◽  
Christian Holm

Soft Matter ◽  
2022 ◽  
Author(s):  
Chamkor Singh

Correction for ‘Guided run-and-tumble active particles: wall accumulation and preferential deposition’ by Chamkor Singh, Soft Matter, 2021, 17, 8858–8866, DOI: 10.1039/D1SM00775K.


2021 ◽  
Author(s):  
Quang D. Tran ◽  
Eric Galiana ◽  
Philippe Thomen ◽  
Céline Cohen ◽  
François Orange ◽  
...  

Phytophthora species cause diseases in a large variety of plants and represent a serious agricultural threat, leading, every year, to multibillion dollar losses. Infection occurs when these biflagellated zoospores move across the soil at their characteristic high speed and reach the roots of a host plant. Despite the relevance of zoospore spreading in the epidemics of plant diseases, it is not known how these zoospores swim and steer with two opposite beating flagella. Here, combining experiments and modeling, we show how these two flagella contribute to generate thrust when beating together, and identify the mastigonemes-attached anterior flagellum as the main source of thrust. Furthermore, we find that steering involves a complex active process, in which the posterior flagellum is stopped, while the anterior flagellum keeps on beating, as the zoospore reorients its body. Our study is a fundamental step towards a better understanding of the spreading of plant pathogens’ motile forms, and shows that the motility pattern of these biflagellated zoospores represents a distinct eukaryotic version of the celebrated “run-and-tumble” motility class exhibited by peritrichous bacteria.


2021 ◽  
Author(s):  
Yang Bai ◽  
Caiyun He ◽  
Junjiajia Long ◽  
Xuefei Li ◽  
Xiongfei Fu

AbstractCoordination of individuals with diversity often requires sophisticated communications and high-order computational abilities. Microbial populations can exhibit diverse individualistic behaviors and yet can engage in collective migratory patterns with a spatially sorted arrangement of phenotypes following a self-generated attractant gradient. However, it’s unclear how individual bacteria without complex computational abilities can achieve the consistent group performance and determine their positions in the group while facing spatiotemporally dynamic stimuli. Here, we investigate the statistics of bacterial run-and-tumble trajectories during group migration. We discover that, despite of the constant migrating speed as a group, the individual drift velocity exhibits a spatially dependent structure that decreases from the back to the front of the group. The spatial modulation of individual stochastic behaviors constrains cells in the group, ensuring the coherent population movement with ordered patterns of phenotypes. These results reveal a simple computational principle for emergent collective behaviors from heterogeneous individuals.


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