An aggregate stochastic model incorporating individual dynamics for predation movements of &lt;em&gt;anelosimus studiosus&lt;/em&gt;

Quijano, Alex John; Joyner, Michele L.; Seier, Edith; Hancock, Nathaniel; Largent, Michael; Jones, Tricia S.

doi:10.3934/mbe.2015.12.585

Cited by 3 publications

(7 citation statements)

References 11 publications

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“…al. [22] using stochastic differential equations and computational algorithms. In [2], the trajectory of the spider is determined by dr(t) = µ{r(t), t} dt + Σ{r(t), t} dW(t)…”

Section: Mathematical Model Of Single Foraging Spidermentioning

confidence: 99%

“…cm. We note that in the formula for e(d), β 0 , β 1 , β 2 , and β 3 are constants estimated in [22] using experimental data and d is the distance between the spider and prey. At distances greater than 12 cm, the error function is set equal to one radian to prevent the error from increasing indefinitely for large distances which could cause the simulated spider to never capture the prey.…”

Section: Mathematical Model Of Single Foraging Spidermentioning

confidence: 99%

“…al. [22] shown in Figure 1. The algorithm has two main loops, the pause loop (when v s = 0) and the run loop (when v s > 0).…”

Section: Mathematical Model Of Single Foraging Spidermentioning

confidence: 99%

“…We assume the duration of the pause is drawn from an exponential distribution with mean q 3 , the velocity varies according to a uniform distribution with mean q 4 , and the duration of the run follows a truncated normal distribution with mean q 5 and degree of variance q 6 . Justifications for the chosen distributions can be found in [22] where a linear relationship was also established between q 1 and q 2 ,…”

Section: Mathematical Model Of Single Foraging Spidermentioning

confidence: 99%

“…The latency period of each spider is different. Using data given in [22], it was determined that the latency period across multiple spiders satisfies an exponential distribution with mean 16.81s. Initially, there are no moving spiders.…”

Section: Latency Periodmentioning

confidence: 99%

See 4 more Smart Citations

Spatio-temporal analysis of foraging behaviors of Anelosimus studiosus utilizing mathematical modeling of multiple spider interaction on a cooperative web

Quijano

Joyner

Ross

et al. 2016

Journal of Theoretical Biology

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In this paper, we develop a model for predation movements of a subsocial spider species, Anelosimus studiosus. We expand on a previous model to include multiple spider interaction on the web as well as a latency period during predation. We then use the model to test different spatial configurations to determine the optimal spacing of spiders within a colony for successful capture during predation. The model simulations indicate that spiders uniformly spacing out along the edge of the web results in the most successful predation strategy. This is similar to the behavior observed by Ross (2013) in which it was determined to be statistically significant that during certain times of the day, spiders were positioned along the edge more than expected under complete spatial randomness.

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“…al. [22] using stochastic differential equations and computational algorithms. In [2], the trajectory of the spider is determined by dr(t) = µ{r(t), t} dt + Σ{r(t), t} dW(t)…”

Section: Mathematical Model Of Single Foraging Spidermentioning

confidence: 99%

Section: Mathematical Model Of Single Foraging Spidermentioning

confidence: 99%

“…al. [22] shown in Figure 1. The algorithm has two main loops, the pause loop (when v s = 0) and the run loop (when v s > 0).…”

Section: Mathematical Model Of Single Foraging Spidermentioning

confidence: 99%

Section: Mathematical Model Of Single Foraging Spidermentioning

confidence: 99%

Section: Latency Periodmentioning

confidence: 99%

See 3 more Smart Citations

Spatio-temporal analysis of foraging behaviors of Anelosimus studiosus utilizing mathematical modeling of multiple spider interaction on a cooperative web

Quijano

Joyner

Ross

et al. 2016

Journal of Theoretical Biology

Self Cite

View full text Add to dashboard Cite

show abstract

Estimation of anthracnose dynamics by nonlinear filtering

Fotsa-Mbogne

2018

Int. J. Biomath.

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In this work, we apply the nonlinear filtering theory to the estimation of the partially observed dynamics of anthracnose which is a phytopathology. The signal here is the inhibition rate and the observations are the fruit volume and the rotted volume. We propose stochastic models based on deterministic models studied previously in the literature, in order to represent the noise introduced by uncontrolled variations on parameters and errors on the measurements. Under the assumption of Brownian noises, we prove the well-posedness of the models in either they take into account the space variable or not. The filtering problem is solved for the nonspatial model giving Zakai and Kushner–Stratonovich equations satisfied respectively by the unnormalized and the normalized conditional distribution of the signal with respect to the observations. A prevision problem and a discrete filtering problem are also studied for the realistic cases of discrete and possibly incomplete observations. We illustrate the filter behavior through figures displaying the average estimation relative error and a 95% confidence region obtained after a hundred of numerical simulations with initial conditions taken randomly with respect to uniform law.

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Force transmission characteristics in a multiple-fulcrum supporting platform with heavy loads

Deng

Ding

Yin

et al. 2020

MBE

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<abstract> <p>This study aims to investigate the force transmission characteristics of a multiple-fulcrum supporting platform, and the significance of this paper is to creatively put forward the law of uniform force characteristics of multiple-fulcrum supporting platform with heavy loads and layout reconfiguration methods to realize the law. In this paper, firstly, a force transmission model for the multiple-fulcrum supporting platform has been constructed, the relationship between force transmission characteristics and layout parameters for all fulcrums has been discussed in detail, and the layout law for all fulcrums with the same supporting force has been discovered. Then, layout reconfiguration methods have been proposed to realize the uniform force characteristics of all fulcrums under different types of constraint surfaces (rectangular or square constrained surface, circular constrained surface, and unconstrained surface). Finally, layout reconfiguration methods have been applied to some engineering problems by ADAMS simulation. The simulation results show that the supporting force of all fulcrums in the supporting platform is equal when the layout central point (LCP) of all fulcrums is coincident with the force equivalent point (FEP) of external loads. The results provide theoretical guidance and support for the reconfiguration of multiple-fulcrum supporting platforms that can realize uniform forces among all fulcrums.</p> </abstract>

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An aggregate stochastic model incorporating individual dynamics for predation movements of <em>anelosimus studiosus</em>

Cited by 3 publications

References 11 publications

Spatio-temporal analysis of foraging behaviors of Anelosimus studiosus utilizing mathematical modeling of multiple spider interaction on a cooperative web

Spatio-temporal analysis of foraging behaviors of Anelosimus studiosus utilizing mathematical modeling of multiple spider interaction on a cooperative web

Estimation of anthracnose dynamics by nonlinear filtering

Force transmission characteristics in a multiple-fulcrum supporting platform with heavy loads

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